Nature Neuroscience Journal ~ August 2005, Volume 8 No 8

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VOLUME 8 NUMBER 8 AUGUST 2005

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BOOK REVIEW During embryonic neurogenesis, HMG-box transcription factors Sox1/2/3 suppress neural differentiation, maintaining progenitors in a proliferative state. Muhr and colleagues now demonstrate that the related transcriptional repressor Sox21 is induced by proneural transcription factors. Sox21 counteracts the activity of Sox1/2/3 and enables neuronal differentiation. The cover shows a coronal section through the spinal cord of a 4 day-old chick embryo. Sox21 is labeled in red, Sox3 in green and the neuron marker NF1 in blue. (p 995)

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Imaging in Neuroscience and Development: A Laboratory Manual edited by Rafael Yuste and Arthur Konnerth Reviewed by Marla B Feller

NEWS AND VIEWS 975

How visual salience wins the battle for awareness Steven Yantis 왘 see also p 1110

977

The synaptic Aβ hypothesis of Alzheimer disease Rudolph E Tanzi 왘 see also p 1051

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Beyond migration: Dlx1 regulates interneuron differentiation Carl Wonders & Stewart Anderson 왘 see also p 1059

981

Less is more: progenitor death and cortical size Pasko Rakic

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Rethinking the thalamus Paul W Glimcher & Brian Lau

Origins of Cajal-Retzius cells (p 1002)

Nature Neuroscience (ISSN 1097-6256) is published monthly by Nature Publishing Group, a trading name of Nature America Inc. located at 345 Park Avenue South, New York, NY 10010-1707. Periodicals postage paid at New York, NY and additional mailing post offices. Editorial Office: 345 Park Avenue South, New York, NY 10010-1707. Tel: (212) 726 9319, Fax: (212) 696 0978. Annual subscription rates: USA/Canada: US$199 (personal), US$1,240 (institution). Canada add 7% GST #104911595RT001; Euro-zone: €289 (personal), €1,279 (institution); Rest of world (excluding China, Japan, Korea): £175 (personal), £775 (institution); Japan: Contact Nature Japan K.K., MG Ichigaya Building 5F, 19-1 Haraikatamachi, Shinjuku-ku, Tokyo 162-0841. Tel: 81 (03) 3267 8751, Fax: 81 (03) 3267 8746. POSTMASTER: Send address changes to Nature Neuroscience, Subscriptions Department, 303 Park Avenue South #1280, New York, NY 10010-3601. Authorization to photocopy material for internal or personal use, or internal or personal use of specific clients, is granted by Nature Publishing Group to libraries and others registered with the Copyright Clearance Center (CCC) Transactional Reporting Service, provided the relevant copyright fee is paid direct to CCC, 222 Rosewood Drive, Danvers, MA 01923, USA. Identification code for Nature Neuroscience: 1097-6256/04. Back issues: US$45, Canada add 7% for GST. CPC PUB AGREEMENT #40032744. Printed by Publishers Press, Inc., Lebanon Junction, KY, USA. Copyright © 2005 Nature Publishing Group. Printed in USA.

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Persistent hippocampal CA1 LTP in mice lacking the C-terminal PDZ ligand of GluR1 C-H Kim, K Takamiya, R S Petralia, R Sattler, S Yu, W Zhou, R Kalb, R Wenthold & R Huganir

988

Cortical calcium waves in resting newborn mice H Adelsberger, O Garaschuk & A Konnerth

991

Neural correlates of genetically abnormal social cognition in Williams syndrome A Meyer-Lindenberg, A R Hariri, K E Munoz, C B Mervis, V S Mattay, C A Morris & K F Berman

Dlx1 regulates interneuron survival (p 979 and 1059)

ARTICLES 995

Sox21 promotes the progression of vertebrate neurogenesis M Sandberg, M Källström & J Muhr

1002 Multiple origins of Cajal-Retzius cells at the border of the developing pallium F Bielle, A Griveau, N Narboux-Nême, S Vigneau, M Sigrist, S Arber, M Wassef & A Pierani 1013 Ephrin-As mediate targeting of eye-specific projections to the lateral geniculate nucleus A D Huberman, K D Murray, D K Warland, D A Feldheim & B Chapman

Ephrin-As guide retinogeniculate axons (p 1013 and 1022)

1022 Ephrin-As and neural activity are required for eye-specific patterning during retinogeniculate mapping C Pfeiffenberger, T Cutforth, G Woods, J Yamada, R C Renteria, D R Copenhagen, J G Flanagan & D A Feldheim 1028 Hair bundle motion of outer hair cells and the cochlear amplifier D Z Z He & S Jia 1035 A deafness mutation isolates a second role for the tectorial membrane in hearing P K Legan, V A Lukashkina, R J Goodyear, A N Lukashkin, K Verhoeven, G Van Camp, I J Russell & G P Richardson 1043 Distinct triggering and expression mechanisms underlie LTD of AMPA and NMDA synaptic responses W Morishita, H Marie & R C Malenka 1051 Regulation of NMDA receptor trafficking by amyloid-β E M Snyder, Y Nong, C G Almeida, S Paul, T Moran, E Y Choi, A C Nairn, M W Salter, P J Lombroso, G K Gouras & P Greengard 왘 see also p 977 1059 Mice lacking Dlx1 show subtype-specific loss of interneurons, reduced inhibition and epilepsy I Cobos, M E Calcagnotto, A J Vilaythong, M T Thwin, J L Noebels, S C Baraban & J L R Rubenstein 왘 see also p 979 1069 Activation of p75NTR by proBDNF facilitates hippocampal long-term depression N H Woo, H K Teng, C-J Siao, C Chiaruttini, P T Pang, T A Milner, B L Hempstead & B Lu

Glial ATP increases postsynaptic efficacy (p 1078)

NATURE NEUROSCIENCE

1078 Norepinephrine triggers release of glial ATP to increase postsynaptic efficacy G R J Gordon, D V Baimoukhametova, S A Hewitt, W R A K J S Rajapaksha, T E Fisher & J S Bains

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1087 Synchronized retinal oscillations encode essential information for escape behavior in frogs H Ishikane, M Gangi, S Honda & M Tachibana Synchronized retinal oscillations and escape behavior (p 1087)

1096 Continuous flash suppression reduces negative afterimages N Tsuchiya & C Koch 1102 Visual field maps and stimulus selectivity in human ventral occipital cortex A A Brewer, J Liu, A R Wade & B A Wandell 1110 Stimulus context modulates competition in human extrastriate cortex D M Beck & S Kastner 왘 see also p 975 1117 Probabilistic word pre-activation during language comprehension inferred from electrical brain activity K A DeLong, T P Urbach & M Kutas

N AT U R E N E U R O S C I E N C E C L A S S I F I E D See back pages.

Functional mapping of ventral visual cortex (p 1102)

NATURE NEUROSCIENCE

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O

n June 6th, the US Supreme Court dealt a blow to patients who use marijuana for medical purposes, ruling that a doctor’s approval is no protection against legal action by federal authorities such as the Drug Enforcement Administration (DEA). The court ruled that using marijuana to treat medical conditions violates federal law, despite laws in several states allowing the use of marijuana to treat symptoms of diseases like cancer. Both sides of this controversy cite scientific findings to support their positions, but selective citations can act as a smokescreen for moral beliefs about drug use that it would be more productive to discuss directly. Because of marijuana’s popularity as a recreational drug— according to one news report1, 95 million Americans over the age of 12 have tried it at least once—the debate over medical marijuana rapidly gets bogged down in politics. Scientific results need not be the last word in such decisions, but they should be represented fairly in the debate. The 1970 Controlled Substances Act (CSA) lists marijuana and its most active ingredient THC (∆9-tetrahydrocannabinol) as schedule I drugs, indicating that they have no medical value, are illegal to possess and/or distribute, and are not considered safe for use under medical supervision. Does this accurately reflect the scientific evidence? Marijuana and THC clearly can cause harm. A single marijuana exposure can affect driving ability in humans2 or impair spatial navigation in rats. Although researchers disagree on whether moderate marijuana use causes cognitive impairment, heavy users have lower overall IQ scores than non-users and are slower at immediate and delayed memory tasks3. Prolonged exposure to THC or marijuana may also cause addiction. Squirrel monkeys can learn to self-administer THC at doses comparable to those found in marijuana smoke inhaled by humans, and synthetic CB1 cannabinoid agonists have reinforcing effects in rats and mice4. Withdrawal from marijuana causes relatively mild symptoms, including loss of appetite, irritability and depression. Although the benefits of smoking marijuana remain controversial, the government has already decided that THC itself has medical benefits. Marinol—a synthetic derivative of THC—is federally approved to reduce nausea and stimulate appetite in patients suffering from cancer or HIV infection. (Curiously, Marinol is classified as a schedule III drug, indicating that it is considered less dangerous than THC, with which it shares both chemical structure and biological activity.) Marinol is effective in treating vocal and physical tics due to Tourette’s syndrome5. In clinical trials, oral sprays of a marijuana plant extract called Sativex reduce muscle spasms in patients with multiple sclerosis6. THC also seems to be beneficial in treating neuropathic pain or glaucoma. Moreover, THC is a relatively safe drug: according to Daniele Piomelli, the director for the Center for Drug Discovery at the University of California, Irvine, it would take about 70 grams of pure THC to cause serious damage to a 150-pound adult. It is therefore difficult to justify the DEA classification of THC as a class I drug with no medical value.

NATURE NEUROSCIENCE VOLUME 8 | NUMBER 8 | AUGUST 2005

This decision has potentially dangerous implications for science. It reflects a belief that there can be no value in investigating the medical properties of marijuana because the issue is settled. Igor Grant, the Director for the University of California Center for Medicinal Cannabis Research in San Diego, notes that even though the US National Institutes of Health continue to fund cannabinoid research, investigators are bound to have some reluctance to move into such a charged area, particularly when budgets are tight and the paperwork burdens intense. The extra bureaucratic hurdles involved in getting permission to obtain and use schedule I drugs can deter even established scientists. Piomelli once dropped a project on cannabidiol because the paperwork would have required an extra year. Donald Abrams, the chief of Oncology at the San Francisco General Hospital, points out that he sometimes needs as many as eight different agencies to approve his projects. This intellectual atmosphere cannot help but delay progress in understanding how cannabis works and whether it has medical benefits. The federal government, moreover, would prefer to steer clear of all other marijuana substitutes; this June, John Walters, the director for the US National Drug Control Policy issued a statement that “Our national medical system relies on proven scientific research, not popular opinion. Marinol—the synthetic form of THC and the psychoactive ingredient contained in marijuana—is already legally available for prescription by physicians whose patients suffer from pain and chronic illness…” (http://www.whitehousedrugpolicy.gov/pda/060605.html). However, advocates of medical marijuana point out that natural marijuana contains other ingredients such as cannabidiol, which may not only counterbalance the psychotropic effects of pure THC, but may also afford some therapeutic benefits on its own. Smoking also provides relief quickly, whereas orally administered THC may take hours to produce an effect and has variable effects across individuals. In light of the data, more research into the medical effects of marijuana is clearly warranted. Indeed, a report from the US National Academy of Sciences (http://books.nap.edu/html/marimed) on medical marijuana concluded that “…the existing data are consistent with the idea that this would not be a problem if the medical use of marijuana were as closely regulated as other medications with abuse potential.” Thus it seems hard to justify regulations that allow doctors to prescribe cocaine and morphine, but not marijuana. Lumping marijuana and THC in the same category as LSD and heroin also reflects a failure to identify the different degrees of danger posed by the different substances. As Piomelli notes7, “Any young person who has smoked marijuana and seen a friend ravaged by heroin can tell the difference between these drugs. Why can’t we?” 1. 2. 3. 4. 5. 6. 7.

Peplow, M. [email protected] 7 June 2005 (doi:10.1038/news050606-6). Kurzthaler, I. et al. J. Clin. Psychiatry 60, 395–399 (1999). Fried, P.A. et al. Neurotoxicol. Teratol. 27, 231–239 (2005). Justinova, Z. et al. Pharmacol. Biochem. Behav. 81, 285–299 (2005). Muller-Vahl, K.R et al. Pharmacopsychiatry 34, 19–24 (2001). Wade, D.T. et al. Mult. Scler. 10, 339–340 (2004). Piomelli, D. The Washington Post June 12 (2005), p. B03.

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How visual salience wins the battle for awareness Steven Yantis Voluntarily paying attention to one object in a crowded scene enhances perception of that object and increases the activity of neurons representing it. Attention can also be drawn involuntarily by salient objects—for example, by the sudden onset of a bright stimulus. A study now shows how this involuntary type of attention may mediate competition between representations in human visual cortex.

The intuition that we open our eyes and see all that is before us has long been known to be an illusion. In fact, vision is highly selective. Even without moving our eyes, we can choose voluntarily to attend to one or another object in a scene, and this leads to improved sensitivity and more rapid detection1 as well as a more vivid appearance2. In other words, conscious experience of a scene depends both on the contents of the retinal image and on the attentive state of the brain. When multiple stimuli are present in a scene, they compete for cortical representation3. Voluntary deployments of attention can resolve the competition: ‘top-down’ signals that originate in executive control regions of prefrontal cortex promote increased spiking in neurons that represent the attended object. However, not all attention is voluntary: when a door slams in the library, every head looks up to the source. In this issue, Beck and Kastner report important new evidence about how this type of control—attentional capture by salient stimuli—may arise from a purely ‘bottom-up’ form of cortical competition in visual parts of the brain4. Competition for cortical representation is a consequence of the hierarchical architecture of the visual system: neural receptive fields are small (0.5–1.5°) in primary visual cortex (V1) and represent simple, local visual properties such as edge orientation and contrast (Fig. 1). Neurons in later visual areas such as V2, V4 and inferotemporal (IT) cortex have receptive fields that increase in size and in complexity of visual properties to which they are tuned5. Neurons in area Steven Yantis is in the Department of Psychological and Brain Sciences, Johns Hopkins University, 3400 N. Charles St., Baltimore, Maryland 21218, USA. e-mail: [email protected]

V4 have receptive field diameters that are roughly equal to the distance of their centers from the fovea, and respond to moderately complex contours6. In IT, neurons can have large receptive fields that encompass much of a hemifield, and they can respond to complex shapes and faces7. This hierarchical structure efficiently codes complex visual object properties, but the efficiency comes at a cost. When

both an effective sensory stimulus and an otherwise ineffective sensory stimulus are present within the receptive field of, say, a V4 or IT neuron, competition for representation arises: should the neuron’s response be robust, reflecting the effective stimulus, or weak, reflecting the ineffective stimulus? Without attention, the response is a compromise: roughly the mean of the strong and weak responses. When voluntary attention is

Figure 1 The visual system is organized hierarchically; receptive field size and complexity increase from V1 to V4 to inferotemporal (IT) cortex. Cartoons below V1, V4 and IT represent oriented edges, simple contours and complex object shape, respectively. This presents a problem: when two objects appear with the same large receptive field (say, of the highlighted neuron in IT), which of the stimuli should drive the neuron’s response? In this example, the competition for representation has been biased in favor of the cube, either by a top-down signal that reflects current behavioral goals, or by differences in local feature contrast (salience). Every level of the visual hierarchy now cooperates to represent the attended object, which enters awareness. RF, receptive field.


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Time2: after inhibitory interactions


Het

Pop

Ann Thomson

directed to one of the stimuli, the competition is biased so that the attended stimulus in the receptive field drives the cell8, and that stimulus ultimately enters awareness and becomes available for report or encoding into memory. The effects of attention are propagated throughout the visual hierarchy so that a stable, coherent ensemble of neurons distributed across cortical areas represents the attended object via synchronized activity and reentrant feedback signals. Kastner and colleagues previously documented how attention can bias competition in human cortex9. They compared brain activity evoked by a display containing multiple stimuli presented one at a time (so that inhibitory interactions could not occur), which produced a strong response, or presented simultaneously (allowing inhibitory interactions), which produced a weaker response. When attention was directed to one of the stimuli, it reduced the suppression caused by the competing stimuli, causing an increased response, particularly in area V4. Such voluntary deployments of attention allow observers to actively seek information needed to achieve current behavioral goals and can modulate activity in the representation of different spatial locations, sensory dimensions or objects10. Activity in a network of cortical regions that include the posterior parietal cortex and the frontal eye fields is critical for voluntary deployments of attention11. On the other hand, it is sensible that certain sensory events should capture attention involuntarily, providing an ‘early warning system’ for rapid assessment and response to salient and potentially harmful events, obviating deliberation and saving precious time12. Many behavioral studies have documented the efficiency with which salient visual objects can be detected in visual search1. In the new paper4, Beck and Kastner have investigated human brain activity to salient and non-salient visual stimuli using fMRI.

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Figure 2 Cartoon of the context effects described by Beck and Kastner4. Each panel shows an array of four colored, oriented Gabor patches; the size of each patch represents the magnitude of the neural response to that stimulus, and the thickness of the black lines between them (representing inhibitory connections) represents the strength of the inhibitory interaction. Left column represents initial appearance of stimuli, and right column represents relative neural response to the stimuli after some time has passed to allow inhibitory interactions to occur. Stimuli with different feature values (colors and orientations) show moderate-strength mutual inhibition, whereas stimuli with the same color and orientation produce strong isofeature inhibition. When stimuli first appear (left), their physical contrasts initially produce approximately equal neural responses. Following inhibitory interactions, (right), mutual inhibition in the heterogeneous displays (top) produces an approximately equal degree of sensory suppression for all stimuli. However, the unbalanced inhibitory pattern in the pop-out displays (bottom) produces more sensory suppression in the stimuli that share features (blue horizontal Gabor patches), which in turn reduces the degree to which they inhibit the feature singleton (red vertical Gabor patch), producing a relatively enhanced response to that object. Het, heterogeneous display; Pop, pop-out display.

To ensure that the effects they measured were purely stimulus-driven (and not a consequence of voluntary attention), they required observers to carry out an attentionally demanding visual task at the fovea, and they measured response times in the foveal task to ensure that attention was not diverted to the peripheral stimuli that were the focus of their brain measurements. Beck and Kastner found that the sensory suppression that usually results from simultaneous presentation of multiple competing stimuli is reduced if one of the objects is a feature singleton (that is, an object that differs in both color and orientation from the remaining items in the display). In a heterogeneous display (Fig. 2, top), multiple stimuli with different features interact in a mutually inhibitory, competitive fashion, producing a moderate degree of sensory suppression. Stimuli with identical features show stronger mutual inhibition, a phenomenon sometimes termed ‘isofeature suppression’13. Thus, when the contextual elements all have the same color and orientation (Fig. 2, bottom), they strongly inhibit one another, and this reduces their combined inhibitory effects on the unique item, which in turn increases the neural response to that item. In the Beck and Kastner study, this was manifested in less sensory suppression for pop-out displays than for heterogeneous displays. In other words, the suppression caused by context items was greater for the heterogeneous displays, where mutual suppression was balanced among the items, than for the pop-out displays, where the strong isofeature suppression of the homogenous background reduced its inhibitory effect on the singleton. This finding can be viewed as an instance of the very general principle that perceptual systems encode contrast, rather than the absolute level of some attribute. This kind of contrast effect has been documented through measurements of single-cell responses in macaque

area V1 (ref. 14). An oriented bar was placed in the receptive field of the cell, and a field of identically oriented bars, all outside the classical receptive field, was introduced. The presence of any context suppressed the cell’s response compared with a blank surround, reflecting competitive intracortical interactions. When the bars in the contextual field had the same orientation as the center bar, the cell’s response was more strongly suppressed than when they had a contrasting orientation. The authors interpreted this as a neural correlate of the perceptual salience of feature singletons. Once the neural response to the salient item dominates the responses to the uniform contextual items, this signal can propagate to other levels of the visual hierarchy and increase the likelihood that this stimulus enters visual awareness. These stimulus-driven effects are combined with and modulated by top-down effects to determine the overall attentive state of the brain. For example, when two stimuli are presented within a V4 receptive field, increasing the contrast of one of them biases the competition in its favor15. This stimulus-driven effect is magnified if the animal is also induced to voluntarily attend to that stimulus. These findings contribute to a growing understanding of the role of attention in perception. Cooperative interactions across levels of the visual hierarchy give rise to robust perceptual representations of attended objects; competitive interactions within visual areas lead to the suppression of competing representations. As the visual scene changes, local feature contrast will bias competition in favor of newly salient events. As behavioral goals change, modulatory signals from prefrontal and parietal cortex bias competition in favor of task-relevant information. The dynamic interplay of stimulusdriven and goal-directed factors determines the content of perceptual experience as it evolves over time.

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1. Egeth, H.E. & Yantis, S. Annu. Rev. Psychol. 48, 269– 297 (1997). 2. Carrasco, M., Ling, S. & Read, S. Nat. Neurosci. 7, 308–313 (2004). 3. Desimone, R. & Duncan, J. Annu. Rev. Neurosci. 18, 193–222 (1995). 4. Beck, D.M. & Kastner, S. Nat. Neurosci. 8, 1108–1114 (2005). 5. Rousselet, G.A., Thorpe, S.J. & Fabre-Thorpe, M. Trends Cog. Sci. 8, 363–370 (2004).

6. Pasupathy, A. & Connor, C.E. Nat. Neurosci. 5, 1332– 1338 (2002). 7. Grill-Spector, K. Curr. Opin. Neurobiol. 13, 159–166 (2003). 8. Reynolds, J.H., Chelazzi, L. & Desimone, R. J. Neurosci. 19, 1736–1753 (1999). 9. Kastner, S., De Weerd, P., Desimone, R. & Ungerleider, L.G. Science 282, 108–111 (1998). 10. Yantis, S. & Serences, J. Curr. Opin. Neurobiol. 13, 187–193 (2003).

11. Corbetta, M. & Shulman, G.L. Nat. Rev. Neurosci. 3, 201–215 (2002). 12. Rauschenberger, R. Psychon. Bull. Rev. 10, 814–842 (2003). 13. Li, Z. Proc. Natl. Acad. Sci. USA 96, 10530–10535 (1999). 14. Knierim, J.J. & Van Essen, D.C. J. Neurophysiol. 67, 961–980 (1992). 15. Reynolds, J.H. & Desimone, R. Neuron 37, 853–863 (2003).

The synaptic Aβ hypothesis of Alzheimer disease Rudolph E Tanzi Aβ peptide is linked to Alzheimer pathology, but its toxic mechanism remains unclear. New work shows that Aβ leads to internalization of NMDA receptors, reducing their availability at synapses. The authors also suggest a molecular mechanism for this endocytosis.

The amyloid hypothesis of Alzheimer disease states that the accumulation and deposition of fibrillar β-amyloid is the primary driver of neurodegeneration and cognitive decline leading to dementia1,2. Recent studies, however, are prompting a shift to the synaptic Aβ hypothesis, which places a greater emphasis on the pathogenic role of non-fibrillar Aβ oligomers specifically at the synapse. Now, in this issue, Snyder and colleagues3 report a signaling pathway through which Aβ may act to impair glutamatergic transmission, compromise synaptic function and reduce long-term potentiation (LTP), a form of synaptic plasticity associated with learning and memory4. Over the past twenty years, the amyloid hypothesis has been strongly supported by a wealth of evidence, including data from genetic studies of Alzheimer disease5. All four of the established Alzheimer disease genes, the β-amyloid precursor protein (APP), presenilin 1 and 2 (PSEN1, PSEN2) and apolipoprotein E (APOE) harbor mutations or variants that influence the accumulation of the Aβ peptide. Aβ is generated by cleavage from APP and is the central building block of β-amyloid. In the case of the earlyonset Alzheimer disease genes (APP, PSEN1 and PSEN2), over 160 autosomal dominant mutations have been discovered that cause Alzheimer disease with virtual certainty5, usually before the age of 60. All but a handful of these mutations increase the relative rate of production of Aβ42, the longer form of the peptide that is much more prone to oligoRudolph E. Tanzi is at the Genetics and Aging Research Unit, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts 02129, USA. e-mail: [email protected]

merization and fibrillization than its more abundant counterpart in the brain, Aβ40. The traditional amyloid hypothesis remains controversial, mainly because spatial and temporal patterns of amyloid deposition (mostly in the form of senile plaques consisting of fibrillar Aβ) do not correlate very well with the clinical degree of dementia in Alzheimer disease. In contrast, cognitive decline correlates very well with synapse loss6. This is particularly interesting in light of studies that strongly implicate non-fibrillar Aβ oligomers in disrupting synaptic function. For example, synaptic perturbations, including impaired LTP, are observed in APP-V717 (PD-APP) mutant transgenic mice before the development of Aβ deposits7. In addition, non-fibrillar, low molecular weight Aβ oligomers block LTP in brain slices8 and, in vivo, in PD-APP mice9. Soluble Aβ oligomers, including dimers and trimers, are both necessary and sufficient to transiently disrupt learned behavior in APP-Swedish ('APPSwe’ or TG2576) transgenic mice10. Collectively, these data implicate soluble Aβ oligomers (as opposed to fibrillar β-amyloid deposits, such as senile plaques) in promoting ‘synaptoxicity’ and ensuing neurodegeneration in Alzheimer disease. These findings, together with the strong correlation of synapse loss with degree of clinical dementia in Alzheimer disease, suggest that the original amyloid hypothesis may be in need of revision to a synaptic Aβ hypothesis, underscoring the role of prefibrillar Aβ oligomers in Alzheimer disease pathogenesis, particularly at synapses. The role of Aβ oligomers in Alzheimer disease pathology has been further bolstered by the finding that auto-antibodies to small oligomeric cross-linked Aβ peptides are selectively depleted in Alzheimer disease plasma11.


Researchers have only recently begun to address the mechanism by which Aβ oligomers impair synaptic function. These studies have included attempts to identify the cell surface receptors and signaling pathways mediating Aβ-induced synaptoxicity. For example, Aβ42 can inhibit presynaptic nicotinic acetylcholine receptors (nAChR) and evoke changes in presynaptic Ca2+ levels in rat hippocampus and neocortex12. Given that only picomolar concentrations of Aβ42 were effective in those experiments, the inhibitory action of Aβ42 was postulated to be the result of competing with nicotine to prevent it from stimulating the receptors. The effects were sensitive to α-bungarotoxin and other agents, specifically implicating α7-nAChRs in the pathway by which Aβ42 disrupts synaptic plasticity. Now, in a major leap forward, Snyder et al.3 report a very elegant set of experiments elucidating a potential pathway by which Aβ reduces glutamatergic transmission and NMDA receptor–dependent LTP. In their study, the application of Aβ42 to cultured cortical neurons promoted endocytosis of NMDA receptors, effectively reducing the density of NMDA receptors at synapses. In agreement with this result, reduced levels of surface NMDA receptors were observed on neurons in APPSwe (TG2576) transgenic mice that overproduce Aβ42. Aβ42 also engendered a rapid and persistent depression of NMDA-evoked currents. Delving further into the mechanism by which Aβ42 induces endocytosis of NMDA receptors, Snyder et al.3 found that α7 nicotinic receptors, protein phosphatase 2B (PP2B; calcineurin) and the cytosolic form of the tyrosine phosphatase ‘striatal enriched phosphatase’ (STEP46) were required in the synaptotoxic pathway (Fig. 1). Aβ42, derived from processing of APP, enters into the synaptic cleft and binds the α7-nicotinic receptor, leading to

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Figure 1 Effects of Aβ42 on NMDA receptor internalization at the synapse. Aβ42 promotes the endocytosis of NMDA receptors, reducing the density of NMDA receptors at synapses. Aβ42 can be secreted into the synaptic cleft via sequential cleavage of the Aβ precursor protein (APP, shown presynaptically) by β-secretase and γ-secretase. Familial Alzheimer disease mutations in genes encoding APP and the presenilins (PSEN1 and PSEN2) selectively increase the production of Aβ42. Aβ42 binds the α7-nicotinic receptor (shown postsynaptically), which then leads to the activation of calcineurin (PP2B). PP2B then promotes the dephosphorylation of the tyrosine phosphatase, striatal enriched phosphatase (STEP46), either directly, or through DARPP-32. This leads to the activation of STEP46, which gates NMDA receptor activation and LTP. STEP46 activation promotes the dephosphorylation of Tyr1472 of the NMDA receptor subunit NR2B. This may occur either directly or via STEP46-mediated dephosphorylation or downregulation of the NMDA receptor-associated kinase, Fyn. Tyr1472 regulates binding of the NMDA receptor to PSD-95 and adaptor protein (AP2); dephosphorylation of this residue is postulated to promote endocytosis of the NMDA receptor in clathrin-coated vesicles (CCV). In this manner, persistent binding of Aβ42 to α7-nicotinic receptor leads to reduced NMDA receptor density at synapses, decreasing glutamatergic transmission and impairing synaptic plasticity.

the activation of PP2B. PP2B then promotes the dephosphorylation and thus activation of STEP46, which is known to gate NMDA receptor activation and LTP. STEP46 activation is then postulated to promote dephosphorylation of Tyr1472 of the NMDA receptor subunit, NR2B. This is followed by increased endocytosis of NMDA receptors in clathrin-coated vesicles. The end result is a reduced density of NMDA receptors and impairments in glutamatergic transmission and synaptic plasticity, including reduced LTP. Clearly, this previously unknown pathway, along with the impressive tour de force used to delineate it, will require further investigation and confirmation in future studies. Moreover, several key questions remain to be addressed.

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For example, it is not clear whether PP2B directly activates STEP46 or does so through other factors, such as DARPP-32. Likewise, it is not clear whether STEP46 directly dephosphorylates Tyr1472 of NR2B, or promotes this event by means of downregulation of the NMDA receptor-associated kinase, Fyn, which is believed to phosphorylate Tyr1472. It is also not obvious how dephosphorylation of NR2B-Tyr1472 actually leads to endocytosis of the NMDA receptor. One possibility proposed by Snyder and colleagues is that the phosphorylation state at this tyrosine regulates binding of the NMDA receptor to PSD-95 and the adaptor protein AP-2, and dephosphorylation of this residue promotes endocytosis of the NMDA receptor

in clathrin-coated vesicles (CCV). Finally, given that the authors3 could not completely block NMDA receptor endocytosis with αbungarotoxin, it is possible that additional receptor mechanisms may be involved in Aβ42-induced NMDA receptor internalization. While these and many other details will need to be worked out, Snyder et al.3 have put forward a compelling working model for how Aβ42 reduces NMDA receptor density at synapses, leading to attenuated glutamatergic transmission and impaired synaptic plasticity. This synaptotoxic Aβ pathway raises two critical questions. First, can synaptic plasticity be restored by reducing levels of Aβ42 in synapses, thereby ameliorating cognitive deficits in Alzheimer disease? Second, regarding potential therapies aimed at achieving this goal, should we be concerned that Aβ may have a physiological role in regulating LTP in glutamatergic and other synapses? Regarding the second question, low, non-toxic concentrations of Aβ can reduce LTP and glutamatergic transmission13. Based on these data, these authors proposed that activity-dependent modulation of Aβ may normally provide negative feedback to keep neuronal hyperactivity in check. Furthermore, they suggested that disruption of this feedback system and prolonged depression of NMDA receptor-mediated transmission by Aβ could contribute to Alzheimer disease pathogenesis. Others have suggested a potential role for Aβ in mediating oxidative stress, which can detrimentally affect synaptic integrity (reviewed in ref. 14). These concerns indicate a need for careful scrutiny of any potential therapeutics aimed at diminishing Aβ levels in synapses. With regard to the therapies that might be used to alleviate Aβ-induced synaptoxicity, two basic strategies can be considered. First, production of Aβ itself can be reduced, for example by inhibiting β-secretase and/or γ-secretase activities. In this option, inhibitors would optimally be selective for APP, to minimize undesirable effects on other secretase substrates. In addition, it would be preferable for the APP-selective γ-secretase inhibitor to preferentially decrease the generation of Aβ42, the species shown by Snyder et al.3 to impair glutamatergic transmission. However, it is important to point out that the relative efficacy of Aβ40 in promoting NMDA receptor internalization is still unclear. In the second therapeutic option, attempts to promote clearance of Aβ42 from synapses could be made. Along these lines, intracerebroventricular injection of naturally secreted human Aβ can inhibit LTP in rat hippocampus, and a monoclonal antibody targeted at Aβ com-



NEWS AND VIEWS pletely blocks this effect15. However, delivering such an antibody safely and effectively to an Alzheimer disease patient’s brain and avoiding adverse effects such as encephalitis might not be trivial. Other therapeutic possibilities might include inhibiting oligomeric Aβ assemblies, for instance, with metal-complexing agents or glycosaminoglycan mimetics. However, in any Aβ clearance strategy it would be important to monitor for the possible effects of dissolution of fibrillar Aβ into potentially synaptotoxic Aβ oligomers. In conclusion, increasing evidence shifts our understanding of Alzheimer disease patho-

genesis toward emphasizing the synaptotoxic properties of oligomeric Aβ rather than fibrillar Aβ, such as is found in β-amyloid plaques. Future investigations addressing the emerging synaptic Aβ hypothesis, and particularly the molecular mechanism by which Aβ promotes synaptic dysfunction, such as that described in the new paper3, will be critical for the design of safe and effective anti–Aβ therapeutics aimed at preventing and treating Alzheimer disease. 1. Glenner, G.G. & Wong, C.W. Biochem. Biophys. Res. Commun. 120, 885–890 (1984). 2. Selkoe, D.J. Neuron 6, 487–498 (1991). 3. Snyder, E. et al. Nat. Neurosci. 8, 1049–1056 (2005).

4. Tanzi, E. Riv. Sperim. Freniatr. Med. 19, 419–472 (1893). 5. Tanzi, R.E. & Bertram, L. Cell 120, 545–555 (2005). 6. Terry, R.D. et al. Ann. Neurol. 30, 572–580 (1991). 7. Larson, J., Lynch, G., Games, D. & Seubert, P. Brain Res. 840, 23–35 (1999). 8. Lambert, M.P. et al. Proc. Natl. Acad. Sci. USA 95, 6448–6453 (1998). 9. Walsh, D.M. et al. Nature 416, 535–539 (2002). 10. Cleary, J.P. et al. Nat. Neurosci. 8, 79–84 (2005). 11. Moir, R.D. et al. J. Biol. Chem. 280, 17458–17463 (2005). 12. Dougherty, J.J., Wu, J. & Nichols, R.A. J. Neurosci. 23, 6740–6747 (2003). 13. Kamenetz, F. et al. Neuron 37, 925–937 (2003). 14. Lee, H.G., Moreira, P.I., Zhu, X., Smith, M.A. & Perry, G. Am. J. Pathol. 165, 1461–1464 (2004). 15. Klyubin, I. et al. Nat. Med. 11, 556–561 (2005).

Beyond migration: Dlx1 regulates interneuron differentiation Carl Wonders & Stewart Anderson A new paper shows that the transcription factor Dlx1, known to be involved in neuronal migration, is also necessary for interneuron survival. Mice lacking Dlx1 show subtype-specific loss of interneurons, a reduction in inhibitory currents and generalized seizures.

A century ago, Cajal speculated that the remarkable diversity of cortical interneuron morphology underlies specific functions that are fundamental to human thought. Later studies revealed that most of these neurons use the inhibitory neurotransmitter GABA, and that the inhibition of GABA signaling produces fear-related behaviors and seizures. In addition, interneuron function has been implicated in the coordinated recruitment of large networks of pyramidal neurons that underlies a key component of prefrontal cortical function: working memory1. Analyses of mutant rodents with abnormal numbers or function of cortical interneurons, with correlated behavioral abnormalities, have advanced our understanding of interneuron function2–6. However, the lack of specificity of these mutations for cortical interneurons has complicated the interpretation of these studies. A paper7 in this issue by Cobos et al. marks an important advance in understanding the genetic regulation of postnatal interneuron development and function. In the basal embryonic forebrain, the transcription factor gene Dlx1 and the related gene Dlx2 regulate the ability of newly born neurons to migrate Carl Wonders and Stewart Anderson are at the Department of Psychiatry, Weill Medical College of Cornell University, 1300 York Avenue, New York, New York 10021, USA. e-mail: [email protected]

away from the proliferative zone. One neuronal subgroup affected in Dlx1/Dlx2 double mutants are cortical interneurons, most of which, in rodents, originate in the basal forebrain. In mice and in humans, both Dlx1 and Dlx2 continue to be expressed as interneurons migrate to and begin to differentiate within the cerebral cortex, but a function of these proteins in later aspects of interneuron development had not been described. Through an impressive combination of histological, electrophysiological and cell transplantation studies, Cobos et al. demonstrate that adult mice lacking Dlx1 develop selective interneuron losses and seizures7. They began by showing that, during the first few postnatal weeks, Dlx2 expression in cortical interneurons subsided, while Dlx1 expression became restricted to subgroups of interneurons expressing calretinin, neuropeptide Y and somatostatin (Fig. 1). Analysis of Dlx1–/– mice revealed selective losses of these same interneuron subgroups by the third or fourth postnatal week. In contrast, interneurons expressing the interneuron subgroup marker parvalbumin were not affected. Although the number of GAD67-expressing, inhibitory interneurons at postnatal day 12 was normal, the Dlx1–/– mice showed increased numbers of apoptotic cells by 4 weeks of age. This suggests that Dlx1 function is required for the survival of many calretinin-, neuropeptideY- and somatostatin-expressing interneurons.


Furthermore, this selective loss of interneurons was associated with a reduction of inhibitory postsynaptic current in the hippocampus and neocortex, increased seizures by 2 months of age, and evidence of seizure-induced histological changes. The selective losses of those interneuron subgroups that normally maintain Dlx1 expression is remarkable, but how can one prove that this reflects a cell-intrinsic function of Dlx1? To address this, the authors used a new transplantation assay, in which the Dlx1 mutant mice were crossed into a pan–green fluorescent protein (GFP)-expressing line, and interneuron progenitors from the basal telencephalon of these mutants were transplanted directly into the cortical plate of neonatal pups. This technique allowed the authors to study the role of Dlx1 in transplanted progenitors while they differentiated within a ‘normal’ cortical environment. Like the results from histological analysis of the Dlx1 mutants, two months after transplantation of Dlx1–/– interneuron progenitors, there was a marked reduction in the percentage of surviving neurons that expressed calretinin, neuropeptide Y and somatostatin. Transplanted interneurons expressing parvalbumin were not affected. Analysis of transplants after shorter survival times showed that decreased dendritic length and branching preceded the cell loss. Thus, the authors are able to demonstrate a cell-autonomous requirement for Dlx1 within a subset of

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NEWS AND VIEWS cortical interneurons and also identify a new potential function of Dlx1 in the maturation of dendritic morphology. In outbreeding the Dlx1-null mice to the GFP-expressing line for transplantation studies, Cobos et al. produced a remarkable alteration in mutant phenotype. Inbred Dlx1–/– mice on a C57/B6 background generally die by the fourth postnatal week. Thus, a single generation of outbreeding resulted in a dramatic shift in survival. This shift raises the question of whether inbred Dlx1 nulls also have normal numbers of GAD67-expressing cells at P12, or whether the apparent selectivity of the interneuron phenotype to the post-migratory phase of their development is a product of the outbreeding itself. In addition, would further outbreeding attenuate the observed phenotype, and what other genetic variations are interacting with Dlx1 to cause such a profound change? Several other questions remain. First, how does the postnatal phenotype of the Dlx1 mutants relate to the prenatal loss of most interneuron migration into the cerebral cortex in the Dlx1/Dlx2 double mutants? The authors point out that the Dlx1-null phenotype develops roughly as the postnatal expression of Dlx2 subsides, raising the possibility that this timing reflects the functional redundancy of these genes at both embryonic and postnatal stages. Knockin strategies that test the ability of one gene to substitute for the other should shed light on this issue. Beyond that, could the targets of Dlx1 and Dlx2 be similar at embryonic and postnatal stages? It has been suggested that disinhibition of Notch signaling accounts for aspects of the phenotype of Dlx1/Dlx2–/– mice with respect to the developing striatum8. The postnatal Dlx1 phenotype could be directly connected to the developmental phenotype through Notch regulation of dendritogenesis, in which increased Notch signaling is associated with restriction or retraction of dendritic growth (by cortical projection neurons in vitro)9. Alternatively, a link between the Dlx1/Dlx2-null prenatal and the Dlx1-null postnatal phenotypes could involve the regulation of cytoskeletal components of neurite extension and neuronal migration. Indeed, treatment of dissociated striatal cultures with antisense oligonucleotides against Dlx2 reduces dendritic extension10. To date, however, specific targets of Dlx1 include only the Dlx5/Dlx6 intergenic enhancer11. A second question relates to the relationships between the observed reduction of cortical interneurons and the changes in physiology that the authors observed. Cobos et al. found that the Dlx1–/– mice had reductions in both the frequency and the amplitude of spontaneous inhibitory postsynaptic currents in both the neocortex and the hippocampus. The mice

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Figure 1 Transcription factor markers of cortical interneuron subgroup development. ‘p’ denotes a precursor stage that does not yet express the given marker. MGE, medial ganglionic eminence; CGE, caudal ganglionic eminence; Pv, parvalbumin; Som, somatostatin; NPY, neuropeptide Y; CR, calretinin.

developed seizures when subjected to mild stressors such as noise or handling when they were over 2 months old, and they also showed histological changes (increased neuropeptide Y immunoreactivity, ectopic expression of neuropeptide Y in projecting neurons and axonal sprouting) associated with seizures at this age. Dlx1–/– mice also had greater theta rhythm amplitude during exploratory activity than did wild-type littermates, and they developed cortical seizures. Detailed electrophysiological and connectivity studies comparing normal and Dlx1–/– mice, in a homogeneous genetic background, will be required to connect these levels of GABAergic phenotypes. Finally, what causes the 1-month delay between the detectable loss of somatostatinand calretinin-expressing interneurons and the onset of seizures? The authors discuss several plausible explanations, including the possibility that compensatory mechanisms such as increased feedback inhibition can temporarily prevent epileptogenesis. An alternative possibility is that the onset of seizure activity is determined by the interaction between interneuron losses and the normal maturation of cortical circuitry. There is considerable refinement in both excitatory and inhibitory aspects of cortical circuitry during the peripubertal period12. Moreover, in mice, maturation of cortical inhibition mediates the alterations in cortical plasticity that occur over the peripubertal age range13. This effect is mediated by

the GABAA receptor α1 subunits that mainly localize to the cell soma and axon initial segment of projection neurons, the primary targets of parvalbumin-expressing interneurons (not directly affected in the Dlx1 mutants). Thus, the refinement of cortical connectivity during puberty, in combination with the loss of some somatostatin- and calretinin-expressing interneurons, may dictate the onset of seizure activity. Interestingly, parvalbumin knockout mice themselves have a lower seizure threshold, apparently owing to increased activity in the normally parvalbumin-expressing interneurons that produces hypersynchrony6. This discussion raises a crucial point concerning the importance of the Cobos et al. paper in its implication for cortical disease. The authors point out that the brains of people with schizophrenia show a tendency for reduced connectivity of a subtype of parvalbumin-expressing interneuron. As a model of schizophrenia per se, Dlx1 mutants may not be useful, as people with schizophrenia have neither reductions in calretinin-expressing interneurons14 nor increases in epilepsy, and their abnormality of cortical synchrony is primarily in the gamma band15 rather than in the theta band as reported for the Dlx1–/– mice. However, as a model of a phenotype that may be fairly specific for postnatal interneuron development, studied with a combination of histological, electrophysiological and cell transplantation methods, this paper raises the bar



NEWS AND VIEWS for future studies on the relationship between interneuron development and cortical function. Further extension of this analysis to the question of how the histological and behavioral phenotypes affect, and are affected by, normal developmental changes will begin to bridge the connection between gene function and ‘late’ developmental phenotypes. Armed with conditional knockout and knock-in strategies, more detailed stereological and behavioral methods and electrophysiological recording from transplanted cells, researchers may find that answers to some of the most complex questions of

interneuron development and cortical function are finally ripe for the picking. 1. Wang, X.J., Tegner, J., Constantinidis, C. & GoldmanRakic, P.S. Proc. Natl. Acad. Sci. USA 101, 1368– 1373 (2004). 2. Sarkisian, M.R., Frenkel, M., Li, W., Oborski, J.A. & LoTurco, J.J. Cereb. Cortex 11, 734–743 (2001). 3. Powell, E.M. et al. J. Neurosci. 23, 622–631 (2003). 4. Pillai-Nair, N. et al. J. Neurosci. 25, 4659–4671 (2005). 5. Erbel-Sieler, C. et al. Proc. Natl. Acad. Sci. USA 101, 13648–13653 (2004). 6. Schwaller, B. et al. Mol. Cell. Neurosci. 25, 650–663 (2004).

7. Cobos, I. et al. Nat. Neurosci. 8, 1057–1066 (2005). 8. Yun, K. et al. Development 129, 5029–5040 (2002). 9. Sestan, N., Artavanis-Tsakonas, S. & Rakic, P. Science 286, 741–746 (1999). 10. Ding, M. et al. J. Mol. Neurosci. 8, 93–113 (1997). 11. Zhou, Q.P. et al. Nucleic Acids Res. 32, 884–892 (2004). 12. Anderson, S.A., Classey, J.D., Conde, F., Lund, J.S. & Lewis, D.A. Neuroscience 67, 7–22 (1995). 13. Fagiolini, M. et al. Science 303, 1681–1683 (2004). 14. Daviss, S.R. & Lewis, D.A. Psychiatry Res. 59, 81–96 (1995). 15. Spencer, K.M. et al. Proc. Natl. Acad. Sci. USA 101, 17288–17293 (2004).

Less is more: progenitor death and cortical size Pasko Rakic Cerebral cortex size in individuals and species is determined by cortical progenitor mitosis and death during embryogenesis. EphA signaling—important in axon guidance and patterning—also seems to be critical in regulating the survival of cortex progenitors.

Nothing in biology, it is said, makes sense unless viewed in light of evolution. Thus the mechanisms underlying expansion of the cerebral cortex are central to understanding the potential and limits of our mental capacity. The species-specific size of the cerebral cortex is determined by proliferation and apoptosis rates in the embryonic proliferative zones situated near the surface of the fluid-filled cerebral ventricles. Genetic and cellular mechanisms by which the neocortex expands have only begun to be explored, and a number of candidate genes that control cell proliferation have been identified. A recent report in Nature by Depaepe et al.1 adds another potentially important player, the ephrin-A/EphA signaling pathway, to the list of genes involved in the managed production of cortical neurons. Their finding, that the level of EphA signaling determines the rate of programmed death (apoptosis) of neuronal progenitors, is surprising because ephrin signaling has not been previously implicated in regulating cell death or in the apoptosis of neural progenitor cells. Furthermore, the new paper1, along with several previous studies, provides an instructive example of the synergy between pro- and antiapoptotic effects and how less (i.e., progenitor death) can result in more (i.e., adult neurons) in the cerebral cortex (Fig. 1). Pasko Rakic is in the Department of Neurobiology and the Kavli Institute for Neuroscience, Yale University School of Medicine, 333 Cedar Street, New Haven, Connecticut 06511, USA. e-mail: [email protected]

The cerebral cortex is by far the largest structure of the human brain, but its constituent neurons are not generated locally in the cortex itself. As in other mammalian species, human cortical neurons are produced in the proliferative ventricular and subventricular zones (VZ and SVZ) and migrate from there into distinct cerebral cortical areas. Postmitotic cells, produced in succession within these zones, migrate across the intermediate and subplate zones following transient radial glial scaffolding before entering the increasingly more distant cortical plate where they form arrays of radial columns2. According to the radial unit hypothesis, increased cell production at early stages (before the onset of neurogenesis) would result in increased numbers of founder cells that give rise to radial columns, whereas increases in production at later stages would increase the number of neurons within each column2 (Fig. 1). There are several examples of how these two phases of cell proliferation can be regulated by distinct sets of genes. For example, overexpression of β-catenin in the mouse brain produces a larger number of neuronal progenitors and eventually more neurons by inhibiting the decision of progenitors to exit the cell cycle in the proliferative zones at early stages3. The increase in the number of radial columns in the cortical plate leads to the formation of elaborate cortical convolutions in this rodent species that normally has a smooth (lissencephalic) hemispheric surface3. In contrast, overexpression of cyclin-depen-


dent kinase (cdk) inhibitor p27 at later stages increases production of neurons that form radial columns, thus increasing the thickness of the superficial layers of the cortex, without increasing its surface area4,5. Programmed cell death of progenitor cells can also affect cerebral cortical size6,7. For example, activation of the Notch signaling pathway induces apoptosis in the VZ by activation of the p53 tumor suppressing pathway, leading to a smaller telencephalon8. Conversely, reduction in the apoptosis of founder cells in the ventricular zone can produce supernumerary progeny. Thus, when caspases, the mammalian homologs of the nematode CED-3 family of killer genes, are knocked out, apoptosis decreases in the cerebral ventricular zone, resulting in the formation of supernumerary cells in the telencephalon9,10. Many of these cells accumulate in the white matter. However, in confirmation of the radial unit hypothesis2 (Fig. 1), a larger-than-normal number of founder cells resulted in a cortex with an increased surface area and the formation of convolutions11. This suggests that the observed phenotype resulted from interference with the programmed death of progenitors in the VZ during early neurogenesis without affecting the ability of excessive cells to migrate normally and deploy radially in the cortex. Interestingly, the survival of cells can also be increased by slowing down the clearance of apoptotic cells by preventing the normal course of phagocytosis in the VZ with a similar effect on cortical expansion12.

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Figure 1 Radial unit lineage model of cortical neurogenesis. The model illustrates how changes in the mode and the rates of cell proliferation and/or programmed cell death within the pool of neural stem cells in the ventricular zone that divide symmetrically at early embryonic stages causes an exponential increase in the number of radial columns. That in turn results in surface expansion of the cerebral cortex without changes in its thickness. In contrast, similar changes in proliferation kinetics occurring in the founder cells, which divide asymmetrically, cause a linear increase in number of neurons within radial columns without a change in the cortical surface area. VZ, ventricular zone. SD, symmetrical division. CC, cerebral cortex. AsD, asymmetrical division. Figure adapted from ref. 2.

Now, Depaepe et al.1 provide evidence that ephrins and Eph receptor genes, which are generally considered important players in pattern formation and axonal guidance, are also involved in controlling neuronal production in the telencephalon. Their experiments using dissociated cortical progenitors show that stimulation with soluble ephrin-A5-Fc can induce caspase-3 activity and produce TUNEL-positive apoptotic cells, all within 15 min. This rapid induction of apoptosis suggests that some specific effector pathway downstream of the ephrin-Eph receptor interaction can directly trigger apoptosis in neural progenitors. It is surprising that this rapid pro-apoptotic effect of ephrin signaling has not been previously identified. Depaepe et al.1 also generated doubly transgenic mice that express ephrin-A5 under the control of the EphA7 regulatory elements.

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Overexpression of ephrin-A5 in progenitors expressing EphA7 resulted in increased apoptosis of neuron-producing progenitors, which in turn resulted in an overall smaller cerebral cortex. In addition, the authors used a battery of tests, including expression of pan-neuronal and class-specific neuronal markers, to show that cell migration, the settling pattern and even initial differentiation of neural precursors were normal. These gain-of-function experiments indicate that over-activation of ephrin/Eph signaling can decrease production of cortical founder progenitors. Next, Depaepe et al. showed that the opposite occurred when ephrinA/EphA7 signaling was abolished. In mice lacking EphA7 (ref. 13), apoptosis was reduced by about half, resulting in formation of a larger-than-normal cerebral cortex. Again, probably owing to preservation of radial scaffolding, most

overproduced neurons migrated properly, resulting in a larger cortical surface that begins to show incipient convolutions. The overproduced neurons did not make a large lump or thicker cortical plate but rather produced a relatively normal-looking cortex with an enlarged surface, indicating that the saved progenitors have retained the cellular machinery that delivers their progeny sequentially into overlying radial columns. All of the diverse metabolic pathways mentioned above are involved in some way in regulating production of neurons destined for the cerebral cortex. No one has expected that so many molecules would be involved. As a next step, it will be important to find out how such complex and diverse molecular cascades are orchestrated. Future studies are also needed to discern the molecular mechanism that couples ephrin signaling to apoptosis. Moreover, it will be of interest to determine whether ephrin signaling can trigger caspase activity locally to regulate cell migration and/or growth cone guidance during axon pathfinding. It may be significant that all effects occur predominantly in the forebrain. Finally, because ephrins and Eph receptors often show reciprocal expression patterns in the developing cerebral wall, one may wonder whether the ephrin signaling–induced apoptosis may serve as a mechanism to confine the distribution of neural progenitor cells to specific areas. Regional differences in the expression of ephrins in the embryonic cerebrum have been detected in both rodents and higher primates14,15, opening the opportunity to investigate molecular mechanisms and cellular events that have driven expansion of the cerebral cortex during evolution. 1. Depaepe, V. et al. Nature 435, 1244–1250 (2005). 2. Rakic, P. Trends Neurosci. 18, 383–388 (1995). 3. Chenn, A. & Walsh, C.A. Cereb. Cortex 13, 599–606 (2003). 4. Delalle, I. et al. Cereb. Cortex 9, 824–832 (1999). 5. Tarui, T. Cereb. Cortex 15, published online 12 January 2005 (doi:10.1093/cercor/bhi017). 6. Blaschke, A.J., Staley, K. & Chun, J. Development 122, 1165–1174 (1996). 7. Thomaidou, D., Mione, M.C., Cavanagh, J.F. & Parnavelas, J.G. J. Neurosci. 17, 1075–1085 (1997). 8. Yang, X. et al. Dev. Biol. 269, 81–94 (2004). 9. Kuida, K. et al. Nature 384, 368–372 (1996). 10. Kuida, K. et al. Cell 94, 325–333 (1998). 11. Haydar, T.F., Kuan, C.-Y., Flavell, R.A. & Rakic, P. Cereb. Cortex 9, 621–626 (1999). 12. Li, M., Sarkisian, M.R., Mehal, W., Rakic, P. & Flavell, R.A. Science 302, 1560–1563 (2003). 13. Dufour, A. et al. Neuron 39, 453–465 (2003). 14. Campbell, D.C. & Holt, C.E. Neuron 37, 939–952 (2003). 15. Donoghue, M.J. & Rakic, P. Cereb. Cortex 9, 586–600 (1999).


NEWS AND VIEWS

Rethinking the thalamus Paul W Glimcher & Brian Lau


Reward-sensitive neurons are present throughout the brain. A report in Science now shows that a subset of thalamic neurons respond selectively to the smaller of two rewards, as opposed to just reflecting reward magnitude, as do neurons in other brain areas.

Most neurobiologists working today were brought up to believe in a few fundamental truths: the neuron doctrine, the electrical nature of the action potential and that the thalamus is uninteresting. Recently, however, neuroscientists have been trying to explain why so many neural circuits seem to involve multiple, highly organized passes through this ‘uninteresting’ structure. Surely this indicates that the thalamus must do something, but what? One group of theoreticians proposed that striatal loops involving the thalamus may help select a single action for execution out of the multiple actions competing for access to the musculature1,2. In parallel, physiologists have recorded from neurons throughout these striatal loops in monkeys performing visuomotor tasks. The most recent physiological study of these loops attempts to consolidate these two approaches by adding a twist to the competition hypothesis. In Science, Kimura and colleagues3 present neurophysiological data from the intralaminar thalamus suggesting the existence of a previously unknown process that is activated when an animal must execute an action that yields a relatively small reward. To understand this new work, however, one has to place it within the context of other studies of the thalamus. Besides containing sensory nuclei such as the lateral and medial geniculate nuclei, the thalamus seems to be locked into at least two interrelated sets of processing loops4–6. The first are the parallel corticostriatal loops proposed in ref. 4 and later elaborated upon anatomically7. These loops consist of cortical projections to the striatum, which, through the basal ganglia output nuclei, connect to the thalamus and then back to the originating cortical regions. These pathways are segregated into five largely independent functional subloops that have been the subject of much physiological inquiry8,9. There is also compelling evidence for the existence of five additional loops6 that pass Paul Glimcher and Brian Lau are at the Center for Neural Science, New York University, New York, New York 10003, USA. e-mail: [email protected]

through midline regions of the thalamus (Fig. 1a). These connect the striatum, an area known to process reward-related information, to itself. The thalamostriatal loops involve the midline intralaminar nuclei, particularly the caudal intralaminar group, which is composed primarily of the centromedian-parafascicular complex. It is this complex that forms the main way station for most of the thalamostriatal loops. In the skeletomotor thalamostriatal loop, for example, the centromedian nucleus projects to the postcommisural putamen, a skeletomuscular nucleus of the basal ganglia. This region of the putamen projects, in turn, to the globus pallidus, which closes the loop by projecting back to the centromedian thalamus (Fig. 1b). Kimura and colleagues have been examining the properties of neurons in the skeletomuscular thalamostriatal loop for some time now, focusing on neurons of the centromedian-parafascicular complex. Their initial studies10,11 showed that these neurons are multimodal, responding to a variety of sensory signals both during and outside of operantly conditioned reaching tasks. They have classified neurons into two physiologically distinct groups on the basis of the speed with which they respond to visual or auditory stimuli: short-latency facilitatory neurons found mostly in the parafascicular nucleus (and thus associated with limbic and cognitive thalamostriatal loops) and long-latency facilitatory neurons found mostly in the centromedian nucleus (and thus associated primarily with the skeletomotor thalamostriatal loop). Furthermore, inactivation of the centromedian-parafascicular complex decreases the reward-related responses of tonically active neurons in the regions of the striatum to which they project10. Kimura and colleagues3 now report recordings from long-latency facilitatory centromedian neurons in macaques trained to perform a traditional ‘go’/‘no-go’ reaching task. In this task, the monkey placed one hand on a central button to begin each trial. After a delay, a second button was illuminated yellow at one of two possible locations; then it changed either to green or to red. As soon as the monkey detected the onset of the green


button (a ‘go’ trial) he had to reach for it to earn a fluid reward. If, however, he detected a red button instead (a ‘no-go’ trial,) he had to hold position on the initial yellow button for 0.75 s to be rewarded. Across blocks of 60–120 trials, the authors varied which action was associated with a large reward (+R) and which was associated with a small reward (–R). Therefore, on the first block, the monkey might have earned a large reward for the go response on go trials and a small reward for the no-go response on no-go trials. This was then reversed in the next block. Of course, making the wrong response—for example, a go response on a no-go trial—earned the monkey no reward regardless of whether it was a +R or a –R condition. The authors found that many neurons in the centromedian thalamus responded more vigorously on –R trials than on +R trials irrespective of trial type (go or no-go). This finding is important for three reasons. First, this is the first time that thalamic neurons—in this case, in the thalamostriatal loop associated with skeletal movements—have been shown to be influenced by reward magnitude. Second, the neurons responded strongly for both go and no-go trials that yielded low rewards, indicating that the neurons were not selective for the action that the monkey was required to produce, but rather for the more abstract value of the trial. Third, this modulation seems to be reversed compared with most of the reward-related responses that have been observed in other areas. For example, neurons in posterior and frontal cortex respond more strongly to larger rewards. In contrast, centromedian neurons responded more for small rewards than for large rewards, a phenomenon that has not been reported previously. To interpret these findings, it is important to note that the activity of many neurons outside the thalamus has been correlated with response bias, the behavioral observation that subjects are often biased toward selecting one particular response over another. If reaching for a lighted button earns a large reward and withholding that action earns a small reward, then human and animal subjects are more likely to reach for the button than to withhold the movement; they show a response bias that favors reaching. Neurons

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Figure 1 Parallel thalamostriatal loops involving the basal ganglia and the thalamus in monkeys (after ref. 6). (a) These loops have been classified on the basis of the anatomical segregation of neurons in the striatum, which project to distinct pallidal regions, either the internal segment of the globus pallidus (GPi) or the substantia nigra pars reticulata (SNr). The intralaminar loops are closed after passing through distinct nuclei of the centromedian (CM)-parafascicular (PF) complex. (b) Major thalamic nuclei involved in corticostriatal and thalamostriatal loops.

throughout the visual-oculomotor pathway, for example, show enhanced responses such as shifts in baseline activity12,13 that are correlated with these behavioral biases. The thalamic signal Kimura and colleagues have identified does not correspond directly to a response bias of this type. Their neuronal signal is strongest when the animal must choose between a movement that will yield a small reward and withholding that movement, where withholding the movement will yield no reward on this trial but has yielded large rewards on other trials. They therefore propose that the behaviorally observed phenomenon of response bias may be the product of two complementary underlying neural processes. The first of these would be, in essence, a pre-bias process (a process more strongly correlated with large rewards than the choice behavior of the animal), and the second would be a complementary pre-anti-bias process (a process that is active when an animal must choose a relatively small reward action). They hypothesize that it is the combination of these two signals that yields the overall response bias we observe in behavior and that the thalamic signals they have observed reflect this antibias process. Although the precise form of their hypothesis is unique in some ways, previous work14 has identified signals in the basal ganglia that may be related to the pre-bias process that Kimura and colleagues propose, and another study15 has identified signals in the frontal eye fields that can also be characterized as competing go and no-go processes. As well, signals in the supplementary eye fields

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are correlated with the interactions of these go and no-go processes. Working with their notion that a pre-bias process would be most active whenever a large-reward go trial was imminent, one might expect that the complementary anti-bias process would also have to be more active if the monkey had to withhold that go response for some reason. To examine this prediction, they trained another monkey on a version of the go/no-go task where a large reward trial was guaranteed after a maximum of three small reward trials. They found that centromedian responses were strongest on small-reward nogo trials that were the third and last in a series of small-reward trials. So it was not just a small reward that activated these neurons; instead, a small reward certain to be followed by a large reward activated these neurons more than a small reward likely to be followed by another small reward. Kimura and colleagues hypothesize that this is the case specifically because thalamic activity serves as a compensatory anti-bias process that offsets a growing prebias signal, which was suggested by the error rate data in this version of the task. If these centromedian neurons inhibit or counteract a pre-bias signal, then strong artificial activation of centromedian neurons should reveal the anti-bias process by eliciting the incorrect action—an action the monkeys know to be unreinforced. To test this, Kimura and colleagues microstimulated in the centromedian nucleus just before a small fraction of high-reward go trials. They found that stimulation on these trials did slow reaction

times, although it only rarely stopped the go movement completely. This inhibition of a go response, in effect causing a no-go response, is consistent with the predictions of their model. The result, however, raises the question of whether stimulation during large-reward no-go trials might result in accidental go responses. It also leads one to ask what effect centromedian microstimulation has when the animal is equally reinforced on go and no-go trials? Is centromedian stimulation effective only when the rewards for two or more actions have different magnitudes? Kimura and colleagues have suggested a bold new hypothesis for response selection. They have proposed that the tight linkage that has been observed between behavior and activity in a number of decision-making areas may reflect the activity of two processes: a pre-bias process and a complementary process driven by neurons of the centromedian thalamus. Even more exciting, however, is that they are exploring this hypothesis in the thalamus. Response bias–related signals have been observed throughout the cortex and basal ganglia, both of which are intimately connected with the thalamus. By exploring issues related to cognitive processes in the thalamus, Kimura and colleagues are helping to open a critical avenue for future research. Future experiments will have to be conducted to test this new model against its competitors, but now those tests will have to include physiological studies in the thalamus, a development that has been long overdue. 1. Redgrave, P., Prescott, T.J. & Gurney, K. Neuroscience 89, 1009–1023 (1999). 2. Wise, S.P., Murray, E.A. & Gerfen, C.R. Crit. Rev. Neurobiol. 10, 317–356 (1996). 3. Minamimoto, T., Hori, Y. & Kimura, M. Science 308, 1798–1801 (2005). 4. Alexander, G.E., DeLong, M.R. & Strick, P.L. Annu. Rev. Neurosci. 9, 357–381 (1986). 5. Parent, A. & Hazrati, L.N. Brain Res. Rev. 20, 91–127 (1995). 6. Smith, Y., Raju, D.V., Pare, J.F. & Sidibe, M. Trends Neurosci. 27, 520–527 (2004). 7. Middleton, F.A. & Strick, P.L. Brain Res. Rev. 31, 236–250 (2000). 8. Sommer, M.A. Curr. Opin. Neurobiol. 13, 663–670 (2003). 9. Wyder, M.T., Massoglia, D.P. & Stanford, T.R. J. Neurophysiol. 91, 2628–2648 (2004). 10. Minamimoto, T. & Kimura, M. J. Neurophysiol. 87, 3090–3101 (2002). 11. Matsumoto, N., Minamimoto, T., Graybiel, A.M. & Kimura, M. J. Neurophysiol. 85, 960–976 (2001). 12. Platt, M.L. & Glimcher, P.W. Nature 400, 233–238 (1999). 13. Shadlen, M.N. & Newsome, W.T. J. Neurophysiol. 86, 1916–1936 (2001). 14. Lauwereyns, J., Watanabe, K., Coe, B. & Hikosaka, O. Nature 418, 413–417 (2002). 15. Schall, J.D., Stuphorn, V. & Brown, J.W. Neuron 36, 309–322 (2002).



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Persistent hippocampal CA1 LTP in mice lacking the C-terminal PDZ ligand of GluR1 Chong-Hyun Kim1, Kogo Takamiya1, Ronald S Petralia2, Rita Sattler1, Sandy Yu1, Weiguo Zhou3, Robert Kalb3, Robert Wenthold2 & Richard Huganir1 The C-terminal PDZ ligand of the AMPA receptor GluR1 subunit may be important for expression of CA1 hippocampal long-term potentiation. To test this directly in vivo, we generated a knock-in mouse lacking the last seven residues of GluR1, comprising the PDZ ligand. This deletion did not affect basal GluR1 synaptic localization, basal synaptic transmission, long-term potentiation or long-term depression, indicating that the ligand is not required for CA1 hippocampal synaptic plasticity. Recent studies have suggested that the regulated exocytosis and endocytosis of vesicles containing AMPA receptors or the lateral movement of AMPA receptors along the plasma membrane could be an important mechanism regulating the level of synaptic AMPA receptors after the induction of long-term potentiation (LTP) and long-term depression (LTD)1. A variety of data have indicated that

Figure 1 Generation of GluR1 mutant mice lacking the last seven amino acids comprising the PDZ ligand. (a) Schematic representation of GluR1 protein and C-terminal amino acid sequence after modification of stop codon. (b) Immunoblot analysis of wild-type (+/+), heterozygous mutant (+/) and homozygous mutant (/) mice. GluR1 with the seven-amino-acid deletion can be detected by an antibody raised against the last 80 amino acids of the GluR1 C terminus (a GluR1-C80) but not by an antibody against the last 20 amino acids of the GluR1 C terminus (a GluR1-C20). aSAP97N, antibody against the N terminus of SAP97; aGluR2/3, antibody against GluR2/3. (c) Co-immunoprecipitation of GluR1 and SAP97 in vivo. Membrane fractions of brain homogenate of wild-type (WT), homozygous GluR1D7 mutant (D7) and GluR1 knockout mice (KO; Supplementary Fig. 4) were solubilized and immunoprecipitated with antibody to SAP97 (a SAP97) and detected with an antibody to the GluR1 N terminus (a GluR1N). Lower panel shows immunoprecipitated SAP97. (d) Gross hippocampal anatomy and localization of GluR1 immunoreactivity in wild-type and GluR1D7 mutant mice. Left, Nissl staining; right, GluR1 N-terminal immunocytochemistry. (e) Immunoelectron microscopic labeling of GluR1 receptor localization in wild-type and GluR1D7 mutant mice. ‘Pre’ indicates presynaptic terminal. Scale bar, 200 nm. All experiments were done in accordance with the policies of the Animal Care and Use Committee at the Johns Hopkins School of Medicine.

AMPA receptor interactions with PDZ domain–containing proteins may be an important regulatory step during these cellular processes1–7. A recent study has reported that a single amino acid mutation (T887A) within the PDZ ligand of GluR1 blocks the synaptic delivery of virally overexpressed GluR1 during LTP induction in CA1 region of organotypic hippocampal slices8. These results indicate a critical role of the GluR1 PDZ ligand in the membrane insertion of AMPA receptors during activity-dependent processes. To test the role of the GluR1 PDZ ligand in the synaptic targeting of GluR1 and synaptic plasticity in vivo directly, we generated a knock-in mouse (GluR1D7) that lacks the last seven amino acids of GluR1, which constitute the PDZ ligand (Fig. 1a and Supplementary Fig. 1 online). The GluR1D7 mutant mice are viable, breed normally and have no obvious behavioral or developmental phenotypes. We first examined whether the GluR1 PDZ ligand deletion mutation affected the expression of GluR1, by western blotting using an N-terminal GluR1 antibody. The expression of the mutated GluR1 was normal compared to that in wild-type mice (Fig. 1b), as was the expression of GluR2 and GluR3. Previous studies have shown that GluR1 interacts with the PDZ domain–containing synapse associated protein 97 (SAP97) through its C-terminal PDZ ligand9–11. We therefore measured the expression of SAP97 in the GluR1D7 mice and found

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1Department

of Neuroscience and Howard Hughes Medical Institute, The Johns Hopkins University, Baltimore, Maryland 21205, USA. 2Laboratory of Neurochemistry, National Institute on Deafness and Other Communication Disorders, National Institute of Health, Bethesda, Maryland 20892, USA. 3Children’s Hospital of Philadelphia, Joseph Strokes, Jr. Research Institute, ARC 814, 3615 Civic Center Blvd., Philadelphia, Pennsylvania, 19104, USA. Correspondence should be addressed to R.H. ([email protected]). Published online 10 July 2005; doi:10.1038/nn1432

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Figure 2 Basal and activity-dependent synaptic properties of CA1 pyramidal neurons from GluR1D7 mice. (a) Left, sample fEPSP traces evoked with incremental stimulus strength. Scale: 200 mV, 10 ms. Right, plot of input-output slopes from slices from both wild-type (+/+) and mutant (/) mice. Two-tailed t-test (a ¼ 0.05) showed that slopes from the mutant mice are not significantly different from those from wild-type mice (wild-type, 1.98 7 0.17; mutant, 2.46 7 0.21, P ¼ 0.06). Open squares indicate mean values and error bars s.e.m. (b) Analysis of mEPSC from 3-month-old mice shows no significant difference in mEPSC amplitude, mEPSC frequency, rise time (10–90%) or decay time constant between wild-type and mutant mice. Sample traces are shown at left. Scale: 10 pA, 125 ms. (c) Single theta burst–induced LTP shows no significant difference 60 min after LTP induction between wild-type and mutant mice (3 months old). Arrow indicates the time when single theta burst was applied. Inset, sample average traces recorded at time 1 and 2; scale: 200 mV, 10 ms. (d) Low-frequency stimulus (LFS, 1 Hz, 900 pulses)-induced LTD shows normal depression 30 min after LFS in mutant mice. Insets, sample average traces recorded at times 1 and 2 (scale: 300 mV, 10 ms). Gray box indicates the period when LFS was applied. (e) Pairing-induced whole-cell LTP shows similar potentiation 40 min after pairing between wild-type and mutant mice. Arrow indicates the time when pairing stimuli were applied. Filled symbols: LTP path; open symbols: non-LTP path. Circles: wild-type mice; triangles: mutant mice. Insets, sample average traces recorded at time 1 and 2 from mutant mice. Left traces are from LTP path and right traces are from non-LTP path (scale: 200 mA, 10 ms). (f) Pairing-induced whole-cell LTD also shows no significant difference in depression 30 min after pairing between wild-type and mutant mice (3 to 6 weeks old). Gray box indicates the period when pairing stimuli were applied. Filled symbols: LTD path; open symbols: non-LTD path. Circles: wild-type mice; triangles: mutant mice. Insets, sample average traces recorded at time 1 and 2 from mutant mice. Left traces are from LTD path and right traces are from non-LTD path (scale: 100 mA, 10 ms).

that it was similar to that in wild-type mice (Fig. 1b). To examine the interaction of GluR1 and SAP97 in wild-type and GluR1D7 mutant mice, we carried out co-immunoprecipitation experiments, using GluR1 knockout mouse brain samples as a negative control. The interaction of GluR1 with SAP97 in vivo was abolished in GluR1D7 mutant mice (Fig. 1c). These results strongly indicate that the GluR1D7 mutation severely diminishes GluR1 binding to PDZ domains in mutant mice. Next, we examined the distribution of GluR1 in hippocampal sections by immunostaining using an antibody against the N terminus of GluR1 (Fig. 1d). Mutant mice show a pattern of immunostaining similar to that in wild-type mice. To analyze the localization of the mutant GluR1 subunit at synapses, we used immunogold electron microscopic methods with two different antibodies against the GluR1 N terminus (Fig. 1e). Three independent analyses, each with two pairs of animals, showed no significant difference in the distribution of GluR1 in wild-type and homozygous mutant mice (GluR1D7), either in the average number of gold particles per synapse (wild-type, 0.41 7 0.028, n ¼ 846 synapses; mutant, 0.37 7 0.025, n ¼ 846 synapses; two-tailed t-test, P ¼ 0.352) or in the average number of gold particles

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per labeled synapse (wild-type, 1.47 7 0.062, n ¼ 233 labeled synapses; mutant, 1.44 7 0.052, n ¼ 217 labeled synapses; P ¼ 0.714; Fig. 1e). This suggested that there are no major changes in the GluR1 synaptic trafficking in the mutant mice. We also analyzed the extrasynaptic distribution of GluR1 and found no obvious difference in the number of gold particles per postsynaptic process between wild-type and mutant mice (wild-type, 0.11 7 0.03, total 983 counts; mutant, 0.14 7 0.03, total 1,120 counts; P ¼ 0.46). To check the basal synaptic transmission properties, we first examined the evoked synaptic input-output relationship in acute hippocampal slices. To do this, we first plotted the rising slope of field excitatory postsynaptic potential (fEPSP) against the amplitude of presynaptic fiber volley potential with ten incremental input strengths per slice (not shown). We then calculated the slope of the plot (fEPSP slope vs. fiber volley potential amplitude) of each slice by linear regression (wild-type, n ¼ 28; mutant, n ¼ 26 slices; Supplementary Methods and Fig. 2a). The result showed that mutant mice have a postsynaptic response range similar to that in wild-type mice, indicating that there was no significant difference in synaptic input-output relationship. Next, to test the role of GluR1 PDZ ligand on the basal

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B R I E F C O M M U N I C AT I O N S synaptic AMPA receptor (AMPAR) trafficking, we measured AMPARmediated miniature excitatory postsynaptic current (mEPSC) in the presence of 1 mM tetrodotoxin and 100 mM AP5 (Fig. 2b). The results showed no significant difference in the amplitude (in pA: wild-type, 10.42 7 0.28; mutant, 9.72 7 0.22, P ¼ 0.06), frequency (in Hz: wild-type, 2.99 7 0.19; mutant, 3.02 7 0.19, P ¼ 0.89), rise time (10–90% of peak amplitude, in ms: wild-type, 2.11 7 0.08; mutant, 2.21 7 0.07, P ¼ 0.34) or decay time constant (in ms: wild-type, 5.89 7 0.13; mutant, 5.90 7 0.11, P ¼ 0.97) of mEPSC between wild-type (n ¼ 30) and mutant mice (n ¼ 26), suggesting no major perturbation in basal synaptic AMPAR trafficking in CA1 pyramidal neurons of GluR1D7 mutant mice. This result is consistent with the immunoelectron microscopy data that showed no changes in the number of synaptic GluR1 in the mutant mice. Furthermore, the whole-cell current and voltage relationship of both AMPAR- and NMDA receptor (NMDAR)-mediated currents in the mutant mice were similar to those in wild-type mice (Supplementary Fig. 2). These results suggest that removal of GluR1 PDZ ligand does not affect the basal AMPAR and NMDAR trafficking at synapses. To test whether the mutation had any effect on presynaptic vesicle release properties, we measured paired-pulse facilitation, but we did not find any significant change in mutant mice (Supplementary Fig. 2). To investigate the role of the GluR1 PDZ ligand in synaptic plasticity, we first examined LTP induced by single theta burst in the CA1 dendritic region of hippocampal slices (Fig. 2c). We observed LTP in slices from the GluR1D7 mutant mice, and we did not find any significant change in the magnitude of LTP for up to 2 h of recording as compared with wild-type slices (wild-type, 131 7 8%, n ¼ 14; mutant, 132 7 4%, n ¼ 12, measured 60 minute after theta burst and normalized to the baseline, P ¼ 0.59). Although not significant (P ¼ 0.251, 2 h after LTP induction), there was a slight difference in the apparent decay of LTP in the mutant mice, suggesting that there may be a small difference in the late phase of LTP in the GluR1D7 mutant mice. Induction of LTD (induced by 1 Hz, 900 pulses) in the mutant mice was also similar to induction in wild-type mice (Fig. 2d, wild-type, 83 7 3%, n ¼ 18; mutant, 87 7 5%, n ¼ 13, 30 min after LFS, P ¼ 0.11). To further confirm the field LTP data, we induced whole-cell LTP by a pairing protocol from CA1 pyramidal neurons. We found no significant difference in the magnitude of LTP between the wild type and mutants in 3-week-old to 6-month-old mice. Figure 2e shows the LTP data from 6-month-old male mouse pairs (wild-type, 417 7 71%, n ¼ 11; knockout, 378 7 36%, n ¼ 9, 40 min after wholecell LTP, P ¼ 0.68). The pairing-induced LTP was NMDAR-dependent and CaMKII-dependent, as AP5 or CaMKII inhibitory peptide could block LTP induction in both wild-type and mutant mice (Supplementary Fig. 3). We also tested pairing-induced LTD and found no significant difference 30 min after pairing (Fig. 2f, wild-type, 81 7 4%, n ¼ 11; mutant, 76 7 7%, n ¼ 11, P ¼ 0.22). De-depression after LTD induction was also induced normally compared to wild-type mice (Supplementary Fig. 2). These results show that removal of the GluR1 PDZ ligand has no obvious effect on the induction of activitydependent synaptic plasticity such as LTP and LTD.


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In another approach, we tried to acutely inhibit the function of the endogenous GluR1 PDZ ligand in wild-type mice by perfusing a peptide corresponding to the GluR1 PDZ ligand (15 amino acids, 200 mM) into the cell and then waiting 30 min before LTP induction. The results show that postsynaptic perfusion of the GluR1 PDZ ligand peptide had no effect on the induction of pairing-induced LTP in rat hippocampal CA1 pyramidal neurons (Supplementary Fig. 3). This data is in contrast with a previous report that showed that overexpression of GFP-tagged constructs containing the whole C-terminal domain of GluR1 (80 amino acids) blocks LTP induction in CA1 pyramidal neurons in slice culture12. However, the experimental conditions for this study are quite different from the peptide perfusion experiments: the whole C terminus, which contains many other protein-protein interaction sites, was overexpressed in the previous experiments, and the GFP-tagged C-terminal domain was expressed for 24 h, whereas our peptide perfusion experiments were acute experiments. Taken together, these results indicate that NMDAR-dependent LTP can be induced in the absence of the GluR1 PDZ ligand in vivo. This is in contrast to previous results using overexpression of GluR1 PDZ ligand point mutants (T887A) in hippocampal slice culture, which implicate the GluR1 PDZ ligand as a critical factor for CA1 LTP expression8. The reason for the discrepancy between these studies is not clear. It is possible that the point mutation of the GluR1 PDZ ligand has different functional effects compared with a complete deletion of the PDZ ligand, or alternatively, the properties of the trafficking of overexpressed GluR1 in organotypic cultures may be different from those seen in vivo. However, our studies clearly show that deletion of the GluR1 PDZ ligand has little effect on activity-dependent synaptic plasticity and basal synaptic targeting of GluR1 in vivo. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS This work was supported by US National Institutes of Health grant NS36715 and the Howard Hughes Medical Institute. COMPETING INTERESTS STATEMENT The authors declare competing financial interests (see the Nature Neuroscience website for details). Received 1 February; accepted 24 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. 2. 3. 4. 5. 6.

Song, I. & Huganir, R.L. Trends Neurosci. 25, 578–588 (2002). Kim, E. & Sheng, M. Nat. Rev. Neurosci. 5, 771–781 (2004). Bredt, D.S. & Nicoll, R.A. Neuron 40, 361–379 (2003). Malinow, R. & Malenka, R.C. Annu. Rev. Neurosci. 25, 103–126 (2002). Sheng, M. & Lee, S.H. Cell 105, 825–828 (2001). Carroll, R.C., Beattie, E.C., von Zastrow, M. & Malenka, R.C. Nat. Rev. Neurosci. 2, 315–324 (2001). 7. Turrigiano, G.G. Neuron 26, 5–8 (2000). 8. Hayashi, Y. et al. Science 287, 2262–2267 (2000). 9. Leonard, A.S., Davare, M.A., Horne, M.C., Garner, C.C. & Hell, J.W. J. Biol. Chem. 273, 19518–19524 (1998). 10. Colledge, M. et al. Neuron 27, 107–119 (2000). 11. Cai, C., Colman, S.K., Miemi, K. & Keinanen, K. J. Biol. Chem. 277, 31484–31490 (2002). 12. Shi, S., Hayashi, Y., Esteban, J.A. & Malinow, R. Cell 105, 331–343 (2001).

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Cortical calcium waves in resting newborn mice Helmuth Adelsberger1,2, Olga Garaschuk1,2 & Arthur Konnerth1 Using a new optical fiber–based approach, we demonstrate the presence of recurrent Ca21 transients in cortical neurons of non-anesthetized newborn mice in vivo. These Ca21 waves reflect the correlated activity of thousands of cells and were detected only in resting, but not in moving pups. Our results suggest that Ca21-dependent cortical maturation occurs predominantly during the intermittent sleep-like resting periods that are characteristic for the first days of postnatal life. The first two weeks after birth represent a period of decisive changes in the organization of the rodent cortex. The total mass of the brain tissue increases fourfold1, the density of cortical synapses increases 30-fold1 and cortical columns start to form2. During these early stages of development, in which cortical activation through extrinsic (sensory) stimuli is very restricted, various forms of intrinsic firing patterns guide the wiring of the neural networks (reviewed in refs. 2,3). Several in vitro studies, including pioneering work performed in the spinal cord4 and in the retina5, have indicated that such patterned early forms of network activity are associated with changes in neuronal intracellular Ca2+ concentration3,6,7. Such Ca2+ signals regulate, at least under in vitro conditions, various developmental processes including gene expression8, neuronal growth and differentiation9, neurite outgrowth9 and synapse formation3. In the neocortex, the most prominent type of patterned spontaneous activity are the so-called early network oscillations (ENOs)6. To monitor intracellular Ca2+ signals in the neonatal mouse cortex in vivo, we first stained a column-like region of the neocortex (of about 400–600 mm diameter) with the fluorescent Ca2+ indicator dye Oregon green 488 BAPTA-1 using the multi-cell bolus loading method10. For both excitation of the fluorescent dye and collection of the emitted light

we used a single optical fiber (+ ¼ 200 mm, Fig. 1a–c) implanted in the stained cortical region (see Supplementary Methods online), usually at a depth of 300–400 mm. Recordings from the temporal cortex of non-anesthetized newborn mice showed spontaneous calcium transients (Fig. 1d, upper panel). These periodically recurring transients reflect the correlated activity of thousands of neurons (see below). A similar pattern of activity, albeit with smaller amplitudes, was detected when placing the tip of the fiber just on top of the cortical surface (Fig. 1d inset), indicating that damage through fiber insertion does not contribute to or induce the activity. At the end of the in vivo experiments, the mice were decapitated, the brains removed and cortical slices including the stained cortical regions prepared using standard methods6. Without additional staining, slices were used for two-photon calcium imaging experiments (Fig. 1c). We found, as in vivo, periodically recurring spontaneous Ca2+ transients (Fig. 1d, lower panel). These were strongly reminiscent of the ENOs described previously in cortical slices from newborn rats6 and mice7.

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Figure 1 In vivo recordings of spontaneous Ca2+ waves in the neonatal cortex. (a) The experimental setup. (b) Schematic diagram of the implanted optical fiber. (c) Top: transmitted light image of a slice obtained from the in vivo stained brain; entorhinal (EN), temporal (TE) and parietal (PA) cortex. Bottom and inset: two-photon images of the stained area. (d) In vivo optical fiber recordings (top) and two-photon slice recordings (bottom) of spontaneous Ca2+ waves from the same in vivo stained brain. Inset at top: in vivo recordings with optical fiber placed on the pial surface. (e) Combined transmitted light and fluorescence image of a cortical slice. The dashed circle delimits the region of interest from which fluorescence signals shown in f (top) were collected. (f) Ca2+ waves recorded simultaneously with the CCD camera and the optical fiber.

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Institut, Ludwig-Maximilians Universita¨t Mu¨nchen, Pettenkoferstr. 12, 80336 Mu¨nchen, Germany. 2These authors contributed equally to this work. Correspondence should be addressed to A.K. ([email protected]).

Published online 10 July 2005; doi:10.1038/nn1502

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To determine how many cells contributed to the signals, we made simultaneous recordings with a CCD (charge-coupled device) camera and the optical fiber (Fig. 1e,f). The recordings, obtained by delivering the excitation light through the fiber, demonstrated that both systems reported highly similar Ca2+ signals. The analysis of the imaging data (Supplementary Methods) suggested that individual transients recorded through the fiber were the result of the correlated activity of thousands of cells. Asynchronous Ca2+ transients occurring in single cells did not produce detectable signals in the fiber recordings (data not shown). The Ca2+ waves had variable amplitudes (Figs. 1d and 2a,b). Highmagnification (4120) two-photon imaging in slices indicated that similar proportions of the cortical cells contributed to the large and smaller waves (on average, 85% of all imaged cells, n ¼ 142 Ca2+ waves, 862 cells, 11 mice). The smaller size of some waves was due to a general reduction in the amplitudes of the active cells contributing to that wave. Whereas 94.9 7 2.1% of all neurons participated in the Ca2+ waves, the astrocytes did not (Supplementary Fig. 1). The time-course analysis showed that the Ca2+ waves had rather fast rise times (559 7 51 ms) and decay time constants in the range of 1–4 s (Fig. 2a–e). On average, the in vivo Ca2+ waves lasted for 3.8 7 0.1 s (481 waves, 11 mice) and were markedly similar to their in vitro counterparts (Fig. 2b–e). In 9/15 experiments conducted with implanted (n ¼ 11) as well as surfaceattached (n ¼ 4) optical fibers there was no significant difference between the decay time constants of the Ca2+ waves and their frequency in vivo and in vitro (Fig. 2e,f). The similarity between Ca2+ waves recorded in slices and those found in vivo suggests that even reduced cortical networks can sustain this global activity. The surgical separation of the cortex from the thalamus in slice recordings did not alter the Ca2+ waves significantly (wave frequency after separation was 107.6 7 4.6% of the control frequency, n ¼ 4), indicating that they result from intrinsic cortical activity. We first tried to use two-photon Ca2+ imaging to analyze Ca2+ waves in vivo (Supplementary Fig. 2). However, Ca2+ waves were never detected under urethane (n ¼ 8 mice) or isoflurane (n ¼ 5 mice) anesthesia. The absence of Ca2+ waves in anesthetized mice was confirmed in several in vivo optical fiber measurements (n ¼ 20 mice). However, as soon as the action of the anesthetics had vanished, spontaneous Ca2+ transients appeared. Furthermore, in vivo Ca2+ waves were blocked completely and reversibly by isoflurane (Supplementary Fig. 2) and irreversibly by urethane. Notably, correlated electrical activity persists in the developing hippocampus11 (Supplementary Note) and retina12 in the presence of anesthetics. To elucidate the relation between ENOs and animal behavior, simultaneous analyses of Ca2+ waves and motion patterns were performed in vivo (Fig. 3). After recovery from anesthesia, mouse pups showed a behavior that is typical for newborn rodents13,14, namely a frequent alternation between resting and motion periods. Overall they spent most of the time in a state with virtually no detectable motion (Fig. 3a,d). The relative amount of time that a fiber-implanted pup spent in the resting state was not significantly

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Figure 2 Comparison of Ca2+ waves recorded in vivo and in brain slices. (a,b) Superposition (left) and average (right) of ten consecutive Ca2+ transients recorded in vivo (a) and in the slice (b). Solid black lines represent mono-exponential fits. (c,d) Distribution of decay time constants (c) and intervals of Ca2+ waves (d) in the same experiment in vivo (top) and in the slice (bottom). Bin width of histograms 0.2 s in c and 4 s in d. (e,f) Summary of mean 7 s.e.m. decay time constants (e) and intervals (f) of Ca2+ waves (n ¼ 15 experiments). See Supplementary Note for pharmacological profile of Ca2+ waves.

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different from that of its non-implanted littermate (Fig. 3e). The motion periods were characterized by fast, irregular displacement signals extracted from digitized video clips (Fig. 3a,b, upper right). Notably, the simultaneous Ca2+ recordings showed a pronounced wave activity during the resting period and a very low activity level during the motion periods (Student’s t-test, P o 0.05; Fig. 3b,f). Similar results were obtained when the neck muscle activity, recorded with an intramuscular electromyogram (EMG), and cortical Ca2+ signals were monitored simultaneously (Fig. 3c). Furthermore, there was a silent post-motion period that was markedly longer than the corresponding mean inter-wave interval at rest (202 7 28%, P o 0.01; n ¼ 7 mice, Fig. 3g). A cross-correlation analysis of the digitized Ca2+ waves and the motion (Fig. 3h) or EMG (Fig. 3i) traces showed no correlation between ENOs and motion episodes. Moreover, the mean cross-correlograms had minima around zero, indicating that the probability of a Ca2+ wave occurring is decreased during motion periods (Fig. 3h,i, inset). Taken together, the data suggest that in vivo Ca2+ waves represent an endogenous brain rhythm, expressed primarily during sleep-like resting states and vanishing or becoming inhibited during the animal’s movements (Supplementary Note). In adults, the sleep-associated slow wave activity is thought to underlie neuronal plasticity and consolidation of memory traces acquired during wakefulness15. In the immature brain, large-scale Ca2+ waves are present during a highly plastic time period in the development of the brain, associated with prominent synaptogenesis and an extensive growth of axons and dendrites1,3. Many of these processes are critically controlled by intracellular Ca2+ signals3,9. As mice (ref. 14 and this study) and rats13 spend 60–80% of their neonatal life in a sleep-like resting state, our results suggest that Ca2+ dependent neuronal maturation in the cortex is driven primarily by ENOassociated neuronal Ca2+ waves.

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Figure 3 Spontaneous Ca2+ waves in behaving mice. (a) Experimental arrangement. Alternation of motion and resting periods in a newborn mouse. (b) Measurement of mouse displacement and cortical Ca2+ transients (bottom) at rest (left) and during motion (right). (c) Simultaneous nuchal EMG and optical fiber–based Ca2+ recordings (bottom) at rest (left) and during motion (right). (d) Summary resting time determined with motion analysis (n ¼ 7, left) and EMG (n ¼ 5). (e) Distribution of resting periods in control animals, in animals anesthetized for 1 h (recordings taken 30 min after anesthesia (post-anesth.)) and in fiber-implanted mouse pups (n ¼ 5, 5 and 7 mice, respectively). (f) Mean frequency of Ca2+ waves at rest and during motion (n ¼ 6 mice) (g) Interval between the end of the motion period and the first Ca2+ wave (post-motion) normalized to the corresponding mean interval at rest (n ¼ 7 mice). *, P o 0.05 in f; *, P o 0.01 in g (Student’s t-test). (h,i) Average cross-correlograms between digitized ENOs and motion traces (h, n ¼ 7) or ENOs and EMG recordings (i, n ¼ 4). Insets: higher magnification of central portion.

Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We thank F. Rucker and M. Noll-Hussong for technical help and J. Davis for comments on the manuscript. The work was supported by the Deutsche Forschungsgemeinschaft. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 2 June; accepted 23 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Uylings, H.B.M., Van Eden, C.G., Parnavelas, J.G. & Kalsbeek, A. in The Cerebral Cortex of the Rat (eds. Kolb, B. & Tees, R.C.) 36–76 (MIT Press, Cambridge, Massachusetts, 1990).

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Feller, M.B. & Scanziani, M. Curr. Opin. Neurobiol. 15, 94–100 (2005). Katz, L.C. & Shatz, C.J. Science 274, 1133–1138 (1996). Gu, X., Olson, E.C. & Spitzer, N.C. J. Neurosci. 14, 6325–6335 (1994). Wong, R.O., Chernjavsky, A., Smith, S.J. & Shatz, C.J. Nature 374, 716–718 (1995). 6. Garaschuk, O., Linn, J., Eilers, J. & Konnerth, A. Nat. Neurosci. 3, 452–459 (2000). 7. Corlew, R., Bosma, M.M. & Moody, W.J. J. Physiol. (Lond.) 560, 377–390 (2004). 8. Buonanno, A. & Fields, R.D. Curr. Opin. Neurobiol. 9, 110–120 (1999). 9. Spitzer, N.C., Root, C.M. & Borodinsky, L.N. Trends Neurosci. 27, 415–421 (2004). 10. Stosiek, C., Garaschuk, O., Holthoff, K. & Konnerth, A. Proc. Natl. Acad. Sci. USA 100, 7319–7324 (2003). 11. Leinekugel, X. et al. Science 296, 2049–2052 (2002). 12. Maffei, L. & Galli-Resta, L. Proc. Natl. Acad. Sci. USA 87, 2861–2864 (1990). 13. Jouvet-Mounier, D., Astic, L. & Lacote, D. Dev. Psychobiol. 2, 216–239 (1970). 14. Daszuta, A. & Gambarelli, F. Brain Res. 354, 39–47 (1985). 15. Steriade, M. & Timofeev, I. Neuron 37, 563–576 (2003).

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Andreas Meyer-Lindenberg1–3, Ahmad R Hariri3,6, Karen E Munoz2,3, Carolyn B Mervis4, Venkata S Mattay2,3, Colleen A Morris5 & Karen Faith Berman1,3 Williams-Beuren syndrome (WBS), caused by a microdeletion of approximately 21 genes on chromosome 7q11.23, is characterized by unique hypersociability combined with increased non-social anxiety. Using functional neuroimaging, we found reduced amygdala activation in individuals with WBS for threatening faces but increased activation for threatening scenes, relative to matched normal controls. Activation and interactions of prefrontal regions linked to amygdala, especially orbitofrontal cortex, were abnormal, suggesting a genetically controlled neural circuitry for regulating human social behavior. Social neuroscience continues to grow in importance1, but little is known about specific genetic factors influencing human social cognition, although social skills are highly heritable and critical for survival. Great interest has therefore been directed at a unique social-behavioral phenotype, high sociability2,3 and empathy, found in individuals with WBS, who eagerly, often impulsively, engage in social interaction, even with strangers4. Associated with this remarkable persistent hypersociability is an undercurrent of anxiety3: individuals with WBS show extremely high rates of excessive worrying (57%; ref. 4) and specific phobia (symptoms in 96%; ref. 4). The neural mechanisms underlying this social phenotype remained unknown, partly because of the intellectual impairment usually associated with the syndrome, which limits comparison to a normal control group. We addressed this problem by examining a highly select group of normal-intelligence participants with WBS5, reasoning that abnormalities found even there would be characteristic of the syndrome and reflect its genetic substrate. In addition to the amygdala’s role in reward, its response and regulation are believed to be central to socially protective neural processing through the monitoring of environmental events such as danger1. Lesions of the amygdala and linked cortical regions, such as orbitofrontal cortex (OFC), impair social function6 and can cause disinhibition7. Of great importance to the WBS phenotype, the effects of neonatal amygdala lesions in nonhuman primates suggest dissociable systems for social and non-social fear6. In the present study, we used two tasks requiring processing of threatening visual stimuli

previously established to reliably engage amygdala8. The first task required matching one of two simultaneously presented faces with a different target face of the same emotion (angry or afraid)8. In the other task, participants matched one of two simultaneously presented fearful/threatening scenes with an identical target9. As a control task, participants matched simple shapes (circles or ellipses). Thirteen participants with WBS and controls matched for age, sex and IQ participated in this study after giving written informed consent (see Supplementary Methods). Performance during the matching tasks (but not the control tasks) did not differ between groups (Supplementary Table 1) and showed that the faces task (where all three identities differed) was more difficult for both groups. In normal controls, ventral amygdala was more highly activated for faces than for scenes, as shown previously8. The opposite pattern (scenes 4 faces) was observed in this region in individuals with WBS. Single-subject analyses in native space confirmed these findings (Supplementary Figs. 1,2). Controls showed significantly greater amygdala activation for faces than did individuals with WBS, whereas the response was significantly higher for scenes in individuals with WBS than in controls (Fig. 1 and Supplementary Table 2). Subsequent analyses focused on right amygdala, where differential effects were more pronounced. ANOVA of differential BOLD signal change (Fig. 2) confirmed a significant group-by-task interaction (F1,46 ¼ 5.7, P o 0.03). Overall amygdala BOLD signal change was comparable for both groups (Fig. 2b). Normal controls

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Figure 1 Amygdala activation by task. Significant activations (P o 0.05, corrected for multiple comparisons in amygdala region of interest) rendered on normal coronal MRI at 71 mm to the anterior commissure (left ¼ left) for face (top) and scene (bottom) stimuli. First column: normal controls; second column: participants with WBS; third column: significant differences between groups (blue: normal controls4WBS, red: WBS4normal controls). See Supplementary Table 2 for detailed statistical information.

1Section

on Integrative Neuroimaging and 2Neuroimaging Core Facility of the 3Clinical Brain Disorders Branch, Genes, Cognition and Psychosis Program, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland 20892, USA. 4Neurodevelopmental Sciences Laboratory, Department of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky 40292, USA. 5Department of Pediatrics, University of Nevada School of Medicine, Las Vegas, Nevada 89102, USA. 6Present address: Department of Psychiatry, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, Pittsburgh, Pennsylvania 15213, USA. Correspondence should be addressed to A.M.L. ([email protected]). Published online 10 July 2005; doi:10.1038/nn1494


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Amygdala reactivity to threatening faces was significantly diminished in individuals with WBS. This was not likely to be attributable to abnormal visual processing because, as previously5, we did not observe activation differences in the ventral visual stream (Supplementary Table 3). As amygdala signaling is critical for appropriate avoidance behavior1, abnormal activation to threatening faces may contribute to diminished fear of strangers and consequent social disinhibition in individuals with WBS3 because of reduced responsivity to social danger. Conversely, and again in excellent agreement with the clinical profile of WBS, amygdala reactivity to scenes was not simply preserved, but was in fact abnormally increased. As specific phobia has been associated with increased amygdala reactivity10, this observation suggests a potential mechanism for high non-social anxiety in WBS4. Because abnormal amygdala reactivity in individuals with WBS was not attributable to general functional impairment, our data suggested alterations in amygdala modulation and regulation. We therefore examined whole brain group-by-task interaction maps to identify regions outside the amygdala showing differential reactivity as a function of task (Fig. 2a and Supplementary Table 3). These were located exclusively in prefrontal cortex (Fig. 2c–e), where normal controls differentially activated dorsolateral-prefrontal (DLPFC), medial-prefrontal (MPFC) and orbitofrontal cortex in the more difficult condition (face matching). In contrast, participants with WBS showed a task-invariant pattern: OFC was not differentially activated, and both MPFC and DLPFC were activated to similar degrees in both tasks. Both MPFC and OFC are densely interconnected with amygdala and DLPFC11 and have been implicated in the regulation of amygdala function, social cognition1 and representation of social knowledge12. Structural abnormalities in OFC have been reported both in these same participants5 and in participants with WBS and mental retardation13. Our finding of the absence of OFC activation also provides evidence for a deficiency during social processing. OFC activity and OFC-amygdala

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interactions have been associated with representation and reevaluation of relative reward value and stimulus-reinforcement association learning14. In social cognition, OFC-amygdala interactions are hypothesized to link sensory representations with social judgments on the basis of motivational value1, and OFC lesions are associated with social disinhibition and impaired ability to detect faux pas. In this context, our observation of functionally abnormal OFC is consistent with the observations of social disinhibition and impairments in adjusting behavior according to social clues in individuals with WBS3. We also found a perigenual MPFC region persistently activated in individuals with WBS. Convergent evidence suggests that dynamic interactions of this area with amygdala are critical for inhibitory amygdala regulation, especially for fear extinction15. MPFC has been associated with empathy, representation of social knowledge12 and integration of emotional information about others and self1. Again, the relatively preserved, or even increased, activity of MPFC maps well on phenotypic characteristics of relative social strengths of individuals with WBS, such as increased empathy2. To directly investigate regulatory interactions between identified prefrontal regions and amygdala, we employed path analysis5, a method allowing assessment of functional interregional interactions (which should not, however, be interpreted to indicate direct anatomical connections). Using data from OFC, MPFC, DLPFC and right amygdala during face processing (where both groups showed prefrontal engagement), we obtained a well-fitting model for both participant groups (Fig. 2f–g). The final model included efferent pathways from MPFC and OFC to amygdala, and from DLPFC to MPFC and OFC, consistent with anatomical data11. The overall pattern of connections within this regulatory system was highly significantly different between groups (w2(4) ¼ 13.91, P o 0.008). In normal individuals, both MPFC and OFC were strongly negatively linked to amygdala. DLPFC showed a positive interaction with OFC and a negative path to MPFC (Fig. 2f).

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B R I E F C O M M U N I C AT I O N S In contrast, in individuals with WBS, OFC showed no connection either with amygdala or DLPFC (Fig. 2g). While the negative link between MPFC and amygdala was similar to that in controls (w2(1) ¼ 1.87, P 4 0.17), DLPFC and MPFC were strongly positively linked in individuals with WBS, a significant difference from the negative interaction in controls (w2(1) ¼ 4.32, P o 0.03). Our path analyses suggested that OFC did not participate in regulatory interactions with amygdala in WBS, whereas normal controls showed a highly significant connection of OFC with both amygdala and DLPFC. Moreover, DLPFC, although not directly linked to amygdala, showed a differentiated reciprocal interaction with both ventral prefrontal regions (OFC and MPFC) that was significantly altered in WBS. These results support abnormal regulatory interactions between the PFC and amygdala in WBS. In particular, the finding that OFC was not only not differentially activated but also functionally disconnected from amygdala provided evidence for impairment of this regulatory mechanism in WBS. In normal controls, although signs of path coefficients cannot be directly interpreted as neural excitation or inhibition, our data do indicate a differential network by which DLPFC can adjust amygdala reactivity in both directions according to task demand. Evidence indeed suggests that activation of DLPFC modulates the amygdala in a task-specific fashion9. Our data extend understanding of this regulation by illustrating that DLPFC may exert this influence on the amygdala despite the absence of direct connections11 through reciprocal interactions with MPFC and OFC. It is commonly assumed that a primary role of DLPFC in social cognition is the representation of goal states and consequent modification of relevant social-emotional interactions1. Our results suggest a regulatory system through which these goal-directed demands can be neurally instantiated. In WBS, this modulation was significantly altered: OFC connections were absent and interactions between DLPFC and MPFC had a positive sign. Moreover, in individuals with WBS, both DLPFC and MPFC were found to be active to the same degree in both tasks, suggesting that this abnormal modulation is enduring, whereas normal controls recruited only prefrontal cortex as required by task type or difficulty. On the basis of the cross-sectional data presented here, it is impossible to determine whether the abnormal interaction between DLPFC and MPFC represents a primary abnormality or is secondary to the lack of OFC function in this regulatory network in individuals with WBS. We propose that the observed task-independent facilitation of MPFC by DLPFC may represent a compensatory mechanism using the intact pathway in the context of congenitally non-functional OFC in individuals with WBS. Together with nonhuman primate findings of increased social but decreased non-social fear after neonatal amygdala lesions6, our data suggest the possibility that the opposite pattern of


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dissociated fear (decreased social fear and increased non-social fear) found in individuals with WBS may be a consequence of a congenital deficiency in a prefrontal system involved in inhibitory amygdala regulation (and by implication, possibly associated with relatively disinhibited amygdala activity during maturation). In this first study of the neural basis of emotional cognition in WBS, we opted for a low-level baseline task in order to increase our power to detect amygdala activity, which had been hypothesized to be deficient3. As our data indicated no reduction of overall magnitude of amygdala activation (Fig. 2b), further research should use other emotional stimuli (such as happy or sad, compared to neutral) in fully factorial designs to further characterize amygdala response in WBS and link these suggestive findings to emotional regulation with certainty. We anticipate that identification of an intermediate neural phenotype for a genetically dependent abnormality in social cognition will facilitate the search for specific genes underlying social cognition in individuals with WBS and in healthy individuals. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We thank N. Dixit, A. Bonner-Jackson, R. Olsen and J. Holt for research assistance; A. Goldman and Q. Chen for single-subject analyses and D. Weinberger for helpful discussion. This work was supported by the US National Institute of Mental Health intramural program and National Institute on Neurological Disorders and Stroke grant NS35102 to C.B.M. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 25 May; accepted 17 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Adolphs, R. Nat. Rev. Neurosci. 4, 165–178 (2003). 2. Klein-Tasman, B.P. & Mervis, C.B. Dev. Neuropsychol. 23, 269–290 (2003). 3. Bellugi, U., Adolphs, R., Cassady, C. & Chiles, M. Neuroreport 10, 1653–1657 (1999). 4. Dykens, E.M. Dev. Neuropsychol. 23, 291–316 (2003). 5. Meyer-Lindenberg, A. et al. Neuron 43, 623–631 (2004). 6. Prather, M.D. et al. Neuroscience 106, 653–658 (2001). 7. Amaral, D.G. Biol. Psychiatry 51, 11–17 (2002). 8. Hariri, A.R., Tessitore, A., Mattay, V.S., Fera, F. & Weinberger, D.R. Neuroimage 17, 317–323 (2002). 9. Hariri, A.R., Mattay, V.S., Tessitore, A., Fera, F. & Weinberger, D.R. Biol. Psychiatry 53, 494–501 (2003). 10. Dilger, S. et al. Neurosci. Lett. 348, 29–32 (2003). 11. Ghashghaei, H.T. & Barbas, H. Neuroscience 115, 1261–1279 (2002). 12. Wood, J.N., Romero, S.G., Knutson, K.M. & Grafman, J. Neuropsychologia 43, 249– 259 (2005). 13. Reiss, A.L. et al. J. Neurosci. 24, 5009–5015 (2004). 14. Kringelbach, M.L. & Rolls, E.T. Prog. Neurobiol. 72, 341–372 (2004). 15. Quirk, G.J., Likhtik, E., Pelletier, J.G. & Pare, D. J. Neurosci. 23, 8800–8807 (2003).

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Sox21 promotes the progression of vertebrate neurogenesis Magnus Sandberg, Magdalena Ka¨llstro¨m & Jonas Muhr The generation of neurons constitutes the foundation of nervous system development, yet the mechanisms underlying neurogenesis are not well established. The HMG-box transcription factors Sox1, Sox2 and Sox3 (Sox1–3) have previously been shown to suppress neurogenesis by maintaining neural cells in an undifferentiated state. Here we report that another HMG-box protein, Sox21, has the opposite activity and promotes neuronal differentiation. Using genetic studies in the chick embryo, we found that Sox21 mediates this function by counteracting the activity of Sox1–3. Accordingly, the balance of Sox21 and Sox1–3 activities determines whether neural cells remain as progenitors or commit to differentiation. Proneural basic helix-loop-helix proteins are essential for the establishment of neuronal fates. We now show that proneural proteins promote neurogenesis by upregulating Sox21 expression. These data establish a key role for Sox21 in the progression of neuronal differentiation and indicate that an important role of proneural proteins is their capacity to upregulate the expression of Sox21.

Neurons are generated from self-renewing precursor cells residing in the ventricular zone of the developing CNS. During neurogenesis, precursor cells exit the division cycle, downregulate progenitor markers and migrate toward the marginal zone to begin to express neuronal properties. Although progress has been made in defining genetic pathways that regulate neurogenesis, the molecular mechanisms that prompt neural cells to initiate programs of neuronal differentiation remain poorly defined. Proneural basic helix-loop-helix (bHLH) transcription factors are essential for the establishment of neuronal fates1,2. The fraction of progenitor cells expressing proneural bHLH proteins is determined by the interaction between Notch receptors and their ligands3. Notch receptor signaling restricts the expression of proneural proteins, whereas other positive-feedback mechanisms upregulate the expression of proneural proteins in selected progenitors4,5. A high level of proneural protein activity is sufficient to drive neurogenesis by directing cell-cycle exit6 and by activating the expression of downstream differentiation markers7,8. Proneural proteins function as transcriptional activators, but it is not yet known how these proteins induce neural cells to suppress progenitor features and commit to the irreversible set of events that results in terminal neuronal differentiation1,2. The HMG-box transcription factors Sox1–3 are expressed by most progenitor cells within the developing CNS9–12. Sox1–3 proteins have previously been shown to counteract neurogenesis by maintaining neural cells in an undifferentiated state12,13. However, the ability of Sox1–3 proteins to block neurogenesis is not due to the suppression of proneural gene expression. Instead, Sox1–3 proteins hinder the capacity of proneural proteins to induce downstream events of neuronal differentiation12. Thus, suppression of Sox1–3 activities seems to be a

prerequisite for proneural proteins to promote neuronal differentiation12,13. Sox1–3, together with Sox14 and Sox21, constitute the B group of the Sox gene family14. Although the HMG domains of these proteins are highly conserved, transcriptional analyses have shown that Sox14 and Sox21, in contrast to Sox1–3, harbor a transcriptional repressor motif in their C-terminal portions14,15. Whereas the expression of Sox14 is limited to a population of post-mitotic interneurons, Sox21 is expressed within the ventricular zone and at all axial levels of the CNS15,16, raising the possibility that Sox21 could have a more general role in regulating the progression of neurogenesis. In the present study, we examined the role of Sox21 in the regulation of neurogenesis in the chick neural tube. We show that Sox21 promotes differentiation of neural cells, an activity opposite to that of Sox1–3. Notably, Sox21 mediates this function by counteracting the activity of Sox1–3 proteins. Thus, the balance of Sox21 and Sox1–3 activity determines whether neural cells remain in a progenitor state or commit to neuronal differentiation. The ability of Sox21 to direct neural cells to a differentiated state is independent of the intrinsic status of proneural protein activity. However, the ability of proneural bHLH proteins to promote neurogenesis seems to be based on their capacity to upregulate the level of Sox21 expression. Together, these findings establish a key role for Sox21 in the progression of neurogenesis and further indicate that an important function of proneural bHLH proteins during neurogenesis is the capacity to upregulate the expression of Sox21. RESULTS Expression of Sox21 in CNS progenitors To examine the role of Sox21 during neurogenesis, we first defined its expression profile in the caudal part of the chick neural tube at

Ludwig Institute for Cancer Research, Karolinska Institute, Box 240, SE-171 77, Stockholm, Sweden. Correspondence should be addressed to J.M. ([email protected]). Published online 3 July 2005; doi:10.1038/nn1493


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Figure 2 Sox21 functions as a transcriptional repressor. (a–f) Forced expression of Sox21-myc suppressed progenitor identities (a,b) and facilitated the expression of Lim2 (c) and NeuN (d), but not Tuj1 or NF1 (e,f). (g–i) Twenty hours after HMG-EnR transfection, most cells were in a post-mitotic state (g) and had upregulated expression of Lim2 (h) and NeuN (i). (j–l) Cells electroporated with HMG-VP16 were maintained in a progenitor state (j) and did not upregulate the expression of neuronal markers (k,l). Scale bars, 60 mm in a–i and 100 mm in j–l. (m) Percentage of cells incorporating BrdU 20 h after Sox21 transfection. Ctrl: nontransfected control side. (n) Percentage of cells expressing the neuronal markers after Sox21, HMG-EnR or HMG-VP16 transfection (mean 7 s.d.).

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Sox21 promotes neuronal differentiation Sox1 and Sox2 activate the d1-crystallin enhancer DC5, whereas Sox21 inhibits this Sox21 NeuroM Sox21 NeuN Sox1/Sox2–activated gene expression15. Thus, f g one possible function of Sox21 during neurogenesis is to counterbalance the activity of c Sox1–3 in differentiating progenitor cells. The ability of Sox1–3 to suppress the formation of neurons12,13 prompted us to examine, by chick embryo electroporation, whether Figure 1 Expression of Sox21 in the developing CNS. (a,b) Pattern of Sox21 mRNA (a) and Sox21 and Sox21 could influence neurogenesis when Sox3 protein (b) expression in a chick spinal cord at HH stage 20. (c–g) Analysis of Sox21 expression + + + + + misexpressed in the neural tube. Electroin Sox3 (c), BrdU (d), Ngn2 (e), NeuroM (f) and NeuN (g) cells. Scale bar, 60 mm in a, 45 mm in b porated cells were analyzed 10–20 h after and 15 mm in c–g. transfection for the expression of markers defining progenitor cells or differentiated Hamburger-Hamilton (HH) stage 20 (see ref. 17 for description of neurons. Forced expression of Sox21 caused cells to exit the cell cycle, stages). Sox21 mRNA was detected at most levels of the dorsoventral as detected by the lack of BrdU incorporation, and to downregulate the axis, but it was predominately expressed in three stripes that encom- expression of the progenitor markers Sox3 and Pax6 (ref. 23; Fig. 2 and passed a dorsal, medial and ventral domain of the ventricular zone15,16 data not shown). The suppression of progenitor features was accom(Fig. 1a). Sox21 protein was generally confined to Sox1–3+ progenitor panied by premature expression of Lim2 and NeuN, but not Tuj1 or cells10,12 (Fig. 1b,c and data not shown) and was detected in all NF1 (Fig. 2c–f,n). Thus, a high level of Sox21 expression induces cells proliferating cells incorporating BrdU (Fig. 1d), although the expres- to leave their proliferative progenitor state and to upregulate an array of sion level of Sox21 varied between different cells (Fig. 1c,d). Moreover, neuronal markers, the opposite of the effects of Sox1–3. Electroporation the majority of cells expressing the proneural bHLH protein Ngn2 of Sox21 did not, however, result in an upregulation of Ngn2 expression (ref. 18) were Sox21+ (Fig. 1e), whereas expression of the bHLH (data not shown). Furthermore, the capacity of Sox21 to promote the protein NeuroM19 was identified only in the most lateral Sox21+ cells formation of differentiated cells expressing neuronal markers was not (Fig. 1f). Additional Ngn2- and NeuroM-expressing cells were detected affected by co-electroporated Id2 (see Supplementary Fig. 1 online). As in a narrow domain lateral to the Sox21+ boundary, defined as the Id2 blocks the activity of proneural proteins24 and suppresses neuronal intermediate zone19. Thus, the expression of Sox21 appears to be differentiation25 (Supplementary Fig. 1), these results suggest that the downregulated simultaneously as differentiating NeuroM+ cells depart ability of Sox21 to direct neural cells to a differentiated state is from the ventricular zone. Furthermore, cells expressing the definitive independent of the expression of proneural proteins. neuronal markers6,20 NeuN, Tuj1 or NF1, or the interneuron marker21 Lim2, were generally Sox21-negative (Fig. 1g and data not Myc Sox3 Myc BrdU Lim2 NeuN Tuj1 NF1 shown). Post-mitotic V2 interneurons cond e f a b c tinued to express Sox21 together with the V2 interneuron-specific marker Chx10 (ref. 22, data not shown). Together, these analyses show that the expression of Sox21 is mainly limited to Sox1–3+ progenitor cells10,12 and

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Figure 3 The activities of Sox21 and Sox3 are distinguished by their C-terminal regions. (a) Constructs used: C-terminal regions of Sox3 (blue) and Sox21 (yellow) were fused to a myc-epitope tag (dark gray; CtSox3-myc and CtSox21-myc) and to the HMG domains of Sox21 (green; HMGSox21-CtSox3-myc) and Sox3 (red; HMGSox3-CtSox21-myc). (b–f) Forced expression of HMGSox3-CtSox21 suppressed progenitor features (b,c) and promoted the expression of Lim2 (d) and NeuN (e) but not NF1 (f). (g–k) Misexpression of HMGSox21-CtSox3 maintained transfected cells in a progenitor state (g,h) and hindered the expression of neuronal markers (i–k). Scale bars, 60 mm in b–f and 100 mm in g–k.

Next, we determined whether the capacity of Sox21 to promote differentiation of progenitor cells reflects its function as a transcriptional repressor or activator. To examine this, the HMG domain of Sox21 was either expressed alone or fused to heterologous transcriptional repressor or activator domains. The HMG domain, misexpressed alone, had no detectable activity (data not shown). However, transfection of the HMG domain fused to the repressor domain of the Drosophila melanogaster protein Engrailed26 (HMG-EnR) mimicked the activity of full-length Sox21 protein and promoted electroporated cells to exit the cell cycle and upregulate the expression of the neuronal markers Lim2 and NeuN (Fig. 2g–i,n). Similar to full-length Sox21, HMG-EnR did not promote the expression of Tuj1 or NF1 (data not shown). In contrast, Myc cells transfected with the HMG domain fused Sox21:Sox3 a to the activator domain of the viral protein ratio

VP16 (HMG-VP16; ref 27) did not upregulate the expression of neuronal proteins and continued to incorporate BrdU even 45 h after electroporation (Fig. 2j–l,n). Together, these results indicate that Sox21 promotes neural cell differentiation through its function as a transcriptional repressor, whereas an activator form of Sox21 had similar activity as Sox1–3 (ref. 12,13) and maintained neural cells as progenitors. Specification of Sox21 and Sox3 activities Our results support the idea that Sox21 and Sox1–3 regulate a similar repertoire of target genes15. Accordingly, the distinct activities

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Figure 4 Sox21 counterbalances the activity of Sox1–3. (a,b) Cells transfected with Sox21 and Sox3 for 20 h at a vector ratio of 0.25:1 expressed the progenitor marker Pax6 (a) but not the neuronal marker NeuN (b). (c,d) Cells transfected with Sox21 and Sox3 at a vector ratio of 1:1 showed suppressed progenitor identities (c) but did not upregulate the expression of NeuN (d). (e–h) Cotransfection of Sox21 and Sox3 at a vector ratio of 2:1 promoted cells to suppress progenitor features (e) and upregulate the expression of NeuN (f), whereas cells electroporated with Sox21 and Sox3 at the reverse vector ratio, 1:2, remained in a progenitor state (g) and did not upregulate neuronal traits (h). (i–l) Transfection of Sox21 alone (0.25:0, which equals a Sox21 vector concentration of 0.25 mg/ml) promoted cells to suppress progenitor characteristics (i) and to upregulate the expression of NeuN (j), whereas electroporation of Sox3 without Sox21 (0:1, which equals a Sox3 vector concentration of 1 mg/ml) blocked the generation of neurons (l) and maintained cells in a progenitor state (k). Scale bars, 60 mm in a–j and 100 mm in k and l. (m) Percentage of cells incorporating BrdU or expressing NeuN after Sox21 and Sox3 cotransfection (mean 7 s.d.).

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Figure 5 Decreased levels of Sox21 protein inhibit neurogenesis. (a–e) Expression of Sox21 shRNA decreased the endogenous level of Sox21 protein expression by 32 7 5% (n ¼ 400 cells; 6 sections; a). Under these conditions the generation of differentiated cells expressing neuronal markers was reduced by more than 55% (n ¼ 6 sections) (c–e) compared with the nonelectroporated control side. (f–j) Expression of Sox21 (f) and the progenitor marker Sox3 (g) and the neuronal markers Lim2, NeuN, NF1 and Tuj1 (h–j) in cells electroporated with control shRNA. (k,l) Histograms show reduction in expression of Sox21 (k) and neuronal markers (l) after Sox21 and control shRNA transfection, compared with nonelectroporated control side of neural tube. (m,n) Expression of Sox21 shRNA reduced the number of NeuroM-expressing cells by approximately 60% (n), whereas the number of Ngn2-expressing cells remained relatively constant, compared with the nonelectroporated control side (m). (o) Expression of Sox21 shRNA increased the number of BrdU-incorporating Ngn2+ cells more than fivefold, compared with the control side. (p–r) Control shRNA did not alter the number of Ngn2- or NeuroM-expressing cells (p,q) or the number of BrdU-incorporating Ngn2+ cells (r). (s) Reduction in expression of Ngn2 and NeuroM after Sox21 and control shRNA transfection, compared with nonelectroporated control side. (t) Percentage of Ngn2+ cells incorporating BrdU after Sox21 transfection and control shRNA transfection, compared with nonelectroporated control side. All data are mean 7 s.d. Scale bars: 100 mm (a–j); 60 mm (m–r).

measured with Sox21 and Sox1–3 proteins12,13 might be based primarily on regulatory differences outside their respective HMG domains. To examine this notion, the C-terminal portion14 of Sox21 was either misexpressed alone or fused with the HMG domain of Sox3 (Fig. 3a). Alone, the C-terminal domain of Sox21 did not alter the expression profile of progenitor and neuronal markers (data not shown). However, a derivative containing the Sox21 C-terminal domain fused to the Sox3 HMG domain (Fig. 3a) induced cells to exit the division cycle, suppress Pax6 expression and upregulate neuronal markers, all within 15 h of electroporation (Fig. 3b–f). Thus, the ability of Sox21 to promote differentiation appears to be conferred by its C-terminal region. Conversely, cells transfected with a derivative containing the C-terminal portion of Sox3 fused to the Sox21 HMG domain (Fig. 3a) were maintained in a proliferative and Pax6+ progenitor state and failed to upregulate the expression of Lim2, NeuN or NF1, even 45 h after transfection (Fig. 3g–k). The C-terminal domain of Sox3 had no measurable activity when transfected alone (data not shown). Hence, the opposite activities of Sox21 and Sox3

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appear to be conferred by the distinct regulatory functions of their C-terminal regions14 and are independent of their HMG domains. Sox21 counterbalances the activity of Sox1–3 The varying expression levels of Sox21 within Sox1–3+ progenitor cells (Fig. 1c) raise the possibility that the intrinsic balance of Sox21 and Sox1–3 expression determines whether neural cells remain as progenitors or commit to neuronal differentiation. To examine this possibility, we co-electroporated a fixed amount of vector expressing Sox3 with different amounts of vector expressing Sox21. Sox21 could not promote premature expression of neuronal markers when cotransfected with Sox3 at a vector ratio of 0.25:1 (Fig. 4). Instead, electroporated cells remained in a self-renewing Pax6+ progenitor state (Fig. 4a,m). Electroporation of Sox21 alone at this specific concentration caused cells to differentiate and upregulate the expression of neuronal markers, whereas transfection of Sox3 for 48 h on its own blocked the formation of neurons and maintained transfected cells in a Pax6+ progenitor state12,13 (Fig. 4i–l). Transfection of Sox21 and Sox3 expression vectors

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Figure 6 Sox21 expression is upregulated by proneural protein activity. (a,b) Ten hours after Ngn2 electroporation, the expression of Sox21 was markedly upregulated in transfected progenitor cells. Scale bar, 60 mm. (c,d) Forty-five hours after electroporation, cells transfected with Id2 had reduced Sox21 expression. Scale bars, 100 mm.

in a 1:1 ratio induced cells to exit the cell cycle and downregulate progenitor markers, but it did not induce the expression of NeuN (Fig. 4c,d,m). Transfection of Sox21 together with Sox3 at a vector ratio of 2:1 suppressed progenitor cell features and upregulated neuronal markers (Fig. 4e,f,m), whereas cells electroporated with Sox21 and Sox3 at the reverse vector ratio, 1:2, remained in a Pax6+ progenitor state and did not upregulate neuronal markers (Fig. 4g,h,m). Thus, transfected cells are prompted to express either progenitor, post-mitotic or neuronal traits, depending on the relative levels of Sox21 and Sox3 activities. The amount of Sox21 protein was approximately five times greater in cells transfected with Sox21 and Sox3 expression vectors at a ratio of 2:1, respectively, compared with cells transfected at a vector ratio of 0.25:1 (confocal measurements, data not shown). Notably, similar results were obtained when Sox21 was co-electroporated with vectors expressing Sox1 or Sox2 (data not shown). Together, these findings indicate that the intrinsic balance of Sox21 and Sox1–3 activities determines the status of differentiation of neural cells. Decreased level of Sox21 inhibits neurogenesis To examine the necessity of Sox21 activity for the progression of neurogenesis, we next reduced the endogenous level of Sox21 expression by RNA interference28. Short RNA hairpins (shRNA)29 directed against a chick Sox21-specific sequence lowered Sox21 protein expression by more than 32% (Fig. 5a). Under these conditions the generation of cells expressing definitive neuronal markers was decreased by more than 55% (Fig. 5b–e). The ability to suppress neurogenesis could not be mimicked by control RNA hairpins containing a scrambled but identical repertoire of nucleotides (Fig. 5f–l). Together these results indicate that Sox21 activity is required for the generation of neurons. We next investigated at which step during neurogenesis Sox21 activity is required for progenitor cells to differentiate into neurons. High levels of Sox3 have previously been shown to suppress neurogenesis by blocking the step at which differentiating progenitor cells upregulate the expression of the intermediate zone marker NeuroM12,19. Thus, one possible function of Sox21 is to facilitate differentiating neural cells to progress from an Ngn2+ to a NeuroM+ state. Indeed, misexpression of Sox21 shRNA reduced the number of NeuroM+ cells but did not lower the number of cells expressing Ngn2 (Fig. 5m,n). Instead, transfection of Sox21 shRNA markedly increased the number of Ngn2+ cells incorporating BrdU (Fig. 5o). Control shRNA did not alter the expression of NeuroM or the amounts of Ngn2+ cells incorporating BrdU (Fig. 5p–t). Thus, Sox21 seems to counteract the activity of Sox1–3 and promote the step at which differentiating progenitor cells leave the division cycle to upregulate the expression of NeuroM. In contrast, Sox21 does not seem to influence the earlier generation of Ngn2-expressing cells.


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Sox21 is upregulated by proneural protein activity The finding that reduced levels of Sox21 expression hindered Ngn2+ cells in committing to differentiation prompted us to investigate whether the capacity of Ngn2 to drive the generation of neurons from progenitor cells30,31 is accompanied by increased Sox21 expression. Indeed, 10 h after electroporation, Sox21 was substantially upregulated in Ngn2-transfected cells (Fig. 6a,b). Furthermore, transfection of another proneural bHLH protein, Ascl1 (also known as Mash1) had similar activity as electroporated Ngn2 and induced high levels of Sox21 expression (data not shown). Notably, Sox21 was upregulated before Ngn2 had initiated the expression of post-mitotic neuronal markers (Supplementary Fig. 2). Thus, the generation of neurons by Ngn2 overexpression seemed to be preceded by increased expression of Sox21, whereas overexpression of Id2 decreased the level of Sox21 expression (Fig. 6c,d) and suppressed the generation of neurons (Supplementary Fig. 1). Together, these results demonstrate that proneural protein activity can upregulate the level of Sox21 expression in neural cells. Furthermore, transfection of Sox21 together with Ngn2 promoted the expression of a full array of neuronal markers, including NF1 and Tuj1, within 10 h of transfection (Supplementary Fig. 2). Thus, in addition to the regulatory relationship between Ngn2 and Sox21, they seem to function synergistically in the formation of neurons from progenitor cells. DISCUSSION Our data suggest that the generation of neurons from precursor cells depends on Sox21 repressor activity, which promotes neurogenesis by counteracting the function of Sox1–3. Thus, whether neural cells remain as progenitors or commit to neuronal differentiation seems to depend on the intrinsic balance of Sox21 and Sox1–3 activity. Our data show that proneural proteins upregulate the expression of Sox21 and thereby shift the balance of Sox21 and Sox1–3 activity. Our findings position Sox21 in a central role during neurogenesis and suggest that an important function of proneural bHLH proteins is their capacity to upregulate the expression of Sox21. Sox21 and Sox1–3 have distinct regulatory functions during neurogenesis, yet their opposite activities seem to be conferred by regions outside of their DNA-binding HMG domains. We have shown that a chimeric protein consisting of the HMG domain of Sox21 fused to the heterologous transcriptional activator VP16 mimics the activity of Sox1–3 proteins and thus blocks neurogenesis. Moreover, swapping the C-terminal regions of Sox21 and Sox3 proteins confirms that specific properties of Sox21 and Sox3 rely on protein domains other than the HMG domain. The most plausible interpretation of these results is that Sox21 and Sox1–3 regulate a common set of target genes and that the expression status of these genes determines whether neural cells commit to differentiation or remain undifferentiated (Supplementary Fig. 3). In line with this idea, in vitro analyses have shown that Sox21 can counteract Sox1/Sox2–mediated activation of the d-crystalline minimal enhancer DC5 (ref. 15). Furthermore, our data show that high levels of Sox3 prevent Sox21 from promoting differentiation, whereas Sox3-transfected cells readily differentiate when co-electroporated with high levels of Sox21. These findings are consistent with a model in which Sox1–3 and Sox21 activate and repress, respectively, a common set of target genes which, in turn, maintain the undifferentiated state of neural progenitor cells (Supplementary Fig. 3). According to our model, whether neural cells differentiate or remain as progenitors depends on the relative balance of Sox21 and Sox1–3 activities. Thus, one possible developmental mechanism is that the amount of Sox21 expression progressively increases in progenitor cells

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ARTICLES until a critical level is reached at which Sox1–3–activated genes are repressed, inducing these cells to commit to differentiation. Indeed, our findings favor this idea, as the expression of Sox21 was most pronounced in the lateral aspect of the ventricular zone. Hence, the activity of Sox21, and its ability to promote differentiation, may be reflected by its level of expression. However, the widespread expression pattern of Sox21 within the ventricular zone indicates that the activity level of Sox21 is likely to be regulated by other mechanisms as well. For instance, the specificity and stability of the interaction between Sox proteins and DNA have been shown to be influenced by the presence of specific partner factors14. Furthermore, the activity of Sox proteins can be altered by small ubiquitin-like modifiers32, and Sox21 has been reported to be antagonized by the transcription factor YB-1 (ref. 33). Thus, the expression of such factors may provide an alternative post-transcriptional mechanism for the regulation of the activity of Sox21. Notch receptor signaling restricts the neurogenic potential of precursor cells by activating transcriptional repressors of the Hes gene family3 which, in turn, suppress the expression of proneural genes34. Hence, Notch receptor activation determines whether neural cells should commit to differentiation by controlling the expression of proneural genes. In contrast, neither Sox1–3 nor Sox21 seems to control the expression of proneural genes. Sox1–3 proteins suppress, instead, the capacity of proneural proteins to induce downstream events of neuronal differentiation12, and we now show that the function of proneural proteins is dependent on Sox21. Thus, the expression of proteins regulated by Sox1–3 and Sox21 seems to control the ability of proneural proteins to coordinate downstream events of neuronal differentiation. Accordingly, the capacity of proneural proteins to upregulate Sox21 activity is likely to represent a mechanism that enables proneural proteins to promote neural cells to suppress progenitor features and commit to downstream events of neuronal differentiation. Collectively, our results demonstrate that the generation of neurons from progenitor cells is regulated by Sox and proneural bHLH proteins. Interestingly, neural crest differentiation and muscle cell differentiation are coordinated by bHLH transcription factors35,36 and counteracted by Sox10 and Sox15 proteins, respectively37,38. In light of this, it is plausible to speculate that the mechanism committing neural cells to differentiation has parallels in stem cell populations outside the developing CNS. METHODS This work was approved by the Swedish Animal Research Committee in Stockholm (approval number n211/02). Immunohistochemistry and in situ hybridization. Antibody staining was performed as described previously21. Rabbit antisera were generated against the chick Ngn2 peptide (C terminus: CEHWPPPRGRFAPPPPPHR) and guinea pig antisera against the chick Sox21 peptide (N terminus: GGHTHSHPSPGNPGY MIPC). Additional antibodies and BrdU labeling methods are described elsewhere12. The procedure for in situ hybridization was performed as described previously39 using chick probes for Sox21 (ref. 15). Expression constructs and in ovo electroporation. cDNAs encoding chick Sox21 and Sox3 were used. DNA encoding the HMG domains of Sox21 (amino acids (given in parentheses) 8–82) and Sox3 (43–120) were fused to the following: a myc tag, a VP16 activator domain (400–488), a myc-tagged En repressor (2–298), a myc-tagged C-terminal domain of Sox3 (141–313) and a myc-tagged C-terminal domain of Sox21 (102–281). cDNAs were subcloned into the CMV-based vectors pCS+MT and pCAGGS. Vectors expressing short RNA hairpins were constructed basically as described29 to specifically target chick Sox21 mRNA (nucleotides 302–332). Expression vectors were

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electroporated into the neural tube of HH stage 10 chick embryos12. After 5–48 h of incubation, embryos were fixed and processed for immunohistochemistry and in situ hybridization. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We thank H. Kondoh for Sox21 chick cDNA, and we are grateful to J. Ericson, T. Perlmann and members of the Muhr lab for discussions and comments on the manuscript. J.M. is supported by The Swedish Natural Research Council, The Swedish Foundation for Strategic Research, the Ake Wiberg Research Foundation, the Magnus Bergvall Foundation, the Jeansson Research Foundations and the Ludwig Institute for Cancer Research. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 20 May; accepted 2 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Kintner, C. Neurogenesis in embryos and in adult neural stem cells. J. Neurosci. 22, 639–643 (2002). 2. Bertrand, N., Castro, D.S. & Guillemot, F. Proneural genes and the specification of neural cell types. Nat. Rev. Neurosci. 3, 517–530 (2002). 3. Davis, R.L. & Turner, D.L. Vertebrate hairy and Enhancer of split related proteins: transcriptional repressors regulating cellular differentiation and embryonic patterning. Oncogene 20, 8342–8357 (2001). 4. Koyano-Nakagawa, N., Kim, J., Anderson, D. & Kintner, C. Hes6 acts in a positive feedback loop with the neurogenins to promote neuronal differentiation. Development 127, 4203–4216 (2000). 5. Bae, S., Bessho, Y., Hojo, M. & Kageyama, R. The bHLH gene Hes6, an inhibitor of Hes1, promotes neuronal differentiation. Development 127, 2933–2943 (2000). 6. Farah, M.H. et al. Generation of neurons by transient expression of neural bHLH proteins in mammalian cells. Development 127, 693–702 (2000). 7. Lee, J.E. et al. Conversion of Xenopus ectoderm into neurons by NeuroD, a basic helixloop-helix protein. Science 268, 836–844 (1995). 8. Ma, Q., Kintner, C. & Anderson, D.J. Identification of neurogenin, a vertebrate neuronal determination gene. Cell 87, 43–52 (1996). 9. Kamachi, Y., Uchikawa, M., Collignon, J., Lovell-Badge, R. & Kondoh, H. Involvement of Sox1, 2 and 3 in the early and subsequent molecular events of lens induction. Development 125, 2521–2532 (1998). 10. Pevny, L.H., Sockanathan, S., Placzek, M. & Lovell-Badge, R. A role for SOX1 in neural determination. Development 125, 1967–1978 (1998). 11. Uwanogho, D. et al. Embryonic expression of the chicken Sox2, Sox3 and Sox11 genes suggests an interactive role in neuronal development. Mech. Dev. 49, 23–36 (1995). 12. Bylund, M., Andersson, E., Novitch, B.G. & Muhr, J. Vertebrate neurogenesis is counteracted by Sox1–3 activity. Nat. Neurosci. 6, 1162–1168 (2003). 13. Graham, V., Khudyakov, J., Ellis, P. & Pevny, L. SOX2 functions to maintain neural progenitor identity. Neuron 39, 749–765 (2003). 14. Kamachi, Y., Uchikawa, M. & Kondoh, H. Pairing SOX off: with partners in the regulation of embryonic development. Trends Genet. 16, 182–187 (2000). 15. Uchikawa, M., Kamachi, Y. & Kondoh, H. Two distinct subgroups of Group B Sox genes for transcriptional activators and repressors: their expression during embryonic organogenesis of the chicken. Mech. Dev. 84, 103–120 (1999). 16. Rex, M., Uwanogho, D.A., Orme, A., Scotting, P.J. & Sharpe, P.T. cSox21 exhibits a complex and dynamic pattern of transcription during embryonic development of the chick central nervous system. Mech. Dev. 66, 39–53 (1997). 17. Hamburger, V. The stage series of the chick embryo. Dev. Dyn. 195, 273–275 (1992). 18. Fode, C. et al. The bHLH protein NEUROGENIN 2 is a determination factor for epibranchial placode-derived sensory neurons. Neuron 20, 483–494 (1998). 19. Roztocil, T., Matter-Sadzinski, L., Alliod, C., Ballivet, M. & Matter, J.M. NeuroM, a neural helix-loop-helix transcription factor, defines a new transition stage in neurogenesis. Development 124, 3263–3272 (1997). 20. Caccamo, D.V. et al. An immunohistochemical study of neuropeptides and neuronal cytoskeletal proteins in the neuroepithelial component of a spontaneous murine ovarian teratoma. Primitive neuroepithelium displays immunoreactivity for neuropeptides and neuron-associated beta-tubulin isotype. Am. J. Pathol. 135, 801–813 (1989). 21. Tsuchida, T. et al. Topographic organization of embryonic motor neurons defined by expression of LIM homeobox genes. Cell 79, 957–970 (1994). 22. Tanabe, Y., William, C. & Jessell, T.M. Specification of motor neuron identity by the MNR2 homeodomain protein. Cell 95, 67–80 (1998). 23. Ericson, J. et al. Pax6 controls progenitor cell identity and neuronal fate in response to graded Shh signaling. Cell 90, 169–180 (1997). 24. Yokota, Y. Id and development. Oncogene 20, 8290–8298 (2001). 25. Dubreuil, V., Hirsch, M.R., Jouve, C., Brunet, J.F. & Goridis, C. The role of Phox2b in synchronizing pan-neuronal and type-specific aspects of neurogenesis. Development 129, 5241–5253 (2002). 26. Smith, S.T. & Jaynes, J.B. A conserved region of engrailed, shared among all en-, gsc-, Nk1-, Nk2- and msh-class homeoproteins, mediates active transcriptional repression in vivo. Development 122, 3141–3150 (1996).

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ARTICLES 27. Berk, A.J. et al. Mechanisms of viral activators. Cold Spring Harb. Symp. Quant. Biol. 63, 243–252 (1998). 28. Hannon, G.J. RNA interference. Nature 418, 244–251 (2002). 29. Paddison, P.J., Caudy, A.A., Bernstein, E., Hannon, G.J. & Conklin, D.S. Short hairpin RNAs (shRNAs) induce sequence-specific silencing in mammalian cells. Genes Dev. 16, 948–958 (2002). 30. Mizuguchi, R. et al. Combinatorial roles of olig2 and neurogenin2 in the coordinated induction of pan-neuronal and subtype-specific properties of motoneurons. Neuron 31, 757–771 (2001). 31. Novitch, B.G., Chen, A.I. & Jessell, T.M. Coordinate regulation of motor neuron subtype identity and pan-neuronal properties by the bHLH repressor Olig2. Neuron 31, 773–789 (2001). 32. Komatsu, T. et al. Small ubiquitin-like modifier 1 (SUMO-1) modification of the synergy control motif of Ad4 binding protein/steroidogenic factor 1 (Ad4BP/SF-1) regulates synergistic transcription between Ad4BP/SF-1 and Sox9. Mol. Endocrinol. 18, 2451– 2462 (2004). 33. Ohba, H. et al. Sox21 is a repressor of neuronal differentiation and is antagonized by YB1. Neurosci. Lett. 358, 157–160 (2004).


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34. Kageyama, R. & Nakanishi, S. Helix-loop-helix factors in growth and differentiation of the vertebrate nervous system. Curr. Opin. Genet. Dev. 7, 659–665 (1997). 35. Tajbakhsh, S., Rocancourt, D., Cossu, G. & Buckingham, M. Redefining the genetic hierarchies controlling skeletal myogenesis: Pax-3 and Myf-5 act upstream of MyoD. Cell 89, 127–138 (1997). 36. Ma, Q., Fode, C., Guillemot, F. & Anderson, D.J. Neurogenin1 and neurogenin2 control two distinct waves of neurogenesis in developing dorsal root ganglia. Genes Dev. 13, 1717–1728 (1999). 37. Kim, J., Lo, L., Dormand, E. & Anderson, D.J. SOX10 maintains multipotency and inhibits neuronal differentiation of neural crest stem cells. Neuron 38, 17–31 (2003). 38. Beranger, F., Mejean, C., Moniot, B., Berta, P. & Vandromme, M. Muscle differentiation is antagonized by SOX15, a new member of the SOX protein family. J. Biol. Chem. 275, 16103–16109 (2000). 39. Schaeren-Wiemers, N. & Gerfin-Moser, A. A single protocol to detect transcripts of various types and expression levels in neural tissue and cultured cells: in situ hybridization using digoxigenin-labelled cRNA probes. Histochemistry 100, 431–440 (1993).

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Multiple origins of Cajal-Retzius cells at the borders of the developing pallium Franck Bielle1, Ame´lie Griveau1,5, Nicolas Narboux-Neˆme1,5, Se´bastien Vigneau1,4, Markus Sigrist2, Silvia Arber2, Marion Wassef1 & Alessandra Pierani1,3 Cajal-Retzius cells are critical in cortical lamination, but very little is known about their origin and development. The homeodomain transcription factor Dbx1 is expressed in restricted progenitor domains of the developing pallium: the ventral pallium (VP) and the septum. Using genetic tracing and ablation experiments in mice, we show that two subpopulations of Reelin1 Cajal-Retzius cells are generated from Dbx1-expressing progenitors. VP- and septum-derived Reelin1 neurons differ in their onset of appearance, migration routes, destination and expression of molecular markers. Together with reported data supporting the generation of Reelin1 cells in the cortical hem, our results show that Cajal-Retzius cells are generated at least at three focal sites at the borders of the developing pallium and are redistributed by tangential migration. Our data also strongly suggest that distinct Cajal-Retzius subtypes exist and that their presence in different territories of the developing cortex might contribute to region-specific properties.

The cerebral cortex has a laminar organization in which earlier- and later-born neurons accumulate according to an inside-out gradient. Until recently, it was thought that neuronal classes were produced by the local pallium ventricular zone and reached their final laminar destination by means of radial glia–mediated migration1,2. This model has now been complemented by evidence supporting the existence of tangential migration from the subpallium to the cerebral cortex3. Retzius (1893) and Cajal (1899) described cells with a complex morphology located in the marginal zone of humans at the time of cortical lamination, and now named Cajal-Retzius cells. Similar cells with simpler morphology have been described in the marginal zone of rodents4. The number of Cajal-Retzius cells seems to decrease after the completion of cortical lamination1,5. The most well documented function of Cajal-Retzius cells is to control the formation of cortical layers by means of the expression of the extracellular glycoprotein Reelin3,6,7. Additional functions for Cajal-Retzius cells have been proposed as in the regulation of the radial glia phenotype8 and in the development of hippocampal connections9. Until now, the term ‘Cajal-Retzius cells’ has been used to identify a heterogeneous population of morphologically and molecularly distinct cell types in the marginal zone/layer I of different species and at different times during embryogenesis and postnatal life4,5,10,11. However, the lineage relationship between these cell types is unresolved. The consensus emerging from recent reports is that Cajal-Retzius cells are glutamatergic and express pallial markers11. Their pallial origin has

been demonstrated by genetic tracing using an Emx1-Cre mouse line12, as Emx-1 is expressed exclusively in the pallium. They seem to be born between embryonic day (E) 10.5 and E12.5 in mice and are thus among the first neurons to be generated in the developing cortex. In addition, it is now agreed that Reelin in the marginal zone is a marker of CajalRetzius cells in the embryonic cortex of several species. Despite many years of study, the origins and molecular properties of Cajal-Retzius cells are still unresolved. Cajal-Retzius cells were thought to be produced by the local pallium ventricular zone1 and thus throughout the neocortical neuroepithelium11,13, but focal pallial and subpallial sources for Cajal-Retzius cells have also been proposed: the retrobulbar area14, the olfactory primordium5, the cortical hem13,15 and the medial ganglionic eminence16. Evidence supporting a cortical hem source has come from studies of the IG17 transgenic mouse using in utero electroporation17. However, several sources of Reelin+ cells in the developing marginal zone remain hypothetical, and the roles of putative subpopulations are largely unknown. The investigation of these questions has been limited so far because of the lack of molecular markers available to identify subclasses of Cajal-Retzius cells and to trace them from their site of origin to the time of neural network formation in the postnatal cortex. Cell fate allocation and cell diversity are determined at very early stages in progenitor cells at precise coordinates along the dorsoventral and anteroposterior axis18–20. The Dbx1 homeodomain transcription factor is expressed in progenitors at the boundary between the dorsal and ventral plates21–23 of the caudal neural tube, from

1Centre National de la Recherche Scientifique-Unite ´ Mixte de Recherche 8542, Ecole Normale Supe´rieure, 46 rue d’Ulm, 75005 Paris, France. 2Biozentrum, Department of Cell Biology, University of Basel, Klingelbergstrasse 70, 4056 Basel, Switzerland, and Friedrich Miescher Institute, Maulbeerstrasse 66, 4058 Basel, Switzerland. 3Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Center for Neurobiology and Behavior, Columbia University, New York, New York 10032, USA. 4Current address: Unite´ Geńe´tique Molećulaire Murine, Institut Pasteur, 28 rue du docteur Roux, 75724 Paris, France. 5These authors contributed equally to this work. Correspondence should be addressed to A.P. ([email protected]).


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Figure 1 Dbx1 expression at dorsoventral boundaries in the telencephalon: septum and ventral pallium. (a,e,f) Whole-mount in situ hybridization of Dbx1 mRNA in E11.5 wild-type mouse embryos. (b,c,d,g) Whole-mount X-gal staining in E11.5 Dbx1nlslacZ/+ (b,g), E11.5 Dbx1Cre/+;bactin:lacZ (c) and E12.5 Dbx1Cre/+;bactin:lacZ (d) embryos. (h) Dbx1 mRNA is detected only in the septum but not at the PSB in E4 chick embryos. a–d show lateral views of dissected forebrains; e, medial view of a sagittally hemisected brain; f and g, dorsal views. Black lines in a correspond to rostral (r) and caudal (c) sections shown in m–r. Brackets in f and g show rostrocaudal extension of mRNA and X-gal detection, respectively. In a–e and h, rostral is at the left; in f,g, rostral is at the bottom. (i,j) In situ hybridization of Dbx1 mRNA on cryostat sections of E11.5 caudal (i) and E12.5 rostral (j) wild-type telencephalons. (k,l) X-gal staining on cryostat sections of E12.5 Dbx1nlslacZ/+ (k) and Dbx1Cre/+;bactin:lacZ (l) telencephalon at comparable rostral levels as j. In i–l, dorsal is at the top. Se: septum; hy: hypothalamus; th: thalamus. (m–r) Comparison of Dbx1 mRNA in situ hybridization (m,o,q) and X-gal staining (n,p,r) in E11.5 Dbx1nlsLacZ/+ embryos (serial sections). Brackets mark dorsoventral extent of mRNA and X-gal detection. Open arrowheads: sites of Dbx1 expression; filled arrowheads: b-gal+ cells located at the farthest distance from sites of Dbx1 expression. Scale bar: 1 mm (a–g), 50 mm (m–r), 300 mm (i–l). (s,t) Putative migration routes of Dbx1-derived b-gal+ cells.

which postmitotic cells migrate tangentially to their final destination. In the spinal cord, the spatially restricted expression of Dbx1 in progenitors is critical in establishing the distinction between Evx1/2 (V0) and En1 (V1) interneuron cell fates and helps to coordinate diverse phenotypic features24,25. In the telencephalon, Dbx1 is expressed in restricted progenitor domains at the borders of the developing pallium: the VP at the pallial-subpallial boundary (PSB), the septum and the preoptic area/anterior entopeduncular area (POA/AEP)26,27. In this study, we trace the fate of cells derived from Dbx1 progenitors in the telencephalon from embryonic to postnatal stages using a genetic approach in mice. By combining genetic tracing and DiI labeling, we show that Dbx1-derived cells migrate from the septum to the medial and piriform cortex and from the PSB to the dorsolateral and piriform cortex. Cells derived from Dbx1+ progenitors express Reelin and are Cajal-Retzius cells in the postnatal cortex. These Dbx1-derived CajalRetzius cells seem to have distinct origins, onsets of appearance and final destinations, and they differ in expression of calretinin. Our genetic approach proves the existence of two previously unknown sites of origin for Cajal-Retzius cells and suggests that distinct subpopulations of Cajal-Retzius cells are present in different territories of the developing cortex.


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RESULTS Dbx1 is expressed at border regions of the telencephalon The expression of the Dbx1 gene is restricted to a narrow domain at the dorsoventral boundary in the spinal cord and telencephalon21–23,26,27. We mapped the onset and location of Dbx1 expression in the telencephalon of mouse embryos using in situ hybridization (Fig. 1). Expression began around E10.5 in the septum and POA/AEP. At E11.5 it reached its maximum in the septum, in the POA/AEP and near the PSB in the VP with a caudalhighrostrallow gradient (Fig. 1a,e,f,i,j)26. Dbx1 expression was restricted to progenitor cells in the ventricular zone. Dbx1 mRNA was detected on cells located close to the pial surface of the septum (Fig. 1j,m), whereas it is detected throughout the ventral pallium neuroepithelium (Fig. 1i,o,q). Dbx1 transcripts and protein were never observed in the ventricular zone of the lateral and medial ganglionic eminences (LGE and MGE, respectively) or in the neuroepithelium of the dorsal and medial pallium (Fig. 1i,j)26,27. Dbx1 expression progressively declined after E12.5 (ref. 27) but was still detectable during late embryogenesis (data not shown). Genetic manipulation of the Dbx1 locus As Dbx1 expression was transitory and exclusively detected in the ventricular zone, we used a mouse genetic approach to label cells

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ARTICLES derived from Dbx1-expressing progenitors. In the Dbx1nlslacZ line the insertion of the lacZ gene into the Dbx1 locus allows for short-term lineage tracing24. To permanently label Dbx1-derived cells, we generated a Dbx1Cre knock-in mouse line, which we subsequently crossed to reporter strains. Animals obtained by crossing Dbx1Cre and bactin: loxP-stop-loxP-nlslacZ28 or TauloxP-stop-loxP-MARCKSeGFP-IRES-nlslacZ reporter mice will be called Dbx1Cre/+;bactin:lacZ and Dbx1Cre/+;TauGFP, respectively. The use of these animals allowed us to label Dbx1-derived cells at various times after their generation (mitotic and early postmitotic in Dbx1nlslacZ/+ versus early- and late-postmitotic in Dbx1Cre/+;bactin:lacZ embryos). Representative images of cryostat sections from E12.5 Dbx1nlslacZ/+ and Dbx1Cre/+;bactin:lacZ embryos (Fig. 1k,l) show the subsequent labeling of Dbx1-expressing progenitors at the ventral pallium ventricular zone using a Dbx1 mRNA in situ probe (Fig. 1j) and Dbx1-derived b-galhigh (early postmitotic) and b-gallow (postmitotic) cells spanning from the ventricular zone to the mantle zone in Dbx1nlslacZ/+ embryos at more ventral and dorsal positions (Fig. 1k). Finally, permanently labeled Dbx1-derived postmitotic cells and their arborizations were detected in the mantle zone of Dbx1Cre/+;bactin:lacZ and Dbx1Cre/+;TauGFP embryos (Fig. 1l and data not shown). Dbx1-derived cells are highly motile We compared Dbx1 expression and b-gal activity at E11.5 in Dbx1nlslacZ/+ and Dbx1Cre/+;bactin:lacZ telencephalons using wholemount in toto preparations. Dbx1nlslacZ/+ embryos showed broader 5-bromo-4-chloro-3-indolyl-b-D-galactoside (X-gal) activity with respect to the detection of the Dbx1 mRNA along the rostrocaudal axis at the PSB and the septum, and along the dorsoventral axis at the PSB (compare Fig. 1a,b and Fig. 1f,g). Notably, Dbx1Cre/+;bactin:lacZ telencephalons at E12.5 showed even more X-gal cells along the rostral PSB, suggesting that Dbx1-derived cells migrate rostrally along the PSB. In addition, scattered X-gal cells were observed in the dorsofrontal half of the developing cortex (Fig. 1d). To better map the position of Dbx1-derived b-gal+ cells with respect to the sites of Dbx1 mRNA production, we analyzed serial sections of E11.5 Dbx1nlslacZ/+ embryos for Dbx1 transcripts by in situ hybridization and X-gal staining. At E11.5 in the telencephalon, b-gal+ cells were located at a distance from Dbx1+ cells, dorsally and ventrally to the rostral and caudal PSB ventricular zone and to the septum (compare Fig. 1m to Fig. 1n, Fig. 1o to Fig. 1p and Fig. 1q to Fig. 1r). b-gal+ cells were observed in the forming preplate of the medial, dorsolateral and ventral pallium (Supplementary Fig. 1). b-gal+ cells were located mostly dorsal to the PSB at rostral levels (Fig. 1o,p) and preferentially ventral to the PSB at more caudal levels (Fig. 1q,r). Between E11.5 and E12.5 Dbx1-derived b-gal+ cells seemed to be streaming ventrally and dorsally (Fig. 1k), and many were located in the preplate/marginal zone of the piriform territory and of the medial and dorsal pallium. b-gal+ nuclei in the marginal zone were oriented both parallel and perpendicular to the pial surface, and the number of nuclei and cell bodies oriented perpendicular to the surface increased with time (Supplementary Fig. 1). We believe that round nuclei perpendicular to the pial surface correspond to cells that have stopped migrating and have reached their final position. Thus, Dbx1 progenitors in the septum and VP generate mostly preplate/marginal zone cells between E10.5 and E12.5, and some Dbx1-derived cells seem to have already reached their final destination at E12.5. In order to test the capacity of Dbx1-derived cells to migrate, explants containing Dbx1+ progenitors were grown in a collagen matrix. Beginning at 1 d in vitro (DIV), b-gal+ cells were observed within and at a distance from rostral PSB (n ¼ 6) and caudal PSB

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(n ¼ 6) explants of Dbx1nlslacZ/+ E12.5 telencephalons (Supplementary Fig. 1). Similar results were obtained using septum and caudal PSB explants of E11.5 Dbx1Cre;bactin:lacZ embryos after 3 DIV (data not shown). Compared with interneuronal migration from MGE explants at E12.5, both speed and distance of Dbx1-derived b-gal+ cells in PSB and septum explants was very similar (data not shown). Taken together, these results suggest that Dbx1-derived cells are highly motile and migrate from their sites of origin to populate different cortical regions. Dbx1Cre/+;TauGFP cells migrate both dorsally and ventrally To study the routes of migration of Dbx1-derived b-gal+ cells, DiI labeling experiments were performed on coronal slices of E12.0–E12.5 Dbx1Cre/+;TauGFP telencephalons cultured in vitro. One DIV after the insertion of a crystal in the rostral septum (n ¼ 4; Fig. 2a,d–f), DiI+ cells were observed dorsally and ventrally in the marginal zone of the medial and ventral wall (Fig. 2b), respectively, and had traveled a long distance up to the dorsal cortex. Several DiI+ cells were colabeled with GFP (Fig. 2d–f, white arrow) and had a morphology consistent with migrating cells. However, when DiI crystals were inserted at progressively more caudal levels of the medioventral wall, the extent of dorsal migration decreased, whereas that of ventral migration remained unchanged (n ¼ 14, Fig. 2c and data not shown). DiI+/GFP+ cells were detected in a ventral stream up to the ventrolateral wall at the level of the piriform territory. When crystals were inserted at the PSB (n ¼ 11; Fig. 2g–r), DiI+ cells were observed ventrally (Fig. 2h,i), as expected from previous reports29–31. We were surprised to find that DiI+ cells were also detected dorsally in the intermediate zone and marginal zone of the dorsal pallium (Fig. 2g,h,j–r). The migration in the intermediate zone was more prominent in caudal sections. Colabeling of DiI and GFP was observed in cells in the marginal zone of the ventral pallium (Fig. 2i) and the dorsal pallium (Fig. 2j,o,p). DiI+/GFP+ cells were observed reaching as far dorsal as the prospective isocortex and as far ventral as the prospective piriform cortex. The extent of dorsal and ventral migration was quite similar at all caudorostral levels at this stage. DiI+/GFP– cells were also present in the migrating stream (about 30–50% of the total DiI+ cells were GFP–). These results reflect either an incomplete expression of the IRES in Dbx1-derived cells of Dbx1Cre/+ animals or that cells derived from progenitors other than Dbx1-expressing cells, most probably from the ganglionic eminences, can also migrate through the DiI-labeled area toward the cortex. Many GFP+ cells are present at this stage in the basal telencephalon in caudal sections and are likely to have been derived from Dbx1 progenitors in the POA. Thus, Dbx1-derived cells generated in the septum and the ventral pallium ventricular zone migrate in culture dorsally and ventrally along superficial routes of migration and reach the piriform cortex/isocortex and the medial wall/piriform cortex, respectively, within 24 h. Early-born Dbx1-derived cells express Reelin To begin investigating the identity of the cells derived from septum and PSB Dbx1+ progenitors, we first analyzed the time and position of their first appearance in the telencephalon. The first b-gal+ cells to be detected in Dbx1nlslacZ/+ embryos were located in the area of the septum at E10.5 (Fig. 3a and data not shown). At this stage, very few b-gal+ cells were present in proximity to the caudal PSB, whereas cells were detected between E11.0 and E11.5 at the rostral PSB (Fig. 3a,b,i,n and Fig. 1m–r). Dbx1-derived b-gal+ cells were among the first postmitotic cells to be generated, as suggested by their superficial position and by the lack of BrdU colabeling upon injection of BrdU at E10.75 (Fig. 3a,b).

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Figure 2 Dbx1Cre;TauGFP cells migrate dorsally and ventrally from the PSB and the septum in vitro. DiI+/GFP+ cells reach as far as the dorsal cortex in 24 h. (a,g,m) Bright-field images of DiI crystals inserted in the rostral septum (a) and PSB (g,m). (b,h,n) Dark-field images using a rhodamine filter of a,g,m, respectively. (c,d,i,j,o,p) Confocal images of double-labeled DiI and GFP cells. Areas enlarged in d,i,j,o are indicated by boxes in b,h,n. (d–f,j–l) d–f show medial wall dorsal to the septum; c shows basal wall of the telencephalon lateral to the septum; h,j–l,m–r show dorsal cortex and i ventral cortex after DiI insertion at the caudal PSB. (e,k,q) DiI single-label images. (f,l,r) Single-label GFP images. c,d,i,j,o,p show merged images (DiI and GFP). White arrowheads indicate DiI+/GFP+ double-labeled cells and black arrowheads DiI-only labeled cells. Scale bars ¼ 400 mm (a,b,g,h), 100 mm (m,n), 40 mm (c,d,i,j), 20 mm (o,p).

As Reelin seems to be a specific marker for the early-born CajalRetzius neurons in the marginal zone4, we tested whether Dbx1-derived cells express Reelin. The majority of Reelin+ cells at E10.5 are concentrated in the septum and rostral pallium and few in the caudomedial hem (Fig. 3d). Very few, if any, scattered Reelin+ cells are detected in the forming preplate in other telencephalic regions at this stage. Most (98%, n ¼ 153) postmitotic preplate Dbx1-derived cells in Dbx1nlslacZ/+ embryos expressed Reelin at E10.5–E11.0 (Fig. 3a–c). These results strongly suggest that Reelin+ neurons derived from Dbx1 progenitors in the septum were born at E10.5 and are consistent with the reported generation of a vast proportion of Reelin+ layer I neurons at this stage11. In addition, in Dbx1nlslacZ/+ embryos at E11.5 and E12.5, b-gal+/Reelin+ cells were detected at progressively longer distances from the Dbx1 progenitor zones (septum and PSB) up to the medial pallium, dorsal pallium and piriform cortex (Fig. 3e–s). A large proportion of b-gallow (differentiating Dbx1-derived) cells in the marginal zone of Dbx1nlslacZ/+ embryos between E10.5 and E12.5 expressed Reelin (rostrally 82%, n ¼ 116; caudally 67%, n ¼ 30 at E11.5). Rostrally, Dbx1-derived Reelin+ cells were scattered in the marginal zone around the whole telencephalic vesicles including the dorsal cortex (data not shown). Furthermore, at E11.0–E11.5 in the rostral half of the telencephalon, 72% of Reelin+ cells (n ¼ 57) in the piriform region, dorsolateral and medial pallium preplate and 50–60% of Reelin+ cells (n ¼ 84) in the superficial layer of


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the basolateral telencephalon express b-gal and thus derive from Dbx1 progenitors. As b-gal expression is lost in late postmitotic cells in Dbx1nlslacZ/+ animals, we analyzed Dbx1Cre embryos to trace later derivatives of Dbx1 progenitors (Fig. 3h). In the marginal zone of E12.5 Dbx1Cre/+; bactin:lacZ embryos, about 50–98% of b-gal+ cells were Reelin+, depending on the cortical or subcortical zones, the highest percentage being detected in the septum (98%) and in the rostral and caudal piriform cortex (80–85%). In addition, different proportions of Reelin+ cells were b-gal+ in distinct regions of the telencephalic vesicles. Rostrally and caudally, 90 to 43%, respectively, of Reelin+ cells colabeled with b-gal in the piriform territory, 40–50% in the lateral cortex, 12–20% in the dorsal-most cortex (medial and lateral), 99% in the intermediate medial wall (dorsal to the septum) and around 50–78% in the basal telencephalon. Moreover, beginning at E12.5, not all b-gal+ cells in the cortex expressed Reelin, and b-gal+/Reelin– cells were also detected in the caudal intermediate zone. As we did not observe colabeling of GABA and b-gal in PSB explants of E12.5 Dbx1nlslacZ/+ embryos kept in culture for 48 h (Fig. 6m), and no interneurons seem to be generated from the PSB until at least E12.5–E13.5, we believe that b-gal+ cells in the caudal intermediate zone represent populations of interneurons derived from Dbx1 progenitors in the caudal/ventral septum or AEP/POA (data not shown). These data strongly suggest that between E10.5 and E12.5, Reelin+ marginal zone neurons derived

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from the septum and the PSB preferentially populate rostral and dorsolateral/piriform cortex, respectively. As Reelin+ cells are homogeneously distributed around the telencephalic vesicles at E12.5, our results also suggest that caudodorsal and caudomedial cortical regions are populated by Reelin+ cells derived from a Dbx1-independent caudal source, which is likely to be the cortical hem17.

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Dbx1-derived Reelin+ cells are layer I Cajal-Retzius cells As Cajal-Retzius cells are defined by morphological criteria in layer I of the developed cortex, we genetically traced the fate of early Dbx1derived neurons in the late embryonic and postnatal cortex. b-gal+ cells were observed in the marginal zone/layer I and the cortical plate (CP) of the piriform cortex and the isocortex and in the hippocampus at E17

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Figure 3 Early-born Dbx1-derived cells in the preplate/marginal zone express Reelin. (a,b) Immunohistochemistry on a rostral section at septum level of an E10.75 Dbx1nlsLacZ/+ embryo labeled with BrdU 1 h before collection. b A higher-magnification view of a in PSB area. (c) High-magnification views of boxed area in a. (d) Whole-mount in situ hybridization of Reelin mRNA in E10.5 wild-type embryos; lateral view of telencephalic vesicle. Inset: frontal view of the right part of the head. (e–j,n–o) b-gal and Reelin staining in E11.5 Dbx1nlsLacZ/+ telencephalon at the level of the septum (e,f) rostral PSB (i,j) and caudal PSB (n,o). g shows the rostrocaudal level and the areas of confocal images acquisition. h shows schematic representation of Dbx1-derived b-gal+/Reelin+ cells in different regions of E12.5 Dbx1Cre/+;bactin:lacZ telencephalons (coronal section, lateral and dorsal views). (k) X-gal staining of an E12.5 Dbx1nlsLacZ/+ telencephalon section at an intermediate level along the rostrocaudal axis. Inset: magnification of marginal zone in lateral cortex of an E14.5 Dbx1Cre/+;bactin:lacZ embryo showing b-gal+ nuclei parallel (migrating) and perpendicular (resident) to the pial surface. (l,m) b-gal (green) and Reelin (red) staining in E12.5 Dbx1nlsLacZ/+ telencephalon sections at the same level as k. m shows high-magnification view of the piriform cortex. (p) X-gal staining of an E12.5 Dbx1Cre/+;bactin:lacZ section at the same level as k. (q–s) b-gal (red) and Reelin (green) staining in E12.5 Dbx1Cre/+;bactin:lacZ telencephalon sections at the same level as p. r,s are high-magnification images of areas indicated in p. White arrowheads: double-labeled b-gal+/Reelin+ cells. Black arrowheads: Reelin+-only cells. Immunohistochemical images were acquired with a confocal microscope. r: rostral; c: caudal; d: dorsal; v: ventral; se: septum; pir: piriform territory; pa: pallium. Scale bars ¼ 100 mm (a,i,j,l,n,o,q), 40 mm (b), 20 mm (c,e,f,m,r,s).

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Figure 4 Populations of Cajal-Retzius neurons in layer I are derived from Dbx1+ progenitors. (a,b) Location of areas enlarged in c–h. (c–e) X-gal staining on sections from the telencephalon of Dbx1Cre/+;bactin:lacZ E17.5 embryos. (f–h) Same view as c–e in P8 mice. White arrowheads: b-gal+ cells in the marginal zone. Black arrowheads: b-gal+ cells in other cortical layers. (d,g) b-gal+ cells (of which some were Reelin+; data not shown) were also located in the other layers (ventricular zone (VZ)/subventricular zone (SVZ) and cortical plate (CP) of the isocortex of P8 Dbx1Cre/+;bactin:lacZ animals. (i,j) Double labeling with Reelin and b-gal in Dbx1Cre/+;bactin:lacZ P8 animals. CA1, CA3: Ammon’s horn field 1 and 3; DG: dentate gyrus; pa: pallium; st: striatum; mz: marginal zone; cp: cortical plate; iz: intermediate zone; D, dorsal; L, lateral; M, medial; V, ventral. (k–o) Triple labeling with b-gal, Reelin and BrdU on cryostat sections of P2 Dbx1Cre/+;TauGFP cingulate cortex after BrdU injection at E10.5 during gestation. m–o show single confocal images corresponding to merge in l: Reelin (m), BrdU (n) and b-gal (o). l–o show high-magnification view of layer 1 in k. Scale bars ¼ 40 mm (i,j,l–o); 200 mm (c–h,k).

(Fig. 4a,c–e) and P8 (Fig. 4b,f–h) in Dbx1Cre/+;bactin:lacZ animals. In order to determine the birthdates of Dbx1-derived cells present in the postnatal cortex, we analyzed b-gal+ cells in Dbx1Cre/+;TauGFP-IRESnlslacZ animals at P2 after a single BrdU injection at E10.5 of gestation. Dbx1derived b-gal+ cells were observed as in P8 animals in the marginal zone/layer I and the CP (Fig. 4k). However, only b-gal+ cells in the marginal zone/layer I coexpressed Reelin (Fig. 4k,l). In addition, cells in the marginal zone/layer I exclusively were labeled with BrdU, and some of the BrdU+ cells in the marginal zone/layer I were bgal+ and Reelin+ (Fig. 4l–o). We conclude that b-gal+/Reelin+ cells present in the marginal zone/layer I were born at least in part at E10.5; this is consistent with the early birth date of Cajal-Retzius cells. b-gal+ cells (of which some were Reelin+) were also located in the other layers (ventricular zone (VZ)/subventricular zone (SVZ) and CP) of the isocortex of P8 Dbx1cre/+;bactin:lacZ animals (Fig. 4d,g and data not shown). As Reelin+ interneurons have been described in the postnatal cortical plate starting at P5 (refs. 10,11), b-gal+/Reelin+ cells in the CP at P8 are probably later-born Dbx1-derived interneurons. Moreover, b-gal+ cells seemed to start decreasing in number in the isocortex and hippocampus at P8, consistent with the reported progressive disappearance of Cajal-Retzius cells from the marginal zone/layer I after P7 (Fig. 4d,g,e,h). Finally, some b-gal+/Reelin+ cells in the marginal zone/ layer I of Dbx1Cre/+;bactin:lacZ animals at P8 had the typical morphology, position and orientation of Cajal-Retzius neurons: at this stage their cell body had reached a final depth of about 20–30 mm, but they still had ascending branchlets that contacted the pial membrane (Fig. 4i,j).


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We conclude that Dbx1+ progenitors at the septum and PSB give rise to Reelin+ bona fide postnatal Cajal-Retzius neurons on the basis of the following evidence: (i) the Reelin immunoreactivity of Dbx1-derived cells between E10.5 and E12.5 in the pallial preplate/marginal zone, (ii) the localization of these cells in the marginal zone/layer I of the isocortex, piriform and hippocampus at P8, (iii) their birth date at E10.5 in BrdU-injected P2 animals and (iv) their morphology. Loss of Reelin+ cells upon ablation of Dbx1-expressing cells In order to analyze the effect of eliminating Dbx1 progenitors on Reelin+ cell development, we inserted an IRES-loxP-stop-pGKneo-loxPDTA (diphtheria toxin) cassette into the Dbx1 locus by homologous recombination (Dbx1loxP-stop-loxP-DTA). A functional DTA is expressed exclusively upon Cre-mediated recombination. Mutant animals were crossed with a Nes:Cre mouse line which expresses the Cre recombinase ubiquitously in the neuroepithelium starting around E11.0 (ref. 32), allowing spatially and temporally restricted expression of the toxin. Because of the multiple origins of Reelin+ cells, we first analyzed Reelin mRNA expression using whole-mount in situ hybridization. Although Reelin is widely expressed throughout the telencephalic vesicles at E11.5, some areas seemed to be more intensively stained, namely the septum and the piriform territory (Fig. 5b,c). These same regions show stronger X-gal activity in E11.5 Dbx1Cre/+;bactin:lacZ (Fig. 5a) and thus seem to correspond to areas where two of the migratory routes of Dbx1-derived cells are located. We observed a strong decrease in the number of Reelin-expressing cells in the most rostral and caudal piriform cortex in recombined Dbx1DTA;Nes:Cre

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embryos at E11.5 (Fig. 5d, white arrowhead) as well as an almost complete loss in the septum (Fig. 5d, black arrowheads). At E12.5, we detected a strong loss of Reelin staining in the rostral piriform, caudal piriform/amygdaloid complex and septum as well as a significant reduction in the ‘intermediate rostrocaudal’ piriform cortex (Fig. 5e– h). An overall reduction of the rostrocaudal axis of the telencephalic vesicles and of the olfactory bulb was also observed. Using a TUNEL reaction we showed that Dbx1-derived cells start to die around E11.0 in the septum and at E11.5 at the PSB (Supplementary Fig. 2). Therefore, it is possible that some early Dbx1-derived cells are spared from cell death and thus account for some of the Reelin+ neurons still present in the piriform cortex and in the most rostrodorsal cortex. Notably, a strong reduction of Reelin expression was detected in the septum as well as in the dorsolateral, medial and caudal piriform cortex in E12.5 Dbx1DTA;Nes:Cre embryo sections (Fig. 5i,j,o–r and data not shown). No differences were observed between wild-type mice and mutants in the cortical hem (Fig. 5m,n). In contrast, when Reelin expression was

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Figure 5 Ablation of Dbx1-derived cells results in loss of Reelin+ cells in different cortical regions and in cortical defects. (a) Whole-mount X-gal staining (blue) in E11.5 Dbx1Cre/+;bactin:lacZ telencephalon. (b–h) Whole-mount in situ hybridization with a Reelin mRNA probe (purple) in E11.5 wild-type (Dbx1LoxP-Stop-LoxP-DTA; b,c), E11.5 Dbx1DTA;Nes:Cre (d), E12.5 wild-type (e,g) and E12.5 Dbx1DTA;Nes:Cre (f,h) embryos. White arrowheads: rostral and caudal piriform areas. Black arrowheads: septum. (i,j,m–r) In situ hybridization with a Reelin mRNA probe on sections of E12.5 wild-type (i,m,o,q) and Dbx1DTA;Nes:Cre (j,n,p,r) embryos at rostral (i,j) and caudal (m–r) levels. m–r show highmagnification views of different telencephalic regions. (k,l) In situ hybridization with a Reelin mRNA probe on rostral sections of E14.5 wildtype (k) and Dbx1DTA;Nes:Cre (l) embryos at level equivalent to i,j. High-magnification view of the lateral pallium. LP: lateral pallium; MP: medial pallium; se: septum; pir: piriform cortex. (s–v) Cresyl violet staining of P0 wild-type (s,u) and Dbx1DTA;Nes:Cre (t,v) telencephalons at rostral (s,t) and caudal levels (u,v) showing differences in cortical cytoarchitecture. Insets in s,t: high-magnification view of the cingulate cortex. White arrowheads: position of rhinal fissure. Black arrowheads: position of Layer VIb. hi: hippocampus. Scale bars ¼ 1 mm (a–h), 500 mm (i,j,s–v), 50 mm (k,l–r).

r analyzed at E14.5, no significant differences were observed between the wild-type and ablated cortex (Fig. 5k,l), suggesting that Reelin+ cells from other sources rapidly cover up the regions deprived of Dbx1-derived CajalDbx1DTA ;Nes:Cre Retzius cells. Since these animals die at birth, v to study the effect of Dbx1-derived cell ablation on later cortical development, we analyzed P0 Dbx1DTA;Nes:Cre animals. Differences were consistently observed in the cytoarchitecture of the cerebral cortex between wild-type and mutant animals at both rostral and caudal levels (Fig. 5s–v; n ¼ 3). Defects were more pronounced in the lateral regions of the cortex. The thickness of the cingulate cortex appeared fairly normal (compare insets in Fig. 5s,t). As expected from the rapid repopulation of the ablated cortex with Cajal-Retzius cells from other sources, the mutant cortex did not show a Reeler phenotype, which is characterized by failure of preplate splitting, disorganized cortical plate and cell-dense layer I. Indeed, a cell-poor marginal zone and a distinguishable Layer VIb were present in the mutant cerebral cortex (Fig. 5s–v), suggesting a normal splitting of the preplate. We conclude that ablation of Dbx1 progenitors starting at E11.0 results in (i) loss of Cajal-Retzius cells in distinct regions of the developing cortex, in particular the medial and dorsolateral pallium, and (ii) alteration of the early postnatal cortical cytoarchitecture. VP but not septum-derived Reelin+ cells express calretinin A high proportion, but not all, of the Reelin+ neurons in the marginal zone express calretinin11. In order to determine if Dbx1-derived cells give rise to calretinin+/Reelin+ cells, triple immunolabeling using antibodies against b-gal, Reelin and calretinin were performed on coronal

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sections of E11.5 Dbx1nlslacZ/+ telencephalon. In the presumptive piriform cortex marginal zone, almost all (95%) b-gal+ cells were Reelin+, of which 40–50% were calretinin+ (Fig. 6h–k). We were surprised to find that at the pial surface in the septum 95–98% of b-gal+ cells were Reelin+, but none of these b-gal+/Reelin+ cells coexpressed calretinin (Fig. 6a,b). b-gal+/Reelin+/calretinin– cells were also located ventrally and dorsally to the septum. Consistent with these results, in E12.5 Dbx1Cre/+;TauGFP telencephalon, mediorostral cortical GFP+/Reelin+ cells very rarely coexpressed calretinin (5–10%) whereas 43–55% of piriform and isocortical marginal zone GFP+/Reelin+ cells expressed calretinin (Fig. 6c–g). At later stages (E14.5), likely because of the extensive migration from their multiple sites of origin, Reelin+/calretinin+ or Reelin+/calretinin– cells intermingle in different cortical regions. To test whether the lack of calretinin expression in Dbx1-derived septal Reelin+ cells was not just a temporal delay, we cultured PSB and septum explants of E11.5 Dbx1Cre/+;bactin:lacZ embryos in collagen for 3 DIV and immunolabeled for b-gal, Reelin and calretinin. PSB explants (n ¼ 3) contained many b-gal+/Reelin+ cells, and most of them also expressed calretinin (Fig. 6o). Very few b-gal+/Reelin+/ calretinin– cells were observed in these explants compared with the piriform territory in vivo (Fig. 6f,k). These results suggest that b-gal+/Reelin+/calretinin– cells in the VP of E11.5 Dbx1nlslacZ/+ and E12.5 Dbx1Cre/+;TauGFP telencephalons are likely to express calretinin at later stages rather than representing a real ability of VP Dbx1 progenitors to give rise to two distinct Reelin+ cell populations. On the contrary, explants dissected from the septum (n ¼ 3) contained many b-gal+/Reelin+ cells which were mostly calretinin– (Fig. 6n) after 3 DIV. These results suggest that the ventral pallium and the septum are the origin of b-gal+/Reelin+/calretinin+ and b-gal+/Reelin+/ calretinin– cells, respectively, and that the lack of calretinin expression in septum-derived cells is not due to a developmental delay. We conclude that two subpopulations of Cajal-Retzius neurons with distinct


[

Calr

Figure 6 Dbx1-derived Reelin+ cells from the PSB express calretinin, but those from the septum do not. Confocal microscope images of triple labeling with b-gal (red), Reelin (green) and calretinin (blue) in E11.5 Dbx1nlsLacZ/+ (a,b,h–k) and Reelin (red), GFP (green) and calretinin (blue) in E12.5 Dbx1Cre/+;TauGFP telencephalon (c–g). g shows ventral telencephalic wall including the ventral piriform territory. White arrowheads: triple-labeled b-gal+/Reelin/+calretinin+ cells. Black arrowheads: Reelin+/calretinin+-only cells. Young b-gal+ (b-galhigh) cells in the VZ of the septum and VP are Reelin–/calretinin–. (l) Schematic of the areas dissected as explants of the septum and PSB in m–o. Explants were dissected from E12.5 Dbx1nlsLacZ/+ embryos and kept in culture for 2 d in m and from E11.5 Dbx1Cre/+;bactin:lacZ and for 3 d in n,o. m shows triple labeling with GABA (red), b-gal (green) and b-tubulin (blue). n,o show triple labeling with Reelin (green), bgal (red) and calretinin (blue). Scale bars ¼ 20 mm.

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characteristics (origin, onset of appearance, migration route, destination and gene expression profile) derive from Dbx1+ progenitors of the septum and the ventral pallium.

DISCUSSION Using mouse genetics we have identified two previously unknown sites of origin of CajalRetzius cells: the septum and the PSB. Two distinct subsets of Cajal-Retzius cells are generated during early development from Dbx1+ septal and PSB progenitors and differ in their site of origin, onset of appearance, migration routes, destination and expression of molecular markers. We propose that distinct subpopulations of Cajal-Retzius cells originate from at least three distinct focal areas, including the caudomedial hem17, at the borders of the developing pallium. Different cortical regions are populated by specific combinations of these Cajal-Retzius subtypes. Genetic tracing of cell populations derived from Dbx1+ progenitors Morphological and immunohistological studies have been used to describe populations of cells according to their position, morphology and gene expression profile. Nevertheless, they have limits in determining the relationship between the cell types observed at different stages and their sites of origin and migration routes. We have used a knock-in strategy at the Dbx1 locus to follow the fate of Dbx1-derived cells. Dbx1 is expressed by progenitors in restricted domains of the telencephalon: the VP at the PSB22,26,27, the septum and the AEP/POA. Anatomical studies of often transient and non-overlapping expression profiles in progenitors or differentiated cells had suggested that the VP gives rise to part of the claustroamygdaloid complex27. However, the transient expression of Dbx1 in the ventricular zone has thus far prevented from tracing the derivatives of this domain. Moreover, because of the lack of specific molecular markers, derivatives of the septum have not yet been analyzed in detail. The analysis of Dbx1nlslacZ and Dbx1Cre/+; reporter:LacZ/GFP animals has permitted us to follow the progeny of Dbx1+ progenitors through their entire lifespan from the ventricular zone to their adult location and thus analyze cell identity, migration routes and final location of Dbx1+ progenitors-derived cells. Indeed, we were able to genetically trace the progeny of Dbx1 progenitors and to identify them as the first Reelin+ neurons to appear in the preplate of the septum and of the VP.

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ARTICLES Migration routes of Dbx1-derived neurons Subpallial regions have been shown to be the source of tangentially migrating cells into the cortex3,31. We show that tangential migration also occurs between different pallial territories and that Cajal-Retzius cells migrate from focal progenitor sites at the border of the pallium to different regions of the developing cortex. Indeed, septal Cajal-Retzius cells are clearly pallial, as they coexpress Emx1 (A.P., unpublished results), and the expression of the Dbx1 gene in the lateral wall corresponds to the ventral pallium ventricular zone26,27. DiI has been used to study migration of interneurons from the subpallium to the cortex (for review see refs. 3,31). However, migration from the PSB has been particularly difficult to address, as the PSB does not correlate with morphological landmark (angle) and is crossed by many cells from the subpallium migrating towards the cortex. Previous studies using DiI labeling near the PSB suggested that subpallial cells cross the PSB to form the piriform area29, but the origin and molecular identity of these cells was not determined. Moreover, DiI labeling close to the PSB was reported in the rat16,33. However, these studies failed to identify the PSB as the source of dorsally migrating cells. In addition, it has been suggested16 that Reelin+ but calretinin– Cajal-Retzius cells migrate like interneurons from the MGE to the pallium through the marginal zone. We suggest that these Cajal-Retzius cells traverse the MGE by rostrocaudal and ventrodorsal migration but were born in the septum or AEP/POA. Thus, DiI labeling has fallen short in determining the progenitor sites for some migrating cells. The combination of genetic tracing and DiI labeling has allowed us to unequivocally determine the routes of migration of genetically labeled progenies of Dbx1 progenitors. We provide evidence that populations of Reelin+ Cajal-Retzius cells in the marginal zone of the cortex are derived from progenitors in the VP and septum. We describe ventral and a dorsal migration trajectories from the VP ventricular zone and the septum (Supplementary Fig. 3). If the ventral migration from the VP has already been suggested and might correspond to the lateral/ ventral migratory stream29–31, the others had not been reported previously. Three streams of migration for interneurons, similar to the ones we describe in this work, have been identified34, beginning at E11.5 in the mouse. The authors suggested that an interplay might occur between Cajal-Retzius cells and interneurons to ensure proper cortical integration. Dbx1-derived Cajal-Retzius cell migration is in place earlier than that of interneurons from the subpallium and correlates with the time of appearance of the first-born neurons in the preplate. Thus, they may release cues (if any exist) along these early migration paths (E10.5), which could influence the migration of laterborn cells, including interneurons. Regional differences in Dbx1-derived Cajal-Retzius subtypes Our data show that PSB-derived cells migrate dorsally up to the isocortex and ventrally to the piriform cortex. Dbx1-derived cells from the septum reach the medial cortex dorsally and at least as far as the piriform region ventrolaterally. The piriform cortex might, therefore, be of mixed origin with respect to Cajal-Retzius cells and might be populated by cells derived from the VP and the septum. Taking into account recent results17, we believe that at rostral levels, an early Dbx1-derived population of Cajal-Retzius cells generated from the septum will preferentially populate the frontomedial cortex, whereas populations of Cajal-Retzius cells derived from the hem and the PSB (Dbx1-derived) will colonize the caudomedial/dorsal and lateral cortex, respectively (Supplementary Fig. 3). Because of the high motility of Dbx1-derived Cajal-Retzius cells in vitro and in vivo and that of hem-derived Reelin+ cells in utero17, classes of Cajal-Retzius cells generated at different sites have the capacity to intermingle in

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certain regions of the developing cortex. Our genetic ablation experiments of Dbx1-derived Cajal-Retzius cells using DTA confirm the tracing studies and show a differential loss of Reelin+ cells in cortical regions. Thus, cortical territories are populated by different combinations of molecularly distinct Cajal-Retzius subtypes from early stages of development, when regionalization takes place, and this might contribute to rendering these territories molecularly distinct. Septum and VP-derived Cajal-Retzius subtypes are distinct Our results suggest that two subpopulations of Cajal-Retzius neurons with distinct characteristics (origin, onset of appearance, migration route, destination and gene expression profile) derive from Dbx1+ progenitors of the septum and the ventral pallium. First, the onset of generation of Dbx1-derived cells in the VP seems to be later than that in the septum and correlates precisely with that of Reelin+ cells. VP and septum-derived Reelin+ cells migrate along distinct routes to different regions of the embryonic pallium and are observed in the marginal zone of their postnatal derivatives. Septum- and VP-derived cells preferentially populate rostral and lateral cortical territories, respectively, and some seem to have reached their final destination very early during development. Finally, Dbx1-derived cells of the VP and septum differ in expression of calretinin in vivo and in vitro. These results strongly suggest that two distinct populations of Reelin+ cells are derived from Dbx1+ progenitors: a calretinin+ population from the VP and a calretinin– population from the septum. The origins of Cajal-Retzius cells have been a long unresolved question. The olfactory primordium was proposed as a source of Cajal-Retzius cells in macaque monkeys5. Our results show that the ventral pallium is the source of a calretinin+ population of Cajal-Retzius neurons invading the mouse isocortical and piriform marginal zone. However, b-gal+/Reelin+/calretinin– cells are also present in the piriform cortex and the isocortex at E12.5. These cells might have been generated in the VP and/or the septum, or alternatively might acquire calretinin expression later. The retrobulbar area was also proposed as the source of a population of Cajal-Retzius neurons4 and calretinin– Cajal-Retzius neurons were described in the marginal zone of the hippocampus10. We show that the septum, close to the retrobulbar area, is a source of calretinin– Cajal-Retzius neurons, invading the rostral cortex and possibly the marginal zone of the hippocampus by rostrocaudal migration. The two subpopulations of Cajal-Retzius neurons (septum- and VP-derived) that we describe are likely to intermingle in the dorsal pallium (Supplementary Fig. 3), consistent with the previous observation in the isocortex of a few calretinin– and a majority of calretinin+ Cajal-Retzius neurons11. Recently, the caudomedial wall of the telencephalic vesicles, including the hem, has been reported to be a site of origin of Reelin+ neurons17. Calretinin is expressed in the majority of these cells at late stages of development. These cells migrate extensively throughout the neocortical marginal zone with a caudomedial-rostrolateral gradient and are likely, therefore, to provide Cajal-Retzius calretinin+ cells to dorsal cortical regions. Our experiments do not exclude that additional sites of origin for Cajal-Retzius cells might exist and that some Cajal-Retzius cells could also be generated in the dorsal pallium ventricular zone, as it has been shown for humans5. However, the three focal sites (hem17, septum and ventral pallium) account for a vast proportion of CajalRetzius cells in the mouse, and molecular evidence is lacking that the dorsal pallium neuroepithelium does produce Cajal-Retzius cells under normal conditions in the mouse. The relative importance of focal sources and local production of Cajal-Retzius cells by the dorsal pallium could distinguish primates and rodents, as in the case of interneurons, and may represent a mechanism to ensure cell

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ARTICLES diversity and increase complexity required for the evolution of the human cortex. Several reports have described differences between cortical regions that are consistent with the existence of distinct Cajal-Retzius populations and with the fact that the presence of different CajalRetzius subtypes correlates with region-specific properties. In Tbr1 mutant animals35 the piriform and isocortex are hypocellular, but the hippocampus is not. This correlates with a decrease of Reelin expression in Cajal-Retzius cells in the lateral and piriform cortex but not in the medial cortex. In these animals, differences in lamination are also observed in different cortical territories. Moreover, the differences in the phenotype in the medial versus the lateral cortex in Emx1/2 single and double mutants suggest the existence of Cajal-Retzius populations with different origins13,36,37. Notably, we have detected Emx1 expression in Dbx1-derived cells in the septum but not at the PSB at E11.5 (A.P., unpublished results) suggesting that septum- and PSB-derived Cajal-Retzius cells might differ in expression of Emx genes. These results, together with the role of Cajal-Retzius cells in maintenance of the radial glia phenotype8 and in axonal growth38, strongly suggest additional functions of Cajal-Retzius cells besides their general role in lamination and strongly supports the notion of functional heterogeneity of Cajal-Retzius cells. What is the purpose of subtypes of Cajal-Retzius cells in the cortex? Together with the data from previous reports11,17,39, our results show that molecularly distinct Cajal-Retzius subtypes migrate tangentially from at least three focal sources at the borders of the pallium and populate different cortical territories at early stages of development. Even if these three populations of Cajal-Retzius cells intermingle afterwards, cortical territories will differ in the percentage of distinct Cajal-Retzius subtypes, and this might contribute to determine region and/or area-specific properties. Notably, in animals with mutated p73 (a gene expressed in the caudal hem and tenia tecta), hem-derived Cajal-Retzius cells are lost, and an expansion of calretinin expression is detected in dorsal cortical regions15. These data are consistent with our results that show the existence of a rapid compensation mechanism between distinct classes of Cajal-Retzius cells. In addition, a dorsal shift of the entorhinal cortex and a transformation of occipital and posterior temporal areas into an enthorhinal-like cortex is observed in the p73 mutants40. Consistent with these findings, lamination also differs between cortical regions, and the presence of Cajal-Retzius subtypes correlates with differences in the numbers of cell layers (three in allocortical regions, such as the hippocampus or the piriform cortex, four in mesocortical regions and six in the isocortex), and thus it is possible that distinct Cajal-Retzius classes might have a role in regionspecific lamination. Notably, Dbx1 expression is conserved in the septum of the chick telencephalon but not in the PSB (VP) and correlates with the medial cortex being a laminated region in this species, unlike the dorsal ventricular ridge, a derivative of the VP/LP (lateral pallium) in birds and reptiles41. In addition, the presence of an anterior piriform cortex in this species is consistent with a contribution from the septum as we have suggested in the mouse. Thus, the PSB expression of Dbx1 might have been recruited during evolution to support a function or functions specific to mammals. METHODS Generation of Dbx1 mutant mice. The Dbx1nlsLacZ mutant mouse line was generated by replacing the Dbx1 gene coding sequence with an nlslacZ/pGK-neo cassette as previously reported24. In this construct, the lacZ gene coding for a nuclear b-galactosidase protein is translated at the first ATG of the Dbx1 gene. Dbx1loxP-stop-loxP-DTA animals were generated by inserting an IRES-loxP-stoppGK-neo-loxP-DTA cassette into the BamHI restriction site present in the 3¢ UTR of the Dbx1 gene. In this cassette, the open reading frame of the diphtheria


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toxin gene (DTA)42 is interrupted by a pGK-neo cassette (for selection in embryonic stem cells) flanked by loxP sites43. The cassette is preceded by an IRES (internal ribosome entry site). Dbx1Cre animals were generated by inserting an IRES-CRE-pGK-Hygror cassette into the BamHI site present in the 3¢ UTR of the Dbx1 gene. Recombination was achieved in two steps using the I-SceI-induced gene replacement system developed previously44. Both the Dbx1Cre and Dbx1loxP-stop-loxP-DTA were constructed by inserting an IRES cassette in the same 3¢ UTR site; therefore, expression from the recombinant loci are expected to be very similar. Differences in labeling in Dbx1nlslacZ/+ and Dbx1Cre/+; bactin:lacZ embryos were observed. These are likely to correspond to a delay in the recombination and expression of the reporter gene in Dbx1Cre/+;bactin:lacZ embryos, and thus the earliest Dbx1-derived cells are not labeled in these animals. Use of mice in this study was approved by Veterinary Services of Paris. Animal strains. bactin:loxP-stop-loxP-lacZ reporter animals were a gift from D. Anderson, (California Institute of Technology, Pasadena, California)28. In this transgenic line, the lacZ gene under the control of the chick b-actin promoter is preceded by a transcription-translation stop cassette surrounded by two loxP sites. TauloxP-stop-loxP-MARCKSeGFP-IRES-nlslacZ was obtained by replacing the coding sequence of the Tau gene (microtubule associated protein) with a sequence coding for a MARCKS (myristoylated alanine-rich C-kinase substrate) protein fused to green fluorescent protein (GFP) and followed by an IRESnlslacZ cassette45. The gene coding for the MARCKS protein is preceded by a transcription-translation stop cassette surrounded by two loxP sites. All animals are kept in a C57B6 background. The deleter Nes:Cre animals expressing the Cre recombinase under the control of the Nestin promoter were previously described and were a gift from F. Tronche32 (College de France, Paris). Embryos and postnatal animals were genotyped by PCR using primers specific for the different alleles (Cre, lacZ, GFP, Dbx1 and DTA). Dbx1Cre;TauGFP recombined embryos were sorted directly with a fluorescence binocular lens. In situ hybridization, X-gal staining and immunocytochemistry. For staging of embryos, midday of the vaginal plug was considered as embryonic day 0.5 (E0.5). Embryos for immunocytochemistry were fixed at 4 1C using 4% paraformaldehyde (PFA) in 0.1 phosphate buffer (PB) pH 7.3 for 2 h; rinsed in PBS for 2 h; cryoprotected overnight using 30% sucrose, 0.1 M PB and embedded in O.C.T. compound (Sakura). Embedded tissue was sectioned on a cryostat with a 12 mm step. b-gal activity was revealed by incubating sections or whole-mount embryos for 3 h to overnight at 37 1C in a 600 mg/ml X-gal solution in 0.1 M PB, 2.0 mM MgCl2, 0.01% sodium desoxycholate, 0.02% NP40, 5 mM K3Fe(CN)6, 5 mM K4Fe(CN)6. In situ hybridization on sections and antibody staining was performed as previously described24. In situ probes were mouse Reelin46, chick Dbx1 (ref. 23) and mouse Dbx1 (ref. 47). Wholemount in situ hybridization was performed according to a previously described protocol48. Immunohistochemistry on sections and explants were performed as previously described23. Primary antibodies were rabbit anti-b-galactosidase (Rockland; 1:1,000), G10 mouse anti-Reelin (1:1,000; gift of A. Goffinet, University of Louvain Medical School, Brussels), goat anti-calretinin (Swant; 1:500); rat anti-BrdU (Accurate Chemical; 1:400). All fluorescent secondary antibodies were purchased from Jackson ImmunoResearch. TUNEL was performed according to the supplier’s protocol (Roche). Postnatal animals at P2 and P8 were perfused using 4% PFA. Dbx1Cre;TauGFP P2 animals and E10.75–E11.0 embryos were obtained from females injected intraperitoneally with a single dose of BrdU (15 mg/kg) at E10.5 of gestation. Explant and slice cultures and DiI injection. After removal from the placenta, embryos were maintained in PBS containing 50 U/ml penicillin G (Invitrogen), 50 mg/ml streptomycin sulfate (Invitrogen) and 6 mg/ml glucose at 0 1C. The same conditions were used for explant and slice cultures. For explant cultures, the head was dissected, the meninges were removed and explants of PSB and septum were isolated from the telencephalic vesicles. After polymerization of a 20 ml layer of collagen (90% Vitrogen 100, 10% 5 culture medium (DMEM 2.5/F12 2.5 (Invitrogen), 0.15% NaHCO3) in a well 15 min at 37 1C, explants were immersed in a second 20 ml drop of collagen and polymerized 45 min at 37 1C before adding 500 ml of the culture medium. For slice cultures, the dissected telencephalon was embedded in 3% low melting point agarose (Invitrogen) in L15 (Invitrogen) supplemented with 50 U/ml penicillin G,

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ARTICLES 50 mg/ml streptomycin sulfate and 5.4 mg/ml glucose at 37 1C, chilled at 0 1C, and coronal sections of 250 mm were prepared using a vibratome. Sections were positioned on a Millicell membrane (0.4 mm, Millipore) laid on 1.1 ml of culture medium in one well of Nunclon (6 wells, Nunc). The culture medium for both explant and slice cultures was prepared as follow: DMEM 0.5, F12 0.5, 2 mM L-glutamine, 6 mg/ml glucose, 0.075% NaHCO3, 10 mM HEPES, 500 U/ml penicillin G, 500 mg/ml streptomycin sulfate, 1 B27 supplement (Invitrogen). DiI crystals (Molecular Probes) were inserted into the septum or PSB of coronal slices at different rostrocaudal levels of Dbx1Cre/+;TauGFP embryos. Slices and explants were cultured at 37 1C in a humidified atmosphere containing 5% CO2 for 1 and 2–4 d, respectively. We analyzed GFP and DiI colabeling using a confocal microscope, and as DiI strong spots could have bled into the green channel, we considered DiI+/GFP+-only cells in which the GFP staining was homogeneously distributed along all the processes and cell body. Thus, it is likely that we underestimated the number of colabeled cells. Images acquisition. Pictures were acquired using a digital camera coupled to a fluorescence binocular lens or a confocal microscope (Leica TCS Sp2). Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We are indebted to T.M. Jessell for having made this work possible. We thank K. Campbell for suggesting that Dbx1 progenitors give rise to Cajal-Retzius cells; M. Sunshine and D. Littman for helping in the generation of the Dbx1loxP-stop-loxP-DTA mouse line; A. Nemes and M. Mendelsohn for embryonic stem cell transfection and injection of the Dbx1Cre line; F. Tronche for providing the Nes:CRE mouse line, D. Anderson for the bactin:loxP-stop-loxP-lacZ mice and A. Goffinet for the G10 anti-Reelin monoclonal antibodies; M. CohenTannoudji and F. Jaisser for the I-SceI-induced gene replacement system; P. Alexandre and R. Goiame for technical help and advice and M. Ensini, S. Garel, C. Goridis, T.M. Jessell and O. Marin for comments on the manuscript. F.B. was the recipient of a fellowship from the Acade´mie Nationale de Me´decine (France). S.A. and M.S. were supported by a grant from the Swiss National Science Foundation, by the Kanton of Basel-Stadt and by the Novartis Research Foundation. A.P. and M.W. are CNRS (Centre National de la Recherche Scientifique) Investigators. This work was supported by the Ministe`re de la Recherche (ACI grant # 0220575) and the Association pour la Recherche sur le Cancer (grant # 4679) to A.P. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 10 May; accepted 27 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Marin-Padilla, M. Cajal-Retzius cells and the development of the neocortex. Trends Neurosci. 21, 64–71 (1998). 2. Kriegstein, A.R. & Noctor, S.C. Patterns of neuronal migration in the embryonic cortex. Trends Neurosci. 27, 392–399 (2004). 3. Marin, O. & Rubenstein, J.L. Cell migration in the forebrain. Annu. Rev. Neurosci. 26, 441–483 (2003). 4. Meyer, G., Goffinet, A.M. & Fairen, A. What is a Cajal-Retzius cell? A reassessment of a classical cell type based on recent observations in the developing neocortex. Cereb. Cortex 9, 765–775 (1999). 5. Zecevic, N. & Rakic, P. Development of layer I neurons in the primate cerebral cortex. J. Neurosci. 21, 5607–5619 (2001). 6. D’Arcangelo, G. et al. A protein related to extracellular matrix proteins deleted in the mouse mutant reeler. Nature 374, 719–723 (1995). 7. Ogawa, M. et al. The reeler gene-associated antigen on Cajal-Retzius neurons is a crucial molecule for laminar organization of cortical neurons. Neuron 14, 899–912 (1995). 8. Super, H., Del Rio, J.A., Martinez, A., Perez-Sust, P. & Soriano, E. Disruption of neuronal migration and radial glia in the developing cerebral cortex following ablation of CajalRetzius cells. Cereb. Cortex 10, 602–613 (2000). 9. Del Rio, J.A. et al. A role for Cajal-Retzius cells and reelin in the development of hippocampal connections. Nature 385, 70–74 (1997). 10. Alcantara, S. et al. Regional and cellular patterns of reelin mRNA expression in the forebrain of the developing and adult mouse. J. Neurosci. 18, 7779–7799 (1998). 11. Hevner, R.F., Neogi, T., Englund, C., Daza, R.A. & Fink, A. Cajal-Retzius cells in the mouse: transcription factors, neurotransmitters, and birthdays suggest a pallial origin. Brain Res. Dev. Brain Res. 141, 39–53 (2003). 12. Gorski, J.A. et al. Cortical excitatory neurons and glia, but not GABAergic neurons, are produced in the Emx1-expressing lineage. J. Neurosci. 22, 6309–6314 (2002). 13. Shinozaki, K. et al. Absence of Cajal-Retzius cells and subplate neurons associated with defects of tangential cell migration from ganglionic eminence in Emx1/2 double mutant cerebral cortex. Development 129, 3479–3492 (2002).

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14. Meyer, G. & Wahle, P. The paleocortical ventricle is the origin of reelin-expressing neurons in the marginal zone of the foetal human neocortex. Eur. J. Neurosci. 11, 3937–3944 (1999). 15. Meyer, G., Perez-Garcia, C.G., Abraham, H. & Caput, D. Expression of p73 and Reelin in the developing human cortex. J. Neurosci. 22, 4973–4986 (2002). 16. Lavdas, A.A., Grigoriou, M., Pachnis, V. & Parnavelas, J.G. The medial ganglionic eminence gives rise to a population of early neurons in the developing cerebral cortex. J. Neurosci. 19, 7881–7888 (1999). 17. Takiguchi-Hayashi, K. et al. Generation of reelin-positive marginal zone cells from the caudomedial wall of telencephalic vesicles. J. Neurosci. 24, 2286–2295 (2004). 18. Jessell, T.M. Neuronal specification in the spinal cord: inductive signals and transcriptional codes. Nat. Rev. Genet. 1, 20–29 (2000). 19. Schuurmans, C. & Guillemot, F. Molecular mechanisms underlying cell fate specification in the developing telencephalon. Curr. Opin. Neurobiol. 12, 26–34 (2002). 20. Campbell, K. Dorsal-ventral patterning in the mammalian telencephalon. Curr. Opin. Neurobiol. 13, 50–56 (2003). 21. Lu, S., Bogarad, L.D., Murtha, M.T. & Ruddle, F.H. Expression pattern of a murine homeobox gene, Dbx, displays extreme spatial restriction in embryonic forebrain and spinal cord. Proc. Natl. Acad. Sci. USA 89, 8053–8057 (1992). 22. Shoji, H. et al. Regionalized expression of the Dbx family homeobox genes in the embryonic CNS of the mouse. Mech. Dev. 56, 25–39 (1996). 23. Pierani, A., Brenner-Morton, S., Chiang, C. & Jessell, T.M. A sonic hedgehog-independent, retinoid-activated pathway of neurogenesis in the ventral spinal cord. Cell 97, 903–915 (1999). 24. Pierani, A. et al. Control of interneuron fate in the developing spinal cord by the progenitor homeodomain protein Dbx1. Neuron 29, 367–384 (2001). 25. Lanuza, G.M., Gosgnach, S., Pierani, A., Jessell, T.M. & Goulding, M. Genetic identification of spinal interneurons that coordinate left-right locomotor activity necessary for walking movements. Neuron 42, 375–386 (2004). 26. Yun, K., Potter, S. & Rubenstein, J.L. Gsh2 and Pax6 play complementary roles in dorsoventral patterning of the mammalian telencephalon. Development 128, 193–205 (2001). 27. Medina, L. et al. Expression of Dbx1, Neurogenin 2, Semaphorin 5A, Cadherin 8, and Emx1 distinguish ventral and lateral pallial histogenetic divisions in the developing mouse claustroamygdaloid complex. J. Comp. Neurol. 474, 504–523 (2004). 28. Zinyk, D.L., Mercer, E.H., Harris, E., Anderson, D.J. & Joyner, A.L. Fate mapping of the mouse midbrain-hindbrain constriction using a site-specific recombination system. Curr. Biol. 8, 665–668 (1998). 29. de Carlos, J.A., Lopez-Mascaraque, L. & Valverde, F. Dynamics of cell migration from the lateral ganglionic eminence in the rat. J. Neurosci. 16, 6146–6156 (1996). 30. Corbin, J.G., Nery, S. & Fishell, G. Telencephalic cells take a tangent: non-radial migration in the mammalian forebrain. Nat. Neurosci. 4, 1177–1182 (2001). 31. Marin, O. & Rubenstein, J.L. A long, remarkable journey: tangential migration in the telencephalon. Nat. Rev. Neurosci. 2, 780–790 (2001). 32. Tronche, F. et al. Disruption of the glucocorticoid receptor gene in the nervous system results in reduced anxiety. Nat. Genet. 23, 99–103 (1999). 33. Tamamaki, N., Fujimori, K.E. & Takauji, R. Origin and route of tangentially migrating neurons in the developing neocortical intermediate zone. J. Neurosci. 17, 8313–8323 (1997). 34. Ang, E.S., Jr., Haydar, T.F., Gluncic, V. & Rakic, P. Four-dimensional migratory coordinates of GABAergic interneurons in the developing mouse cortex. J. Neurosci. 23, 5805–5815 (2003). 35. Hevner, R.F. et al. Tbr1 regulates differentiation of the preplate and layer 6. Neuron 29, 353–366 (2001). 36. Mallamaci, A. et al. The lack of Emx2 causes impairment of Reelin signaling and defects of neuronal migration in the developing cerebral cortex. J. Neurosci. 20, 1109–1118 (2000). 37. Mallamaci, A., Muzio, L., Chan, C.H., Parnavelas, J. & Boncinelli, E. Area identity shifts in the early cerebral cortex of Emx2 –/– mutant mice. Nat. Neurosci. 3, 679–686 (2000). 38. Borrell, V. et al. Reelin regulates the development and synaptogenesis of the layerspecific entorhino-hippocampal connections. J. Neurosci. 19, 1345–1358 (1999). 39. Meyer, G., Soria, J.M., Martinez-Galan, J.R., Martin-Clemente, B. & Fairen, A. Different origins and developmental histories of transient neurons in the marginal zone of the fetal and neonatal rat cortex. J. Comp. Neurol. 397, 493–518 (1998). 40. Meyer, G. et al. Developmental roles of p73 in Cajal-Retzius cells and cortical patterning. J. Neurosci. 24, 9878–9887 (2004). 41. Aboitiz, F., Montiel, J. & Lopez, J. Critical steps in the early evolution of the isocortex: insights from developmental biology. Braz. J. Med. Biol. Res. 35, 1455–1472 (2002). 42. Palmiter, R.D. et al. Cell lineage ablation in transgenic mice by cell-specific expression of a toxin gene. Cell 50, 435–443 (1987). 43. Lee, K.J., Dietrich, P. & Jessell, T.M. Genetic ablation reveals that the roof plate is essential for dorsal interneuron specification. Nature 403, 734–740 (2000). 44. Cohen-Tannoudji, M. et al. I-SceI-induced gene replacement at a natural locus in embryonic stem cells. Mol. Cell. Biol. 18, 1444–1448 (1998). 45. Hippenmeyer, S. et al. A developmental switch in the response of DRG neurons to ETS transcription factor signaling. PLoS Biol. 3, e159 (2005). 46. Schiffmann, S.N., Bernier, B. & Goffinet, A.M. Reelin mRNA expression during mouse brain development. Eur. J. Neurosci. 9, 1055–1071 (1997). 47. Lu, S., Wise, T.L. & Ruddle, F.H. Mouse homeobox gene Dbx: sequence, gene structure and expression pattern during mid-gestation. Mech. Dev. 47, 187–195 (1994). 48. Wilkinson, D.G., Bhatt, S., Ryseck, R.P. & Bravo, R. Tissue-specific expression of c-jun and junB during organogenesis in the mouse. Development 106, 465–471 (1989).

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Ephrin-As mediate targeting of eye-specific projections to the lateral geniculate nucleus Andrew D Huberman1,4, Karl D Murray1, David K Warland1,2, David A Feldheim3 & Barbara Chapman1,2 Axon guidance cues contributing to the development of eye-specific visual projections to the lateral geniculate nucleus (LGN) have not previously been identified. Here we show that gradients of ephrin-As and their receptors (EphAs) direct retinal ganglion cell (RGC) axons from the two eyes into their stereotyped pattern of layers in the LGN. Overexpression of EphAs in ferret RGCs using in vivo electroporation induced axons from both eyes to misproject within the LGN. The effects of EphA overexpression were competition-dependent and restricted to the early postnatal period. These findings represent the first demonstration of eyespecific pathfinding mediated by axon guidance cues and, taken with other reports, indicate that ephrin-As can mediate several mapping functions within individual target structures.

In mammals, retinal ganglion cell (RGC) axons are segregated into eyespecific layers in the lateral geniculate nucleus (LGN). Early in development, however, retinogeniculate axons from the two eyes are intermingled1–3. The segregation of eye-specific projections into layers is an established model system for studying axon targeting during development4. Technically, the term ‘‘layers’’ refers to discrete cellular groupings. However, ‘‘eye-specific LGN layers’’ is also used to refer to the regions of stereotyped size, shape and position formed by RGC axons arising from each eye. (Hereafter we use the term ‘‘layers’’ only in this latter sense.) The regularity of eye-specific layers is a distinguishing feature of mammalian brains; their spatial arrangement is different between, but invariant within, species5. In carnivores such as cats and ferrets, layer A contains axons from the contralateral eye and always resides in the inner portion of the LGN, whereas layer A1 contains axons from the ipsilateral eye and always resides in the outer LGN5. This invariance is in bold contrast to eye-specific projections found elsewhere along the visual pathway, such as eye-specific patches in the superior colliculus (SC)6 or ocular dominance columns in visual cortex7, which vary tremendously across individuals of a given species in terms of their size, shape and position. Numerous studies have shown that altering neural activity perturbs eye-specific retinogeniculate segregation8–12. However, the invariant positioning of eye-specific LGN layers cannot be explained by purely activity-dependent mechanisms13,14 and recent data have challenged the idea that neural activity plays a direct, instructive role in segregation of eye-specific projections to the LGN15. Non-activity-based explanations for patterning of eye-specific layers have been proposed, such as the differential arrival time of axons from the contralateral versus ipsilateral eye13,16,17. Unfortunately, timing of ingrowth is a difficult variable to manipulate, so this hypothesis has never been directly tested. Another

hypothesis is that axon guidance cues mediate patterning of eye-specific layers10,15,18–21, but a direct role for axon guidance cues in the development of eye-specific connectivity has not previously been reported. What sort of axon guidance cue might regulate patterning of eyespecific layers? In mammals with highly developed binocular vision such as carnivores and primates, each ‘‘eye-specific’’ layer receives RGC axons strictly from either the nasal portion of the contralateral retina or the temporal portion of the ipsilateral retina. Indeed, in the LGN of achiasmatic carnivores, axons arising from the nasal retina segregate from those arising from the temporal retina of the same eye, into regions identical to layers A and A1 (ref. 21). Also, animals with coatcolor mutations, despite having aberrant RGC axon decussation patterns at the optic chiasm, still segregate nasal axons from temporal axons within the LGN22,23. These observations indicate that the nasalretina versus temporal-retina distinction (as opposed to the left-eye versus right-eye distinction) is the key parameter for patterning of eyespecific projections in the LGN. Numerous experiments carried out in lower vertebrates and mice indicate that ephrin-As mediate retinotopic mapping of the nasal-temporal axis in the SC and LGN24–30. We wanted to test whether ephrin-As have a second function in retinogeniculate mapping: dictating the stereotyped patterning of the eyespecific LGN layers. We decided to address this question in ferrets because, unlike in mice31,32, eye-specific layers in ferrets obey the nasalversus temporal-retina distinction33, and retinotopic mapping and eye segregation occur during distinct stages of development34–36. In the normal development of eye-specific retinogeniculate projections in the ferret (Fig. 1a,b), retinal innervation of the LGN occurs from embryonic day (E) 27 until roughly E40 (ferret gestation ¼ 42 d)37. Retinotopic mapping is already adult-like at birth in this species; axons that convey information from the same location

1Center for Neuroscience, 1544 Newton Ct., University of California, Davis, California 95616, USA. 2Section of Neurobiology, Physiology and Behavior, 1 Shields Ave., University of California, Davis, California 95616, USA. 3Department of Molecular, Cellular and Developmental Biology, 225 Sinsheimer Labs, University of California Santa Cruz, Santa Cruz, California 95064, USA. 4Present address: Department of Neurobiology, Fairchild Building, Stanford University School of Medicine, Palo Alto, California 94305, USA. Correspondence should be addressed to B.C. ([email protected]).



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RESULTS EphA and Ephrin-A expression in postnatal visual system We first used affinity-probe binding of EphA3 linked to alkaline phosphatase (EphA3-AP) to detect all the ephrin-A proteins40 in the ferret LGN. Ephrin-A proteins were seen in an outer 4 inner gradient in the LGN (Fig. 1c,d). No staining was evident in LGNs treated with AP alone (Fig. 1e). We also performed in situ hybridization to detect ephrin-A5 mRNA28–30,41. This confirmed the presence of an outer 4 inner gradient of ephrin-A5 mRNA in the LGN that could be seen in both the horizontal (Fig. 1f) and coronal (Fig. 1g) planes. The outer 4 inner gradient was not simply a consequence of edge artifacts; ephrinA5 gradients were also observed in more medial-residing thalamic nuclei, such as the ventral-posterior nucleus (not shown), and were consistently absent from non-LGN edges of the same tissue sections

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in visual space terminate along a common line of projection, which extends along the outer-inner axis of the LGN34,35. The line of decussation (contralateral versus ipsilateral projection pattern of RGC axons at the optic chiasm) is also adult-like at birth33. The binocular overlap in the LGN on postnatal day 0 (P0) is due to RGC axons extending rudimentary arborizations at multiple locations along the outer-inner axis of the LGN and ipsilateral eye axons projecting, along with contralateral eye axons, to the inner limit of the LGN (Fig. 1a)2,20,38. Eye-specific segregation is completed by P10 (refs. 2,20,38). This process reflects (i) the elimination of inappropriate arborizations found along RGC axon shafts, (ii) the retraction of ipsilateral eye arborizations from the inner LGN, (iii) the elaboration of ipsilateral eye arborizations in the outer LGN and (iv) the elaboration of contralateral eye arborizations in the inner LGN (Fig. 1b)38,39. Here we show that, during the period of eye-specific segregation, EphAs are differentially expressed in the contralateral-eye RGC axons versus ipsilateral-eye RGC axons that converge on the same line of projection. We also show that ephrin-As are distributed in an outergreater-than-inner (outer 4 inner) gradient within the LGN. This arrangement should promote the characteristic contralateral:inner, ipsilateral:outer mapping of RGC axons to the principal (A and A1) layers of the LGN. EphA overexpression in RGCs using in vivo electroporation supported this hypothesis, forcing axons from both eyes to project into the inappropriate eye-specific regions of the LGN. EphA overexpression did not alter levels or patterns of spontaneous retinal activity. Thus, ephrin-A:EphA interactions directly mediate targeting of eye-specific retinogeniculate projections through their effects on axon guidance.

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Figure 1 Eye-specific development and ephrin-As in the ferret LGN. (a,b) Schematic diagram of RGC axon ingrowth and arborization during eyespecific segregation in the P1 and P10 LGN. Horizontal plane is shown and, for simplicity, only the retinal projection to the left LGN is shown. Asterisks (in the retinas) indicate the location of contralateral and ipsilateral RGCs that project to the left LGN. O.C., optic chiasm; T, temporal pole; N, nasal pole; A, contralateral eye layer; A1, ipsilateral eye layer; C, nonprincipal layers; A/P, anterior-posterior axis; O.T., optic tract. (c) Expression of pan-ephrin-A protein in a horizontal section of the P3 ferret LGN. (d) Color-scaled densitometry plot of ephrin-A protein in the P3 LGN. (e) Secreted embryonic alkaline phosphatase (SEAP)-AP shows no staining in the P3 ferret LGN. (f) Outer 4 inner gradient of ephrin-A5 mRNA expression in horizontal section of the P0 ferret LGN. (g) Outer 4 inner gradient of ephrin-A5 mRNA seen in a coronal plane section of the P1 ferret LGN. Asterisks indicate an edge of the same tissue section that does not exhibit dioxigenin (DIG) labeling, indicating that the outer 4 inner gradient in the LGN is not due to edge artifacts. D-V, dorsal-ventral axis; vLGN, ventral lateral geniculate nucleus. Scale bars, 150 mm (c–g).

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(asterisks in Fig. 1g). No staining or gradients were observed using sense riboprobe controls (data not shown). Next we examined the expression of EphAs and ephrinAs in the developing ferret retina. Using an ephrin-A5-AP probe to detect EphA proteins, we observed a central-greater-than-peripheral (central 4 peripheral) gradient of EphAs within the RGC layer (Fig. 2a–e). The lowest densities of EphAs were found at the far-nasal and far-temporal poles, and the highest density of EphAs was found near the central retina (Fig. 2a–e). A central 4 peripheral gradient was present at all dorsal-ventral retinal locations (Fig. 2e). We also examined the distribution of EphA5 mRNA by in situ hybridization using antisense riboprobes for mouse EphA5 (refs. 28–30) and ferret EphA5. This confirmed the central 4 peripheral gradient of EphA5 mRNA in the RGC layer (Fig. 2f). In situ hybridization also showed the presence of a nasal 4 temporal gradient of mRNA for ephrin-A5 (Fig. 2g), which indicates that the central 4 peripheral expression of EphA5 in the

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Figure 2 EphAs in the postnatal ferret retina. (a) Horizontal section through the P3 ferret retina labeled for pan-EphA protein. Scale bar, 500 mm. (b–d) High-magnification images of the (b) nasal, (c) central and (d) temporal retina (corresponding to the boxed regions in a). RGC, retinal ganglion cell layer. The dark staining at the top of each image is the photoreceptor layer and pigmented epithelium and vasculature. Scale bar, 200 mm (b–d). (e) Densitometry plot of EphA concentrations in the RGC layer along the nasal-temporal axis of the retina, averaged from dorsal-, mid- and ventralretina sections. (f,g) In situ hybridization with S35-labeled riboprobes, demonstrating (f) a central 4 peripheral gradient of EphA5 mRNA in the P1 ferret retina (horizontal plane) and (g) a nasal 4 temporal gradient of ephrin-A5 mRNA in the P1 ferret retina (also horizontal plane). pONH, peri-optic nerve head; N, nasal pole; T, temporal pole. (f,g) Dashed line encompasses the neural retina. Scale bar, 250 mm. (h) Model for eye-specific mapping of ipsiprojecting RGCs (red arrow) and contra-projecting RGCs (green arrow) from the two eyes, to different locations along a single line of projection (dashed black line) in the LGN. Axons from the far nasal retina (double-headed green arrow) project to multiple locations along the outer-inner axis in the anterior LGN. A single retina is shown only for schematic purposes; in reality the contralaterally projecting axons and the ipsilateral projecting axons that converge on the same line of projection in the LGN arise from opposite retinas.

retina (Fig. 2f) is not simply due to lower RGC densities in the peripheral versus central retina. The nasal 4 temporal expression of ephrin-A5 (Fig. 2g) may also have implications for mapping of retinal projections to the LGN42. Ephrin-A model for eye-specific targeting Ephrin-As have consistently been shown to repel RGC axons expressing relatively higher levels of EphAs24–30,43. In the ferret, the temporal-most 12–20% of RGCs do not cross at the chiasm and thereby project to the ipsilateral LGN32,33. The central 4 peripheral gradient of EphAs in the retina means that there are relatively higher levels of EphAs expressed in the RGC axons from the contralateral eye than in the RGC axons from the ipsilateral eye that converge on a the same line of projection in the binocular (posterior) region of the LGN. The outer 4 inner gradient of ephrin-As in the LGN should therefore repel the contralateral eye axons into the inner LGN (layer A), whereas the ipsilateral eye axons should map to the more outer LGN (layer A1) (Fig. 2h and Supplementary Fig. 1). Axons from the far-nasal retina of the contralateral eye would still map all along the outer-inner axis in the monocular (anterior) LGN (Fig. 2h and Supplementary Fig. 1). We did not directly consider the C layers in this study. For clarity, however, C layers are labeled in the photomicrographs and are discussed below. In vivo electroporation of RGCs To test whether interactions between ephrin-A and EphA regulate eyespecific layer formation, we developed an electroporation protocol to transfect postnatal ferret RGCs in vivo (Fig. 3a). Electroporation with control cDNAs encoding green fluorescent protein (GFP) resulted in widespread GFP expression in the RGC layer within 24 h (Fig. 3b). Retinal electroporation with GFP on P1 followed by an in vivo injection of the anterograde tracer Cholera toxin b-Alexa 594 (red) into the same eye on P10 resulted in complete concordance between the GFP and tracer label on RGC axons within the P10 LGN (Fig. 3c,d). The GFP/tracer-labeled axons terminated in a pattern normal for the P10 ferret LGN2,9,10,15,20. Thus, our electroporation protocol rapidly and stably transfects a large number of RGCs and the transgene is expressed on retinogeniculate axon terminals. Furthermore, our electroporation/ transfection protocol does not itself alter patterning of eye-specific retinogeniculate projections. When we transfected RGCs with EphA3 or EphA5 constructs (EphA3/5) on P1 and then examined the localization of EphA proteins


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in the retina using ephrin-A5-AP, we observed increased EphA levels in the RGC layer, indicating functional overexpression of EphAs (Fig. 3e). EphA3/5 overexpression did not alter RGC density (Fig. 3f). To examine EphA overexpression on RGC axons within the LGN, we electroporated the retinas of P1 ferrets with an EphA5:V5 fusion construct (Supplementary Methods) and then examined the LGN for expression of the fusion protein, using antibodies directed against the V5 epitope tag. Immunoreactivity for EphA5:V5 was evident throughout the LGN (Fig. 3g), indicating that the overexpressed EphA5 protein was trafficked to retinogeniculate axon terminals. Does EphA overexpression perturb eye-specific targeting? In P10 ferrets electroporated with control plasmids on P1, normal eyespecific projections to the LGN were observed (Fig. 4a). By contrast,

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ARTICLES Figure 3 In vivo ganglion cell electroporation. RGC layer (P2) Anti-V5 immuno (LGN contralateral (a) Diagram of the electroporation procedure. RGCs to transfected eye) EphA protein (b) Flat-mount view of a P2 retina that was P5 ** electroporated with GFP on P1. Brightly labeled (Horiz.) + – cell bodies are present throughout the RGC layer. vLGN Ant. Scale bar, 150 mm. (c) GFP-labeled RGC axons in Lens the LGN of a P10 ferret that was monocularly electroporated with GFP on P1. The LGN Control LGN ipsilateral to electroporated eye (P10) 1,200 ipsilateral to the electroporated eye is shown in EphA GFP CTβ-594 the horizontal plane; GFP-positive (GFP+) axons 1,000 LGN are in the normal layer-A1 pattern. The normal 800 ipsilateral C layer is also apparent. (d) The GFP600 A1 A1 electroporated eye was also injected with 400 O.T choleratoxin b (CTb-594) to label all RGC 200 C C axons originating from that eye. (c,d) Scale 0 D/M D/P N/M N/P T/M T/P V/M V/P bar, 150 mm. (e) P10 ferret retina that was transfected with EphA5 on P1 and then processed for ephrin-A5-AP affinity probe binding to detect EphA protein. The far-temporal retina is shown, which normally expresses very low levels of EphAs (see Fig. 2). The same result was observed for the far-nasal retina (not shown). Asterisks indicate pigmented epithelium. Scale bar, 200 mm. (f) RGC densities from control and EphA-electroporated retinas (paired t-test; n ¼ 4 retinas per group; error bars represent s.e.m.; D, dorsal; N, nasal; T, temporal; V, ventral; M, mid retina; P, peripheral retina). No significant differences between groups were present at any location. (g) Axons expressing an EphA5:V5 fusion construct seen on RGC axons in the LGN of a P5 ferret that was electroporated in the contralateral eye on P1. Scale bar, 200 mm.

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P10 ferrets that had been electroporated with EphA3 or EphA5 cDNAs on P1 showed markedly perturbed retinogeniculate projections (Figs. 4 and 5) (n ¼ 14 ferrets: n ¼ 7 EphA3, n ¼ 7 EphA5). Most notably, axons from the ipsilateral eye were mistargeted to the inner LGN, into territory normally occupied only by axons from the contralateral eye (Figs. 4b and 5b–f). In addition, axons from

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Figure 4 Effect of EphA overexpression on eyespecific targeting and comparison to activity blockade. (a–c) Contralateral eye inputs (top), ipsilateral eye inputs (middle) and their merged representation (bottom) in the left and right LGNs of (a) a P10 control ferret, (b) a P10 ferret that was binocularly electroporated with EphA5 on P1 and (c) a P10 ferret that had all retinal activity blocked from P1 to P10. Horizontal sections are shown. O.T., optic tract; MIN, medial intralaminar nucleus; vLGN, ventral lateral geniculate nucleus; A, contralateral layer; A1, ipsilateral layer; C, nonprincipal C layers; the boundaries of A and A1 and the optic tract are shown with dashed lines for the left LGN. The outer-inner axis (perpendicular to eye-specific layers) is shown by arrows (merged panels). Scale bar, 100 mm. (d) Quantification of the extent of the ipsilateral eye projection area and the degree of binocular intermingling in the LGN. Both EphA overexpression and activity blockade caused significant increases in the area of the LGN containing ipsilateral eye input and the intermingling of ipsi- and contralateral axons, compared to controls (***P o 0.005). The effect of activity blockade was significantly greater than the effect of EphA overexpression on both these measures (*P o 0.05, unpaired t-test; n ¼ 22 control cases; n ¼ 15 binocular EphA5; n ¼ 12 activity blocked). (e) Quantification of aspect ratio (long axis:short axis) for ipsilateral eye input to LGN in control (n ¼ 12), EphA-transfected (n ¼ 15) and retinal activity–blocked (n ¼ 11) ferrets. (P 4 0.05, not significant (N.S.); **P o 0.01; t-test).

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Figure 6 Effects of EphA overexpression on targeting of individual retinogeniculate axons. (a,b) RGC axons labeled from the far temporal retina of (a) a control P10 ferret and (b) a control P12 ferret, seen in the ipsilateral LGN. Lowmagnification photomicrographs show the location within the LGN where axons were imaged (corresponds to same case as in a). Arrows indicate the optic tract. (c,d) RGC axons labeled from the far temporal retina of (c) a P10 EphA5transfected (binocular electroporation) ferret and (d) a P12 EphA5-transfected (binocular electroporation) ferret, in the ipsilateral LGN. Low-magnification image corresponds to c. (e) Quantification of the maximum extent of the outer-inner axis in which axons from the ipsilateral retina are found. Axons from EphA animals projected significantly farther inward than did those from controls (n ¼ 7 control; n ¼ 7 binocular EphA5; ***P o 0.005, paired t-test). (f) RGC axon originating from the far-nasal retina of a control-transfected ferret, seen within the anterior portion of the contralateral LGN. (g) RGC axon labeled from the far nasal retina of an EphA5-electroporated ferret (binocular) seen in the anterior portion of the contralateral LGN. Low-magnification image shows nasal axon in the anterior LGN from an additional control. (a–g) Scale bar, 200 mm. In low-magnification images, scale bar ¼ 400 mm. Horizontal plane is shown.

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outer-inner axis of the LGN, perpendicular to eye-specific layers. In activity-blocked ferrets, the degree of expansion of the ipsilateral eye territory was approximately equal along the two axes, resulting in an ipsilateral region of larger size, but with the same aspect ratio, as that of control animals (Fig. 4e). In contrast, EphA-transfected animals showed a large expansion along the outer-inner axis, but very little expansion along the anterior-posterior axis, resulting in a significantly lower aspect ratio (Fig. 4e). We also directly compared the degree of ipsilateral eye axon expansion along the anterior-posterior axis in control, EphA-electroporated and activity-blocked ferrets. In the EphA group, ipsilateral eye axons extended over slightly more of

of EphA-electroporated ferrets (Figs. 4b and 5d–f). Indeed, the degrees of ipsilateral eye axon mistargeting and intermingling of binocular projections caused by EphA overexpression were similar in magnitude to the most extreme cases observed after complete retinal activity blockade from P1 to P10 (refs. 9,20) (Fig. 4b–d). Qualitatively, however, the effects of Eph-A overexpression were somewhat different than those caused by retinal activity blockade; retinal activity blockade resulted in axons from the ipsilateral eye extending much farther than normal across both the anterior-posterior (retinotopic) and outerinner (eye-specific) axes of the LGN9,15,20 (Fig. 4c). Overexpression of EphAs, on the other hand, misdirected RGC axons primarily along the


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Figure 5 EphA overexpression causes ipsilateral eye axons to misproject into opposite eye territory. (a–c) Ipsilateral eye inputs to the P10 LGN of (a) a control-electroporated ferret, (b) a ferret monocularly electroporated with EphA3 and (c) a ferret binocularly electroporated with EphA5. (d–f) In a P10 ferret that was binocularly electroporated with EphA5 on P1, (d) contralateral eye axons, (e) ipsilateral eye axons and (f) their merged representation. Ipsilateral eye expansion into contralateral eye territory was observed here and in every EphA-electroporated ferret examined (n ¼ 16 ferrets). Horizontal plane is shown. Scale bars, 100 mm. Boxed areas (in schematics at right) indicate the site in the LGN where the photomicrographs were taken.

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the anterior-posterior axis of the LGN than in controls (control mean ¼ 48.1 ± 1.25%; n ¼ 12; EphA mean ¼ 55.5 ± 2.4%, n ¼ 14), an effect that was statistically significant (P o 0.05; unpaired t-test). In the activity-blocked group, ipsilateral eye axons were found over a much greater extent of the anterior-posterior axis when compared to control or EphA animals (activity block mean ¼ 88.25 ± 1.9%, n ¼ 12, P o 0.001 for activity blockade versus control and activity blockade versus EphA). In sum, EphA overexpression in the ferret induced drastic eye-specific pathfinding errors along the outer-inner axis of the LGN (Fig. 6) and significant but relatively less severe retinotopic errors along the anterior-posterior axis. Activity blockade seems to severely alter both eye-specific and retinotopic pathfinding. EphA overexpression perturbs individual axon targeting Whole-retina anterograde tracing of RGC axons shows the macroscopic organization of eye-specific projections to the LGN, but it cannot show whether individual ganglion cell axons make targeting errors within regions containing predominantly same-eye axons, nor can it indicate whether individual axons are displaced primarily along a single axis. Therefore, we traced individual axons arising from RGCs in defined retinotopic locations within the retina. As expected2,38, in every control P10 ferret examined, RGC axons from the temporal portion of the retina were restricted to layer A1 within the ipsilateral LGN (Fig. 6a). At P12, temporal retina RGC axon arborizations formed a more restricted termination zone within A1, presaging the formation of on-off sublamination38 (Fig. 6b). By contrast, in P10 and P12 ferrets that had been electroporated with EphA5 on P1, RGC axons arising

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from the temporal retina extended much farther along the outer-inner axis of the LGN (Fig. 6c,d). In half of the cases examined (n ¼ 4), axons terminated all the way at the innermost limit of the LGN (Fig. 6c). In the remaining cases there was a dense terminal zone formed midway along the outer-inner axis of the LGN, but axon terminals could also be seen projecting ectopically into the inner LGN (Fig. 6d). Neither pattern was ever seen in control ferrets of these ages. Quantification showed that ipsilateral projecting axons in the LGN of EphA-electroporated ferrets terminated significantly further inward along the outerinner axis of the LGN (Fig. 6e). Does EphA overexpression cause targeting errors only in the binocular region of the LGN where axons from the two eyes compete? Normally, axons from the far-nasal retina project to the anterior portion of the contralateral LGN (Fig. 6f), which never receives axons from the ipsilateral eye2,20. In P10 ferrets that were electroporated with EphA5 on P1, axons from the far nasal retina were correctly targeted to the anterior contralateral LGN (Fig. 6g) (n ¼ 5 control; n ¼ 7 EphA far nasal axons). Thus, EphA overexpression seems to cause eye-specific targeting errors only in the posterior portion of the LGN where axons from the two eyes converge, consistent with a competition-based model for ephrin signaling29,43. Ephrin-As are developmentally regulated in the LGN Ephrin-As were robustly expressed in the P0–P3 LGN (Fig. 1), but by P5 their levels were reduced conspicuously (Fig. 7a). This was not a false negative, because ephrin-A expression remained high in the SC and inferior colliculus of the same tissue sections where no LGN label was seen (Fig. 7b). Retinal EphAs, on the other hand, were stably expressed until P10 in the central 4 peripheral pattern described above (data not shown). To determine whether the presence of ephrin-As in the LGN is necessary for EphA overexpression to affect eye-specific pathfinding, we electroporated ferrets with EphA3/5 on P5 or P10. Despite robust overexpression of EphA3/5 in RGCs (data not shown), there was no effect on eye-specific projections to the LGN (Fig. 7c–e) (n ¼ 6 ferrets). This indicates that interactions between retinal EphAs and target-derived ephrin-As are critical for eye segregation. DISCUSSION The results presented here are, to our knowledge, the first direct evidence for axon guidance cue–mediated targeting of eye-specific projections. Our data indicate an outer 4 inner gradient of ephrinA ligand that extends along the axis of projection in the LGN. In addition, along a given line of projection, the RGCs that project to the inner LGN (layer A) express higher levels of EphAs than do the RGCs that project to the more outer LGN (layer A1). Based on the fact that

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ARTICLES ephrin-A ligands repel RGC axons expressing relatively higher levels of EphAs24–30,43, these ephrin-A:EphA distributions ensure that axons from the contralateral retina will project to the inner LGN and that axons from the ipsilateral retina will project to the more outer LGN. Overexpressing EphAs forced axons from the ipsilateral retina inward, into territory normally occupied only by the contralateral eye. Contralateral eye axons were mistargeted within the binocular region of the LGN as well. The targeting errors we observed following EphA overexpression were similar in magnitude to those observed following complete retinal activity blockade from P1 to P10, which is remarkable given that overexpression was induced on a background of an endogenous central 4 peripheral retinal EphA gradient. Our data indicate that precise levels and distributions of retinal EphAs are important for normal eye-specific pathfinding. Developmentally regulated expression of ephrin-As Ephrin-As are rapidly downregulated in the postnatal ferret LGN and EphA overexpression leads to disruptions in eye-specific layering only when ephrin-As are present in the LGN. Previous experiments20,44 showed that delaying the onset of eye-specific segregation until after P10 permanently abolishes normal patterning of eye-specific inputs to the LGN, indicating that there is a critical period for development of this feature. The present data suggest that temporally restricted expression of ephrin-As within the LGN may regulate this critical period. Because eye-specific segregation occurs gradually from P1 to P10 in the ferret2, we were at first surprised to see downregulated ephrin-As in the LGN by P5. In mice too, however, ephrin-As are downregulated in the LGN and SC prior to the retraction of RGC axons to their retinotopically appropriate locations28,29. It remains unknown why ephrin-A downregulation occurs before axon targeting is complete. Eye-specific versus retinotopic pathfinding The ephrin-A expression patterns and the effects of EphA overexpression we describe here directly implicate these molecules in eye-specific retinogeniculate targeting. The effects of EphA overexpression on retinotopic pathfinding, however, were relatively minor in comparison. This is likely because, in ferrets, retinotopic mapping occurs prenatally, before the onset of eye-specific segregation34–36. Ephrin-As may well mediate retinotopic mapping in the ferret, but this is likely to occur at earlier developmental ages than we consider here. Indeed, over 40 years ago, it was proposed that, in animals with a high degree of binocular vision, a central 4 peripheral gradient of a mapping cue would be present in the retina to induce retinotopic mapping of nasal and temporal RGC axons to the same line of projection45. We thus suspect that the central 4 peripheral gradient of retinal EphAs we observed acts in combination with an anterior 4 posterior gradient of ephrin-A in the prenatal ferret LGN to accomplish this. Unfortunately, examining the pattern of ephrin-A expression in the prenatal ferret LGN has not been possible because of the extremely small size of the nucleus at the relevant ages. In mice, retinotopy and eye-specific segregation emerge during the same developmental period and eye-specific layers do not obey the contralateral:nasal, ipsilateral:temporal distinction; RGCs from throughout the entire retina project contralaterally32. Thus, in mice, disrupting ephrin-As should alter both retinotopy and patterning of eye-specific layers, and indeed this is the case28,46. Do neural activity and ephrin-As interact? Altering neural activity has repeatedly been shown to disrupt eyespecific patterning in the LGN8–12. However, there is debate regarding whether the effects observed in those experiments are caused by


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disruptions in Hebbian plasticity at retino-geniculate synapses or whether they are nonspecific ‘permissive’ effects of the activity manipulations15. Activity manipulation can strongly affect RGC axon outgrowth47 and pathfinding48, both of which could indirectly impact eye-specific segregation. In theory, activity manipulations could also act permissively by perturbing EphA expression. However, this has not been observed; normal EphA and ephrin-A mRNA expression persists in the face of chronic epibatidine application46—a treatment that markedly alters eye-specific retinogeniculate pathfinding in mice11 and ferrets9,15,20. Its is also noteworthy that altering retinal activity causes RGC axons to extend both anteriorly and across the outer-inner axis of the LGN9,15,20, whereas overexpression of EphAs misdirects RGC axons more along the outer-inner axis of the LGN, perpendicular to eye-specific layers (Figs. 4–6). It is unlikely that the phenotype we observed following EphA overexpression reflects alterations in RGC activity levels; if overexpression of EphAs reduced or eliminated RGC activity, then in monocularly electroporated ferrets, the nontransfected eye would have expanded its projection to the LGN at the expense of the transfected eye9,12. This was never the case. Monocular electroporation always resulted in an expansion of axons ipsilateral to the EphA transfected eye (Fig. 5b). We also directly tested whether EphA overexpression affects spontaneous retinal activity by recording from RGCs using multi-site extracellular recordings in P3, P5 and P7 ferret retinal explants. Those experiments confirmed that normally patterned spontaneous retinal activity is present in EphA-electroporated retinas; at every age examined, ‘waves’9,44 of excitation periodically emerged and spread laterally across restricted domains of the retina, engaging closely spaced RGCs to fire in synchrony (Supplementary Figs. 2–4, Supplementary Table 1 and Supplementary Movies 1,2). No significant differences were evident in the correlation strengths measured in control versus EphA-electroporated retinas at any age (Supplementary Figs. 2–4 and Supplementary Table 1). The presence of normal correlated retinal activity patterns indicates that the effects of EphA overexpression on retinogeniculate pathfinding are not due to eliminating or disrupting spontaneous retinal activity. Rather, they reflect direct actions of ephrin-As and EphAs on RGC axon targeting in the LGN. Non-ephrin-A contributions to eye-specific targeting Our ephrin-A model does not address eye-specific segregation in the C layers because in ferrets, eye specificity within the C layers is not well established anatomically until roughly P20 (ref. 2). Mapping of RGC inputs to the C layers may rely on ephrins and/or other cues. Microarray-based genetic screens have shown the presence of molecular markers that distinguish between the C and A/A1 layers of the ferret LGN49, but whether those molecules mediate RGC axon pathfinding remains untested. Our data do not rule out the possibility of axon guidance molecules expressed strictly in the contralateral versus ipsilateral eye layers of the LGN. Others have attempted to identify genes differentially expressed in layer A versus A1 of the ferret LGN and did not find evidence for such markers. They therefore hypothesized that the cues that mediate eye-specific targeting are expressed in gradients49. Our findings support this hypothesis. Differential timing of ingrowth of RGC axons from the contralateral versus ipsilateral retina could also contribute to the invariant positioning of eye-specific layers13. RGC axons from the contralateral eye arrive earlier in the LGN than do axons from the ipsilateral eye16,17. We think it is unlikely, however, that the invariant positioning of eye-specific layers is due only to differences in timing of ingrowth because modern tracing techniques show that in the P1–P3 ferret, axons from the contralateral and ipsilateral eye project to the inner limit of the

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LGN15,20. Timing of ingrowth may, however, impart an advantage to contralateral eye axons for securing the innermost LGN through differences in arborization maturation and synaptic efficacy. CONCLUSION We favor a model whereby, after axons from the two eyes map to their retinotopically appropriate locations in the LGN, axons from the contralateral retina are biased to arborize at more inner LGN locations than retinotopically matched axons from the ipsilateral eye, by virtue of the relatively greater levels of EphAs they express. Ephrin-As that are present directly on RGC axons as well as on LGN cells may be important in this process42. METHODS Animals. Male and female pigmented ferrets (Marshall Farms) were maintained on a 16:8 h light:dark cycle. All procedures were in compliance with approved animal protocols from University of California, Davis and US National Institutes of Health guidelines. Affinity probe detection of ephrin-A and EphA proteins. Procedures for AP probe detection of Ephrin-A ligands and receptors were identical to those described previously28,29,40. For detailed procedures, see Supplementary Methods. In situ hybridization. Riboprobes generated from rodent-specific templates were previously shown to work well in ferrets41. Riboprobe templates for mouse ephrin-A5 and EphA5 were generated from early postnatal mouse SC using primers based on verified sequences from the public database at the National Center for Biotechnology and Information (NCBI, http://www. ncbi.nlm.nih.gov/). We cloned a ferret-specific template for EphA5 from neonatal ferret superior and inferior colliculas using PCR amplification with the same primers used to generate mouse EphA5. For detailed procedures, see Supplementary Methods. EphA5:V5 expression plasmid. To examine the distribution of overexpressed EphA5 in the LGN, we fused the epitope tag V5 to the C terminus of fulllength EphA5. Details of this construct are available in the Supplementary Methods. Expressed EphA5-V5 was detected by immunocytochemistry using a monoclonal antibody against the V5 peptide (Invitrogen) at a dilution of 1:100, and secondary detection was done with goat anti-mouse Alexa 594 (Molecular Probes). Affinity probe densitometry analysis. We quantified sections from the dorsal, mid and ventral portions of the retina (Scion Image). The midpoint along the nasal-temporal axis was aligned, scanned and scaled for length, and densitometry values were averaged. The zero point in the plot represents the half-way point between the nasal and temporal poles. Multiple retinas were examined for each age (n ¼ 3–4 at every postnatal day from P0–P10 and on P15). Results were compared to those achieved with SEAP. In vivo ganglion cell electroporation. Full length cDNAs encoding EphA3 or EphA5 in the mammalian expression vector pcDNA3 were used. cDNAs encoding the reporter gene enhanced green fluorescent protein (EGFP; Clontech) and/or the expression vector pcDNA3 alone were used as controls and for coelectroporation experiments. We injected 2 ml of cDNA solution (1 mg/ml) into the vitreal chamber using a 33-gauge needle inserted at the corneo-scleral junction. The eye was clasped with a paddle electrode (1 3 mm; BTX systems). One or two 950-ms, 10- to 12-V pulses were applied (interpulse interval ¼ 100 ms). Although longer pulse trains (5–10 pulses) with these voltages can be used with no evidence of cell death or eye damage, we consistently achieved the highest transfection efficiency by applying only 1–2 pulses. Quantification of RGC density. Measurements of RGC density were carried out from matched locations in the central and peripheral retina of all four quadrants of age-matched control and electroporated flat-mounted retinas. Dye labeling was used to identify RGCs. Our cell counts were comparable to those reported previously12,20,33.

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Whole-retina tracing of retinogeniculate afferents. Retinogeniculate projections were labeled using previously published protocols20. CTb conjugated to Alexa dye 488 (green label) was used for the right eye, and CTb conjugated to Alexa dye 594 (red label) was used for the left eye (Molecular Probes; CTb has no biological activity). For detailed procedures, see Supplementary Methods online. Ages written in this article correspond to age at time of death. All retinas were carefully inspected for damage using previously described criteria20. All animals exhibiting retinal damage were excluded from the study (n ¼ 6 ferrets). Imaging and quantification of eye-specific retinogeniculate projections. Image acquisition and quantification of the extent of ipsilateral eye axons and overlap were identical to previous reports12,15,20. For details of quantification of long and short axis length, aspect ratio and extent of ipsilateral eye terminations, see Supplementary Methods online. Labeling and quantification of individual retinogeniculate axons. A small (B1 mm diameter) crystal of DiI (Molecular Probes) was placed in the ventrotemporal or far nasal retina of ferrets using a 33-gauge sterile needle inserted through the sclera. The animal was perfused with 4% paraformaldyhyde 48 h later, which provided time for diffusion of the DiI while the animal was still alive. A more thorough description of the single-axon labeling procedures is available online. To quantify the extent of arborization along the outer-inner axis of the LGN, the distance between the optic tract and the perigeniculate/ LGN border was measured at the location of the axon arborization of interest. The inward-most termination of each temporal axon arborization was measured along this axis and expressed as a percentage for each case (to normalize for differences in the width of the LGN). Seven cases each were examined for control and EphA transfected groups. Retinal activity blockade. Details of the activity blockade procedure have been described previously9,15,20. Ferrets received binocular injections of epibatidine (1–2 ml per eye;1 mM; Sigma) every 48 h from P1 to 10. Recording spontaneous retinal activity. Retinas were isolated and submerged in buffered and oxygenated medium (Eagle’s minimum essential medium, Sigma M7278; n ¼ 2 control; n ¼ 2 EphA5-electroporated retinas were recorded for three ages, P3, P5 and P7, for a total of 12 retinas). Isolated retinas were placed with the RGC layer side down onto a multi-electrode array50 (Multi-Channel Systems), held in place with a piece of dialysis membrane and superfused at 1–2 ml/min at 37 1C. Simultaneous analog data were acquired from the array of 60 electrodes, and individual spike trains were then identified using Offline Sorter (Plexon) using spike amplitude and width clustering. Because many RGCs fire together during a wave event, this standard spike identification method may result in multiple cells being assigned to one spike event because spike signals overlap. For details on the procedure used for quantifying the correlation index, see Supplementary Methods. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We thank P. Nguyen, R. Kumar, D. Van Der List and G. Woods for technical assistance, M. Greenberg for the gift of the EphA3 and EphA5 expression plasmids and Colin Akerman for permission to adapt his ferret visuotopic map diagram. This work was supported by the US National Eye Institute (NEI; EY11369 to B.C. and EY14689-01 to D.A.F.), the NEI Vision Science Training Fellowship (EY015387 to A.D.H.), NS39094 (E.G. Jones, University of California, Davis, provided support for K.D.M.) and NEI Core Grant (EY12576 to L.M. Chalupa). COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 29 April; accepted 23 June 2005 Published online at http://www.nature.com/natureneuroscience/

1. Rakic, P. Prenatal genesis of connections subserving ocular dominance in the rhesus monkey. Nature 261, 467–471 (1976). 2. Linden, D.C., Guillery, R.W. & Cucchiaro, J. The dorsal lateral geniculate nucleus of the normal ferret and its postnatal development. J. Comp. Neurol. 203, 189–211 (1981).

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29. Feldheim, D.A. et al. Genetic analysis of ephrin-A2 and ephrin-A5 shows their requirement in multiple aspects of retinocollicular mapping. Neuron 25, 563–574 (2000). 30. Feldheim, D.A. et al. Loss-of-function analysis of EphA receptors in retinotectal mapping. J. Neurosci. 24, 2542–2550 (2004). 31. Godement, P., Salaun, J. & Imbert, M. Prenatal and postnatal development of retinogeniculate and retinocollicular projections in the mouse. J. Comp. Neurol. 230, 552–575 (1984). 32. Herrera, E. et al. Zic2 patterns binocular vision by specifying the uncrossed retinal projection. Cell 114, 545–557 (2003). 33. Cucchiaro, J.B. Early development of the retinal line of decussation in normal and albino ferrets. J. Comp. Neurol. 312, 193–206 (1991). 34. Jeffery, G. Retinotopic order appears before ocular separation in developing visual pathways. Nature 313, 575–576 (1985). 35. Jeffery, G. Shifting retinal maps in the development of the lateral geniculate nucleus. Brain Res. Dev. Brain Res. 46, 187–196 (1989). 36. Chalupa, L.M. & Snider, C.J. Topographic specificity in the retinocollicular projection of the developing ferret: an anterograde tracing study. J. Comp. Neurol. 392, 35–47 (1998). 37. Johnson, J.K. & Casagrande, V.A. Prenatal development of axon outgrowth and connectivity in the ferret visual system. Vis. Neurosci. 10, 117–130 (1993). 38. Hahm, J.O., Cramer, K.S. & Sur, M. Pattern formation by retinal afferents in the ferret lateral geniculate nucleus: developmental segregation and the role of N-methyl-Daspartate receptors. J. Comp. Neurol. 411, 327–345 (1999). 39. Sretavan, D.W. & Shatz, C.J. Prenatal development of retinal ganglion cell axons: segregation into eye-specific layers within the cat’s lateral geniculate nucleus. J. Neurosci. 6, 234–251 (1986). 40. Flanagan, J.G. et al. Alkaline phosphatase fusions of ligands or receptors as in situ probes for staining of cells, tissues, and embryos. Methods Enzymol. 327, 19–35 (2000). 41. Hayes, S.G., Murray, K.D. & Jones, E.G. Two epochs in the development of gammaaminobutyric acidergic neurons in the ferret thalamus. J. Comp. Neurol. 463, 45–65 (2003). 42. Hornberger, M.R. et al. Modulation of EphA receptor function by coexpressed ephrinA ligands on retinal ganglion cell axons. Neuron 22, 731–742 (1999). 43. Brown, A. et al. Topographic mapping from the retina to the midbrain is controlled by relative but not absolute levels of EphA receptor signaling. Cell 102, 77–88 (2000). 44. Muir-Robinson, G., Hwang, B.J. & Feller, M.B. Retinogeniculate axons undergo eyespecific segregation in the absence of eye-specific layers. J. Neurosci. 22, 5259–5264 (2002). 45. Sperry, R.W. Chemoaffinity in the orderly growth of nerve fibers and connections. Proc. Natl. Acad. Sci. USA 50, 703–710 (1963). 46. Pfeiffenberger, C. et al. Ephrin-As and neural activity are required for eye-specific patterning during retinogeniculate mapping. Nat. Neurosci. 8, 1020–1025 (2005). 47. Goldberg, J.L. et al. Retinal ganglion cells do not extend axons by default: promotion by neurotrophic signaling and electrical activity. Neuron 33, 689–702 (2002). 48. Ming, G., Henley, J., Tessier-Lavigne, M., Song, H. & Poo, M. Electrical activity modulates growth cone guidance by diffusible factors. Neuron 29, 441–452 (2001). 49. Kawasaki, H., Crowley, J.C., Livesey, F.J. & Katz, L.C. Molecular organization of the ferret thalamus. J. Neurosci. 24, 9962–9970 (2004). 50. Meister, M., Wong, R.O., Baylor, D.A. & Shatz, C.J. Synchronous bursts of action potentials in ganglion cells of the developing mammalian retina. Science 252, 939–943 (1991).

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Ephrin-As and neural activity are required for eyespecific patterning during retinogeniculate mapping Cory Pfeiffenberger1, Tyler Cutforth2, Georgia Woods1, Jena Yamada1, Rene´ C Renterıá3, David R Copenhagen3, John G Flanagan4 & David A Feldheim1 In mammals, retinal ganglion cell (RGC) projections initially intermingle and then segregate into a stereotyped pattern of eyespecific layers in the dorsal lateral geniculate nucleus (dLGN). Here we found that in mice deficient for ephrin-A2, ephrin-A3 and ephrin-A5, eye-specific inputs segregated but the shape and location of eye-specific layers were profoundly disrupted. In contrast, mice that lacked correlated retinal activity did not segregate eye-specific inputs. Inhibition of correlated neural activity in ephrin mutants led to overlapping retinal projections that were located in inappropriate regions of the dLGN. Thus, ephrin-As and neural activity act together to control patterning of eye-specific retinogeniculate layers.

In the mammalian visual system, RGCs project to their main forebrain target, the dLGN of the thalamus, in an orderly and stereotypical manner. This order is established during development and can be described by two main components. First, the projection pattern from each eye is topographic, with neighboring RGCs connecting to neighboring positions in the dLGN. The Eph family of receptor tyrosine kinases and their cell surface–bound ligands, the ephrins, act as graded labels that are required for topographic mapping in several areas in the central nervous system, including the two main targets of RGCs, the dLGN and the superior colliculus (SC)1–5. The second organizing feature of visual connectivity is the segregation of projections from each eye, a phenomenon that is thought to depend mechanistically on neural activity. Early in development, the retinogeniculate projections of the two eyes overlap, but then they segregate and form eye-specific layers postnatally6,7. Inhibiting activity in the retina or in the whole brain prevents the segregation of RGC axons8–10. Neural activity has been theorized to drive axon-axon competition for dLGN territory between the two eyes, and indeed, when the balance of activity in the two eyes is altered, inputs from the more active eye occupy a larger area within the dLGN10–14. It is thought that activity-based competition relies on the ability of inputs from each eye to cooperate with one another to strengthen synaptic connections in a Hebbian manner, although exactly how activity functions in this context remains controversial15,16. Although activity-dependent models can account for how eyespecific inputs segregate, they cannot explain the stereotypical placement of the layers within the dLGN. Segregation models based solely on neural activity predict that layer placement should be stochastic, such that in some animals a given layer of the dLGN would be innervated from the left eye whereas in other animals it would be innervated by the

right eye, or alternatively, that axons from each eye would segregate in a ‘salt-and-pepper’ pattern17,18. Several theories have been proposed to explain the stereotypical placement of the eye-specific layers, including temporal differences between ipsi- and contralateral ingrowth into the dLGN, layer-specific molecular labels, and eyespecific axon guidance molecules18–21. Here we test whether ephrins are important for the segregation of eye inputs within the mouse dLGN. EphA receptors and ligands are expressed in opposing gradients along the nasotemporal axis in the retina and also across the recipient SC and dLGN axes. Ephrin-A2 and ephrin-A5 are the predominant ephrin-A ligands that are present in the SC and dLGN and are required in vivo for topographic mapping of RGCs along these axes1,2,5,22. To test the relative contributions of ephrins and presynaptic activity toward the development of retinogeniculate projections, we analyzed retinal inputs to the dLGN in three populations: ephrin-A mutants, wild-type mice without correlated presynaptic activity and ephrin-A mutants without correlated presynaptic activity. RESULTS Ephrin-A expression in the developing retinogeniculate projection Multiple EphA receptors and ephrin-A ligands were expressed in gradients in the developing retinogeniculate projection (Fig. 1 and Supplementary Fig. 1 online). In the RGC layer of the retina, EphA5 and EphA6 were expressed in a temporal (high)-to-nasal (low) gradient, whereas ephrin-A5 was expressed in the opposite nasal (high)-to-temporal (low) gradient. Ephrin-A2 and ephrin-A3 were expressed in RGCs but not in an obvious gradient (data not shown). In the dLGN, ephrin-A2 and ephrin-A5 were expressed in a ventrallateral-anterior (high)–to–dorsal-medial-posterior (low) gradient

1Department of Molecular, Cellular, and Developmental Biology, University of California at Santa Cruz, Santa Cruz, California 95064, USA. 2Center for Neurobiology and Behavior, Columbia University Medical Center, New York, New York 10032, USA. 3Department of Ophthalmology and Department of Physiology, University of California School of Medicine, San Francisco, San Francisco, California 94143, USA. 4Department of Cell Biology and Program in Neuroscience, Harvard Medical School, Boston, Massachusetts 02115, USA. Correspondence should be addressed to D.A.F. ([email protected]).


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Figure 1 Expression of EphA receptors and EphA3-AP Ephrin-A5 EphA3-AP Ephrin-A3 EphA7 ephrin-A ligands in the developing mouse visual wt tko system. (a–c) Coronal sections of mouse P0 brain were treated with RNA hybridization probes for dLGN (a) ephrin-A5, (b) EphA7 and (c) ephrin-A3. dLGN dLGN (d,e) Total ephrin-A ligand expression in the developing thalamus consists of ephrin-A2, vLGN vLGN ephrin-A3 and ephrin-A5. Coronal sections were vLGN stained with EphA3-AP (to detect ephrin-A Retina LGN ligands) in (d) wild-type (wt) or (e) ephrin-A2/A3/ dLGN EphA dLGN dLGN A5 triple mutants (tko) at P0. Ephrin-As are DL EphA expressed in gradients across the whole dLGN at igl these early time points. (f,g) Gray-scale T N photomicrographs of coronal sections at P6 after Ephrin-A injection of cholera toxin B–Alexa Fluor 594 and cholera toxin B–Alexa Fluor 488 into left and right vLGN vLGN vLGN VM eyes, respectively, showing the retinal axons from Ephrin-A (f) contralateral and (g) ipsilateral eyes projecting into the dLGN. (h) The same section treated with EphA3-AP to detect ephrin-A ligands in the LGN at P6. No staining was ever seen when alternate sections were stained with AP alone. (i) Schematic of EphA receptor and ephrin-A ligand in the retina and dLGN during early periods of visual mapping. DL, dorsallateral; igl, intergeniculate layer; N, nasal; T, temporal; vLGN, ventral lateral geniculate nucleus; VM, ventral-medial. Dotted lines denote the approximate boundary of the dLGN. Dorsal is to the top, medial is to the left.

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(along the nasal-temporal mapping axis), whereas EphA7, and possibly other EphA receptors, were expressed in a countergradient. Ephrin-A3 is expressed in small amounts in the dLGN2,3 (Fig. 1). To determine the role of ephrin-A ligands in the mapping of the retinogeniculate projection, we created ephrin-A2/A3/A5 triple-mutant mice by crossing ephrin-A2/A5 double-mutant mice with ephrin-A3 mutant mice1,23. These mice can be viable and fertile, although a substantial number of triple mutants died in utero (data not shown). We first tested whether ephrin-A2, ephrin-A3 and ephrin-A5 account for the bulk of expression of ephrin-As in the dLGN by treating wild-type or triple-mutant coronal thalamic sections with a soluble EphA3–alkaline phosphatase (EphA3-AP) probe that binds to all ephrin-A proteins24. At postnatal day 0 (P0), EphA3-AP recognized a gradient of ephrin-As throughout the dLGN that was ventrallateral (high) to dorsal-medial (low; Fig. 1d), which is consistent with their role in topographic mapping2. At P6, we found that ephrin-A protein became restricted to the contralateral input area of

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the dLGN (Fig. 1f–h). At all ages tested, EphA3-AP staining in the dLGN was abolished in ephrin-A2/A3/A5 triple mutants (Fig. 1e and data not shown). Retinogeniculate projections in ephrin-A triple-mutant mice To determine whether ephrin-As are involved in the placement and segregation of eye-specific layers in the dLGN, we used a two-color whole-eye-fill tracing paradigm, which allowed us to test the location of each eye’s projections in the dLGN and to quantify defects in the segregation of inputs18. We compared the retinal innervation patterns in the dLGN from wild-type mice and from mice lacking combinations of ephrin-A ligands, including ephrin-A2/A3/A5 triple-mutant mice1,22,23. As shown by others, the inputs from each eye were segregated in wild-type adult mice, with a single ipsilateral patch located in the dorsomedial quadrant of the dLGN7 (Fig. 2a,c,e). This pattern of innervation was also seen in ephrin-A2, ephrin-A3 and ephrin-A5 single mutants and in ephrin-A3/A5 and ephrin-A2/A3

Figure 2 Defects in eye-specific layer placement but not in eye-specific segregation in ephrin-A2/A3/A5 triple-mutant mice. Axons from the right eye are shown in green; axons from the left eye are shown in red. (a,b) A series of coronal sections from anterior (top) to posterior (bottom) showing left and right dLGN in representative adult (a) wild-type (wt) and (b) ephrin-A2/A3/A5 triple-knockout (tko) mice. (c) Distribution of ipsilateral axon location within the dLGN. Data are expressed as a percentage of dLGN length along the longest dorsal-medial to ventral-lateral axis in coronal sections from wildtype, ephrin-A2/A5 double-mutant (dko) and ephrin-A2/A3/A5 triple-mutant mice, showing that the location of eye-specific inputs is defective in ephrin mutants. (d) Quantification of the ratio of percent ipsilateral projection area to total dLGN area in wild-type and ephrin-A2/A3/A5 triple-mutant mice. (e) Quantification of the average number of ipsilateral patches seen in a coronal section. A comparison of wild-type and ephrin-A2/A3/A5 triplemutant mice shows that the ipsilateral projection in the dLGN is patchy in ephrin mutant mice. Dotted lines show the outline of the dLGN. *P o 0.001; **P { 0.001; ANOVA test. Wild type, n ¼ 3 mice (four sections each); ephrin-A2/A5 mutant, n ¼ 8 mice (four sections each); ephrin-A2/A3/A5 mutant, n ¼ 9 mice (four sections each). Scale bar, 200 mm. Dorsal is to the top.

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Figure 3 Time course of eye-specific segregation in wild-type and ephrin-A2/A3/A5 triple-mutant mice. (a–h) Photomicrographs of 200-mm-thick coronal sections showing the retinal projections from each eye into the dLGN in (a,c,e,g) wild-type and (b,d,f,h) ephrin-A2/A3/A5 triple-mutant mice at (a,b) P4, (c,d) P6, (e,f) P8 and (g,h) P10. Each set of three images represents (from left to right) the ipsilateral projection, the contralateral projection and the merged image of one dLGN. Dorsal is to the top, medial is to the right in each image. Scale bar, 200 mm. Dotted line shows the outline of the dLGN. (i) Percent of the ipsilateral area in which contralateral projections are also present (‘overlap’), comparing wild-type and ephrin-A2/A3/A5 mutant mice at P4, P6, P8, P10 and adult. Error bars represent one s.d. in either direction. Wild-type P4, P6, P10: n ¼ 4 mice (16 dLGN sections); wild-type P8, adult, triple mutant P4, P6, P8, P10, adult: n ¼ 3 mice (12 dLGN sections).

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Figure 4 Area of dLGN overlap is increased in epibatidine-treated ephrin-A2/ A3/A5 triple-mutant mice as compared with epibatidine-treated wild-type mice. (a–c) Photomicrographs of 150-mm-thick coronal dLGN sections from P9 (a,b) wild-type and (c) ephrin-A2/A3/A5 mutant mice that received binocular intravitreal (a) control PBS injections or (b,c) epibatidine injections every 24 h from P3 to P7. The pictures are shown in groups of four representing (from left to right) the ipsilateral projection, the contralateral projection, the merged image and a binary image representing dLGN area with overlapping ipsilateral and contralateral projections. Dorsal is to the top, medial is to the right. Scale bar, 200 mm. (d) Quantification of ipsilateral and contralateral axonal overlap between control (wt PBS), wild-type (wt epi), and ephrin-A2/A3/A5/ or ephrin-A2/A3+/A5/ (tko epi) mutant mice, presented as the percentage of the ipsilateral area containing overlapping contralateral projections. (e) Quantification of ipsilateral and contralateral axonal overlap between control, wild-type and ephrin-A2/A3/A5/ plus ephrin-A2/A3+/A5/ mutant mice, presented as the percentage of the total dLGN area containing overlap. (f) Quantification of the ipsilateral patch length between control, wild-type and ephrin-A2/A3/A5/ (or ephrin-A2/A3+/A5/) mutant mice, expressed as the percentage of the dLGN length covered by the ipsilateral patch along the dorsal-medial to ventral-lateral axis. *P { 0.001; **P o 0.005; ANOVA test. wt + PBS, wt + Epi: n ¼ 4 mice (16 dLGN sections); ephrin-A2/A3/A5/ plus ephrin-A2/A3+/A5/+ Epi: n ¼ 4 mice (two of each genotype; 16 dLGN sections).

than in ephrin-A2/A5 double mutants (Fig. 2c), indicating that ephrin-A3 may contribute to ipsilateral patch location through its expression in the dLGN, in retinal axons or in both locations. Threedimensional reconstruction analysis of triple-mutant dLGNs shows that the ipsilateral projections are continuous and are shaped like a branching tube (Supplementary Videos 1 and 2). Notably, the ipsilateral projection did not seem to be random in the absence of ephrin-As. In all triple mutants examined, the ipsilateral projection branched and formed medial and central patches, although the exact location of these patches varied slightly from mouse to

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double mutants (data not shown). In contrast, ephrin-A2/A5 double mutants and ephrin-A2/A3/A5 triple mutants had severe defects in the location of the layers in the dLGN, but the segregation of inputs from each eye still occurred (Fig. 2b–e and Supplementary Fig. 2). Therefore, ephrin-A ligands are required for ipsilateral patch location but not the segregation of eye inputs in the dLGN. In ephrin-A2/A3/A5 triple-mutant mice, the ipsilateral patch expands along the entire dorsoventral axis of the dLGN, roughly corresponding to the nasotemporal mapping axis of the retina25. This phenotype was more severe in ephrin-A2/A3/A5 triple mutants

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mouse. Additionally, the two dLGNs from the same mouse showed symmetrical placement defects (Fig. 2b and Supplementary Fig. 2). This symmetrical positioning of the ipsilateral patch is reminiscent of the global symmetry of ocular dominance columns in the squirrel monkey26, whereby column placement differs among individual monkeys, but the column pattern is symmetric within an individual. These findings may indicate that there are additional molecules that participate in layer positioning. It is possible that the improper ipsilateral patch location seen in ephrin-A2/A3/A5 triple-mutant mice could be due to misrouting of axons at the optic chiasm. Nasal axons that normally cross would instead remain ipsilateral and map to their normal ‘contralateral’ termination zone, leading to an ‘ipsi’ patch located in the wrong position. If this were true, we would expect a greater amount of ipsilateral axons in the dLGN. We compared the ratio of ipsilateral patch area to total dLGN area and saw no significant difference between the wild type and ephrin-A2/A3/A5 triple mutants (Fig. 2d). This indicates that the defect seen in ephrin-A2/A3/A5 mutants may not be due to a larger ipsilateral projection into the dLGN or to defects in axon pruning within the dLGN. We also sectioned through the chiasm of mutant mice after labeling each eye’s inputs and saw no obvious defects in the amount of crossing. Finally, we took advantage of the fact that the SC is an exposed structure in early postnatal mice and retrogradely labeled the ipsilateral retina with an injection of DiI into the SC. In both the retinogeniculate and retinocollicular projections, most ipsilateral axons arise from the ventral-temporal retina27, and this was true in ephrin-A2/A3/A5 triple mutants (Supplementary Fig. 3). Taken together, these experiments indicate that ephrin-As may not be required for chiasm recognition. In wild-type mice, axons from the two eyes are intermixed at birth and then segregate by P10 (refs. 6,7). If coarse topography is a prerequisite for eye-specific segregation, one might expect that the segregation of inputs would be delayed or abolished in ephrin-A2/A3/ A5 triple-mutant mice. Even though adult ephrin-A2/A3/A5 triplemutant mice have segregated inputs (Fig. 2), we assessed whether ephrin-As are involved in the normal developmental timing of segregation by carrying out a time-course experiment in which we traced retinal inputs into the dLGN from P4 through adulthood and quantified the percentage of ipsilateral projection area that overlapped with contralateral projection area. In wild-type P4 mice, 92% of the dLGN that received ipsilateral input also contained inputs from the contralateral eye (Fig. 3a,i). Consistent with the findings of others, this overlap decreased with postnatal age to 15% overlap in adults (Fig. 3a,c,e,g)17. Ipsilateral triple-mutant inputs were erroneously positioned as early as

P4, before segregation occurred. Despite these errors, segregation of inputs occurred by P10, similar to what occurs in wild-type mice (Fig. 3b,d,f,h), indicating that coarse topography may not be a prerequisite for the segregation of eye inputs in the LGN. Ephrin-As and neural activity pattern retinal projections Retinal activity is thought to be important for both the establishment and maintenance of eye-specific segregation. Studies in which activity or molecules thought to act downstream of activity have been disrupted show that overlap of eye inputs occurs primarily in the dorsal dLGN7,10,28,29. To determine whether altering presynaptic activity in ephrin-A mutants allows eye-specific inputs to overlap in all regions of the dLGN, we injected epibatidine into both eyes of neonatal pups and assayed the retinogeniculate projection at P9. Epibatidine is a nicotinic acetylcholine receptor agonist that blocks correlated RGC spiking and all calcium waves in vitro by receptor desensitization and disrupts eyespecific segregation in both ferrets and mice7,10,18. Epibatidine injection into both eyes of wild-type mice every 24 h from P3 to P7 prevented segregation at P9 (98% of ipsilateral dLGN area had overlapping contralateral projections as compared with 53% in PBS-injected controls; Fig. 4a,b). Although there was some spread of ipsilateral axons into more ventral regions of the dLGN, the overlap was predominantly in the dorsal dLGN (Fig. 4b,f). This agrees well with studies in mice and ferrets that used epibatidine to assay the role of activity in eyespecific segregation7,10,18,25. Epibatidine prevented eye-specific segregation to a similar degree in ephrin-A2/A3/A5 triple mutants as compared with wild type, but in triple mutants the overlap extended significantly into the ventral dLGN (Fig. 4c–f). This shows that a combination of molecular labels and neural activity act to determine the placement and segregation of eye-specific inputs within the dLGN and indicates that in the absence of ephrin-As and correlated neural activity, regions of the dLGN that are normally occupied by the contralateral eye become competent for innervation from either eye. Ephrin-A function and neural activity Because spontaneous bursting activity in the developing spinal cord regulates EphA4 expression on chick motor axons30, we tested whether EphA receptors in the retina change their expression after inter-retinal injection of epibatidine. We did this in two different ways. First, we isolated total retinal RNA from mice injected with epibatidine or PBS (every 24 h from P3 to P5) and then carried out RT-PCR. We saw no difference in expression of EphA4, EphA5 or EphA6 under these conditions (data not shown). Second, we found no qualitative difference in the spatial distribution of Eph receptors in the retina or of

Figure 5 Spontaneous retinal waves in ephrin-A2/ Spontaneous retinal activity rasters, ephrin-A2/A3/A5 tko Spike correlations A3/A5 triple-mutant retinas. (a) Spike rasters of 1 Normal saline 10 nM epibatidine 2 Single wave spontaneous retinal activity from an ephrinA2/A3/ wt 3 30 Ephrin-A2/A3/A5 tko A5 triple-mutant mouse at P4. Relative electrode 4 1 1 Ephrin-A2/A3/A5 tko + 10 nM epibatidine positions (1–4) for the example neuronal recordings are illustrated in the inset of the right 20 2 2 panel. Closer examination of a typical wave (left panel, 10 s) shows it traveling from electrode 4 to 3 3 10 electrode 1 at 140 mm/s. In contrast, the activity of the same neurons in the presence of 10 nM 4 4 epibatidine shows no waves. (b) Correlation 0 indices were calculated for all pairs of neurons 10 14 18 0 100 200 300 0 100 200 300 100 300 500 700 Time (s) recorded from a P4 wild-type retina (white Interelectrode distance (µm) Time (s) Time (s) circles), a P4 ephrinA2/A3/A5 triple-mutant retina (black circles) and an epibatidine-treated ephrin-A2/A3/A5 triple-mutant retina (black triangles). These are plotted against the distance between the electrodes from which the neuron’s spikes were recorded. In both the wild-type and ephrinA2/A3/A5 mutant retinas, wave activity led to high correlation indices at small distances and lower ones at larger distances. Epibatidine, which eliminated the wave activity but did not eliminate spike activity in the ephrinA2/A3/A5 mutant retina, abolished correlated activity at all distances. wt: n ¼ 3 retinas; ephrin-A2/A3/A5: n ¼ 3 retinas.

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ARTICLES ephrin-A ligands in the dLGN after epibatidine injection as assayed by RNA in situ hybridization (Supplementary Fig. 1). These experiments show that epibatidine does not have a pronounced effect on EphA or ephrin-A expression in the retina or dLGN; however, these techniques cannot discount post-transcriptional regulation of Ephs and ephrins by neural activity. To test whether neural activity patterns in the retina are affected in ephrin-A2/A3/A5 triple-mutant mice, we compared the patterns of neural activity between wild-type and ephrin-A2/A3/A5 triple mutants by recording extracellularly from P4 retinas using a multielectrode array. Like wild-type RGCs, ephrin-A2/A3/A5 RGCs had bursts of action potentials followed by long periods of silence (Fig. 5a). These bursts were highly correlated among nearby RGCs as propagating waves traveled across the recorded retinal area. The addition of 10 nM epibatidine blocked the waves but did not eliminate spontaneous activity. The activity of neighboring RGCs is highly correlated, and the degree of correlation for small time windows decreases over distance31. Notably, triple-mutant retinas had a higher degree of correlation at larger distances in the array (approximately 800 mm) than the wild-type retinas (Fig. 5b). This effect is likely to be due to the waves being somewhat broader and wider in the triple mutant, which could mean that ephrin-As are somehow required for the normal development of the inner retinal circuitry that is responsible for the waves. Nevertheless, segregation of eye-specific inputs in the dLGN occurred in the presence of the retinal waves in triple-mutant mice.

the topographic mapping phase of dLGN development and then act as layer placement labels during the segregation phase. Notably, ephrin-As at P6 are predominantly expressed in the ventrolateral dLGN where they may act to repel ipsilateral axons toward their location in the dorsomedial dLGN (Fig. 1f–h). This expression may be due to changes in ephrin-A expression in dLGN neurons or to ephrin-A ligands that are present on newly arriving nasal RGC axons. Layer-specific expression of ephrin-A ligands has also been observed in the ferret, where topographic mapping is established at birth and eye-specific segregation occurs postnatally between P1 and P10. During the period of eyespecific segregation in ferrets, ephrin-A5 expression is higher in the ipsilateral layer than in the contralateral layer of the dLGN, and ectopic expression of EphA receptors in the postnatal retina causes layering errors, as described in an accompanying article in this issue32. Therefore, just as ephrin gradients have evolved for use in multiple visual targets2 and are proposed to act first in the intermediate target and later in the final target in thalamic-cortical mapping4, they may be used in multiple aspects of mapping within a particular visual target. The relative contributions of guidance cues and neural activity to the functional wiring of the nervous system have long been debated. Here we show, in the model projection from the retina to the dLGN, that both are required for normal wiring. It will be of note to see if the development of structures in the cerebral cortex, such as the formation of cortical columns, will also use a combination of ephrins and neural activity during development.

DISCUSSION The patterning of RGCs within the dLGN involves correct topographic location of contra- and ipsilateral axons, segregation of right and left eye inputs, and the establishment and placement of eye-specific layers. The relative contributions of activity-dependent and -independent mechanisms to each of these aspects of mapping have long been debated. EphA receptors and ephrin-A ligands are required for topographic mapping of the nasal-temporal axis of the retina onto both the SC and the dLGN1–3,22. We show here that ephrin-As are also required for the proper placement of eye-specific inputs in the mouse dLGN but are not essential for the segregation of these inputs. In agreement with others7,10,17, we find that correlated retinal activity is required for the segregation of eye-specific inputs. Notably, the ephrin-A-mediated aspects of mapping (topography and layer placement) act independently of the activity-dependent segregation of inputs. Ephrin-A2/A3/ A5 triple-mutant mice had severe defects in layer placement but still segregated eye inputs in the dLGN with normal developmental timing. In addition, we show that inhibiting correlated presynaptic retinal activity in ephrin-A2/A3/A5 triple-mutant mice abolishes both segregation and layer placement, indicating that the combination of ephrinAs and presynaptic neural activity is necessary to pattern one axis of the retinogeniculate projection. Our analysis of ephrin mutant mice led us to a model whereby a combination of topographic mapping molecules and neural activity–dependent events are parallel mechanisms that together create the stereotypical connectivity patterns in the primary visual system (Supplementary Fig. 4). How might ephrin-As guide the ipsilateral axons to the appropriate place? One possibility is that ipsilateral axons are directed to a specific region of the dLGN by a unique combination of anterior-posterior and dorsal-ventral topographic labels. Ipsilateral axons arise from the ventrotemporal retina, which has high EphA and EphB receptor expression. Therefore, gradients of ephrin-A2 and ephrin-A5 along one axis of the dLGN, combined with an orthogonal gradient of ephrin-Bs, could steer ipsilateral axons to their final location in the dLGN. Alternatively, ephrin-As could act as topographic labels during

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Mice were maintained in the animal facility at University of California at Santa Cruz (UCSC) and were used in accordance with protocols approved by the UCSC Institutional Animal Care and Use Committee. Whole-eye labeling and visualization of the dLGN. A pulled pipette adapted to a Picospritzer III pressure injection system (Parker Hannifin Corporation) was used to inject 2–3 ml of a 2 mg/ml solution of cholera toxin B–Alexa Fluor 594 or cholera toxin B–Alexa Fluor 488 (Molecular Probes) in PBS into the eye. Mice were killed 2 or 3 d later and intercardially perfused with 4% paraformaldehyde in PBS, and their brains were fixed overnight. Brains were embedded in 2–3% agarose (Sigma) in PBS and 150- to 200-mm coronal sections were cut using a vibratome (World Precision Instruments Inc.). Images were captured with an AxioCam Hrm digital camera through a 20 objective on an Axioskop 2 Plus microscope (Zeiss) and were merged using Adobe Photoshop. For threedimensional confocal reconstruction analysis, 100-mm coronal sections were cut on a vibratome and were mounted on glass slides with Fluoromount-G (Southern Biotech) overnight in the dark. Optical sections (10 mm thick) from five serial sections per brain were imaged on an Axiovert 200 inverted microscope (Zeiss) through the LSM 5 Pascal laser scanning module. Images were acquired into the accompanying LSM 5 Pascal software and then were stacked anterior to posterior using Image J (http://rsb.info.nih.gov/ij/). Quantification of overlap of projections. ImageJ was first used to reduce background with a rolling ball filter of 250 pixels. The dLGN was then selected and isolated so that further manipulations were done only on this region, disregarding the optic tract and vLGN. The isolated dLGNs were then thresholded in an unbiased manner, whereby the pixels in the lowest-intensity quintile, as determined by histogram analysis, were discarded. This approach sufficiently eliminates background while creating a binary image that closely mimics the predicted structure of the unthresholded projections. The thresholded ipsilateral and contralateral images were then compared using the image calculator ‘OR’ function and the area of the resulting image was determined to be ‘overlap’. Percent dLGN containing overlap ¼ (overlap/total dLGN area) 100; percent ipsilateral projections containing overlapping contralateral projections ¼ (overlap/total ipsilateral area) 100. To quantify the length of the dLGN, a line was drawn at an angle from the dorsal-medial dLGN to the vLGN to yield the maximum dimension of the dLGN in each section. Ipsilateral projection placement along that line was then measured.

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Percent dLGN length ¼ (total length of the ipsilateral projection)/(total length of the dLGN) 100. All quantification of dLGN projections was done by researchers who were blind to treatment and genotype. Epibatidine injections. To image overlap at P9, 1–2 ml of 1 mM epibatidine (Biomol) in PBS was injected intravitreally into both eyes every 24 h from P3 to P7 using a Picospritzer III. Injections at P3 and P4 were given through the skin covering the eye; at P5 the skin was cut open to allow the three final injections to be carried out through the same hole in the eye. Mice were killed at P9 and processed for visualization in the same way as the whole-eye fills. To collect RNA and assay EphA and ephrin-A RNA expression at P6, 1–2 ml of PBS or 1 mM epibatidine in PBS was injected intravitreally into both eyes every 24 h from P3 to P5. The first injection was given through the skin covering the eye; at P4 the skin was cut open to allow the final two injections to be carried out through the same hole in the eye. Mice were killed on P6. In situ RNA hybridization. In situ probes for ephrin-A5 (nucleotides 102–682 of the open reading frame), ephrin-A3 (nucleotides 100–687) and EphA7 (nucleotides 721–1193) were used to make antisense and sense digoxigeninlabeled RNA probes. Frozen-section in situ hybridization was done as previously described2. Stained sections were photographed using a cool-pix digital camera (Nikon) mounted on a dissecting microscope. Affinity probe in situ. An EphA3-AP in situ was done as described33. Briefly, brains were dissected from neonatal pups and rapidly embedded in 5% agarose in PBS. Coronal sections (250 mm) were cut using a vibratome, and those containing dLGN were treated with EphA3-AP as floating sections. Stained sections were photographed using a cool-pix digital camera (Nikon) mounted on a dissecting microscope. Multielectrode extracellular recording from retina. Mice were killed on P3– P5, after which an eye was removed. The neural retina was dissected and placed ganglion cell–side down in a recording chamber using nitrocellulose paper as support. The multielectrode chambers (MEA-60 system; MultiChannel Systems [MCS], Germany) consisted of an array of 60 planar electrodes in eight rows spaced 100 mm apart for a total array size of 700 mm2. Retinas were perfused at room temperature and incubated at 34 1C for 1 h before recordings were started, and the temperature was maintained at 34 1C throughout the recordings. The saline consisted of 124 mM NaCl, 2.5 mM KCl, 2 mM CaCl2, 2 mM MgCl2, 1.25 mM NaH2PO4, 26 mM NaHCO3 and 22.2 mM glucose, and the pH was maintained at 7.3–7.4 by bubbling with 95%O2/5%CO2 mixed gas. Data were acquired in a response range of 0.1 Hz–3 kHz at 5-kHz sampling rate (MC_Rack, version 2.0; MCS). After recordings were made, action potential waveforms from high-passfiltered data were clustered based on the first two principal components as described previously34 using a k-means algorithm (OfflineSorter, version 1.3; Plexon, Inc). The algorithm eliminated outlier waveforms at a threshold of 1.3 times the mean distance from the calculated cluster center. Obvious automatic sorting errors were corrected for each cluster manually. Timestamps for each action potential of each sorted unit were used to generate peristimulus spike rasters and to carry out auto- and cross-correlation analyses (NeuroExplorer, version 2.6; Nex Technologies). Correlation indices were calculated as described35 using custom macros (IGOR Pro, version 4.0; WaveMetrics). Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We thank B. Chapman and A. Huberman for discussions and sharing data prior to publication. We thank C. Chen, P. Vanderhaeghen and C. Mason for discussions and critical reading of the manuscript and R. Axel for support (T.C.). This work was supported by a US National Institutes of Health (NIH) grant EY014689 (D.A.F.), an NIH predoctoral training grant GM08646 (C.P.) and NIH grants R01 DC04209 and P01 CA23767 (T.C.). COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 29 April; accepted 24 June 2005 Published online at http://www.nature.com/natureneuroscience/


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1. Feldheim, D.A. et al. Genetic analysis of ephrin-A2 and ephrin-A5 shows their requirement in multiple aspects of retinocollicular mapping. Neuron 25, 563–574 (2000). 2. Feldheim, D.A. et al. Topographic guidance labels in a sensory projection to the forebrain. Neuron 21, 1303–1313 (1998). 3. Feldheim, D.A. et al. Loss-of-function analysis of EphA receptors in retinotectal mapping. J. Neurosci. 24, 2542–2550 (2004). 4. Vanderhaeghen, P. & Polleux, F. Developmental mechanisms patterning thalamocortical projections: intrinsic, extrinsic and in between. Trends Neurosci. 27, 384–391 (2004). 5. McLaughlin, T., Hindges, R. & O’Leary, D.D. Regulation of axial patterning of the retina and its topographic mapping in the brain. Curr. Opin. Neurobiol. 13, 57–69 (2003). 6. Metin, C., Godement, P., Saillour, P. & Imbert, M. [Physiological and anatomical study of the retinogeniculate projections in the mouse.] C. R. Seances Acad. Sci. III 296, 157– 162 (1983). 7. Rossi, F.M. et al. Requirement of the nicotinic acetylcholine receptor beta 2 subunit for the anatomical and functional development of the visual system. Proc. Natl. Acad. Sci. USA 98, 6453–6458 (2001). 8. Sretavan, D.W., Shatz, C.J. & Stryker, M.P. Modification of retinal ganglion cell axon morphology by prenatal infusion of tetrodotoxin. Nature 336, 468–471 (1988). 9. Shatz, C.J. & Stryker, M.P. Prenatal tetrodotoxin infusion blocks segregation of retinogeniculate afferents. Science 242, 87–89 (1988). 10. Penn, A.A., Riquelme, P.A., Feller, M.B. & Shatz, C.J. Competition in retinogeniculate patterning driven by spontaneous activity. Science 279, 2108–2112 (1998). 11. Sretavan, D.W. & Shatz, C.J. Prenatal development of retinal ganglion cell axons: segregation into eye-specific layers within the cat’s lateral geniculate nucleus. J. Neurosci. 6, 234–251 (1986). 12. Rakic, P. Development of visual centers in the primate brain depends on binocular competition before birth. Science 214, 928–931 (1981). 13. Godement, P., Salaun, J. & Metin, C. Fate of uncrossed retinal projections following early or late prenatal monocular enucleation in the mouse. J. Comp. Neurol. 255, 97–109 (1987). 14. Stellwagen, D. & Shatz, C.J. An instructive role for retinal waves in the development of retinogeniculate connectivity. Neuron 33, 357–367 (2002). 15. Crowley, J.C. & Katz, L.C. Ocular dominance development revisited. Curr. Opin. Neurobiol. 12, 104–109 (2002). 16. Huberman, A.D. et al. Eye-specific retinogeniculate segregation independent of normal neuronal activity. Science 300, 994–998 (2003). 17. Muir-Robinson, G., Hwang, B.J. & Feller, M.B. Retinogeniculate axons undergo eyespecific segregation in the absence of eye-specific layers. J. Neurosci. 22, 5259–5264 (2002). 18. Huberman, A.D., Stellwagen, D. & Chapman, B. Decoupling eye-specific segregation from lamination in the lateral geniculate nucleus. J. Neurosci. 22, 9419–9429 (2002). 19. Shatz. Emergence of order in visual system development. Proc. Natl. Acad. Sci. USA 93, 602–608 (1996). 20. Crowley, J.C. & Katz, L.C. Development of ocular dominance columns in the absence of retinal input. Nat. Neurosci. 2, 1125–1130 (1999). 21. Chapman, B. Necessity for afferent activity to maintain eye-specific segregation in ferret lateral geniculate nucleus. Science 287, 2479–2482 (2000). 22. Friseń, J. et al. Ephrin-A5 (AL-1/RAGS) is essential for proper retinal axon guidance and topographic mapping in the mammalian visual system. Neuron 20, 235–243 (1998). 23. Cutforth, T. et al. Axonal ephrin-As and odorant receptors: coordinate determination of the olfactory sensory map. Cell 114, 311–322 (2003). 24. Flanagan, J.G. & Vanderhaeghen, P. The ephrins and Eph receptors in neural development. Annu. Rev. Neurosci. 21, 309–345 (1998). 25. Grubb, M.S., Rossi, F.M., Changeux, J.P. & Thompson, I.D. Abnormal functional organization in the dorsal lateral geniculate nucleus of mice lacking the beta 2 subunit of the nicotinic acetylcholine receptor. Neuron 40, 1161–1172 (2003). 26. Adams, D.L. & Horton, J.C. Capricious expression of cortical columns in the primate brain. Nat. Neurosci. 6, 113–114 (2003). 27. Williams, S.E. et al. Ephrin-B2 and EphB1 mediate retinal axon divergence at the optic chiasm. Neuron 39, 919–935 (2003). 28. Pham, T.A., Rubenstein, J.L., Silva, A.J., Storm, D.R. & Stryker, M.P. The CRE/CREB pathway is transiently expressed in thalamic circuit development and contributes to refinement of retinogeniculate axons. Neuron 31, 409–420 (2001). 29. Huh, G.S. et al. Functional requirement for class I MHC in CNS development and plasticity. Science 290, 2155–2159 (2000). 30. Hanson, M.G. & Landmesser, L.T. Normal patterns of spontaneous activity are required for correct motor axon guidance and the expression of specific guidance molecules. Neuron 43, 687–701 (2004). 31. Demas, J., Eglen, S.J. & Wong, R.O. Developmental loss of synchronous spontaneous activity in the mouse retina is independent of visual experience. J. Neurosci. 23, 2851– 2860 (2003). 32. Huberman, A.D., Murray, K.D., Warland, D.K., Feldheim, D.A. & Chapman, B. Ephrin-As mediate targeting of eye-specific projections to the lateral geniculate nucleus. Nat. Neurosci. 8, 1011–1019 (2005). 33. Flanagan, J.G. In situ analysis of embryos with receptor or ligand fusion protein probes. Curr. Biol. 10, R52–R53 (2000). 34. Tian, N. & Copenhagen, D.R. Visual stimulation is required for refinement of ON and OFF pathways in postnatal retina. Neuron 39, 85–96 (2003). 35. Wong, R.O.L., Meister, M. & Shatz, C.J. Transient period of correlated bursting activity during development of the mammalian retina. Neuron 11, 923–938 (1993).

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Motility-associated hair-bundle motion in mammalian outer hair cells Shuping Jia & David Z Z He Mammalian hearing owes its remarkable sensitivity and frequency selectivity to a local mechanical feedback process within the cochlea. Cochlear outer hair cells (OHCs) function as the key elements in the feedback loop in which the fast somatic motility of OHCs is thought to be the source of cochlear amplification. An alternative view is that amplification arises from active hair-bundle movement, similar to that seen in nonmammalian hair cells. We measured voltage-evoked hair-bundle motions in the gerbil cochlea to determine if such movements were also present in mammalian OHCs. The OHCs showed bundle movement with peak responses of up to 830 nm. The movement was insensitive to manipulations that would normally block mechanotransduction in the stereocilia, and it was absent in neonatal OHCs and prestin-knockout OHCs. These findings suggest that the bundle movement originated in somatic motility and that somatic motility has a central role in cochlear amplification in mammals.

It is generally believed that mechanical amplification by hair cells is necessary to enhance the sensitivity and frequency-selectivity of hearing. In the mammalian cochlea, OHCs function as the key elements in a mechanical feedback loop that most likely involves the OHCs, organ of Corti micromechanics and the tectorial membrane (TM), with inner hair cells (IHCs) responding to the output of the feedback loop1,2. OHCs have a voltage-dependent length change termed electromotility3,4. This somatic motility, when driven by the receptor potential in vivo, is thought to underlie cochlear amplification in mammals1–5. An alternative view is that the amplification arises from active hairbundle motion6,7. Active hair-bundle movements ranging between 5 and 80 nm have been observed in several nonmammalian species and can occur spontaneously with amplitudes in excess of that expected for Brownian motion8–10. Such movements have also been observed as reactions to hair-bundle displacement with compliant probes8,11–13, and in response to changes in membrane potential8,9,13–15. The active hair-bundle movements, intimately related to the reclosure of the mechanotransducer channels8,13 and the myosin motors11,16,17 involved in adaptation, can produce forces that amplify mechanical stimuli6,7. The movements are sensitive to extracellular calcium concentration and can be altered by calcium influx through mechanoelectrical transducer channels8,13,15–17. Active hair-bundle motion has been shown to produce all of the characteristics of the active process in non-mammals, but two recent studies18,19 indicate that hair-bundle motion may also have an important role in cochlear amplification in mammals. One study, using a two-chamber in vitro cochlear preparation of gerbils, showed that nonlinear amplification depends on calcium current through the mechanoelectrical transducer channels18. Small hair-bundle motions of inner hair cells were observed in the same study. Another study

shows that hair bundles of rat OHCs can produce force on a submillisecond timescale19. The force, with a magnitude on the order of 500 pN, is linked to adaptation of the mechanotransducer channels19. To date, however, bundle motion has not been thoroughly examined in mammalian OHCs. To determine whether hair-bundle movements are also present in mammalian OHCs, we evaluated voltage-evoked hair-bundle activity in the cochlea of gerbils and prestin knockout mice5. We found that OHCs show bundle movement with peak responses of up to 830 nm. The movement was insensitive to manipulations that would normally block mechanotransduction in the stereocilia, and it was absent in neonatal OHCs and prestin-knockout OHCs. This result suggests that the bundle movement, under the conditions we studied, was not based on mechanotransducer channels but originated in somatic motility. The motility-associated response seems to overshadow transducer channel–based mechanisms in OHCs. RESULTS Sensory epithelia were dissected from the cochleae of adult gerbils and prestin-knockout mice. The resulting coil preparation was bathed in artificial perilymph and viewed under a water-immersion objective microscope. The sensory epithelium was oriented with the hair bundles pointing up toward the objective. At high magnification, the hair bundles behaved as light pipes13 and appeared as bright V-shaped lines under bright-field illumination (Fig. 1a). To measure bundle motion, the magnified (1,260) image of the edge of the hair bundle was projected onto a photodiode through a rectangular slit. The photodiode-based system, mounted on the photo-port of the microscope, had a 3-dB cutoff frequency of 1,200 Hz and was capable of measuring motion down to roughly 5 nm with moderate averaging and low-pass filtering. Cells were selected if no obvious signs of deterioration in the

Hair Cell Biophysics Laboratory, Department of Biomedical Sciences, Creighton University School of Medicine, 2500 California Plaza, Omaha, Nebraska 68175, USA. Correspondence should be addressed to D.Z.Z.H. ([email protected]). Published online 24 July 2005; doi:10.1038/nn1509

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Figure 1 Mechanotransducer current and hair-bundle motion of gerbil OHCs. (a) Hair bundles of OHCs under high magnification (63 water-immersion objective) with bright field illumination. The bundles behaved as light pipes and appeared as bright V-shaped lines when focused at their tips. Doubleheaded arrow indicates the direction of bundle motion. Scale bar, 10 mm. (b) Mechanotransducer currents recorded from a gerbil apical-turn OHC from the coil preparation. The bundle was deflected by an oscillating stream from a fluid jet (tip diameter B10 mm) positioned roughly 20–30 mm away from the bundle. The response shown is the average of three trials. The voltage command (102 Hz) to drive the water jet is presented at the bottom of the panel. Inward current is plotted downward. (c) Voltage-evoked bundle motions of a gerbil OHC at two different extracellular calcium concentrations. The 102-Hz voltage command varied the membrane potential from 100 to 40 mV around a holding potential of 70 mV. Positive bundle motion (toward tall cilia) is plotted upward in this and all subsequent figures. (d) Bundle motion before and after perfusion of 100 mM streptomycin into the OHC stereociliary region. The responses in c and d were the averages of 100 trials. The scale bar in c also applies to the responses in d.

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soma and/or hair bundle were visible at high magnification. Before the voltage-evoked bundle motion was measured, we recorded mechanotransducer currents to verify that the mechanotransducer apparatus in the stereocilia was not damaged. Figure 1b shows an example of such recording from a gerbil apical-turn OHC. The hair bundle was deflected by a fluid jet (with pipette tip diameter of 10 mm) positioned 20–30 mm away from the bundle. Large transducer currents were recorded at the holding potential of 70 mV in the voltage-clamp mode (Fig. 1b). The size of the current was comparable to that observed in previous studies in mammalian OHCs20–22. To determine bundle motions, we applied sinusoidal voltage bursts (102 Hz) to the OHCs through the patch electrode. The voltage command varied the membrane potential from 100 mV to 40 mV, from a holding potential of 70 mV. Examples of the voltage-evoked hair-bundle movements are shown in Fig. 1c (see Supplementary Videos 1,2 for large bundle motion). The observed bundle motion was asymmetrical, with larger bundle motions evoked by depolarization in the direction toward the tallest stereocilia (defined as positive bundle motion) than that evoked by hyperpolarization in the opposite direction (negative bundle motion). The direction of bundle motion during membrane potential change was consistent with that seen in turtle hair cells8,13, but it was of opposite polarity to that seen in bullfrog saccular hair cells14,15. Hair cells of several nonmammalian species show active hair-bundle motion in response to changes in membrane potential8,9,13–15. The active motion, intimately associated with mechanotransducer channel apparatus, is secondary to alteration of calcium influx in the stereocilia and is therefore dependent on the extracellular calcium concentration8,13. We sought to determine whether the bundle motion observed in OHCs operates on a similar basis. We examined bundle motion

when the extracellular calcium concentration was reduced to 5 mM (Fig. 1c). Voltage-evoked bundle motion was compared before and after the ciliary bundle of five cells was perfused with low-calcium medium. We found robust voltage-evoked bundle motion both before and after perfusion, with no statistically significant difference in magnitude. Streptomycin is known to block mechanotransducer channels20 and eliminate active and spontaneous bundle motion13,15. We perfused the ciliary area with 100 mM streptomycin to determine whether it blocked the voltage-evoked bundle motion in OHCs. The bundle motion was not affected by streptomycin (Fig. 1d). Collectively, these results suggest that the observed OHC bundle motion is different from the voltage-evoked bundle motion seen in nonmammalian hair cells. As an alternative to motility derived from mechanotransducer processes, it is possible that bundle motion arises as a consequence of

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Figure 2 Hair-bundle motion of neonatal gerbil OHCs and mouse OHCs. (a) Voltage-evoked bundle motions measured from 4-, 8- and 12-d-old gerbil OHCs. The voltage command is the same as shown in Fig. 1c. (b) Mechanotransducer currents recorded from an apical-turn OHC of a prestin-knockout mouse. The hair bundle was deflected by a fluid jet (with a tip diameter of 10 mm) positioned roughly 20–30 mm away from the bundle. The cell was held at 70 mV under the voltage-clamp condition. (c) Lack of voltage-evoked bundle motion from the prestin-knockout mouse OHC. (d) Voltage-evoked bundle motion of an apical-turn OHC from wild-type mouse. The stimulus waveform and voltage command for c and d are the same as those shown in Fig. 1c.


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ARTICLES somatic motility. To examine this possibility, we studied voltage-evoked bundle motion in neonatal gerbil OHCs. Previous studies have shown that the onset of OHC motility occurs around 6–8 days after birth (DAB)23, whereas mechanotransducer apparatus and mechanotransducer current with fast and slow adaptation are apparent before birth in mouse hair cells24. Consequently, mechanotransduction in the hair bundle is mature well before the onset of OHC motility20,21. Voltageevoked bundle motions of apical-turn OHCs were measured from developing gerbils at 4, 8 and 12 DAB (Fig. 2a). When mechanotransduction had developed and somatic motility had not yet developed at 4 DAB, no voltage-evoked bundle motion was detected (n ¼ 10), even though large transducer currents could be measured (data not shown). At 8 DAB, we observed small bundle motion in one of the eight cells examined. At 12 DAB, when all OHCs typically exhibit electromotility23, voltage-evoked bundle motion was detected in all seven cells studied, with a magnitude of approximately 72% of that of the adult OHCs with the same voltage stimulation. The facts that neonatal OHCs do not have voltage-evoked hair-bundle motion before the onset of motility and that the development of bundle movements correlates with the development of somatic motility suggest that bundle motion, in response to membrane potential change, is related to somatic motility. OHC somatic motility is mediated by the voltage-sensitive, membrane-bound motor protein, prestin25. To directly test whether the observed large bundle motion was related to somatic motility of OHCs, we examined the voltage-evoked bundle motion in prestin-knockout mice5. Such experiments are also important to determine whether there is any small transducer channel–based bundle motion that is overshadowed by the dominant motility-associated bundle motion. These knockout mice have normal morphology of the hair bundles and normal mechanotransducer functions, with no OHC somatic motility5,26. We measured transducer currents first to confirm that their mechanotransducer channels were functional and not damaged. When we recorded the transducer current from an apical-turn OHC of the prestin knockout mouse, a large asymmetrical transducer current was observed (Fig. 2b). We measured the voltage-evoked bundle motion from those OHCs. No voltage-evoked bundle motion was seen in any of the 11 cells examined (Fig. 2c). In contrast, when the voltage-evoked bundle motion was measured from OHCs of wild-type mice, large bundle motions were seen in all cells studied (Fig. 2d). To rule out the possibility that the lack of bundle motion in the prestin-null OHCs was due to perilymph solution bathing the stereocilia, we measured the voltage-evoked bundle motion after perfusing the ciliary area with artificial endolymph in five additional prestin-null OHCs. This mimics the in vivo chemical condition. No voltage-evoked bundle motions were observed in any of the five cells examined. This confirms that the voltage-evoked bundle motion is indeed associated with somatic motility. In coil preparations, or under in vivo conditions, OHCs are constrained by adjacent OHCs and by supporting cells. The physical

connection among neighboring OHCs provides a basis for mechanical interaction among OHCs. Indeed, the influence of somatic motility of a stimulated OHC on the adjacent OHC through mechanical coupling has been shown previously27,28. If the observed voltage-evoked hairbundle motion is associated with somatic motility and the consequent rotation of the reticular lamina, then the bundle motion should also be detected from adjacent OHCs, despite the fact that they are not under direct electrical stimulation. We measured the bundle motion of the stimulated cell (Cell 1 in Fig. 3a) and the adjacent unstimulated cell (Cell 2) in the same row. The stimulated cell was held at 70 mV, and its membrane potential varied from 145 mV to 5 mV at 102 Hz. A large response with peak-to-peak magnitude of 253 nm was detected from the stimulated cell (Fig. 3b). Bundle motion was also observed from the adjacent unstimulated OHC (Cell 2), even though only Cell 1 was stimulated electrically. The magnitude of bundle motion of the adjacent cell was roughly one-half that of the stimulated OHC (Fig. 3b). OHC motility and axial stiffness are sensitive to turgor pressure3,29. When OHCs are mechanically constrained by neighboring OHCs and supporting cells, as is the case in vivo and in the coil preparation, the turgor pressure becomes even more important, due to the mechanical load, for the expression of OHC motility and for the motility-driven reticular lamina rotation. We manipulated the turgor pressure of the stimulated cell to determine whether the bundle motion was also sensitive to turgor pressure. We reduced the turgor pressure by applying negative pressure through the patch electrode. The bundle motion of the stimulated OHC disappeared (Fig. 3c). The bundle motion of the adjacent OHC also disappeared after the stimulated cell lost its turgor pressure. The existence of bundle motion of the adjacent OHC and disappearance of bundle motion after turgor pressure loss indicate that the bundle motion results from rotation of the reticular lamina, as a consequence of somatic motility. Subsequently, we examined bundle motion as a function of membrane potential (input-output function). Figure 4a shows an example of the response measured from a gerbil apical-turn OHC when the membrane potential was stepped up and down from a holding potential of 70 mV. The responses were asymmetrical and nonlinear,

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Figure 4 Input-output function and frequency response of hair-bundle motion. (a) Bundle motions of a gerbil apical-turn OHC as a function of voltage level (from a holding potential of 70 mV). (b) Steady-state response from a was fitted with a second-order Boltzmann function (solid line), and a slope function (dashed line) was obtained as the derivative of the Boltzmann function. The series resistance was 75% compensated. Because membrane conductances were blocked, the uncompensated voltage error (not corrected in the plot) was less than 4 mV at the largest voltage levels. The bundle motion was low-pass filtered at 400 Hz. (c) Motility-associated bundle motions evoked by a series of voltage bursts with different frequencies (frequency is shown on the top of the response waveforms). (d) The peakto-peak response was measured from c and plotted as a function of frequency. The roll-off of the photodiode system was compensated in the frequency response. The response from the photodiode was low-pass filtered at 1,200 Hz.

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membrane of OHCs right above the nucleus to maximize the motion of the cuticular plate. Such measured motion should represent the total length change of OHCs in situ under the constrained condition. The response was asymmetrical and nonlinear, with saturation in both directions (Fig. 5a), similar to that seen in isolated OHCs29. The peakto-peak magnitude of length change was about 1,384 nm, with a maximal sensitivity of 13 nm/mV (Fig. 5b). This value is similar to the maximal sensitivity of somatic motility (5–25 nm/mV) measured from isolated OHCs29. We also measured the bundle motion from the same cell with the same voltage stimulation. The bundle response measured from the hemicochlea resembled that measured from OHCs in the coil preparation (Fig. 4a). For comparison with OHC somatic motility, we plotted the steady-state response of the bundle motion as a function of voltage (Fig. 5b), along with its Boltzmann fit and the slope function. The slope sensitivity of bundle motion was about one-half of that of somatic motility. To quantify the relation between somatic motility and bundle motion, we plotted the magnitude of bundle motion as a function of somatic motility (Fig. 5c): the amplitude of bundle displacement was about one-half of the length change.

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with saturation in both directions, similar to that seen in OHC somatic motility29. We fitted the response with a second-order Boltzmann function; the maximum sensitivity calculated from the derivative of this function was about 6.2 nm/mV (Fig. 3a). The maximum peak-topeak response shown in the example was 623 nm. The largest peak-topeak response observed among the six cells examined was 832 nm (Supplementary Videos 1,2). We also examined the frequency response of the voltage-evoked bundle motion between 50 and 1,000 Hz using sinusoidal voltage bursts (Fig. 4c). Apparently, large bundle motions were still present at 1,000 Hz. The frequency response of the bundle motion was similar to that of OHC somatic motility measured under the whole-cell voltage-clamp condition30. Finally, we attempted to quantify the relation between the bundle motion and somatic motility of OHCs. Since the bundle motion was measured in the coil preparation, where OHCs were loaded by neighboring OHCs and supporting cells, it was necessary to measure the change in OHC length under similar conditions. We measured the change in OHC length using a gerbil hemicochlear preparation31, which allowed us to measure motions of the cuticular plate and the hair bundle as a result of somatic motility from the same cells. The motion of the reticular lamina was measured in a previous study using an isolated cochlear preparation of the guinea pig32. Since the magnitude of reticular lamina motion depends on where the patch electrode holds the cells27, we chose to approach the basolateral

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DISCUSSION Active hair-bundle motions are likely responsible for mechanical amplification of low-amplitude signals in non-mammals, since hair cells in these species do not possess somatic motility33. There is already evidence for either somatic motility or hair-bundle mechanisms in mammals. According to one recent study using a semi-intact cochlear preparation of adult gerbils, nonlinear amplification depends on the

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Figure 5 Relationship between OHC somatic motility and hair-bundle motion. (a) Motions of the reticular lamina as a result of somatic motility of an apical OHC when stimulated with voltage steps. The measurement was taken from a 30-d-old gerbil hemicochlea with the TM detached from the OHC hair bundle. The cell was held at 70 mV under whole-cell voltage-clamp. The patch electrode made contact with the basolateral membrane just above the nucleus of the cell. Movement was measured by the photodiode technique. Upward deflections in the trace represent depolarization. The response was filtered at 1,200 Hz. (b) Steady-state response from a was fitted with a second-order Boltzmann function (filled circles with solid line) and a slope function (solid line) was obtained as the derivative of the Boltzmann function. The bundle motion associated with somatic motility was also measured from the same cell, using the photodiode technique. Steady-state response was obtained and plotted in b. The response was also fitted with a second-order Boltzmann function (open circles with dashed line) and a slope function (dashed line) was obtained as the derivative of the Boltzmann function. (c) Bundle motion as a function of somatic motility. The magnitude of bundle motion is about one-half of that of somatic motility.


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ARTICLES flow of calcium current through the mechanoelectrical transducer channel18. Another study shows that hair bundles of rat OHCs can produce a large force linked to adaptation of the mechanotransducer channels19. Such force can be fed back to the basilar membrane and could thereby amplify basilar membrane vibration6,7. Although the force generated by the hair bundle is almost 20- to 100-fold greater than that predicted by the gating-spring model for mammalian hair cells34, such force is approximately 5 to 10 times less than the force produced by OHC somatic motility (about 3–5 nN)25. The force production based on mechanotransducer channels is also accompanied by a change in stiffness of the bundle19. It is theoretically possible to construct a cochlear amplifier with an in vivo feedback pathway based on ciliary stiffness change35. Our work demonstrates significant hair-bundle motions evoked by OHC electromotility. Yet, in the absence of electromotility (that is, in neonatal gerbil OHCs before the onset of somatic motility and in prestin-knockout mice), ciliary rotation linked to adaptation of the mechanotransducer channels was below the resolution limit of our system (B5 nm). The lack of bundle motion under the condition studied was not due to some malfunction of the mechanotransduction apparatus, since large mechanoelectrical transducer currents were observed. Although we can not rule out small mechanotransducer channel–based bundle motion below the resolution limit of our measurement system, the V-shaped or W-shaped staircase structure of the hair bundle with strong side-links connecting individual stereocilia is not well suited for ciliary rotation. The motility-associated bundle motion was large (over 800 nm), approximately ten times (20 dB) larger than the transducer channel–based ciliary rotation observed in nonmammalian hair cells8,9,13–15. The maximal sensitivity of the bundle motion was approximately 6.5 nm/mV, roughly one-half of that of OHC somatic motility. Voltage-evoked bundle motion of IHCs was reported in a recent study18 using a two-chamber preparation. The IHC bundle motion observed was on the order of 13 nm. In our view, the possibility that such motion may have been mediated by OHC motility can not be completely ruled out. The motility-associated response we observed overshadows transducer channel–based mechanisms in OHCs. It is not fully established how OHC length changes result in bundle motion. However, tilting of the cuticular plate during motility has been reported to occur at high frequencies in coil preparations36. Rotation of the reticular lamina as a result of OHC motility is also seen in situ32. Modeling work also supports the existence of reticular lamina rotation in response to OHC length change37. The bundle motion of unstimulated OHCs as a result of the somatic motility of adjacent OHCs provides direct evidence that tilting of the cuticular plate within the reticular lamina and rotation of the reticular lamina along its fulcrum at the pillar heads during OHC length change could produce bundle movement. It has been proposed that OHC somatic motility3–5 and stiffness change38 are responsible for cochlear amplification in mammals. According to some theories, the force generated by OHC somatic motility amplifies the motion of the basilar membrane–organ of Corti complex39,40. These theories are supported by several observations, such as somatic motility upon ciliary deflection41, electromotility-driven movements of the reticular lamina and basilar membrane in situ32, and findings from experiments using prestin-knockout mice5,26. It has not yet been fully determined how active somatic movements of OHCs excite IHCs. Coupling OHC motility to basilar membrane and movements of the reticular lamina in an appropriate phase would certainly boost their displacements. In addition, the bundle motion associated with OHC somatic motility may provide a mechanism for OHC motility to boost the input to

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IHCs. The V-shaped or W-shaped staircase structure of the OHC stereocilia is well suited for promoting mechanical coupling between the TM and reticular lamina, which can transfer motility-driven hairbundle motion into the radial motion of the TM (data not shown). Such motion could amplify mechanical input to the IHC by increasing fluid motion in the gap between the TM and reticular lamina. This fluid flow stimulates the freestanding IHC cilia42. It is conceivable that fluid pumping by Hensen’s stripe onto the closely apposed IHC cilia is the excitatory mechanism. It is therefore conceivable that the motilityassociated hair-bundle motion may be part of cochlear amplification in mammals. Under this scheme, OHC somatic motility not only boosts basilar membrane vibration but also drives the hair-bundle motion, which can interact with the TM. Since the bundle motion is associated with somatic motility of OHCs, this scheme is consistent with studies using prestin-knockout mice5,26, which support motility-based amplification as the dominant mechanism in the mammalian cochlea. The principal argument against somatic motility as the amplifier is that the low-pass filter characteristics of OHC membranes attenuate receptor potentials at high frequencies. Therefore, the receptor potentials would be too small to drive somatic motility6,7. It has been proposed, however, that extracellular potential changes within the organ of Corti could drive OHC motility at high frequencies43. These extracellular potentials are not filtered by the membrane. Measurements of basilar membrane vibration and extracellular potentials in the guinea pig cochlea at high frequencies provide evidence that those extracellular potentials can indeed drive OHC motors at high frequencies44–46. Extracellular OHC voltage responses at threshold are large and sharply tuned, and they are at least 100 mV at threshold at 18 kHz45,46. Therefore, the potentials could be large enough to drive OHC motility. Furthermore, theoretical modeling also indicates that the piezoelectric property of OHCs can markedly increase the frequency response of OHCs47,48. Finally, characteristics of the mechanical load of OHCs within the organ of Corti may also improve the frequency response of OHCs49. In summary, we have demonstrated that mammalian OHCs show large hair-bundle motion that is dependent on OHC somatic motility. Such bundle motion may boost the mechanical input to the IHC stereocilia through the radial motion of the TM. While forwardtransduction-based hair-bundle motion may underlie cochlear amplification in non-mammals, mammals have evolved OHC somatic motility to boost basilar membrane vibration and to drive the bundle motion, thereby providing mechanical amplification of low-level signals in the mammalian inner ear. METHODS Care and use of the animals in this study were approved by NIH grants and the Animal Care and Use Committee of Creighton University in Omaha, Nebraska. Preparation of the coil. Gerbils ranging in age from 4 to 35 DAB and prestinknockout mice ranging in age from 4 to 7 weeks after birth were used. The animals were decapitated following a lethal dose of sodium pentobarbital (200 mg/kg, intraperitoneal injection). After the cochlear wall was removed, the basilar membrane–organ of Corti complex was unwrapped from the modiolus, from the basal turn to the apical turn, as described elsewhere50. The coil was digested in L-15 medium (Invitrogen), containing 136 mM NaCl, 5.8 mM NaH2PO4, 5.4 mM KCl, 1.4 mM CaCl2, 0.9 mM MgCl2, 0.4 mM MgSO4 and 10 mM HEPES-NaOH (pH 7.4, 300 mmol/l), plus 0.06 mg/ml protease (type XXIV; Sigma). After the TM was lifted off to expose the hair bundles, the tissue was transferred to the experimental chamber. The coil was firmly attached to the bottom of the chamber by the weight of two thin platinum rods (0.5 mm in diameter), with one of their ends anchored in two small droplets of vacuum

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ARTICLES grease on the bottom of the chamber. The tissue was mounted with the hair bundle facing upward toward the water-immersion objective. Details for preparing gerbil hemicochlea are given elsewhere31. The coil preparation (or hemicochlea) was bathed in L-15 medium in an experimental chamber mounted on the stage of an upright microscope (Leica DMLFSA) with Burleigh platform (Giblator). Quality control of coils and hemicochlea was based on the physical appearance of the preparation31. In either preparation, OHCs became swollen in less than 25 min after the organ of Corti was exposed to the extracellular medium. Therefore, all the data presented were collected within 20 min. Experiments were done at room temperature (22 ± 2 1C). Whole-cell voltage-clamp. The coil preparation and the hemicochlea were both bathed in the L-15 medium. The pipette solution contained 140 mM CsCl (or KCl), 0.1 mM CaCl2, 3.5 mM MgCl2, 2.5 mM MgATP, 5 mM EGTA-KOH, 5 mM HEPES-KOH (pH 7.4 and 300 mmol/l). In some experiments, the ciliary area was perfused with artificial endolymph (150 mM KCl, 25 mM CaCl2, 1 mM sodium pyruvate, 5 mM D-glucose and 10 mM K2HPO4 at pH 7.35 and 300 mmol/l) through a second pipette positioned approximately 20–30 mm away from the hair bundle, as described previously for turtle hair cell preparation13. The rate of perfusion and the distance of the perfusion pipette from the recording site were adjusted to ensure that the perfusion from this second pipette did not mechanically stimulate the bundle. The bath was perfused with fresh medium at a rate of 0.5 ml/min. Patch pipette resistance was 3–4 MO. Recordings were made in whole-cell voltage-clamp mode, using an Axopatch 200B patch-clamp amplifier (Axon Instruments). Series resistance was 8–14 MO, and about 75% of series resistance was compensated. The uncompensated voltage error was normally less than 4 mV at the largest voltage levels used since the membrane conductances were blocked. Currents were filtered at 2 kHz, and digitized at 10 kHz with a 16-bit A/D converter (Digidata 1322A) and pClamp 9.2 software (Axon Instruments). The cells were held at 70 mV. To measure mechanotransducer currents in the coil preparation, a fluid-jet technique was used to deflect the hair bundle. The home-made fluid jet was controlled by a Burleigh driver/ amplifier (PZ-150M). Sinusoidal voltage commands (102 Hz) were used to drive the fluid jet. The fluid jet was positioned approximately 20–30 mm away from the stereocilia. Measurements of hair-bundle motion. The preparation was obliquely illuminated by a 100-W lamp. The hair bundle was imaged using a 63 waterimmersion objective (Leica) and magnified by an additional 20 relay lens. The magnified image of the tip of the bundle was then split into two paths: one path projected onto the photodiode (Hamamatsu) through a slit and another projected onto a CCD camera so that the bundle could be viewed at all times on a television monitor. During measurements, the magnified image of the tip of the bundle was positioned near the edge of the slit. The slit was rotatable, based on the orientation of the bundle. The output signal from the photodiode amplifier represented the motion of the tip of the hair bundle. The photodiode system had a 3-dB cutoff frequency of 1,200 Hz. The signal was then amplified by a 60-dB fixed-gain dc-coupled amplifier. The amplified signal was then lowpass filtered (400 or 1,200 Hz) before being delivered to one of the A/D inputs of a Digidata 1322A acquisition board (Axon Instruments) in a Microsoft Windows–based computer. The measurement system was capable of measuring bundle tip motions down to about 5 nm with 100 averages. Calibration of bundle motion was obtained by moving the slit a known amount (1 mm) using a piezo driver attached to the slit50. To measure the motions of hair bundle and reticular lamina in the hemicochlea, we used a preparation in which the TM was detached from the OHC hair bundles. In this preparation, the hair bundle of OHCs is clearly visible on the cuticular plate and its motion is easy to measure under high magnification. We measured the hair-bundle motion and reticular lamina motion as described above, using the photodiode technique. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS This work was supported by grants R01 DC 006496 and R21 DC 006039 to D.Z.Z.H. from the National Institutes on Deafness and Other Communicative Disorders (NIDCD). We would like to thank P. Dallos,


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S. Neely, M.A. Cheatham and R. Hallworth for many helpful discussions and comments on an earlier draft of the manuscript. We thank J. Zuo for providing the prestin-knockout mice. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 31 May; accepted 28 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Dallos, P. The active cochlea. J. Neurosci. 12, 4575–4585 (1992). 2. Santos-Sacchi, J. New tunes from Corti’s organ: the outer hair cell boogie rules. Curr. Opin. Neurobiol. 13, 459–468 (2003). 3. Brownell, W.E., Bader, C.R., Bertrand, D. & de Ribaupierre, Y. Evoked mechanical responses in isolated cochlear outer hair cells. Science 227, 194–196 (1985). 4. Kachar, B., Brownell, W.E., Altschuler, R. & Fex, J. Electrokinetic shape changes of cochlear outer hair cells. Nature 322, 365–368 (1986). 5. Liberman, M.C. et al. Prestin is required for outer hair cell electromotility and the cochlear amplifier. Nature 419, 300–314 (2002). 6. Hudspeth, A.J. Mechanical amplification of stimuli by hair cells. Curr. Opin. Neurobiol. 7, 480–486 (1997). 7. Fettiplace, R., Ricci, A.J. & Hackney, C.M. Clues to the cochlear amplifier from the turtle ear. Trends Neurosci. 24, 169–175 (2001). 8. Crawford, A.C. & Fettiplace, R. The mechanical properties of ciliary bundles of turtle cochlear hair cells. J. Physiol. (Lond.) 364, 359–379 (1985). 9. Ru¨sch, A. & Thurm, U. Spontaneous and electrically induced movements of ampullary kinocilia and stereovilli. Hear. Res. 48, 247–263 (1990). 10. Martin, P. & Hudspeth, A.J. Active hair-bundle movements can amplify a hair cell’s response to oscillatory mechanical stimuli. Proc. Natl. Acad. Sci. USA 96, 14306– 14311 (1999). 11. Howard, J. & Hudspeth, A.J. (1987) Mechanical relaxation of the hair bundle mediates adaptation in mechanoelectrical transduction by the bullfrog’s saccular hair cell. Proc. Natl. Acad. Sci. USA 84, 3064–3068 (1987). 12. Benser, M.E., Marquis, R.E. & Hudspeth, A.J. Rapid, active hair bundle movements in hair cells from the bullfrog’s sacculus. J. Neurosci. 16, 5629–5643 (1996). 13. Ricci, A.L., Crawford, A.C. & Fettiplace, R. Active hair bundle motion linked to fast transducer adaptation in auditory hair cells. J. Neurosci. 20, 7131–7142 (2000). 14. Assad, J.A., Hacohen, N. & Corey, D.P. Voltage dependence of adaptation and active bundle movement in bullfrog saccular hair cells. Proc. Natl. Acad. Sci. USA 86, 2918–2922 (1989). 15. Bozovic, D. & Hudspeth, A.J. Hair-bundle movements elicited by transepithelial electrical stimulation of hair cells in the sacculus of the bullfrog. Proc. Natl. Acad. Sci. USA 100, 958–963 (2003). 16. Gillespie, P.G. & Corey, D.P. Myosin and adaptation by hair cells. Neuron 19, 955–958 (1997). 17. Holt, J.R. et al. A chemical-genetic strategy implicates myosin-1c in adaptation by hair cells. Cell 108, 371–381 (2002). 18. Chan, D.K. & Hudspeth, A.J. Ca(2+) current-driven nonlinear amplification by the mammalian cochlea in vitro. Nat. Neurosci. 8, 149–155 (2005). 19. Kennedy, H.J., Crawford, A.C. & Fettiplace, R. Force generation by mammalian hair bundles supports a role in cochlear amplification. Nature 433, 880–883 (2005). 20. Kros, C.J., Ru¨sch, A. & Richardson, G.P. Mechano-electrical transducer currents in hair cells of the cultured neonatal mouse cochlea. Proc. Biol. Sci. 249, 185–193 (1992). 21. Kennedy, H.J., Evans, M.G., Crawford, A.C. & Fettiplace, R. Fast adaptation of mechanoelectrical transducer channels in mammalian cochlear hair cells. Nat. Neurosci. 6, 832–836 (2003). 22. He, D.Z.Z., Jia, S.P. & Dallos, P. Mechanoelectrical transduction of outer hair cells studied in a gerbil hemicochlea. Nature 429, 766–770 (2004). 23. He, D.Z.Z., Evans, B.N. & Dallos, P. First appearance and development of electromotility in neonatal gerbil outer hair cells. Hear. Res. 78, 77–90 (1994). 24. Ge´leóc, G.S.G. & Holt, J.F. Developmental acquisition of sensory transduction in hair cells of the mouse inner ear. Nat. Neurosci. 6, 1019–1020 (2003). 25. Zheng, J. et al. Prestin is the motor protein of cochlear outer hair cells. Nature 405, 149–155 (2000). 26. Cheatham, M.A., Huynh, K.H., Gao, J., Zuo, J. & Dallos, P. Cochlear function in prestin knockout mice. J. Physiol. (Lond.) 560, 821–830 (2004). 27. Mammano, F., Kros, C.J. & Ashmore, J.F. Patch clamped responses from outer hair cells in the intact adult organ of Corti. Pflugers Arch. 430, 745–750 (1995). 28. Zhao, H.B. & Santos-Sacchi, J. Auditory collusion and a coupled couple of outer hair cells. Nature 399, 359–362 (1999). 29. Santos-Sacchi, J. Asymmetry in voltage-dependent movements of isolated outer hair cells from the organ of Corti. J. Neurosci. 9, 2954–2962 (1989). 30. Santos-Sacchi, J. On the frequency limit and phase of outer hair cell motility: effects of the membrane filter. J. Neurosci. 12, 1906–1916 (1992). 31. Richter, C.P., Evans, B.N., Edge, R. & Dallos, P. Basilar membrane vibration in the gerbil hemicochlea. J. Neurophysiol. 79, 2255–2264 (1998). 32. Mammano, F. & Ashmore, J.F. Reverse transduction measured in the isolated cochlea by laser Michelson interferometry. Nature 365, 838–841 (1993). 33. He, D.Z.Z. et al. Chick hair cells do not exhibit voltage-dependent somatic motility. J. Physiol. (Lond.) 546, 511–520 (2003).

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ARTICLES 34. van Netten, S.M. & Kros, C.J. Gating energies and forces of the mammalian hair cell transducer channel and related hair bundle mechanics. Proc. Biol. Sci. 267, 1915–1923 (2000). 35. McMullen, T.A. & Mountain, D.C. Model of dc potentials in the cochlea: effects of voltage-dependent cilia stiffness. Hear. Res. 17, 127–141 (1985). 36. Reuter, G., Gitter, A.H., Thu¨rm, U. & Zenner, H.P. High frequency radial movements of the reticular lamina induced by outer hair cell motility. Hear. Res. 60, 236–246 (1992). 37. Dallos, P. Organ of Corti kinematics. J. Assoc. Res. Otolaryngol. 4, 416–421 (2003). 38. He, D.Z.Z. & Dallos, P. Somatic stiffness of cochlear outer hair cells is voltagedependent. Proc. Natl. Acad. Sci. USA 96, 8223–8228 (1999). 39. Neely, S.T. & Kim, D.O. A model for active elements in cochlear biomechanics. J. Acoust. Soc. Am. 79, 1472–1480 (1986). 40. de Boer, E. Mechanics of the cochlea: modeling efforts. in The Cochlea (eds. Dallos, P., Popper, A.N. & Fay, R.R.) 258–317 (Springer-Verlag, New York, 1996). 41. Evans, B.N. & Dallos, P. Stereocilia displacement induced somatic motility of cochlear outer hair cells. Proc. Natl. Acad. Sci. USA 90, 8347–8351 (1993). 42. Dallos, P., Billone, M.C., Durrant, J.D., Wang, C. & Raynor, S. Cochlear inner and outer hair cells: functional differences. Science 177, 356–358 (1972).

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43. Dallos, P. & Evans, B.N. High-frequency motility of outer hair cells and the cochlear amplifier. Science 267, 2006–2009 (1995). 44. Fridberger, A. et al. Organ of Corti potentials and the motion of the basilar membrane. J. Neurosci. 24, 10057–10063 (2004). 45. Ko¨ssl, M. & Russell, I.J. The phase and magnitude of hair cell receptor potentials and frequency tuning in the guinea pig cochlea. J. Neurosci. 12, 1575–1586 (1992). 46. Murugasu, E. & Russell, I.J. The effect of efferent stimulation on basilar membrane displacement in the basal turn of the guinea pig cochlea. J. Neurosci. 16, 325–332 (1996). 47. Spector, A.A., Brownell, W.E. & Popel, A.S. Effect of outer hair cell piezoelectricity on high-frequency receptor potentials. J. Acoust. Soc. Am. 113, 453–461 (2003). 48. Weitzel, E.K., Tasker, R. & Brownell, W.E. Outer hair cell piezoelectricity: frequency response enhancement and resonance behavior. J. Acoust. Soc. Am. 114, 1462–1466 (2003). 49. He, D.Z.Z. Mechanical responses of cochlear outer hair cells. in Biophysics of the Cochlea (ed. Gummer, A.W.) 181–184 (World Scientific, Singapore, 2003). 50. He, D.Z.Z. Relationship between the development of outer hair cell electromotility and efferent innervation: a study in cultured organ of Corti of neonatal gerbils. J. Neurosci. 17, 3634–3643 (1997).

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A deafness mutation isolates a second role for the tectorial membrane in hearing P Kevin Legan1, Victoria A Lukashkina1, Richard J Goodyear1, Andrei N Lukashkin1, Kristien Verhoeven2, Guy Van Camp2, Ian J Russell1 & Guy P Richardson1 a-tectorin (encoded by Tecta) is a component of the tectorial membrane, an extracellular matrix of the cochlea. In humans, the Y1870C missense mutation in TECTA causes a 50- to 80-dB hearing loss. In transgenic mice with the Y1870C mutation in Tecta, the tectorial membrane’s matrix structure is disrupted, and its adhesion zone is reduced in thickness. These abnormalities do not seriously influence the tectorial membrane’s known role in ensuring that cochlear feedback is optimal, because the sensitivity and frequency tuning of the mechanical responses of the cochlea are little changed. However, neural thresholds are elevated, neural tuning is broadened, and a sharp decrease in sensitivity is seen at the tip of the neural tuning curve. Thus, using TectaY1870C/1 mice, we have genetically isolated a second major role for the tectorial membrane in hearing: it enables the motion of the basilar membrane to optimally drive the inner hair cells at their best frequency.

The organ of Corti, the mammalian organ of hearing, contains two sensory cell types, the inner and outer hair cells (IHCs and OHCs, respectively), that are sandwiched between two sheets of extracellular matrix, the basilar and tectorial membranes. Sound-induced vibrations of the basilar membrane are detected and transduced by the hair cells, and the resultant electrical signals are transmitted to the brainstem via the cochlear ganglion. The OHCs are mainly innervated by efferent nerve fibers descending from the CNS. They sit directly over the basilar membrane, and their sensory hair bundles are imbedded in the lower surface of the tectorial membrane1. The OHCs are electromotile2 and act as sensory-effector cells that amplify the motion of the basilar membrane at low sound pressure levels and compress it at high levels3–5. The IHCs are extensively innervated by afferent fibers from the cochlear ganglion6 and act primarily as receptors. They are located near the limbal edge of the basilar membrane, and their hair bundles are not directly coupled to the tectorial membrane7. The tectorial membrane is an extracellular matrix with a unique structure1,8. It contains three different types of collagen and three noncollagenous glycoproteins that are expressed at high levels only in the inner ear: a-tectorin, b-tectorin and otogelin9–12. Mutations in a-tectorin are known to cause non-syndromic hereditary hearing loss13. A number of roles have been suggested for the tectorial membrane in hearing14–17, but its precise function in this process has remained relatively obscure. In mice homozygous for a targeted deletion (DENT) in the gene encoding a-tectorin (Tecta), the tectorial membrane lacks all non-collagenous components and is completely detached from the surface of the organ of Corti and the spiral limbus18. The basilar membrane remains tuned in the TectaDENT/DENT mouse but is 35 dB less sensitive18. A comparison of OHC responses in wild-type and

TectaDENT/DENT mice has shown that the tectorial membrane normally allows the OHCs to bias their hair bundles so that they can transduce low-level signals in the most sensitive region of their operating range, and it ensures that the hair bundles of the OHCs respond to basilar membrane displacement rather than basilar membrane velocity18. The tectorial membrane therefore has a key role in cochlear amplification in enabling the OHCs to deliver feedback to the basilar membrane with the appropriate gain and timing. Measurements of basilar membrane motion in wild-type and TectaDENT/DENT mice18 confirm previous data19,20 showing that the tectorial membrane is resonant. For any location along the length of the cochlea the tectorial membrane is tuned to a frequency half an octave below the characteristic frequency of the basilar membrane, the frequency to which the basilar membrane is most sensitive18–21. At the characteristic frequency of the basilar membrane, the tectorial membrane therefore acts as an inertial mass against which the hair bundles can react. As yet, it is not known how the hair bundles of the IHCs are stimulated by basilar membrane vibration. They may be driven by a number of sources of excitation that vary in their contribution with frequency and level22. These include a combination of frictional and inertial fluid movements in the narrow space between the tectorial membrane and the reticular lamina, the apical surface of the organ of Corti that vibrates in response to basilar membrane motion. For sound stimuli above about 1 kHz, the hair bundles of IHCs are driven by inertial forces23–25, as are the freestanding hair bundles in the hearing organ of the lizard, which are driven by vibrations of the reticular lamina26. In the mammalian cochlea, the fluid movements that drive the IHCs are controlled by differential shear between the tectorial membrane and the reticular lamina15,17. The tectorial membrane may

1School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG, UK. 2Medical Genetics Centre, Dept. of Biomedical Sciences, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium. Correspondence should be addressed to I.J.R. ([email protected]) or G.P.R. ([email protected]).



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Figure 1 Targeted integration into the mouse Tecta gene. (a) The targeting construct, the 3¢ region of the Tecta gene spanning exons 15 to 23, and the targeted locus after the first (‘Hit’) and second (‘Run’) rounds of homologous recombination. S, SacI; Xh, XhoI; X, XbaI. (b) Southern blots of SacI-digested genomic DNA from wild-type (W), hit (H) and run (R) embryonic stem cell lines hybridized with probes A or B. Probes A and B hybridize to a 15.4-kb band from the wild-type allele. Probe A hybridizes to a 5.8-kb band from the targeted allele in both the hit (H) and the run (R). Probe B hybridizes to a 16.0-kb band (not resolved from the 15.4 kb band) in the hit (H) and a 9.7 kb band in the run (R). (c) Sequence analysis of the Y1870C allele. The heterozygote carries both A and G at position 5876, confirming the mutation is correctly introduced. (d) PCR of TectaY1870C mice. In Tecta+/+ mice a single product of 403 bp is amplified that is not cut by EcoICRI. In TectaY1870C/+ mice, the product from the mutant allele is cut by EcoICRI, and three bands are seen, a wild-type band of 403 bp and mutant fragments of 307 and 96 bp. In TectaY1870C/Y1870C mice, products from both alleles are cut by EcoICRI, giving bands of 307 and 96 bp.

sharpen the input to the IHCs16, and differences have been observed in the tuning curves of the basilar membrane and the OHCs and those of IHCs and their afferent nerve fibers27,28. The relative contributions of the tectorial membrane and the reticular lamina to IHC excitation remain, however, to be determined. In this study we describe the phenotype of a transgenic mouse with a missense mutation (Y1870C) in Tecta. This mutation is the cause of a moderate-to-severe, dominantly inherited, prelingual hearing impairment in an Austrian family13. The phenotype of the TectaY1870C/+ mouse is distinctly different from that of the TectaDENT/DENT mouse. Although the tectorial membrane shows a number of structural defects in the TectaY1870C/+ mouse, it remains attached to the organ of Corti. Basilar membrane tuning and sensitivity are only mildly affected, but the tuning properties of the IHCs’ neural output are substantially altered both in terms of shape and of sensitivity. The TectaY1870C/+ mouse therefore demonstrates how the tectorial membrane has an additional critical role in hearing in ensuring that the IHCs are excited maximally at their best frequency. RESULTS Two rounds of homologous recombination in embryonic stem cells, a ‘hit’ to provide a 5¢ duplication followed by a ‘run’ to remove the original locus, were used to introduce the single base change (A5876G) into exon 18 of the Tecta locus (Fig. 1a). Integration of the duplicate and its resolution under gancyclovir selection were monitored by Southern blotting (Fig. 1b). The presence of the desired mutation was confirmed by sequencing (Fig. 1c). F1 progeny heterozygous for the mutation were detected by PCR amplification followed by restriction digestion (Fig. 1d). Tectorial membrane is disrupted in TectaY1870C/+ mice The tectorial membrane is a spiral, ribbon-like sheet of matrix that runs along the length of the cochlea. It adheres to the apical surface of the spiral limbus, stretches across the spiral sulcus and lies over the organ of

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Corti, attaching to the tips of the OHCs’ hair bundles. The effects of the Tecta Y1870C mutation illustrated in Figure 2a–l are representative of the morphology observed in 11 wild-type, ten TectaY1870C/+ and three TectaY1870C/Y1870C mice. A number of structural abnormalities were observed in the TectaY1870C/+ mouse. The limbal attachment zone of the tectorial membrane was markedly reduced in thickness, and the lower surface into which the OHC hair bundles are imbedded (Kimura’s membrane) was separated from the main body of the tectorial membrane. The marginal band (a dense thickening running around the peripheral margin) and Hensen’s stripe (a ridge that runs longitudinally along the underside of the tectorial membrane adjacent and parallel to the bundles of the IHCs) were absent, and there were large holes visible within the main body of the matrix (compare Fig. 2a,b). Notably, there was considerable enlargement of the subtectorial space in the vicinity of the IHC hair bundles (Fig. 2a,b). In mice homozygous for the mutation, the tectorial membrane was completely detached from the surface of the organ of Corti and was found associated with Reissner’s membrane and/or the stria vascularis (Fig. 2c). The morphological phenotype of the TectaY1870C/Y1870C mouse is very similar to that previously described for the TectaDENT/DENT mouse18. a-tectorin and two other non-collagenous proteins of the tectorial membrane, b-tectorin and otogelin, were all detected in heterozygous TectaY1870C/+ mice (Fig. 2e,h,k), although the levels of otogelin, a component normally concentrated in the sulcal region, appeared to be reduced (Fig. 2k). a-tectorin and traces of b-tectorin were detected in the detached tectorial membranes of TectaY1870C/Y1870C mice, but otogelin was absent (Fig. 2f,i,l). The ultrastructural characteristics of the tectorial membranes in wild-type and TectaY1870C/+ mice are shown in Figure 3. The whip-like nature of Kimura’s membrane, its separation from the main body of the tectorial membrane and loss of the marginal band in TectaY1870C/+ mice were clearly visible at low magnification (Fig. 3a,b). Clearly defined striated-sheet matrix composed of cross-linked light and dark-staining filaments was visible in the region of the tectorial membrane overlying

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b

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d

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f

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h

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α-tectorin β-tectorin

j

k

l

Otogelin


Toluidine blue

a

the inner and outer hair cells in both wild-type and TectaY1870C/+ mice (Fig. 3c,d). In TectaY1870C/+ mice, however, striated-sheet matrix was not present in the sulcal zone (Fig. 3e,f). Instead, large clumps of dense staining material were visible and the collagen fibrils, rather than projecting radially across the tectorial membrane (Fig. 3e), were oriented almost perpendicular to its surface (Fig. 3f) and were seen erupting through its upper surface (Fig. 3g,h). The limbal zone of the tectorial membrane, a region where the non-collagenous matrix is normally dense and compacted, was extremely reduced in the TectaY1870C/+ mice, and only a few traces of electron-dense material were associated with the microvilli of the interdental cells (Fig. 3i,j). Hair bundle structure is normal in TectaY1870C/+ mice Scanning electron microscopy was used to examine the shape and structure of the hair bundles in the low- and high-frequency turns of the cochlea in wild-type and TectaY1870C/+ mice (Fig. 4a–d). No obvious differences were observed. Remnants of tectorial membrane were observed attached to some of the OHC hair bundles in TectaY1870C/+ mice, mainly those in the first row, but not on those of wild-type mice. These remnants provide evidence that the OHC hair bundles normally contact the tectorial membrane in the TectaY1870C/+ mouse and suggest that Kimura’s membrane is less firmly attached to the main body of the tectorial membrane than it is in wild-type mice, not detaching completely from the hair bundles when the tectorial membrane is removed during sample preparation. Normal mechanotransduction in OHCs of TectaY1870C/+ mice The cochlear microphonic recorded from the round window is dominated by the receptor current of basal-turn OHCs3,18,29. OHCs in this region are sensitive to frequencies above 45 kHz, and therefore the


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Figure 2 Light microscopic analysis of TectaY1870C mice. (a–c) Toluidine blue–stained, 1-mm-thick sections of the cochlear duct from Tecta+/+ (a), TectaY1870C/+ (b) and TectaY1870C/Y1870C (c) mice. Note the considerable reduction in the thickness of the limbal zone (LZ) of the tectorial membrane, the absence of a marginal band (MB) and Hensen’s stripe (HS), and detachment of Kimura’s membrane (arrowhead in b) in the TectaY1870C/+ mouse. In the TectaY1870C/Y1870C mouse, the tectorial membrane (arrow in c) is completely detached from the spiral limbus and the surface of the organ of Corti. Bars: 50 mm. (d–l) Cryosections of the cochlear duct from Tecta+/+ (d,g,j) TectaY1870C/+ (e,h,k) and TectaY1870C/Y1870C (f,i,l) mice stained with antibodies to a-tectorin (d,e,f), b-tectorin (g,h,i) and otogelin (j,k,l). Otogelin staining is seen in the sulcal region of the wild-type tectorial membrane (arrow in j) but is reduced in the sulcal region of the TectaY1870C/+ mouse (k) and absent from that of the TectaY1870C/Y1870C mouse (l). Bars: 50 mm.

cochlear microphonic recorded in response to much lower frequencies is due to receptor current that has not been subject to amplification. Thus, for frequencies well below the sensitive frequency range of the basal turn of the cochlea, the amplitude of these receptor currents, and hence the amplitude of the cochlear microphonic, is governed by the magnitude of the OHC transducer conductance and not by the amplification process. For a 4-kHz tone, the cochlear microphonic level functions were similar in TectaY1870C/+ and Tecta+/+ mice (Fig. 5a), indicating that sensory transduction by OHCs is not influenced by the changes in tectorial membrane structure caused by the TectaY1870C/+ mutation. Furthermore, at this frequency, the cochlear microphonics recorded from TectaY1870C/+ and Tecta+/+ mice were in phase (Fig. 5a, inset). Mechanical coupling between the stimulus and OHC hair bundles must therefore be very similar in TectaY1870C/+ and Tecta+/+ mice. This similarity is also reflected in the symmetry of the cochlear microphonics. The relation between the magnitude of the cochlear microphonic and sound pressure for unfiltered microphonics measured in response to low-level, 4 kHz tones showed the cochlear microphonic was almost perfectly symmetrical in both Tecta+/+ and TectaY1870C/+ mice (Fig. 5b). The Y1870C mutation has little effect on mechanical tuning OHCs are the source of amplification in the cochlea, and when they do not function optimally the sensitivity and frequency tuning of the cochlea becomes impaired. To determine if the OHCs in TectaY1870C/+ mice are operating as effective amplifiers, or if their interaction with the tectorial membrane and basilar membrane is in any way compromised, the frequency tuning response of the basilar membrane was observed. Iso-response tuning curves measured from the same cochlear region in Tecta+/+ and TectaY1870C/+ mice were very similar in form (Fig. 5c,d). The characteristic low-frequency peak (stars in Fig. 5c,d) that has been attributed to the frequency tuning of the tectorial membrane20 was seen in the tuning curves of both Tecta+/+ and TectaY1870C/+ mice. Measurements from Tecta+/+ (n ¼ 16) and TectaY1870C/+ (n ¼ 10) mice showed that frequency tuning curves of TectaY1870C/+ mice were on average 8 dB less sensitive at the characteristic frequency of the recording site than those of Tecta+/+ mice but were similar in other respects (Table 1).

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ARTICLES Figure 3 Ultrastructure of the tectorial membrane in TectaY1870C mice. (a–j) Transmission electron micrographs illustrating the ultrastructure of the tectorial membrane in Tecta+/+ (a,c,e,g,i) and TectaY1870C/+ mice (b,d,f,h,j). Regions shown are the lateral edge with the marginal band and Kimura’s membrane (a,b), the central core of the tectorial membrane overlying the organ of Corti (c,d), the core of the tectorial membrane in the region overlying the spiral sulcus (e,f), the upper surface of the membrane in the sulcal region with covernet fibrils (g,h) and the limbal zone (i,j). Inset in b is a magnified view of Kimura’s membrane showing the attachment site (arrow) for the tallest stereocilium of the first row OHC. Bars: 2 mm (a,b), 200 nm (c–f), 500 nm (g–j).

Otoacoustic emissions demonstrate mild loss in sensitivity Distortion product otoacoustic emissions (DPOAEs) recorded from the cochlea are closely associated with cochlear feedback and OHC motility at all primary tone levels30,31. DPOAE generation probably originates from the modulation of electrical current through the OHC mechanoelectrical transducer conductance32–34. DPOAE measurements are noninvasive and can be used to estimate the sensory amplification function of OHCs across the entire frequency range, unlike basilar membrane motion measurements, which are restricted because of laser access to one region of the cochlea. DPOAE measurements across the 5–60 kHz frequency range (Fig. 5e) demonstrated that the cochleae of TectaY1870C/+ mice were slightly less sensitive than those of Tecta+/+ mice. The average threshold across all frequencies was 45.87 7 0.63 dB SPL for TectaY1870C/+ mice (n ¼ 10) versus 32.38 7 0.75 dB SPL for Tecta+/+ mice (n ¼ 10), an average threshold increase of 13.49 dB SPL in TectaY1870C/+ mice. DPOAE threshold curves from TectaY1870C/+ mice were also significantly more variable (P ¼ 0.01, as measured by the mean 7 s.d. of the s.d.) than those from Tecta+/+ mice (5.58 7 2.03 dB SPL for TectaY1870C/+ mice versus 2.97 7 1.23 dB SPL for Tecta+/+ mice, n ¼ 59). DPOAE-grams recorded from TectaY1870C/+ mice were slightly smaller in magnitude (average decrease across all frequencies ¼ 10.21 dB SPL, with f1/f2 levels at 50/40 dB SPL, and 8.06 dB SPL, with f1/f2 levels at 70/60 dB SPL) and significantly more variable (P ¼ 0.01) than those recorded from Tecta+/+ mice (Fig. 5f). These differences indicate that there is only a mild reduction in the sensory amplification function of OHCs across the entire frequency range. Elevated neural response thresholds in TectaY1870C/+ mice The detection threshold for cochlear microphonics recorded from the round window is determined by the sensitivity of basal-turn OHCs to

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TectaY1870C/+

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the test tone frequency. The round-window neural response to a tone, the compound action potential (CAP), is, however, generated by the type I afferent fibers that innervate IHCs throughout the cochlea35. Thus the CAP threshold for a particular frequency represents the threshold sensitivity of the cochlear region tuned to that frequency36, but the cochlear microphonic threshold for a pure tone at a frequency outside the range of the basal turn will be higher than that of the CAP. As expected, the threshold of the round-window cochlear microphonic to a 22-kHz tone in Tecta+/+ mice was higher than that of the CAP (compare upper and middle trace of Fig. 6a). The cochlear microphonics recorded from Tecta+/+ and TectaY1870C/+ mice to a 22-kHz tone were similar in threshold (45 dB SPL), but the CAP threshold recorded from TectaY1870C/+ mice was much higher (70 dB SPL) than that recorded from Tecta+/+ mice (o20 dB SPL; Fig. 6a,b, upper and middle traces). The low-pass filtered round window recordings (Fig. 6a,b, middle traces) showed that the CAP was associated with a slow after-potential, a potential that is thought to be of neural origin and depends on the presence of the cochlear nucleus37. The concurrent appearance of this slow after-potential and the CAP in TectaY1870C/+ Figure 4 Hair bundle morphology in TectaY1870C mice. (a–d) Scanning electron micrographs illustrating the structure of sensory hair bundles in the apical (a,b) and basal (c,d) regions of the cochlea in Tecta+/+ (a,c) and TectaY1870C/+ mice (b,d). Arrows indicate the single row of IHC hair bundles; arrowheads indicate the three rows of OHC hair bundles. Bars: 5 mm.

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6 7 8 Time (ms)

20 30 40 50 60 70 80 Sound level dB SPL

0.05 –0.00 –0.05

–0.15 –0.10 –0.05 0.00 0.05 0.10 0.15

d

Tecta+/+ Threshold (dB SPL)

70 60 50 40 30

Sound pressure (Pa) 80

TectaY1870C/+

70 60 50 40 30 20

20 20 30 40 50 60 70 Stimulus frequency (kHz)

20 30 40 50 60 70 Stimulus frequency (kHz)

f

70

DPOAE level (dB SPL)

e

30 40 50 60 70 80 dB SP

–0.10 –0.15

60 50 40 30 20 10 0

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30 40 F2 kHz

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60 50 40 30 20 10 0 –10 –20

Wt5040 Wt7060 Tr5040 Tr7060

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30 40 F2 kHz

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mice at levels above 70 dB SPL indicates auditory information is reaching the vicinity of the cochlear nucleus when the auditory nerve is active and that afferent synaptic transmission and neural propagation in the auditory nerve are not impaired in TectaY1870C/+ mice. For frequencies between 5–30 kHz, the CAP threshold of the TectaY1870C/+ mouse (68.3 7 5.37 dB SPL, n ¼ 10) was on average 55 dB higher than the CAP threshold of the Tecta+/+ mouse (13.68 7 3.95 dB SPL, n ¼ 10; Fig. 6c). Broad and insensitive neural tuning in TectaY1870C/+ mice Simultaneous masking tuning curves from Tecta+/+ mice were measured using a 22-kHz probe tone at 30 dB SPL and from TectaY1870C/+

Figure 6 Cochlear microphonics, CAPs and neural masking tuning curves in TectaY1870C mice. (a,b) Cochlear microphonics (CM) and the tonic components (DC) of the cochlear voltage response recorded from the round window to 22-kHz tones, at the levels indicated, from Tecta+/+ (a) and TectaY1870C/+ (b) mice. Upper traces: unfiltered CM response, bandwidth 0–125 kHz. Middle traces: CM response filtered at 0–3 kHz. Lower traces: timing of tone bursts. DC, tonic components of the cochlear voltage response. CAP, compound action potential. SafP, slow after-potential. (c) CAP thresholds as a function of stimulus frequency for Tecta+/+ (red squares) and TectaY1870C/+ (blue squares) mice (mean 7 s.d. from ten Tecta+/+ and ten TectaY1870C/+ mice). (d) Simultaneous masking tuning curves of CAP recorded from the round window. Red squares: masking tuning curve from Tecta+/+ mice (frequency and level of probe: 22 kHz, 30 dB SPL), Q10 dB (bandwidth measured 10 dB from tip/probe frequency) ¼ 5.6. Blue squares: masking tuning curve from TectaY1870C/+ mice, (frequency and level of probe: 22 kHz, 70 dB SPL), Q10 dB ¼ 3.9. Black open circles: masking tuning curve from Tecta+/+ mice, (frequency and level of probe: 22 kHz, 70 dB SPL), Q10 dB ¼ 7.2. Arrow indicates notch at probe frequency in TectaY1870C/+ mice. Colored squares represent mean 7 s.d. for measurements from ten mice; black open circles represent mean 7 s.d. from four mice.


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mice using a 22-kHz probe tone at 70 dB SPL (n ¼ 10 for each genotype, Fig. 6d). The tuning curves measured from the Tecta+/+ mice were sensitive and sharply tuned, while those from the TectaY1870C/+ mice were about 60–70 dB less sensitive at the probe frequency and more broadly tuned. The masking tuning curves measured from the Tecta+/+ mice reached a clear minimum (peak of sensitivity) at 22 kHz, while those measured from the TectaY1870C/+ mice had a prominent notch of insensitivity at the probe frequency (arrow, Fig. 6d). Simultaneous masking tuning curves from Tecta+/+ mice resembled tuning curves that have been obtained from single-fiber recordings38 and had a steep high-frequency slope and a notch of insensitivity below the tip16. The tuning curves obtained from TectaY1870C/+ mice were at least 20 dB less sensitive on the low-frequency shoulder of the tuning curve; that is, at frequencies below the low-frequency notch of the Tecta+/+ mice. The tuning curves from the TectaY1870C/+ mice did not have the lowfrequency notch but had a high-frequency peak at 33 kHz, about one-half octave above the peak. The differences in the frequency tuning curves are not a consequence of the different masker levels. Increasing the probe level to 70 dB in Tecta+/+ mice caused a sharpening and a downward shift in peak frequency of the masking tuning curve (Fig. 6d), as has been previously demonstrated38. The increased

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Figure 5 Cochlear microphonics, basilar membrane tuning and DPOAEs in TectaY1870C mice. (a) Mean 7 s.d. of cochlear microphonic (CM) magnitude as a function of sound pressure level (SPL) for 4 kHz tones from four Tecta+/+ (red circles) and four TectaY1870C/+ mice (blue squares). Inset: CMs from Tecta+/+ (red) and TectaY1870C/+ mice (blue) in response to 4-kHz tones at 80 dB SPL. (b) CM magnitude as a function of sound pressure (in Pascals) for 4-kHz tones from Tecta+/+ (red) and TectaY1870C/+ (blue) mice. Inset: unfiltered CM from Tecta+/+ (red) and TectaY1870C/+ (blue) mice in response to 4-kHz tones at the SPLs indicated; vertical bars: 0.2 mV. (c,d) Basilar membrane displacement tuning curves for two Tecta+/+ mice (c, open and filled red circles; Q10 dB ¼ 10.0 and 10.2, respectively) and two TectaY1870C/+ mice (d, open and filled blue squares; Q10 dB ¼ 10.9 and 8.5, respectively). Black circles in b and d: post-mortem measurements. Threshold criterion is 0.2 nm; stars indicate low-frequency resonance. (e) DPOAE threshold curves (level of f2 required to produce a 2f1–f2 amplitude of 0 dB SPL) as a function of f2 frequency measured as mean 7 s.d. from ten Tecta+/+ mice (red circles) and ten TectaY1870C/+ mice (blue squares). (f) DPOAE-grams (level of 2f1–f2 DPOAEs as functions of F2 frequency) measured as mean 7 s.d. from ten Tecta+/+ mice (red circles) and ten TectaY1870C/+ mice (blue squares). Curves are identified by f1/f2 (dB SPL) levels and identity of mouse strain. Wt: Tecta+/+, Tr: TectaY1870C/+.

0.2 mV

4 kHz Tecta+/+ TectaY1870C/+

20 µV

b

80 70 60 50 40 30 20 10

CAP threshold (dB SPL)

c

dB SPL required to produce 0dB SPL DPOAE


a

CM magnitude (dB re 0.1 µV)

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ARTICLES Table 1 Frequency tuning curve characteristics of Tecta+/+ and TectaY1870C/+ mice


Parameter

Tecta+/+

TectaY1870C/+

Q10dB Threshold (dB SPL)

10.0 7 1.2 25.4 7 2.7

10.2 7 1.7 33.0 7 3.7

PM sens. change Fh/Fl

30.2 7 1.9 1.27 7 0.02

26.0 7 2.4 1.28 7 0.04

16

10

No. of animals

Q10dB: tip frequency/bandwidth, 10 dB from tip. PM sens. change: post-mortem change in sensitivity of the tuning curve tip. Fh/Fl: ratio of the frequencies of the tip of the tuning curve (Fh) and the low-frequency peak (Fl).

probe level had little effect on the low-frequency shoulder of the tuning curve and did not cause the appearance of a high-frequency peak (open circles, Fig. 6d). DISCUSSION The results of this study demonstrate how the tectorial membrane is critical in shaping the frequency tuning of the cochlea’s neural responses through its interaction with the IHCs, a role that can be genetically isolated in the TectaY1870C/+ mouse and is independent of its role in ensuring that feedback from the OHCs is delivered to the basilar membrane at the correct time and with optimal gain. Furthermore, the results show the structural and physiological basis for a type of non-syndromic human hereditary deafness resulting from a missense mutation in the human a-tectorin gene, TECTA. The TectaY1870C mutation is semi-dominant The TectaY1870C mouse demonstrates that the mutation is semi-dominant, with a heterozygous phenotype that is distinctly different from that of the homozygote and a homozygous phenotype that is nearly identical to that observed in TectaDENT/DENT mice with a functionally null deletion in Tecta18. The Y1870C mutation is located in the zona pellucida domain of a-tectorin, a domain that is required for the polymerization of extracellular proteins39 and that is defined by a large amino acid motif40 that is common to more than 100 structural proteins, including b-tectorin, the second major non-collagenous protein of the tectorial membrane11, and the proteins that form the zona pellucida surrounding the unfertilized egg: ZP1, ZP2 and ZP3 (ref. 41). A mutation in the corresponding conserved tyrosine residue of ZP2 (Y430C) considerably reduces the incorporation of the mutated ZP2 protein into the zona pellucida and prevents its secretion from transfected cell lines39. Although this suggests that the mutation may reduce the incorporation of a-tectorin into the tectorial membrane, heterozygous Tecta+/DENT mice have no defects in tectorial membrane structure and function18 and the heterozygous carriers of presumed null mutations in TECTA have normal hearing42, so it is unlikely that the structural anomalies observed in the tectorial membranes of TectaY1870C/+ mice are simply due to haploinsufficiency. Although it is unclear why the mutation causes loss of striated-sheet matrix specifically in the sulcal region of the tectorial membrane, this loss leads to a disruption in the organization of the collagen fibrils in this area, indicating that their normal, radial orientation within the tectorial membrane is critically dependent upon the matrix in which they are imbedded. Reticular lamina drives inner hair cells in Y1870C mutants The frequency tuning characteristics of the basilar membrane in Tecta+/+ and TectaY1870C/+ mice are similar in most respects, although

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a slight reduction in sensitivity is seen at the characteristic frequency in TectaY1870C/+ mice. The mechanical properties of the tectorial membrane in the TectaY1870C/+ mice are therefore sufficient to excite the OHCs and drive the cochlear amplifier. Weaker coupling between the tectorial membrane and OHC bundles, as a consequence of the partial detachment of Kimura’s membrane, may be the cause of the reduction in sensitivity and the variability observed in the DPOAE-grams of TectaY1870C/+ mice. In homozygous TectaDENT/DDENT mice where the tectorial membrane is completely detached from the organ of Corti, the hair bundles of IHCs and OHCs can be driven by vibrations of the reticular lamina, but there is a 30–40 dB loss in basilar membrane sensitivity18. In the TectaY1870C/+ mouse, basilar membrane sensitivity and OHC function are normal, but the increase observed in the subtectorial space in the IHC region and the lack of Hensen’s stripe implies that motion of the reticular lamina alone must drive the IHC hair bundles. The TectaY1870C/+ mouse therefore provides a unique opportunity to investigate the relative contributions of the tectorial membrane and the reticular lamina to IHC excitation in a cochlea where basilar membrane tuning is sharp and sensitive. Matrix drives inner hair cells at their best frequency Masker tuning curves recorded from TectaY1870C/+ mice differ from those of Tecta+/+ mice. The most notable feature is the presence of a sharp notch of insensitivity at the characteristic frequency. This loss in neural sensitivity (60–70 dB) at the characteristic frequency is similar in magnitude to the hearing impairment reported for the affected members of the Austrian DFNA8/12 family with the Y1870C a-tectorin mutation13. Two other major features of the masker tuning curves in TectaY1870C/+ mice are the absence of a notch of insensitivity on the lowfrequency shoulder and the appearance of a lobe of sensitivity on the high-frequency side. If basilar membrane responses were passively transmitted to the IHCs, a loss in coupling of the IHC bundles to the tectorial membrane caused by an enlargement of the subtectorial space would simply desensitize, and possibly broaden, the neural frequency tuning curves. The appearance of a sharp notch rather than a peak at the characteristic frequency in the neural tuning curves of TectaY1870C/+ mice indicates that IHC bundle movements, and hence reticular lamina movements, are specifically reduced at the characteristic frequency in TectaY1870C/+ mice. Basilar membrane vibrations, therefore, are not faithfully relayed to the IHCs through vibration of the reticular lamina over the entire frequency range, and the tectorial membrane must, in wild-type mice, normally dominate the input to IHCs at their characteristic frequency. These observations suggest the vibrations of the basilar membrane are normally transmitted to the IHCs by means of the tectorial membrane rather than through the reticular lamina at the characteristic frequency. Insensitive notches at frequencies below the characteristic frequency are a feature of neural tuning curves from fibers that innervate the highfrequency region of the cochlea43, and high-frequency plateaus have been described in the basilar membrane tuning curves from a variety of mammals44. The absence of a notch on the low-frequency side of the TectaY1870C/+ neural tuning curve and the appearance of a lobe on the high-frequency side can both be attributed to a failure in phase cancellation. Enlargement of the subtectorial space in the IHC region of the TectaY1870C/+ mouse will abrogate interactions between the tectorial membrane and the reticular lamina and prevent such phase cancellation. Low-frequency notches normally generated by phase cancellation will no longer be seen, and high-frequency lobes that are normally suppressed by cancellation will become visible. In the latter case, it should be noted that high-frequency plateaus or lobes are

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ARTICLES expected to become visible only in basilar membrane tuning curves measured from the basal, high-frequency region of the mouse cochlea at frequencies greater than 70 kHz, outside the limits of our recording system, so the tuning curves presented do not exclude the presence of high-frequency lobes in the basilar membrane vibrations. Shaping of IHC and neural tuning curves through phase cancellation of reticular lamina and tectorial membrane vibrations for frequencies above and below the characteristic frequency provides a mechanism for sharpening the frequency response of the neural tuning curves without incurring a temporal trade-off. In conclusion, these data from the TectaY1870C/+ mouse demonstrate the basis for a form of human hereditary deafness resulting from a missense mutation in a-tectorin. Furthermore, they show that the frequency tuning of IHCs and auditory nerve fibers is not a simple, direct consequence of the mechanical tuning of tone-evoked basilar membrane vibrations and their amplification by the OHCs but rather is due to the interaction of two mechanically complex structures, the reticular lamina and the tectorial membrane. Transverse vibrations of the basilar membrane, particularly at the characteristic frequency, are not faithfully transmitted to the IHCs simply through vibrations of the reticular laminar. In addition to ensuring the gain and timing of cochlear feedback are optimal, the tectorial membrane provides the principal drive to the IHCs at the characteristic frequency, interacting with the reticular lamina to shape the frequency responses of IHCs, and hence determining the sharpness and sensitivity of the neural tuning curves. METHODS Construction of the Tecta targeting vector. Clone MG492/2 was isolated from a mouse 129/SvEvBrd genomic DNA library in lFIX (Stratagene) and shown to span exons 15 to 19 of the Tecta gene. An 11-kb SacI fragment of MG492/2 was blunt end ligated into XhoI-cut pBluescript SK+. Two point mutations were introduced by in vitro mutagenesis, an A4G mutation at position 23 of exon 18, corresponding to the human A5610G mutation in DFNA8/12, and a G4C mutation at position 335 of intron 17, introducing a SacI site. The insert was fully sequenced on both strands to confirm only the desired mutations had been introduced. To construct the targeting vector, the HSVtk cassette was cut out of pTBPNS3 (ref. 45) by digestion with SacII and HindIII and the neoR cassette was cut out of pGKneopA with HindIII and XbaI, and both fragments were ligated into pBluescript SK+ cut with SacII and XbaI to create pHSVtk-neo. A 1.5-kb XbaI to XhoI fragment of MG492/2 was then ligated into XbaI/XhoIcut pHSVtk-neo. The resultant clone was cut with SacII and XhoI, and the fragment containing HSVtk, neoR and the 1.5-kb XbaI-XhoI fragment of MG492/2 was ligated into the SacII and XhoI sites of the mutagenized clone. The resulting targeting vector was extensively restriction mapped to confirm correct construction. Isolation of targeted embryonic stem cells. The targeting vector was linearized with XhoI and transfected into CCB embryonic stem cells by electroporation. After eight days of selection with geneticin, resistant colonies were picked, trypsinized and plated into individual wells of duplicate 96-well plates. Genomic DNA was prepared from each clone, digested with SacI and transferred to Hybond-N membranes (Amersham) by Southern blotting. Blots were probed with external probes 5¢ (probe A) and 3¢ (probe B) to the region targeted to identify correctly targeted integrants (‘Hits’). Probes were amplified by PCR using 83GF3 (5¢-CATGTGACAATGTGCACATC-3¢) with MG492-1351R (5¢-GACGTCATGGTGGAGCTGAG-3¢) for probe A, and maZPDF1 (5¢-TTA TGTGGCTGCATTTAACGAACTCAGGGT-3¢) with maZPDR2 (5¢-ATCAGA CTTCTGTAGCCAGA-3¢) for probe B. After gel purification, PCR products were random primer labeled with [a32P]dCTP and hybridized to the blots. To resolve integrants, targeted clones were cultured for 8 d under gancyclovir selection and resistant colonies were picked into individual wells of duplicate 96-well plates and grown to confluence. Genomic Southern blots were prepared and probed as described above to identify correctly resolved integrants (‘Runs’). One cell line was used to generate chimeric mice by microinjection of C57/BL6J


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blastocysts. All physiological and morphological data from wild-type and heterozygous animals were from F1 progeny on a 50:50 129SvEv:C57BL/6J genetic background. Genotyping. Founder mice and their offspring were genotyped by Southern blotting as described above. PCR products spanning exon 18 were amplified from genomic DNA prepared from Tecta+/+ and TectaY1870C/+ mice using primers E18seqF1 (5¢-TTCCATGCTGA TGTATTCTAGCCTC-3¢) and E18 seqR1 (5¢-CTACTCTGATGCTGCTAACCTTAGC-3¢) and directly sequenced. Routine genotyping of mice in the Y1870C mutant colony was performed by amplifying a 403-bp region flanking the G4C mutation at position 335 of intron 17, which introduces a SacI site, and digesting the PCR product with the isoschizomer EcoICRI. Genomic DNA was isolated from tail snips according to previously published reports46. Aliquots (2 ml) of tail DNA were added to PCR mixtures containing primers E18genoF1 (5¢-GACTTCCGTTGGCTCTCTTAT GCTTC-3¢) and E18genoR1 (5¢-GAGATAGCAGCAATGCCAGGTGAAC-3¢). Reactions were heated to 98 1C for 2 min and cycled through 98 1C for 15 s, 52 1C for 15 s, 72 1C for 30 s, for a total of 40 cycles. After the PCR, 1 unit of EcoICRI (Promega) was added and the reactions were digested at 37 1C overnight. PCR products were analyzed by 1.5% agarose, 1 TBE gel electrophoresis. Morphological analysis. Procedures for the preparation of cochlear tissues for light and electron microscopy were as described previously18. Antisera R9 and R7 (ref. 47) to chicken a- and b-tectorin were used at dilutions of 1:1,000 and 1:200, respectively, and an antiserum to recombinant mouse otogelin (a gift from C. Petit, Institut Pasteur) was used at 1:2,000. Homozygous TectaY1870C/Y1870C mice used for morphology were obtained by inbreeding heterozygous TectaY1870C/+ F1 mice. Physiological measurements. Mice, normally o3 months of age, were anesthetized with ketamine (0.12 mg/g body weight, intraperitoneal (i.p.)) and xilazine (0.01 mg/g body weight, i.p.) for nonsurgical procedures or with urethane (ethyl carbamate, 2 mg/g body weight, i.p.) for surgical procedures. The animals were tracheotomized, and their core temperature was maintained at 38 1C. To measure basilar membrane displacements, cochlear microphonics, and CAPs, a caudal opening was made in the ventrolateral aspect of the right bulla to reveal the round window. DPOAEs measured before and after surgery indicate that the bulla of the mouse can be opened without loss of sensitivity. Cochlear microphonics and CAPs were measured from the round window membrane using pipettes filled with artificial perilymph with tip diameters of 50–100 mm (recording bandwidth 430 kHz). Signals were amplified with a recording bandwidth of 0–100 kHz. Tone-evoked basilar membrane displacements were measured by focusing the beam of a self-mixing, laser-diode interferometer48 through the round window membrane to form a 20-mm spot on the center of the basilar membrane in the 48–61 kHz region of the cochlea. The interferometer was calibrated at each measurement location by vibrating the piezo stack, on which it was mounted, over a known range of displacements. Tone pulses (rise-fall time 1 ms) during basilar membrane measurements were generated with a Phillips PM 5193 programmable synthesizer and attenuated with digitally controlled attenuators. Voltage responses from the interferometer were measured with a two-channel lock-in amplifier (Princeton 5210) and digitized at 250 kHz with a Data Translation 3010 data acquisition board, and the peak response was stored on a PC. Experimental control, data acquisition and data analysis were performed using a PC with programs written in TestPoint (CEC). Sound was delivered via a probe with its tip within 1 mm of the tympanic membrane and coupled to a closed acoustic system comprising two MicroTech Gefell 1-inch MK102.1 microphones for delivering tones and a Bruel & Kjaer 3135 one-quarter–inch microphone for monitoring sound pressure at the tympanum. The sound system was calibrated in situ for frequencies between 1–70 kHz using a measuring amplifier, and known SPLs were expressed in dB SPL re 2 105 Pa. The position of the coupler was adjusted to minimize peaks and dips in the calibration curve. White noise and tone pulses with risefall times of 0.2 ms were synthesized by a Data Translation 3010 data acquisition board, attenuated and used for sound system calibration and the measurement of electrical and acoustical cochlear responses. Data were digitized at 250 kHz and stored on a PC. To measure DPOAEs, primary tones were

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ARTICLES set to generate 2f1–f2 distortion products at frequencies between 1 and 70 kHz. DPOAEs were measured for levels of f1 ranging from 10–80 dB SPL, with the levels of the f2 tone set 10 dB SPL below that of the f1 tone. DPOAE threshold curves were constructed from measurements of the level of the f2 tone that produced a 2f1–f2 DPOAE with a level of 0 dB SPL where the frequency ratio of f2:f1 was 1.23. System distortion during DPOAE measurements was 80 dB below the primary tone levels. CAP tuning curves were derived from simultaneous tone-on-tone masking38 using a 10-ms probe tone centered on a 40-ms masker tone. The probe tone was set to a level where a stable CAP appeared just above the recording noise floor. The frequency of the masker was set and its attenuation was adjusted until the probe tone CAP was suppressed. The masker frequency and level was noted, a new masker frequency was set and the process repeated. In a second group of experiments the probe level was set to increasingly higher values to see how the CAP tuning curves varied with probe tone level. All procedures involving animals were performed in accordance with UK Home Office regulations with approval from the local ethics committee. ACKNOWLEDGMENTS The authors would like to thank M. Mellado, M. Ko¨ssl and M. Drexl for their helpful criticisms of the manuscript and J. Hartley for expert technical assistance. Supported by grants from The Wellcome Trust, Defeating Deafness and the Fonds Wetenschappelijk Onderzoek – Flanders. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 9 March; accepted 3 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Lim, D.J. Functional structure of the organ of Corti: a review. Hear. Res. 22, 117–146 (1986). 2. Brownell, W.E., Bader, C.R., Betrand, D. & de Ribaupierre, Y. Evoked mechanical responses of isolated cochlear outer hair cells. Science 227, 194–196 (1985). 3. Patuzzi, R.B., Yates, G.K. & Johnstone, B.M. Outer hair receptor currents and sensorineural hearing loss. Hear. Res. 42, 47–72 (1989). 4. Ruggero, M.A. & Rich, N.C. Furosemide alters organ of Corti mechanics: evidence for feedback of outer hair cells upon the basilar membrane. J. Neurosci. 11, 1057–1067 (1991). 5. Ko¨ssl, M. & Russell, I.J. The phase and magnitude of hair cell receptor potentials and frequency tuning in the guinea pig cochlea. J. Neurosci. 12, 1575–1586 (1992). 6. Spoendlin, H. Anatomy of cochlear innervation. Am. J. Otolaryngol. 6, 453–467 (1985). 7. Kimura, R.S. Hairs of the cochlear sensory cells and their attachment to the tectorial membrane. Acta Otolaryngol. (Stockh.) 61, 55–72 (1966). 8. Hasko, J.A. & Richardson, G.P. The ultrastructural organization and properties of the mouse tectorial membrane matrix. Hear. Res. 35, 21–38 (1988). 9. Richardson, G.P., Russell, I.J., Duance, V.C. & Bailey, A.J. Polypeptide composition of the mammalian tectorial membrane. Hear. Res. 25, 45–60 (1987). 10. Thalmann, I. et al. Composition and supramolecular organization of the tectorial membrane. Laryngoscope 97, 357–367 (1987). 11. Legan, P.K., Rau, A., Keen, J.N. & Richardson, G.P. The mouse tectorins: modular matrix proteins of the inner ear homologous to components of the sperm-egg adhesion system. J. Biol. Chem. 272, 8791–8801 (1997). 12. Cohen-Salmon, M., El-Amraoui, A., Leibovici, M. & Petit, C. Otogelin: a glycoprotein specific to the acellular membranes of the inner ear. Proc. Natl. Acad. Sci. USA 94, 14450–14455 (1997). 13. Verhoeven, K. et al. Mutations in human a-tectorin cause autosomal dominant nonsyndromic hearing impairment. Nat. Genet. 19, 60–62 (1998). 14. Davis, H. Transmission and transduction in the cochlea. Laryngoscope 68, 359–382 (1957). 15. Zwislocki, J.J. Theory of cochlear mechanics. Hear. Res. 2, 171–182 (1980). 16. Zwislocki, J.J. Analysis of cochlear mechanics. Hear. Res. 22, 155–169 (1986). 17. Allen, J.B. Cochlear micromechanics - a physical model of transduction. J. Acoust. Soc. Am. 68, 1660–1670 (1980). 18. Legan, P.K. et al. A targeted deletion in a-tectorin reveals the tectorial membrane is required for the gain and timing of cochlear feedback. Neuron 28, 273–285 (2000). 19. Gummer, A.W., Hemmert, W. & Zenner, H.P. Resonant tectorial membrane motion in the inner ear: Its crucial role in frequency tuning. Proc. Natl. Acad. Sci. USA 93, 8727– 8732 (1996).

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20. Hemmert, W., Zenner, H.P. & Gummer, A.W. Three-dimensional motion of the organ of Corti. Biophys. J. 78, 2285–2297 (2000). 21. Lukashkin, A.N., Lukashkina, V.A., Legan, P.K., Richardson, G.P. & Russell, I.J. Role of the tectorial membrane revealed by otoacoustic emissions recorded from wild-type and transgenic Tecta (deltaENT/deltaENT) mice. J. Neurophysiol. 91, 163–171 (2004). 22. Lin, T. & Guinan, J.J. Auditory-nerve-fiber responses to high-level clicks: Interference patterns indicate that excitation is due to the combination of multiple drives. J. Acoust. Soc. Am. 107, 2615–2630 (2000). 23. Dallos, P., Billone, M.C., Durrant, J.D., Wang, C. & Raynor, S. Cochlear inner and outer hair cells: functional differences. Science 177, 356–358 (1972). 24. Russell, I.J. & Sellick, P.M. Low-frequency characteristics of intracellularly recorded receptor potentials in guinea-pig cochlear hair cells. J. Physiol. (Lond.) 338, 179–206 (1983). 25. Patuzzi, R.B. & Yates, G.K. The low-frequency response of inner hair cells in the guinea pig cochlea: implications for fluid coupling and resonance of the stereocilia. Hear. Res. 30, 83–98 (1987). 26. Aranyosi, A.J. & Freemann, D.M. Sound-induced motions of individual cochlear hair bundles. Biophys. J. 87, 3536–3546 (2004). 27. Russell, I.J., Ko¨ssl, M. & Murugasu, E. A comparison between tone-evoked voltage responses of hair cells and basilar membrane displacements recorded in the basal turn of the guinea pig cochlea. in Advances in Hearing Research (eds. Manley, G.A., Klump, G.M., Ko¨ppl, C., Fastl, H. & Oeckinghaus, H.) 125–135 (World Scientific, Singapore, 1995). 28. Narayan, S.S., Temchin, A.N., Recio, A. & Ruggero, M.A. Frequency tuning of basilar membrane and auditory nerve fibers in the same cochleae. Science 282, 1882–1884 (1998). 29. Kletsky, E.J. & Zwislocki, J.J. CM tuning can be compatible with sharply tuned receptor potentials. Hear. Res. 2, 549–557 (1980). 30. Frolenkov, G.I., Belyantseva, I.A., Kurc, M., Mastroianni, M.A. & Kachar, B. Cochlear outer hair cell electromotility can provide force for both low and high intensity distortion product otoacoustic emissions. Hear. Res. 126, 67–74 (1998). 31. Lukashkin, A.N., Lukashkina, V.A. & Russell, I.J. One source for distortion product otoacoustic emissions generated by low- and high-level primaries. J. Acoust. Soc. Am. 111, 2740–2748 (2002). 32. Santos-Sacchi, J. Harmonics of outer hair cell motility. Biophys. J. 65, 2217–2227 (1993). 33. Lukashkin, A.N. & Russell, I.J. A descriptive model of the receptor potential nonlinearities generated by the hair cell mechanoelectrical transducer. J. Acoust. Soc. Am. 103, 973–980 (1998). 34. Mom, T., Telischi, F.F., Martin, G.K. & Lonsbury-Martin, B.L. Measuring the cochlear blood flow and distortion-product otoacoustic emissions during reversible cochlear ischemia: a rabbit model. Hear. Res. 133, 40–52 (1999). 35. Robertson, D. Horseradish peroxidase injection of physiologically characterized afferent and efferent neurones in the guinea pig spiral ganglion. Hear. Res. 15, 113–121 (1984). 36. Davis, H., Tasaki, I. & Goldstein, R. The peripheral origin of activity, with reference to the ear. Cold Spring Harb. Symp. Quant. Biol. 17, 143–154 (1952). 37. Sellick, P., Patuzzi, R. & Robertson, D. Primary afferent and cochlear nucleus contributions to extracellular potentials during tone-bursts. Hear. Res. 176, 42–58 (2003). 38. Dallos, P. & Cheatham, M.A. Compound action potential (AP) tuning curves. J. Acoust. Soc. Am. 59, 591–597 (1976). 39. Jovine, L., Qi, H., Williams, Z. & Wassarman, P.M. The ZP domain is a conserved module for polymerisation of extracellular proteins. Nat. Cell Biol. 4, 457–461 (2002). 40. Bork, P. & Sander, C. A large domain common to sperm receptors (Zp2 and Zp3) and TGF-beta type III receptor. FEBS Lett. 300, 237–240 (1992). 41. Wassarman, P.M., Jovine, L. & Litscher, E.S. A profile of fertilization in mammals. Nat. Cell Biol. 3, E59–E64 (2001). 42. Mustapha, M. et al. An alpha-tectorin gene defect causes a newly identified autosomal recessive form of sensorineural pre-lingual non-syndromic deafness, DFNB21. Hum. Mol. Genet. 8, 409–412 (1999). 43. Liberman, M.C. & Kiang, N.Y.-S. Acoustic trauma in cats. Acta Otolaryngol. Suppl. 358, 1–63 (1978). 44. Robles, L. & Ruggero, M.A. Mechanics of the mammalian cochlea. Physiol. Rev. 81, 1305–1352 (2001). 45. Brookes, A.J., Stevenson, B.J., Porteous, D.J. & Dorin, J.R. A series of vectors that simplify mammalian gene targeting. Transgenic Res. 2, 238–244 (1993). 46. Malumbres, M., Mangues, R., Ferrer, N., Lu, S. & Pellicer, C. Isolation of high molecular weight DNA for reliable genotyping of transgenic mice. Biotechniques 22, 1114–1119 (1997). 47. Knipper, M. et al. Thyroid hormone-deficient period prior to the onset of hearing is associated with reduced levels of beta-tectorin protein in the tectorial membrane: implication for hearing loss. J. Biol. Chem. 276, 39046–39052 (2001). 48. Russell, I.J. & Ko¨ssl, M. Micromechanical responses to tones in the auditory fovea of the greater mustached bat’s cochlea. J. Neurophysiol. 82, 676–686 (1999).

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Distinct triggering and expression mechanisms underlie LTD of AMPA and NMDA synaptic responses Wade Morishita, Helene Marie & Robert C Malenka Although long-term depression (LTD) of AMPA receptor–mediated postsynaptic currents (AMPAR EPSCs) has been extensively examined, little is known about the mechanisms responsible for LTD of NMDA receptor (NMDAR)-mediated EPSCs. Here we show differences in the intracellular signaling cascades that mediate LTD of AMPAR EPSCs versus NMDAR EPSCs in rat hippocampus. Both forms of LTD were blocked by inhibitors of protein phosphatase 1, but only LTD of AMPAR EPSCs was affected by inhibition of calcineurin. Notably, in contrast to LTD of AMPAR EPSCs, LTD of NMDAR EPSCs was unaffected by endocytosis inhibitors. A role for calcium-dependent actin depolymerization in LTD of NMDAR EPSCs was supported by the findings that the actin stabilizer phalloidin and a cofilin inhibitory peptide each blocked LTD of NMDAR EPSCs but not AMPAR EPSCs. These results suggest that the same pattern of afferent activity elicits depression of AMPAR- and NMDAR-mediated synaptic responses by means of distinct triggering and expression mechanisms.

Long-term potentiation (LTP) and LTD of excitatory synaptic transmission in the mammalian brain have been extensively studied, and much has been learned about their detailed molecular mechanisms1. Although most excitatory synapses contain both AMPARs and NMDARs, because basal synaptic responses are solely or primarily mediated by AMPARs, much of the mechanistic work on synaptic plasticity has focused on changes in AMPAR-mediated excitatory postsynaptic responses. Indeed, it is controversial whether NMDAR-mediated excitatory responses increase during LTP in the CA1 region of the hippocampus, although recent work suggests that they can show a delayed enhancement following LTP induction2. However, even when NMDAR-mediated responses are potentiated, little is known about the detailed molecular mechanisms responsible for this enhancement. In contrast to LTP, it has consistently been reported that NMDAR-mediated excitatory postsynaptic potentials (EPSPs) or EPSCs decrease during that form of LTD triggered by NMDARs3–7. Notably, analysis of changes in the coefficient of variation of AMPAR EPSCs and NMDAR EPSCs suggests that the mechanisms underlying LTD of AMPAR EPSCs and NMDAR EPSCs differ5. In support of this conclusion, it is possible to elicit LTD of one component of synaptic responses without affecting the other5. However, as is the case for LTP of NMDAR EPSPs and EPSCs, little is known about the triggering and expression mechanisms that underlie LTD of NMDAR-mediated synaptic transmission. The paucity of knowledge about the mechanisms by which synaptic activity modulates NMDAR-mediated synaptic transmission during LTP and LTD is particularly surprising, given that since the cloning of specific NMDAR subunits, much has been learned about the

modulation of NMDARs by various intracellular signaling pathways8,9. In the context of NMDAR-dependent LTD, which involves endocytosis of AMPARs1,10, of particular note is the demonstration that NMDARs can be internalized both constitutively and in response to agonist application11–13. This form of LTD also involves an NMDAR-dependent increase in intracellular calcium and activation of protein phosphatases1, both of which also modulate NMDAR function8,9. In this study, we focused on the role of protein phosphatases, dynamin-dependent endocytosis and the actin cytoskeleton in LTD of NMDAR EPSCs. We present evidence that the intracellular mechanisms responsible for LTD of AMPAR EPSCs and LTD of NMDAR EPSCs differ. The findings suggest that the same pattern of synaptic activation of NMDARs can initiate signaling cascades that modulate AMPARs and NMDARs through different mechanisms. Such parallel but independent activity-dependent regulation of synaptic AMPARs and NMDARs provides great flexibility to individual synaptic sites and has implications for the roles of NMDARs in both adaptive and pathological brain function. RESULTS LTD of NMDAR EPSCs depends on NMDARs and calcium To examine LTD of NMDAR EPSCs we made whole-cell voltage-clamp recordings from CA1 pyramidal cells in acute hippocampal slices in conditions that isolated the NMDAR EPSC. Applying a 5-Hz, 3-min train of afferent stimulation elicited reliable LTD of NMDAR EPSCs (56 ± 2% of baseline, n ¼ 36; Fig. 1a,b). This was not due to dialysis of cells by the pipette solution, as LTD of isolated NMDAR-mediated field EPSPs was induced by a similar protocol (64 ± 3% of baseline, n ¼ 8; Fig. 1c). Furthermore, two pathway experiments demonstrated

Nancy Pritzker Laboratory, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1201 Welch Rd., Palo Alto, California 94304, USA. Correspondence should be addressed to R.M. ([email protected]). Published online 17 July 2005; doi:10.1038/nn1506


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LTD of NMDAR EPSCs requires PP1 but not PP2B Figure 1 LTD of NMDAR-mediated synaptic transmission at Schaffer collateral–CA1 synapses is Ca2+Inhibitors of protein phosphatase 1 (PP1) dependent and requires activation of NMDARs and not mGluRs. (a) Sample experiment illustrating LTD activity1 or PP1 synaptic targeting14 impair of NMDAR EPSCs. Downward arrow in this and all subsequent figures indicates time at which 5-Hz, LTD of AMPAR EPSCs. Therefore, we next 3-min stimulation train was applied. Complete block of EPSC by D-AP5 (100 mM) confirms that EPSC tested whether loading CA1 cells with PP1 was mediated by NMDARs. In this and all subsequent figures, traces above the graph show averaged EPSCs (5–10 consecutive responses) taken at the times indicated by the numbers on the graph. inhibitors also affected LTD of NMDAR (b) Summary graph of LTD of NMDAR EPSC (n ¼ 36). In this and all subsequent summary graphs, EPSCs. Consistent with a role for PP1, adding points represent mean ± s.e.m. (c) Summary graph of LTD of NMDAR field EPSPs (n ¼ 8). (d) Summary either okadaic acid (1 mM) or membranegraphs comparing LTD of NMDAR EPSC in cells loaded with BAPTA (n ¼ 6) and interleaved control impermeable microcystin LR (20 mM) to cells (n ¼ 6). (e) Summary graph demonstrating that LTD of NMDAR EPSC was not elicited when 5-Hz, the pipette solution prevented LTD of 3-min stimulation train was delivered in the presence of D-AP5 (100 mM; n ¼ 10). (f) Summary graph demonstrating normal LTD of NMDAR EPSC was elicited when 5-Hz, 3-min stimulation train was applied NMDAR EPSCs (okadaic acid, 93 ± 10%, in the presence of the mGluR antagonist, LY341495 (100 mM; n ¼ 5). n ¼ 6, Fig. 2a,b; microcystin LR 93 ± 7%, n ¼ 7, Fig. 2c,d) whereas interleaved control cells showed robust LTD (n ¼ 4 that LTD of NMDAR-mediated synaptic responses was input specific and 7 for okadic acid and microcystin LR experiments, respectively; (control pathway: 92 ± 2% of baseline; LTD pathway: 67 ± 1%; n ¼ 7; P o 0.05; Fig. 2b,d). According to one prominent hypothesis15, PP1 activity increases data not shown). Previous work has demonstrated that LTD of NMDAR EPSCs during LTD induction by means of a disinhibition mechanism requires a rise in postsynaptic calcium5 and activation of involving calcium-dependent activation of protein phosphatase 2B NMDARs3,5. Because our experimental conditions differed and because (PP2B, calcineurin). Consistent with this model, PP2B inhibitors of evidence for a metabotropic glutamate receptor (mGluR)-triggered impair LTD of AMPAR EPSCs16. Therefore, we tested whether these form of LTD in CA1 cells1, we examined whether the rise in same inhibitors blocked LTD of NMDAR EPSCs. Loading cells with the Time (min)

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calcium and activation of NMDARs was still required for LTD of NMDAR EPSCs. Consistent with a critical role for increases in postsynaptic calcium levels, loading CA1 cells with the calcium chelator BAPTA (30 mM) blocked LTD of NMDAR EPSCs (93 ± 12%, n ¼ 6; interleaved control cells 62 ± 5%, n ¼ 6, P o 0.05; Fig. 1d). This rise in calcium is likely to be due to NMDAR activation, as blocking NMDARs with D-AP5 (50–100 mM) during the induction protocol prevented LTD of NMDAR EPSCs (90 ± 15%, n ¼ 10, Fig. 1e) whereas blockade of mGluRs with the antagonist LY341495 (100 mM) had no effect (55 ± 7%, n ¼ 5, Fig. 1f). Thus, like LTD of AMPAR EPSCs1, these results suggested that LTD of NMDAR EPSCs requires an NMDAR-dependent rise in postsynaptic calcium.

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Figure 3 The protein phosphatase 2B (calcineurin) inhibitor FK-506 blocks LTD of AMPAR EPSCs but not LTD of NMDAR EPSCs. (a) Sample experiment in which cell was loaded with FK-506 and LTD of NMDAR EPSCs was elicited. (b) Summary graphs comparing LTD of NMDAR EPSCs in cells loaded with FK-506 (n ¼ 12) and interleaved control cells (n ¼ 7). (c) Sample experiment in which the cell was loaded with FK-506 while attempting to elicit LTD of AMPAR EPSCs. (d) Summary graphs comparing LTD of AMPAR EPSCs in cells loaded with FK-506 (n ¼ 7) and interleaved control cells (n ¼ 7).

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PP2B inhibitor FK-506 (50 mM) had no effect on this form of LTD (49 ± 4%, n ¼ 12, Fig. 3a,b), the magnitude of which was comparable to interleaved control cells (55 ± 6%, n ¼ 7, Fig. 3b). To ensure that the FK-506 was effective, we tested the same batch of FK-506 on LTD of AMPAR EPSCs. This blocked LTD of AMPAR EPSCs (93 ± 9%, n ¼ 7, Fig. 3c,d), whereas interleaved control cells exhibited robust LTD of AMPAR EPSCs (48 ± 8%, n ¼ 7, P o 0.05, Fig. 3d). We also examined the effects of a calcineurin inhibitory peptide16 (500 mM), and similar to FK-506, loading cells with this peptide had no effect on LTD of NMDAR EPSCs (48 ± 6%, n ¼ 4, data not shown).

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Dynamin inhibitors do not block LTD of NMDAR EPSCs Regardless of the signaling cascades that trigger LTD, strong evidence suggests that LTD of AMPAR EPSCs is due, at least in part, to the dynamin-dependent endocytosis of AMPARs1,10. Does LTD of NMDAR EPSCs also involve endocytosis of NMDARs and/or associated synaptic proteins such as PSD-95 (ref. 1)? Such a mechanism would seem to be the most parsimonious, as it could involve the formation of clathrin-coated pits that could simultaneously remove both AMPARs and NMDARs. Furthermore, NMDARs in cell lines and cultured neurons can be internalized both constitutively and in response to agonist application11–13. As an initial attempt to block

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LTD of NMDAR EPSCs. Nonetheless, because a b the conclusions based on these results were unexpected, we performed a third manipulation to inhibit dynamin activity. Specifically, we generated a Sindbis virus that expressed a dominant-negative form of dynamin 1 coexDyn1-K44A Control Dyn1-K44A Control AMPAR EPSC NMDAR EPSC 1+2 1+2 1+2 1+2 pressed with GFP (Dyn1-K44A-IRES-GFP). c d 50 pA 50 pA 25 pA This dynamin mutant has been used exten25 pA 150 125 25 ms 25 ms 50 ms 50 ms sively to study the role of dynamin in endo100 100 1 cytosis by clathrin-coated pits18 and inhibits 75 1 50 agonist-dependent endocytosis of AMPARs in 50 2 25 2 cultured neurons19. To facilitate comparisons 0 0 with previous results, we stereotaxically –10 –5 0 5 10 15 20 25 30 –10 –5 0 5 10 15 20 25 30 35 injected the virus into the CA1 region of the Time (min) Time (min) hippocampus and then prepared standard acute hippocampal slices the next day Figure 5 In vivo expression of a dominant-negative form of dynamin blocks LTD of AMPAR EPSCs but not LTD of NMDAR EPSCs. (a) Left: 4 differential interference contrast (DIC) image of a slice cut from (Fig. 5a,b), a procedure that we have used a hippocampus that was injected 18 h earlier with Sindbis virus encoding a dominant-negative form of previously to study the effects of expressing dynamin 1, Dyn1-K44A, that was co-expressed with GFP (scale bar ¼ 250 mm). Right: corresponding recombinant proteins20. The efficacy of this 4 epifluorescent image. (b) Left: a 40 DIC image of the CA1 region captured from another manipulation was demonstrated by the find- hippocampal slice taken from an injected hippocampus (scale bar ¼ 10 mm). Right: corresponding ing that LTD of AMPAR EPSCs in cells epifluorescent image. (c) Summary graphs comparing LTD of AMPAR EPSCs in cells expressing Dyn1expressing Dyn1-K44A was blocked (107 ± K44A (n ¼ 5) with uninfected cells recorded from the same slices (n ¼ 5). (d) Summary graphs 14%, n ¼ 5, Fig. 5c), whereas uninfected cells comparing LTD of NMDAR EPSCs in cells expressing Dyn1-K44A (n ¼ 7) with uninfected cells recorded from the same slices (n ¼ 5). in the same slices showed robust LTD (55 ± 14%, n ¼ 5, P o 0.05, Fig. 5c). In contrast, robust LTD of NMDAR EPSCs was generated in cells expressing Dyn1- by its blockade by phalloidin23. We therefore examined whether K44A (56 ± 6%, n ¼ 7, Fig. 5d), and this was similar to the LTD of loading cells with phalloidin (100 mM), which inhibits actin depolyNMDAR EPSCs elicited in neighboring cells (64 ± 7%, n ¼ 5, Fig. 5d). merization and stabilizes actin, affects LTD of NMDAR EPSCs and/or Thus, on the basis of the lack of effect of three different inhibitors LTD of AMPAR EPSCs. LTD of NMDAR EPSCs was essentially blocked of dynamin on LTD of NMDAR EPSCs, along with their documented in cells loaded with phalloidin (90 ± 8%, n ¼ 7, Fig. 6a), whereas effects on LTD of AMPAR EPSCs, we conclude that LTD of NMDAR interleaved control cells showed robust LTD (56 ± 4%, n ¼ 6, P o 0.05, EPSCs does not involve dynamin-dependent endocytosis of NMDARs. Fig. 6a). In contrast, phalloidin had no effect on LTD of AMPAR EPSCs (65 ± 5%, n ¼ 5; interleaved controls: 61 ± 7%, n ¼ 6, Fig. 6b) indicating that the block of LTD of NMDAR EPSCs by phalloidin was LTD of NMDAR EPSCs requires actin depolymerization If LTD of NMDAR EPSCs does not require NMDAR internalization, not due to nonspecific effects. We also examined effects of latrunculin B and cytochalasin D, both what calcium-dependent processes might contribute? There is extensive evidence that calcium-dependent modulation of the actin cytos- of which inhibit actin polymerization and promote depolymerization. keleton can have significant effects on NMDARs21–27. Of particular Soaking slices in latrunculin B (20 mM) blocked LTD of both NMDAR interest is the calcium-induced rundown of NMDAR channel activity EPSCs (99.4 ± 4%, n ¼ 3) and AMPAR EPSCs (98 ± 12%, n ¼ 6), but in cultured neurons that involves actin depolymerization, as evidenced these results were difficult to interpret because, as previously

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1+2 1+2 scaled AMPAR reported28, this manipulation has presynaptic component a b + D-AP5 Dual-component EPSC effects, as shown by an increase in the NMDAR a b 50 pA component paired-pulse ratio (data not shown). We 25 pA 125 50 ms 50 ms 100 next loaded CA1 cells directly with latrunculin 75 1 B (200 mM, n ¼ 5) or cytochalasin D (200 mM, a+b 50 n ¼ 3). This caused a rundown of NMDAR 25 2 EPSCs (to 30–40% of initial responses), 0 AMPAR NMDAR –10 –5 0 5 10 15 20 25 30 which did not reach a stable level even after component component Time (min) 40–50 min of recording (data not shown). AMPAR AMPAR 1+2 1+2 1+2 1+2 Although these results were consistent with c component component 50 pA d 50 pA NMDAR NMDAR 5 ms 50 pA 50 pA the hypothesis that actin depolymerization 5 ms component component 25 ms 25 ms 125 125 reduces NMDAR EPSCs, because of the 100 100 difficulty in obtaining a stable baseline, we 1 75 75 1 could not determine whether LTD of 50 50 2 NMDAR EPSCs was reduced or ‘occluded’ 25 2 25 by these manipulations. 0 0 15 20 25 30 –10 –5 0 5 10 15 20 25 30 –10 –5 0 5 10 Several actin-binding proteins may have Time (min) Time (min) roles in activity-induced alterations in synaptic actin dynamics29. To examine a require- Figure 7 Dual-component EPSCs demonstrate selective block of LTD of either AMPAR or NMDAR ment for gelsolin, which may have a role in the components by D15 and phalloidin, respectively. (a) Traces illustrating that a dual component EPSC is calcium-dependent rundown of NMDA- recorded when the membrane voltage is held at –40 mV (trace a). Subsequent application of D-AP5 evoked currents in cultured neurons27, we (trace b) yields an AMPAR EPSC. Superimposition of the traces (a+b) reveals that an ‘AMPAR component’ can be measured early during the rising phase of the EPSC, and an ‘NMDAR component’ prepared slices from knockout mice lacking can be measured later in the tail of the EPSC. (b) Summary graphs showing LTD of the AMPAR 30 this protein . However, robust LTD of component and NMDAR component of the dual-component EPSC (n ¼ 7). (c) Summary graphs NMDAR EPSCs was still elicited in the comparing LTD of the NMDAR component with LTD of the AMPAR component in cells loaded with D15 absence of gelsolin (61 ± 2%, n ¼ 7; data (n ¼ 7). (d) Summary graphs comparing LTD of the NMDAR component with LTD of the AMPAR not shown). To examine the role of cofilin, component in cells loaded with phalloidin (n ¼ 8). Superimposed representative traces above graphs in which, upon dephosphorylation, depoly- b, c, and d are averages of ten consecutive EPSCs recorded before and after the LTD-inducing stimulus merizes actin29,31, we loaded cells with a (arrow). Traces at right in c and d are shown at an expanded time scale. phosphorylated cofilin peptide that competes with endogenous phosphorylated cofilin as a substrate for phospha- synaptic responses mediated solely by AMPARs or NMDARs. An tases and prevents the dendritic spine shrinkage that accompanies alternative approach is to make recordings under conditions in LTD32. LTD of NMDAR EPSCs was blocked by this phosphorylated which both AMPARs and NMDARs contribute to EPSCs. An advancofilin peptide (S3P; 92 ± 5%, n ¼ 11, Fig. 6c) but not by a nonphos- tage of this approach is that, in the same cell at the same time, it is phorylated version (S3; 63 ± 3%, n ¼ 10, Fig. 6c). Neither peptide possible to compare the effects of a manipulation on the AMPARaffected LTD of AMPAR EPSCs (S3P peptide, 60 ± 7%, n ¼ 6; S3 mediated component versus the NMDAR-mediated component of the peptide, 65 ± 4%, n ¼ 6; Fig. 6d). These results suggest that cofilin, but EPSC. A disadvantage is that the two components overlap temporally, not gelsolin, has a role in the actin depolymerization that is required for and therefore it is often difficult to make accurate measurements that solely reflect AMPAR-mediated versus NMDAR-mediated synaptic LTD of NMDAR EPSCs. Calcium/calmodulin can directly interact with the cytoplasmic C currents. Nonetheless, by using a time window on the rising phase of terminus of the NR1 subunit of NMDARs and competitively inhibit the the EPSC (2 ms after EPSC initiation) and a later time window (50 ms binding of a-actinin21,33. This contributes to the calcium-dependent after EPSC initiation) at which the AMPAR-mediated EPSC has inactivation of recombinant NMDARs, presumably by releasing the entirely or largely returned to baseline, it is possible to make measureNMDAR from its anchoring to the actin cytoskeleton21,22,26. To test ments that largely reflect AMPAR-mediated versus NMDAR-mediated whether a similar mechanism contributes to LTD of NMDAR EPSCs synaptic currents respectively (Fig. 7a). Therefore, to further test our we loaded cells with the calmodulin inhibitor W7 (1 mM) and found hypotheses, we recorded dual-component EPSCs and examined the that this manipulation had no effect on LTD of NMDAR EPSCs (56 ± effects of two manipulations that dissociated the mechanisms of LTD of 6%, n ¼ 4, data not shown). To test the efficacy of loading cells with W7 AMPAR EPSCs and LTD of NMDAR EPSCs. We first confirmed that the induction protocol caused depression of we examined its effects on LTD of AMPAR EPSCs, which was significantly lower in W7 loaded cells than in interleaved control cells both the AMPAR-mediated and NMDAR-mediated components of (80 ± 12%, n ¼ 7; control cells, 46 ± 7%, n ¼ 6, P o 0.05, data not EPSCs. Indeed, both components decreased proportionately, as shown). We also examined the effects of a different calmodulin demonstrated by quantitative measurements (AMPAR-mediated cominhibitor, calmidazolium (50 mM), which has been shown to impair ponent: 54 ± 4%; NMDAR-mediated component: 46 ± 5%, n ¼ 7, LTD of AMPAR EPSCs34. This manipulation had no discernable effect Fig. 7b) and by the fact that the EPSC following LTD induction scaled on LTD of NMDAR EPSCs (61 ± 8%, n ¼ 6, data not shown). Thus, to that obtained during the baseline (traces in Fig. 7b). We then calcium/calmodulin binding to cytoplasmic tails of NMDAR subunits examined the effects of loading cells with either the dynamin inhibitory peptide D15 (2 mM) or with phalloidin (100 mM), two manipulations does not seem to be critical for LTD of NMDAR EPSCs. that had opposite effects on LTD of AMPAR EPSCs and LTD of NMDAR EPSCs. In cells loaded with D15, LTD of the AMPARAnalysis of dual-component EPSCs Recording isolated AMPAR EPSCs or NMDAR EPSCs allowed us to mediated component was greatly reduced (86 ± 14%, n ¼ 7, make unequivocal measurements of the effects of manipulations on Fig. 7c), whereas LTD of the NMDAR-mediated component was

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ARTICLES AMPAR EPSCs; both require NMDAR activation, yet most manipulations affected only one of the two. This dissociation suggests 100 that the early triggering events required for these forms of LTD—NMDAR activation and 75 the consequent rise in calcium—were not affected by the experimental perturbations 50 but rather that downstream signaling or expression mechanisms were impaired. It is 25 conceivable that dialysis of cells owing to the whole-cell recording configuration may have 0 influenced the intracellular signaling processes that are responsible for the two forms of LTD. However, this caveat applies to all work that involves whole-cell recording, and Figure 8 Graph summarizing the effects of all of the experimental manipulations on LTD of NMDAR we think it is unlikely to account for our EPSCs and LTD of AMPAR EPSCs. Bars represent average size of EPSCs 30–35 min after the LTD results, given that robust LTD of NMDARinduction protocol as percentage of baseline EPSCs. LFS, low-frequency stimulation. mediated synaptic transmission was also observed when NMDAR-mediated field EPSPs were recorded. Our results (summarized in Fig. 8 and Supplementary Fig. 1) normal (57 ± 12%, Fig. 7c). This differential effect of D15 on the two EPSC components can be visualized by comparing the EPSC waveform suggest that, in contrast to the critical role of AMPAR endocytosis in following LTD to the baseline EPSC (Fig. 7c). The later EPSC LTD of AMPAR EPSCs, dynamin-dependent internalization of components are reduced, whereas the rising phase of the EPSC, NMDARs does not contribute to LTD of NMDAR EPSCs. Instead, which is largely mediated by AMPARs, is unaffected. Cells loaded calcium-dependent modulation of the actin cytoskeleton is important with phalloidin showed the opposite results. LTD of the AMPAR- for this activity-dependent depression of NMDAR-mediated synaptic mediated component was still present (59 ± 7%, n ¼ 8, Fig. 7d) transmission. Indeed, there is abundant evidence that calcium influwhereas LTD of the NMDAR-mediated component was blocked (99 ± ences the actin cytoskeleton29,31 and that in turn the actin cytoskeleton 21%, Fig. 7d). Again, scaling the EPSCs before and after LTD illustrates influences NMDAR function21–27. Of particular relevance is that the this differential effect, although in this case the EPSC tail generated by calcium-dependent rundown of NMDAR channels in cultured neurons NMDARs was unaffected, whereas the early components were reduced. was blocked by phalloidin, suggesting that calcium-induced actin These results provide further support for the conclusion that the depolymerization reduces NMDAR channel activity23. This has been mechanisms underlying LTD of AMPAR EPSCs and LTD of NMDAR suggested to be attributable, at least in part, to competitive displacement EPSCs differ. of a-actinin from the C0 domain of the C terminus of NR1 (ref. 26). Several additional results support the hypothesis that LTD of DISCUSSION NMDAR EPSCs involves depolymerization of the actin cytoskeleton Given the role of NMDARs in experience-dependent and develop- but not internalization of synaptic NMDARs. First, in cultured neurons, mental plasticity as well as in several pathological states, the activity- there is a calcium-dependent rundown of NMDAR-mediated synaptic dependent regulation of synaptic NMDARs has important functional currents35,36 that is suppressed by the actin stabilizing agent jasplakiimplications. Although the complex modulation of NMDAR function nolide36. This rundown was not associated with decreased surface has been documented8,9, much of this work has focused on extra- expression of NMDARs, as would have been expected if NMDAR synaptic or recombinant NMDARs, and thus little is known about how endocytosis contributed36. Conversely, depolymerizing F-actin with patterns of activity that trigger synaptic plasticity modify NMDAR- latrunculin-A in cultured neurons reduced synaptic NMDAR-mediated mediated synaptic transmission. We provide evidence that the decrease currents but not synaptic AMPAR-mediated currents24. Second, bindin NMDAR-mediated synaptic responses during LTD is triggered and ing of NMDARs to PSD95 or other synaptic scaffolding proteins expressed through mechanisms that differ from those responsible for inhibits NMDAR endocytosis13, suggesting that synaptic NMDARs the depression of AMPAR-mediated synaptic responses. Specifically, we are resistant to endocytosis compared with extrasynaptic NMDARs. found that (i) two different PP2B inhibitors that block LTD of AMPAR Third, in cultured neurons, manipulations that stimulate endocytosis of EPSCs had no effect on LTD of NMDAR EPSCs; in contrast, similar to synaptic AMPARs and a depression of AMPAR-mediated synaptic LTD of AMPAR EPSCs, two different inhibitors of PP1 blocked LTD of currents do not affect synaptic NMDARs37–39. Fourth, manipulations NMDAR EPSCs; (ii) three different inhibitors of dynamin, including a of endo- and exocytosis affect AMPAR EPSCs but not NMDAR dominant-negative version of dynamin, all blocked LTD of AMPAR EPSCs17, as does insulin, which causes endocytosis of AMPARs but EPSCs with no discernable effect on LTD of NMDAR EPSCs; and (iii) not NMDARs40. Similarly, manipulations of F-actin affect AMPARs inhibiting actin depolymerization with phalloidin or a cofilin inhibi- and NMDARs in different ways, and NMDARs, but not AMPARs, are tory peptide did not impair LTD of AMPAR EPSCs but blocked LTD of detergent insoluble28,41. Together these and related results have led to NMDAR EPSCs. Furthermore, two of the most critical results, which the conclusion that AMPARs undergo cycling at synaptic plasma support a dissociation between the mechanisms underlying LTD of membranes, but NMDARs are relatively stable10,42. This does not AMPAR EPSCs versus LTD of NMDAR EPSCs, were confirmed by mean that NMDARs are absolutely fixed at synapses. There is evidence examining the effects of manipulations on dual component EPSCs. that synaptic NMDARs in cultured neurons can be internalized12 and An important feature of these experiments was that the exact same that NMDARs can move laterally between synaptic and extrasynaptic induction protocol was used to trigger LTD of NMDAR EPSCs and pools43,44, a transition that may contribute to LTD of NMDAR EPSCs. NMDA

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ARTICLES The importance of our results is that they suggest that during NMDARdependent LTD, dynamin-dependent endocytosis of NMDARs does not contribute. One important factor may be that as synapses mature, the subunit composition of NMDARs changes in a manner that inhibits endocytosis of synaptic NMDARs13. Imaging of actin dynamics in hippocampal slices has directly demonstrated that prolonged low-frequency stimulation, which typically triggers LTD, induces actin depolymerization45. The robust LTD of NMDAR EPSCs in gelsolin knockout mice, however, suggests that this actin-severing protein31 is not required for this form of synaptic plasticity. Instead, the inhibition of LTD of NMDAR EPSCs, but not AMPAR EPSCs, by a phosphorylated cofilin peptide make cofilin an attractive candidate for a key role in modulating the actin cytoskeleton during LTD31,32. Upon dephosphorylation, cofilin depolymerizes actin, and its activation by dephosphorylation can be mediated by PP1 (ref. 31). It is also possible that calcium contributes to LTD of NMDAR EPSCs by directly interfering with the binding of a-actinin to NMDAR subunits26 and that PP1 contributes by dephosphorylating proteins that help preserve the actin cytoskeleton and NMDARs in the state that is necessary to maintain LTD14,26,34. There are two general ways NMDARs might be modulated so as to lead to LTD of NMDAR EPSCs (Supplementary Fig. 1). First, their biophysical properties could be modified such that their overall conductance or probability of opening is reduced. The latter possibility seems the most likely, as this has been related to calcium-induced inactivation of NMDARs via modulation of the actin cytoskeleton23,26. Alternatively, actin depolymerization might facilitate the diffusion of NMDARs from synaptic to extrasynaptic sites in the plasma membrane43. Such lateral diffusion could reduce the concentration of synaptically released glutamate to which the NMDARs are exposed and also modify their biophysical properties36,46. Our results provide further evidence that synaptic AMPARs and NMDARs can be independently regulated by activity through different mechanisms. They also point out the importance of examining synaptic responses in intact preparations and not relying solely on cell biological assays or recordings from cell lines or cultured neurons. Although the latter approaches have provided important information, they often involve examining extrasynaptic receptors, which are not embedded in normal synaptic architecture and therefore often have properties different from those of synaptic receptors (for example, see refs. 14,36,46). The delayed increase in NMDAR-mediated synaptic responses during LTP observed in cortical cells has been suggested to be a mechanism that preserves the relative contribution of AMPARs and NMDARs to synaptic transmission2. Similarly, the depression of NMDAR EPSCs during LTD will accomplish this same task. In addition, not only should LTP be more difficult to elicit at synapses at which LTD has occurred, but patterns of synaptic activity that normally elicit no changes in synaptic strength or even LTP might now elicit LTD (see ref. 47). Such a change in the responsiveness of synapses to afferent input might be important for facilitating the shrinkage or loss of dendritic spines that occurs during LTD32,48. Notably, however, after LTD induction, depressed NMDAR EPSCs can be potentiated5, a result that we have replicated in this study (data not shown). Thus, as is the case for AMPAR-mediated synaptic transmission, activity can exert bidirectional control over NMDAR-mediated synaptic responses, albeit using mechanisms distinct from those controlling synaptic AMPAR function. METHODS Electrophysiology. Hippocampal slices (300 mm) were prepared from 3to 4-week-old Sprague-Dawley rats14. Briefly, slices were cut in ice-cold


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oxygenated (95% O2/5% CO2) solution containing (in mM) sucrose 238, KCl 2.5, NaH2PO4 1, MgSO4 2, CaCl2 0.5, NaHCO3 26.2, glucose 11 (pH 7.4). Slices were stored in warm (B28 1C) oxygenated artificial cerebrospinal fluid (ACSF) containing (in mM) NaCl 119, KCl 2.5, NaH2PO4 1, MgSO4 1.3, CaCl2 2.5, NaHCO3 26.2, glucose 11 and recovered for at least 1.5 h. Slices were visualized in a chamber on an upright microscope (Olympus BX50WI) with transmitted and epifluorescent illumination and were perfused with warm (28–30 1C), oxygenated ACSF. Whole-cell voltage-clamp recordings were made from CA1 pyramidal cells with an Axopatch 1D amplifier (Axon Instruments). Recording pipettes (3–5 MO) were filled with a solution containing (in mM) CsMeSO4 117.5, HEPES 10, TEACl 10, CsCl 15.5, NaCl 8, EGTA 0.25, MgATP 4, NaGTP 0.3, QX-314 5 (pH adjusted to 7.3 with CsOH, 290–305 mOsM). EPSCs were evoked with a glass pipette containing external ACSF. The stimulating pipette was placed in stratum radiatum near the stratum pyramidal boarder to activate proximal Schaffer collateral-CA1 synapses. Following whole cell access synapses were stimulated (at 0.05 Hz) for a minimum period of 5 min prior to data acquisition. During this ‘warmup’ period stimulation intensity was adjusted to obtain stable baseline responses. NMDAR EPSCs and field EPSPs were isolated with the addition of 50 mM picrotoxin and 5 mM NBQX to the ACSF. Baseline NMDA EPSCs were recorded at –40 mV while stimulating afferents at 0.05 Hz. AMPAR and dual-component EPSCs were recorded at –65 mV and –40 mV, respectively, in the presence of 50 mM picrotoxin. LTD was induced with a 5-Hz, 3-min train. LTD of AMPAR EPSCs was induced by depolarizing the cell to –40 mV for the duration of the train. Field recording pipettes were filled with external ACSF. When recording NMDAR field EPSPs, Mg2+ in the ACSF was reduced to 0.5 mM. The peak current amplitudes (average of a 2-ms window) of NMDAR and AMPAR EPSCs were measured online using custom data acquisition software (Igor Pro). Dual-component EPSCs were quantified by measuring the amplitude 2 ms (AMPAR component) and 50 ms (NMDAR component) after EPSC onset. Field NMDAR EPSPs were quantified by measuring the initial slope of the synaptic response. Unless otherwise indicated, drugs and peptides were added to the patch solution and allowed to diffuse into the cell for a minimum period of 15 min before the LTD induction protocol. Series and input resistance were continually monitored throughout an experiment. If the series resistance changed by more than 20%, data were not included in analysis. Results are expressed as mean ± s.e.m. Experimental data were compared with data from interleaved ‘same-day’ control experiments and assessed for statistical significance using an unpaired or paired Student’s t-test with a level of significance (P value) o 0.05. All drugs were made as concentrated stock solutions and diluted 100–1,000 to their test concentrations. The drugs used in the study were D-AP5, NBQX, LY341495, W7 (Tocris); okadaic acid, microcystin LR, FK-506, phalloidin, latrunculin B, cytochalasin D, calmidazolium (Calbiochem); picrotoxin, GDPbS (Sigma) and CsBAPTA (Molecular Probes). The peptides used were calcineurin inhibitor peptide (Calbiochem), purified D15 and S15 (Stanford PAN facility), and purified phosphorylated and nonphosphorylated cofilin peptides32 (Stanford PAN facility). Gelsolin knockout mice (Gsntm1Djk) were obtained from Mutant Mouse Regional Resource Centers (Taconic/SUNY Albany; http://www.mmrrc.org). Virus cloning and production. The dominant-negative dynamin 1 contains a point mutation in the GTPase domain (K44A; construct provided by S.L. Schmid, Scripps Research Institute, via P. DeCamilli, Yale University). The cDNA was introduced into a pSINREP5-IRES-GFP backbone vector derived from pSINREP5 (Invitrogen) and pIRES2-EGFP (Clontech) by PCR cloning. Recombinant Sindbis pseudo-virions were generated using the Sindbis expression kit (Invitrogen). Viral supernatant was harvested 36 h after transfection of BHK cells and concentrated. In vivo injections. Sprague-Dawley rats (3–4 weeks old) were anesthetized with ketamine (50 mg/kg body weight) and xylazine (4.5 mg/kg body weight) by intraperitoneal injection. Experiments were approved by the Administrative Panel on Laboratory Animal Care of Stanford University. After immobilization on a stereotaxic instrument, a hole was drilled at –3.9 mm posterior and 2.5 mm lateral to bregma for injection in the CA1 region of the hippocampus.

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ARTICLES Viral solution (0.5 ml) was injected through a stainless steel cannula at a depth of 2.4 mm using a microinfusion pump (Harvard Apparatus) at a rate of 0.1 ml/min. Note: Supplementary information is available on the Nature Neuroscience website.


ACKNOWLEDGMENTS We thank S.Y. Lee for technical assistance and members of the Malenka lab for constructive comments. This work was supported by US National Institutes of Health grant MH063394 to R.C.M. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 16 May; accepted 24 June 2005 Published online at http://www.nature.com/natureneuroscience/

1. Malenka, R.C. & Bear, M.F. LTP and LTD: an embarrassment of riches. Neuron 44, 5–21 (2004). 2. Watt, A.J., Sjostrom, P.J., Hausser, M., Nelson, S.B. & Turrigiano, G.G. A proportional but slower NMDA potentiation follows AMPA potentiation in LTP. Nat. Neurosci. 7, 518–524 (2004). 3. Gean, P.W. & Lin, J.H. D-2-amino-5-phosphonovaleate blocks induction of long-term depression of the NMDA receptor-mediated synaptic component in rat hippocampus. Neurosci. Lett. 158, 170–172 (1993). 4. Xiao, M.Y., Wigstrom, H. & Gustafsson, B. Long-term depression in the hippocampal CA1 region is associated with equal changes in AMPA and NMDA receptor-mediated synaptic potentials. Eur. J. Neurosci. 6, 1055–1057 (1994). 5. Selig, D.K., Hjelmstad, G.O., Herron, C., Nicoll, R.A. & Malenka, R.C. Independent mechanisms for long-term depression of AMPA and NMDA responses. Neuron 15, 417–426 (1995). 6. Montgomery, J.M. & Madison, D.V. State-dependent heterogeneity in synaptic depression between pyramidal cell pairs. Neuron 33, 765–777 (2002). 7. Xie, X., Berger, T.W. & Barrionuevo, G. Isolated NMDA receptor-mediated synaptic responses express both LTP and LTD. J. Neurophysiol. 67, 1009–1013 (1992). 8. Dingledine, R., Borges, K., Bowie, D. & Traynelis, S.F. The glutamate receptor ion channels. Pharmacol. Rev. 51, 7–61 (1999). 9. Kotecha, S.A. & MacDonald, J.F. Signaling molecules and receptor transduction cascades that regulate NMDA receptor-mediated synaptic transmission. Int. Rev. Neurobiol. 54, 51–106 (2003). 10. Carroll, R.C., Beattie, E.C., Von Zastrow, M. & Malenka, R.C. Role of AMPA receptor endocytosis in synaptic plasticity. Nat. Rev. Neurosci. 2, 315–324 (2001). 11. Vissel, B., Krupp, J.J., Heinemann, S.F. & Westbrook, G.L. A use-dependent tyrosine dephosphorylation of NMDA receptors is independent of ion flux. Nat. Neurosci. 4, 587–596 (2001). 12. Nong, Y. et al. Glycine binding primes NMDA receptor internalization. Nature 422, 302–307 (2003). 13. Roche, K.W. et al. Molecular determinants of NMDA receptor internalization. Nat. Neurosci. 4, 794–802 (2001). 14. Morishita, W. et al. Regulation of synaptic strength by protein phosphatase 1. Neuron 32, 1133–1148 (2001). 15. Lisman, J. A mechanism for the Hebb and the anti-Hebb processes underlying learning and memory. Proc. Natl. Acad. Sci. USA 86, 9574–9578 (1989). 16. Mulkey, R.M., Endo, S., Shenolikar, S. & Malenka, R.C. Involvement of a calcineurin/ inhibitor-1 phosphatase cascade in hippocampal long-term depression. Nature 369, 486–488 (1994). 17. Lu¨scher, C. et al. Role of AMPA receptor cycling in synaptic transmission and plasticity. Neuron 24, 649–658 (1999). 18. Schmid, S.L., McNiven, M.A. & De Camilli, P. Dynamin and its partners: a progress report. Curr. Opin. Cell Biol. 10, 504–512 (1998). 19. Carroll, R.C. et al. Dynamin-dependent endocytosis of ionotropic glutamate receptors. Proc. Natl. Acad. Sci. USA 96, 14112–14117 (1999). 20. Marie, H., Morishita, W., Yu, X., Calakos, N. & Malenka, R.C. Generation of silent synapses by acute in vivo expression of CaMKIV and CREB. Neuron 45, 741–752 (2005).

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21. Zhang, S., Ehlers, M.D., Bernhardt, J.P., Su, C.T. & Huganir, R.L. Calmodulin mediates calcium-dependent inactivation of N-methyl-D-aspartate receptors. Neuron 21, 443–453 (1998). 22. Wyszynski, M. et al. Competitive binding of alpha-actinin and calmodulin to the NMDA receptor. Nature 385, 439–442 (1997). 23. Rosenmund, C. & Westbrook, G.L. Calcium-induced actin depolymerization reduces NMDA channel activity. Neuron 10, 805–814 (1993). 24. Sattler, R., Xiong, Z., Lu, W.Y., MacDonald, J.F. & Tymianski, M. Distinct roles of synaptic and extrasynaptic NMDA receptors in excitotoxicity. J. Neurosci. 20, 22–33 (2000). 25. Lei, S., Czerwinska, E., Czerwinski, W., Walsh, M.P. & MacDonald, J.F. Regulation of NMDA receptor activity by F-actin and myosin light chain kinase. J. Neurosci. 21, 8464–8472 (2001). 26. Krupp, J.J., Vissel, B., Thomas, C.G., Heinemann, S.F. & Westbrook, G.L. Interactions of calmodulin and alpha-actinin with the NR1 subunit modulate Ca2+-dependent inactivation of NMDA receptors. J. Neurosci. 19, 1165–1178 (1999). 27. Furukawa, K. et al. The actin-severing protein gelsolin modulates calcium channel and NMDA receptor activities and vulnerability to excitotoxicity in hippocampal neurons. J. Neurosci. 17, 8178–8186 (1997). 28. Kim, C.H. & Lisman, J.E. A role of actin filament in synaptic transmission and long-term potentiation. J. Neurosci. 19, 4314–4324 (1999). 29. Carlisle, H.J. & Kennedy, M.B. Spine architecture and synaptic plasticity. Trends Neurosci. 28, 182–187 (2005). 30. Witke, W. et al. Hemostatic, inflammatory, and fibroblast responses are blunted in mice lacking gelsolin. Cell 81, 41–51 (1995). 31. dos Remedios, C.G. et al. Actin binding proteins: regulation of cytoskeletal microfilaments. Physiol. Rev. 83, 433–473 (2003). 32. Zhou, Q., Homma, K.J. & Poo, M.M. Shrinkage of dendritic spines associated with longterm depression of hippocampal synapses. Neuron 44, 749–757 (2004). 33. Ehlers, M.D., Zhang, S., Bernhadt, J.P. & Huganir, R.L. Inactivation of NMDA receptors by direct interaction of calmodulin with the NR1 subunit. Cell 84, 745–755 (1996). 34. Mulkey, R.M., Herron, C.E. & Malenka, R.C. An essential role for protein phosphatases in hippocampal long-term depression. Science 261, 1051–1055 (1993). 35. Rosenmund, C., Feltz, A. & Westbrook, G.L. Calcium-dependent inactivation of synaptic NMDA receptors in hippocampal neurons. J. Neurophysiol. 73, 427–430 (1995). 36. Li, B. et al. Differential regulation of synaptic and extra-synaptic NMDA receptors. Nat. Neurosci. 5, 833–834 (2002). 37. Carroll, R.C., Lissin, D.V., von Zastrow, M., Nicoll, R.A. & Malenka, R.C. Rapid redistribution of glutamate receptors contributes to long-term depression in hippocampal cultures. Nat. Neurosci. 2, 454–460 (1999). 38. Ehlers, M.D. Reinsertion or degradation of AMPA receptors determined by activitydependent endocytic sorting. Neuron 28, 511–525 (2000). 39. Lin, J.W. et al. Distinct molecular mechanisms and divergent endocytotic pathways of AMPA receptor internalization. Nat. Neurosci. 3, 1282–1290 (2000). 40. Man, H.-Y. et al. Regulation of AMPA receptor-mediated synaptic transmission by clathrin-dependent receptor internalization. Neuron 25, 649–662 (2000). 41. Allison, D.W., Gelfand, V.I., Spector, I. & Craig, A.M. Role of actin in anchoring postsynaptic receptors in cultured hippocampal neurons: differential attachment of NMDA versus AMPA receptors. J. Neurosci. 18, 2423–2436 (1998). 42. Wenthold, R.J., Prybylowski, K., Standley, S., Sans, N. & Petralia, R.S. Trafficking of NMDA receptors. Annu. Rev. Pharmacol. Toxicol. 43, 335–358 (2003). 43. Tovar, K.R. & Westbrook, G.L. Mobile NMDA receptors at hippocampal synapses. Neuron 34, 255–264 (2002). 44. Groc, L. et al. Differential activity-dependent regulation of the lateral mobilities of AMPA and NMDA receptors. Nat. Neurosci. 7, 695–696 (2004). 45. Okamoto, K., Nagai, T., Miyawaki, A. & Hayashi, Y. Rapid and persistent modulation of actin dynamics regulates postsynaptic reorganization underlying bidirectional plasticity. Nat. Neurosci. 7, 1104–1112 (2004). 46. Li, B., Otsu, Y., Murphy, T.H. & Raymond, L.A. Developmental decrease in NMDA receptor desensitization associated with shift to synapse and interaction with postsynaptic density-95. J. Neurosci. 23, 11244–11254 (2003). 47. Cummings, J.A., Mulkey, R.M., Nicoll, R.A. & Malenka, R.C. Ca2+ signaling requirements for long-term depression in the hippocampus. Neuron 16, 825–833 (1996). 48. Nagerl, U.V., Eberhorn, N., Cambridge, S.B. & Bonhoeffer, T. Bidirectional activitydependent morphological plasticity in hippocampal neurons. Neuron 44, 759–767 (2004).

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Regulation of NMDA receptor trafficking by amyloid-b Eric M Snyder1,6, Yi Nong2, Claudia G Almeida3, Surojit Paul4, Timothy Moran2, Eun Young Choi1, Angus C Nairn1,5, Michael W Salter2, Paul J Lombroso4, Gunnar K Gouras3 & Paul Greengard1 Amyloid-b peptide is elevated in the brains of patients with Alzheimer disease and is believed to be causative in the disease process. Amyloid-b reduces glutamatergic transmission and inhibits synaptic plasticity, although the underlying mechanisms are unknown. We found that application of amyloid-b promoted endocytosis of NMDA receptors in cortical neurons. In addition, neurons from a genetic mouse model of Alzheimer disease expressed reduced amounts of surface NMDA receptors. Reducing amyloid-b by treating neurons with a c-secretase inhibitor restored surface expression of NMDA receptors. Consistent with these data, amyloid-b application produced a rapid and persistent depression of NMDA-evoked currents in cortical neurons. Amyloid-b– dependent endocytosis of NMDA receptors required the a-7 nicotinic receptor, protein phosphatase 2B (PP2B) and the tyrosine phosphatase STEP. Dephosphorylation of the NMDA receptor subunit NR2B at Tyr1472 correlated with receptor endocytosis. These data indicate a new mechanism by which amyloid-b can cause synaptic dysfunction and contribute to Alzheimer disease pathology.

Alzheimer disease is a progressive neurodegenerative disease in which patients have declarative memory impairments and increasingly severe dementia. Numerous pathological changes have been described in the postmortem brains of Alzheimer disease patients, including plaques, tangles, inflammation, neuron loss and synapse loss. Cortical and hippocampal synapse density is reduced early in the disease process, and the loss of these synapses correlates strongly with memory impairments1,2. The prevention and treatment of Alzheimer disease may therefore require a detailed understanding of how synapses are affected in the disease process. In patients with Alzheimer disease, a 40- or 42-amino-acid peptide called amyloid-b is elevated in the brain. The amount of amyloid-b correlates with the onset and severity of memory impairments, consistent with an important role for this peptide in the disease process. This peptide, particularly the 42-amino-acid form (amyloid-b1–42), is highly hydrophobic and accumulates both extracellularly in plaques and intracellularly in multivesicular bodies3. Soluble extracellular amyloid-b may initiate memory impairments before the accumulation of plaques4. The pathogenic 40- and 42-amino-acid forms of amyloid-b are produced by sequential cleavage of the amyloid precursor protein (APP) by enzymatic complexes known as b- and g-secretases. In all familial forms of Alzheimer disease yet examined, mutations in the APP or in the presenilins, essential components of the g-secretase, increase production and/or aggregation of amyloid-b (ref. 5). Transgenic mice that overexpress wild-type human APP or APP with a human familial mutation produce increased amyloid-b and have alterations in synaptic transmission, plasticity and memory6,7. These

memory impairments and synaptic alterations precede neuronal death and plaque formation, indicating that synaptic alterations may be important events that contribute to the memory deficits associated with Alzheimer disease. Amyloid-b can reduce long-term potentiation (LTP), a form of synaptic plasticity that is closely associated with learning and memory and can facilitate long-term depression (LTD), an opposing form of synaptic plasticity4,8. LTP and LTD involve postsynaptic phosphorylation and glutamate receptor trafficking9. The observation that amyloid-b reduces LTP and facilitates LTD is suggestive of a role for amyloid-b in regulating trafficking of glutamate receptors and postsynaptic phosphorylation, but this has not been previously examined. In the current study, we investigated the mechanisms by which amyloid-b affects signaling through NMDA-type glutamate receptors. Amyloid-b deposits first occur in the entorhinal and frontal cortices of Alzheimer disease patients, and the amount of amyloid-b in these regions correlates with memory loss10. Therefore, we examined the effects of amyloid-b on cortical neurons. In cultured cortical neurons, amyloid-b promoted endocytosis of NMDA receptors, without affecting trafficking of GABAA-type receptors. Application of amyloid-b produced a persistent depression of NMDA-evoked currents and reduced signaling to the cAMP response element binding protein (CREB), a transcription factor required for long-term memory and neuronal survival. A reduction in surface-expressed NMDA receptors was also found in neuronal cultures prepared from mice bearing APP with the familial Swedish mutation, with no change in total receptor amounts. Together, these data indicate that amyloid-b can regulate glutamatergic receptor endocytosis and that it does so in a genetic

1Laboratory for Molecular and Cellular Neuroscience, Rockefeller University, 1230 York Avenue, New York, New York 10021, USA. 2Program in Brain and Behavior, Hospital for Sick Children, Toronto, Ontario M5G 1X8, Canada. 3Department of Neurology and Neuroscience, Weill Medical College of Cornell University, 525 East 68th Street, New York, New York, 10021, USA. 4The Child Study Center, Yale University School of Medicine, 230 South Frontage Road, New Haven, Connecticut 06520, USA. 5Department of Psychiatry, Yale University School of Medicine, 34 Park Street, New Haven, Connecticut 06508, USA. 6Current address: McKinsey and Company, 600 Campus Drive, Florham Park, New Jersey 07932, USA. Correspondence should be addressed to E.M.S. ([email protected]).



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Figure 1 Amyloid-b1–42 promotes endocytosis of glutamate receptor subunits. (a) Neurons were treated with control medium (Ctl) or with medium containing amyloid-b1–42 (Ab42) and then surface proteins were measured by biotinylation (see Methods). (b) Quantification of biotinylation immunoblots. NR2B: P o 0.03, n ¼ 4; NR1: P o 0.03, n ¼ 7; GABAAb2/3: P 4 0.1, n ¼ 5. Error bars indicate s.e.m. (c) Measurement of surface NR1 after treatment of cultured neurons with the reverse amyloid-b peptide 42–1. (d) Internalization of surface receptors was measured using a cleavable biotin protocol in cortical cultures. Left panel shows that stripping removes biotin labeling of surface receptors NR2B, NR1 and GABAAb2/3. Center panel shows the amount of internalized surface receptor protein under control conditions, which is measured by biotinylating surface receptors and stripping after 15 min at 37 1C in control medium or in medium containing 1 mM amyloid-b. Right panel shows a western blot of total receptor protein in control and amyloid-b–treated cultures. (e) Quantification of immunoblots for receptors labeled with cleavable biotin. NR2B: P o 0.03, n ¼ 5; NR1: P o 0.05, n ¼ 5.

Amyloid-b1–42 promotes endocytosis of NMDA receptors Amyloid-b could decrease surface expression of NMDA receptors either by promoting endocytosis of receptor proteins or by preventing surface delivery. Endocytosis of NMDA receptors was examined in cultured cortical neurons using cleavable biotin18. Amyloid-b promoted the endocytosis of biotin bound to the NMDA receptor subunits NR2B and NR1 (to 209 ± 31% and 171 ± 16% of control internal biotin amounts, respectively; Fig. 1d,e). Amyloid-b did not, however, promote endocytosis of GABAAb 2/3 receptors (Fig. 1d,e). These data indicate that amyloid-b promotes endocytosis of NMDA receptors, without generally promoting endocytosis of other ionotropic neuronal receptors. These data indicate that APP processing regulates NMDA receptor surface expression.

model of Alzheimer disease. The effect of amyloid-b on endocytosis of NMDA receptors is likely to contribute to synaptic dysfunction in Alzheimer disease. RESULTS Amyloid-b decreases surface expression of NMDA receptors Low amounts of secreted soluble amyloid-b regulate glutamatergic currents mediated by both NMDA and AMPA receptors without affecting GABA receptor currents11. The effect of amyloid-b on NMDA currents is of particular interest as this receptor regulates synapse density and memory formation. NMDA receptors undergo regulated endocytosis12–15. To examine the effect of amyloid-b on NMDA receptor endocytosis, cultured cortical neurons were treated with amyloid-b (1 mM for 1 h; Supplementary Methods), and cell surface receptors were quantified using biotinylation12,16. Amyloid-b reduced the surface expression of the NMDA receptor subunit proteins NR2B and NR1 to 55 ± 8% and 64 ± 6% of control amounts, respectively; however, no change was observed in the total amount of NR2B or NR1 (Fig. 1a,b). As a control for the amyloid-b1–42 peptide, we treated neurons with the reverse peptide 42–1 (1 mM, 1 h) and found that it had no effect on the surface expression of NR1 (95 ± 8% of control; Fig. 1c). NMDA and GABAA receptors are coexpressed on the cell surface of forebrain neurons but at different synapses17. Amyloid-b1–42 did not affect the surface expression of GABAAb 2/3receptor subunits (amyloid-b: 93 ± 7% of control; Fig. 1a,b), indicating that amyloid-b1–42 affected NMDA receptors but not all other ionotropic receptors.

Figure 2 Amyloid-b (Ab) reduces synaptic NMDA receptors. (a–f) Cultured cortical neurons were treated with control medium (a–c) or medium containing 1 mM amyloid-b (d–f). Neurons were immunostained for synapsin 1 (a,d) and NR1 (b,e). Overlays of stained neurons are shown in c and f. (g) Quantification of staining. NR1: P o 0.05, n ¼ 10 cells, 150 synapses; synapsin 1: P 4 0.2, n ¼ 150 synapses in 10 cells. Error bars indicate s.e.m.

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Amyloid-b1–42 reduces synaptic NMDA receptors We used immunocytochemistry to assay whether amyloid-b can reduce the density of NMDA receptors at synapses. Cortical cultures were treated with control medium or with medium containing amyloidb1–42 (1 mM) for 1 h and were then fixed, permeabilized and stained for the synaptic marker synapsin 1 and the NMDA receptor subunit NR1. NR1 staining showed a punctate distribution that localized with a majority of synapsin 1 in control neurons (Fig. 2). Treatment with amyloid-b did not affect staining intensity for synapsin 1 but did significantly reduce the presence of NR1 at synaptic sites. In amyloid-btreated cultures, NR1 background staining appeared unchanged, and some puncta were observable; however, localization with synapsin 1 was greatly reduced. Quantification showed that although staining for

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synapsin remained at 97 ± 6% of control amounts, amyloid-b reduced staining for NR1 at synaptic sites to 61 ± 8% (Fig. 2g). Given that we see no change in total NR1 with western blots, we believe these data reflect a redistribution of NMDA receptors away from synaptic sites and toward nonclustered extrasynaptic sites. Although we did not observe an increase in extrasynaptic staining for NMDA receptors, these observations are consistent with other published accounts of NMDA receptor redistribution19. Naturally-secreted amyloid-b reduces surface NMDA receptors Because of its hydrophobicity and predilection toward aggregation, synthetic amyloid-b may induce effects that are different from those induced by naturally secreted amyloid-b. We therefore treated cultured cortical neurons with medium from a neuronal cell line that secretes high amounts of amyloid-b: N2A cells that stably express APPSwe and presenilinD9 (APPSwe/D9; ref. 20). As a control, medium from untransfected wild-type N2A cells, which secrete little endogenous amyloid-b, was used. Medium from untransfected N2A cells did not affect surface or total NR1 (Fig. 3a). In contrast, medium from APPSwe/D9 N2A cells reduced surface NR1 within 30 min but did not change the total amount of NR1 (Fig. 3a). Quantification showed a significant difference (P o 0.04) in surface NR1 after a 30-min exposure to the amyloidb–containing cell medium (Fig. 3b). The decrease persisted through 60 min of treatment. Treatment of APPSwe/D9 N2A cells with the g-secretase inhibitor DAPT (200 nM for 72 h) substantially reduced the amount of amyloid-b (Fig. 3c). DAPT treatment completely blocked the ability of APPSwe/D9 medium to reduce surface expression of NR1 (APPSwe/D9 in DAPT: 97 ± 5% of wild-type surface NR1; Fig. 3d). These data indicate that processing of APP is necessary for the effects of conditioned medium from APPSwe/D9-transfected N2A cells on surface expression of NMDA receptors. Reduced surface NR1 in neurons from APPSwe mice We next investigated whether surface expression of NR1 is reduced in a genetic model of Alzheimer disease. Cortical neurons were cultured


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Figure 3 Naturally secreted amyloid-b reduces surface NMDA receptors. (a) Wild-type medium had no effect on surface NR1 (upper left) or total NR1 (lower left). APPSwe/D9 medium reduced surface NR1 (upper right) without affecting total NR1 (lower right). (b) Quantification shows that APPSwe/D9 medium reduced NR1 amounts to 75 ± 5% within 30 min and 77 ± 7% after 60 min. Error bars indicate s.e.m. (c) Analysis of amyloid-b in conditioned medium from APPSwe/D9 cells in the presence of the g-secretase inhibitor DAPT or 0.1% DMSO (vehicle). (d) Left: surface NR1 after 60 min in wild-type or APPSwe/D9 medium from cells grown in 0.1% DMSO. Right: surface NR1 after 60 min in wild-type or APPSwe/D9 medium from cells grown in the presence of 200 nM DAPT. (e) Primary cortical neurons were prepared from APPSwe mice or wild-type littermates. Surface expression of NR1 was reduced in neurons from APPSwe mice but was restored by DAPT. Total amount of NR1 was not affected by APPSwe expression or DAPT treatment (lower panel). (f) Quantification of treated cortical neurons.

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from mice that express human APP with the familial Swedish mutation. These mice have deficiencies in LTP in vivo, which correlate with reduced learning and memory6. Neurons from these mice survive in culture, extend processes and seem to be generally healthy for up to 3 weeks in vitro3. Using the biotinylation assay, we found that surface expression of NR1 was much lower in 12-day-old cultured neurons from APPSwe mice than in neurons from wild-type littermates, although total receptor protein was not affected (Fig. 3e). Surface expression of NR1 in neurons from APPSwe mice was 46.2 ± 8.8% of that observed in wild-type littermates (n ¼ 10; P o 0.01; Fig. 3f). Treatment of wild-type neurons with the g-secretase inhibitor DAPT for 24 h slightly reduced surface NR1 (control, 100 ± 9.8%; DAPT, 84.2 ± 6%; n ¼ 10). Treatment of APPSwe neurons with DAPT restored surface NR1 (80 ± 4.2%; n ¼ 7). Role of a-7 nicotinic receptor and protein phosphatase 2B Amyloid-b binds to the a-7 nicotinic receptor with picomolar affinity21 and promotes Ca2+ influx in neurons22. In cortical neurons, a-7 nicotinic receptors are expressed postsynaptically at over 70% of synapses, where they may regulate glutamate receptors23. Pretreatment with the a-7 nicotinic receptor antagonist a-bungarotoxin (BTX; 10 mM) for 30 min before treatment with amyloid-b partially inhibited the reduction in surface expression of NR1 (BTX, 98 ± 5% of control; amyloid-b + BTX, 90 ± 11% of control; Fig. 4). A structurally distinct antagonist, methyllycaconitine (MLA; 1 mM) also substantially inhibited the reduction in surface NR1 (MLA, 90 ± 6% of control; amyloid-b + MLA, 87 ± 8% of control; n ¼ 3; see Supplementary Fig. 1 online). These data are consistent with a role for the a-7 nicotinic receptor in mediating the effects of amyloid-b on NMDA receptor endocytosis. The a-7 nicotinic receptor can activate PP2B, a Ca2+-sensitive enzyme that regulates NMDA receptor transmission and synaptic plasticity24,25. Inhibition of PP2B with cyclosporin (20 mM) markedly reduced the effects of amyloid-b1–42 on surface expression of NR1 (cyclosporin, 90 ± 6% of control; cyclosporin + amyloid-b, 84 ± 5% of

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control; Fig. 4). Neither BTX or cyclosporin altered the total amount of NR1. These data indicate that PP2B activity is necessary for amyloidb–induced endocytosis of NMDA receptors. Amyloid-b activates the tyrosine phosphatase STEP Tyrosine phosphorylation regulates NMDA receptor function26 and surface expression27. One tyrosine phosphatase that has been shown to regulate NMDA receptor function is the striatal-enriched phosphatase (STEP)28. STEP is expressed in brain regions that receive dopaminergic input including the striatum, hippocampus and cortex. STEP is alternatively spliced to produce a 61-kDa membrane-associated protein (STEP61) and a 46-kDa cytosolic fragment (STEP46). STEP61 is present in postsynaptic densities and coimmunoprecipitates with the NMDA receptor complex28, although its specific binding partners within the complex remain unknown. STEP activity reduces NMDA currents and the induction of LTP28. Both STEP61 and STEP46 are phosphorylated by protein kinase a A (PKA) at a common site (STEP61 at Ser221 Ctl. and STEP46 at Ser49) within its substratePhosphobinding domain. Phosphorylation of STEP STEP at this site by PKA reduces the affinity of STEP for its substrates, whereas dephosphorTotal STEP ylation by PP2B activates STEP29.

We hypothesized that the amyloid-b–induced activation of PP2B might lead to dephosphorylation and activation of STEP. Amyloid-b treatment reduced phosphorylation of STEP to 64 ± 5% of control amounts without affecting total amounts of STEP61 (Fig. 5a,b). We measured the phosphorylation of STEP in vivo in the cerebral cortices of 10-month-old APPSwe mice. Phosphorylation of STEP was significantly lower in the brains of the APPSwe mice than in their wild-type littermates (83 ± 3% of wild-type amounts; Fig. 5a,b). To study the role of STEP in NMDA receptor trafficking further, we used a dominant-negative fusion protein. We made a recombinant fusion protein of STEP46 with two mutations: an inactive enzymatic domain (C300S) and a mutation to mimic dephosphorylation (S49A). These two mutations make the fusion protein a dominant negative, as it promotes substrate interaction but not dephosphorylation29. The fusion protein was coupled with the HIV-Tat peptide, which efficiently enters neurons (dnSTEP-Tat). We also coupled Tat to myc, to control for any effect of the Tat protein on its own (myc-Tat). A series of control experiments showed that the Tat fusion proteins were efficiently transduced into cells within 30 min when treated at 1–5 mM (data not shown). Pretreatment with dnSTEP-Tat (5 mM for 45 min) caused no significant change in surface NR1 (99.5 ± 10% of myc-Tat control)

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Figure 5 Amyloid-b promotes dephosphorylation of STEP, which controls glutamate receptor trafficking. (a) Left: neurons were treated with control medium or medium containing amyloid-b, and the tyrosine phosphatase STEP was immunoprecipitated. Right: STEP protein was immunoprecipitated from the cortices of 10-month-old APPSwe mice or their wild-type littermates. (b) Amyloid-b treatment reduced phosphorylation of STEP (n ¼ 5, P o 0.04). In the brains of APPSwe mice, STEP phosphorylation was reduced (n ¼ 4, P o 0.05). Error bars indicate s.e.m. (c) dnSTEP-TAT reduces the effect of amyloid-b on NR1, whereas myc-Tat has no effect. (d) Quantification shows that in myc-Tat, amyloid-b reduced surface NR1 to 54 ± 8% of myc-Tat alone (n ¼ 5; P o 0.05). (e) dnSTEP-Tat blocks the dephosphorylation of Tyr1472 that occurs in the presence of amyloid-b. Total NR2B was not affected. (f) Quantification shows that amyloid-b reduced phosphorylation of NR2B at Tyr1472 (n ¼ 5; P o 0.05).

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Figure 6 Amyloid-b depresses NMDA receptor (NMDAR) currents. (a) Top: recordings from a cultured cortical neuron showing responses to two applications of amyloid-b Bottom: current-voltage (I-V) relationship for currents evoked by amyloid-b from another cortical neuron. (b) Left: the NMDAR peak current amplitude recorded in a cultured cortical neuron is shown before and after treating the neuron with amyloid-b Traces above the graph illustrate responses to the test applications recorded from this cell; NMDA and glycine were applied during the period indicated by the bar above each trace. The traces were taken before and after treating with amyloid-b peptide at the time points indicated by numbers, which correspond to those in the graph. Right: The I-V relationship of the peak current 35 min after treatment with amyloid-b. Traces above the I-V curve illustrate superimposed responses to the test applications recorded at membrane potentials from 60 mV (bottom) to +60 mV (top) in increments of 20 mV. (c) Left: normalized NMDAR peak currents (mean ± s.e.m.) are plotted before and after treatment with amyloid-b. Peak currents were normalized to the average of first six responses. The cells were treated either with regular ECS (filled squares); with ECS plus amyloid-b peptide, which did not induce an inward current (open circles), or with ECS plus amyloid-b peptide, which did induce an inward current (filled triangles). Right: the normalized I-V relationship of NMDA-evoked peak currents from cells 20 min after treatment with ECS only (filled circle; n ¼ 3 cells) or ECS plus amyloid-b (filled triangles).

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but blocked amyloid-b–induced endocytosis of NR1 (Fig. 5c,d). In the presence of dnSTEP-Tat, amyloid-b treatment slightly increased surface NR1 to 121 ± 12% of control amounts (n ¼ 5; Fig. 5c,d); however, this increase was not significant as compared with treatment with dnSTEPTat alone (P 4 0.16). The Tat peptides did not alter total amounts of NR1 (Fig. 5c). The NR2B subunit regulates NMDA trafficking and is phosphorylated at three tyrosine residues in its C terminus. One phosphotyrosine residue (Tyr1472) is in a region that regulates NMDA receptor endocytosis13 and binding of the receptor to the synaptic scaffolding protein PSD-95 and the clathrin adaptor protein AP-2 (ref. 30). We hypothesized that the amyloid-b–induced activation of STEP would promote dephosphorylation of Tyr1472. Amyloid-b (1 mM for 1 h) promoted dephosphorylation of NR2B to 62 ± 7% of control amounts (in the presence of myc-Tat; Fig. 5e,f). In the presence of dnSTEP-Tat, however, this dephosphorylation was blocked (107 ± 11% of control amounts; n ¼ 5). These data are consistent with the hypothesis that amyloid-b promotes dephosphorylation and endocytosis of the NMDA receptor by activating STEP. Amyloid-b rapidly depresses NMDA-evoked currents Reducing the density of NMDA receptors at the cell surface is expected to reduce NMDA receptor–mediated currents as well. Accordingly, we carried out whole-cell patch-clamp recordings in pyramidal neurons. Amyloid-b (1 mM), when applied by rapid local perfusion, caused an inward current that developed over the first 1 s of the start of the application and ended within 1 s after the application ceased


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(Fig. 6a). The reversal potential for this current was approximately 0 mV, indicating that, with the ionic composition of the recording solutions used, it was a nonselective cation current. The amplitude of the current recorded at 60 mV ranged from 40 to 800 pA. This current was reliably evoked with repeated amyloid-b application but was observed in fewer than half the neurons tested. These cells appeared morphologically similar to cells that responded to amyloid-b and did not differ in holding current, input resistance or characteristics of NMDA-evoked responses (data not shown). It is not clear if the cells that had no response to amyloid-b are indicative of a population of neurons that are resistant to amyloid-b under these experimental conditions. To investigate the effect of amyloid-b on NMDA currents, we probed NMDA receptors with regularly timed test applications (3-s duration) of NMDA (50 mM) and glycine (1 mM). Under these conditions, currents evoked by NMDA are stable for more than 45 min14. We recorded test NMDA-evoked currents for at least 10 min to establish a stable baseline and then applied amyloid-b (1 mM) for 5 min; the test applications of NMDA were not made during the period when amyloid-b was applied. In neurons where amyloid-b evoked an inward current (which was sustained for the 5-min application; data not shown), the amplitude of NMDA-evoked currents was decreased and remained decreased for the remainder of the recording period (up to 30 min; Fig. 6b,c). On average, the amplitude of the NMDAevoked currents was reduced to 63.1 ± 4.6% of the amplitude before amyloid-b application (n ¼ 8 cells; Fig. 6c). By contrast, in cells where amyloid-b did not evoke an inward current, we found that NMDA

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ARTICLES dysfunction, synapse loss and neuronal death. The most notable result from the current study is that amyloid-b is capable of regulat15 Aβ Ctl. ing the surface expression and endocytosis of PhosphoNMDA-type glutamate receptors. Our results 10 CREB are consistent with recent findings demon* strating that nontoxic amounts of secreted 5 amyloid-b reduce LTP and glutamatergic Total transmission11. Prolonged depression of 0 CREB Ctl. Aβ Ctl. Aβ Ctl. Aβ NMDA receptor–mediated transmission may + forskolin + NMDA initiate the pathological changes observed in Alzheimer disease. Figure 7 Amyloid-b reduces NMDA-induced CREB phosphorylation. (a) Cultured neurons were treated Synaptic NMDA receptor activation prowith amyloid-b for 1 h and then were treated with forskolin (100 mM) or NMDA (10 mM) for 10 min. Immediately after treatment, western blotting was performed for CREB phosphorylated at Ser133 (top) motes the phosphorylation of CREB and or for total CREB (bottom). (b) Both forskolin and NMDA induced CREB phosphorylation. Amyloid-b did transcription of target genes. These target not affect basal CREB phosphorylation (which decreased slightly to 0.94 ± 0.1 of control values; n ¼ 5; genes include those involved in synapse forP 4 0.2). NMDA increased CREB phosphorylation in control cultures, but the phosphorylation was mation, neuronal survival (BDNF33,34, BCL-2 significantly reduced in amyloid-b–treated cultures (n ¼ 6; P o 0.03). (ref. 35)) and long-term memory formation (C/EBP)36. Decreased CREB phosphorylation currents were not altered and remained at 98.4 ± 1.3% of the has been detected in the brains of Alzheimer disease patients37, baseline (n ¼ 5 cells; Fig. 6c). Likewise, after a 5-min control indicating that amyloid-b may reduce neuronal growth and survival application of extracellular solution (ECS), NMDA-evoked currents through this transcription factor. remained at 97.6 ± 1.1% of the baseline (n ¼ 5 cells; Fig. 6c). Amyloid-b binds to several cell surface proteins and initiates The depression of NMDA currents by amyloid-b1–42 was not associated numerous signaling cascades. We find that amyloid-b-induced endowith a change in the reversal potential, which was near 0 mV cytosis of NMDA receptors involves the activation of the a-7 nicotinic after applying amyloid-b1–42 or ECS (Fig. 6c). Thus, the whole-cell receptor and PP2B (Supplementary Fig. 2). These findings are conNMDA-evoked conductance, rather than the driving force, was sistent with previous data demonstrating that amyloid-b can bind and activate a-7 nicotinic receptors and that this class of receptors can decreased by amyloid-b. reduce NMDA receptor signaling through PP2B24,25. Given that we did not see a complete blockade of NMDA receptor endocytosis with the Amyloid-b reduces NMDA signaling to CREB We examined whether amyloid-b could influence NMDA receptor– nicotinic receptor antagonist BTX, there may be additional receptor mediated biochemical signaling. Stimulation of synaptic NMDA mechanisms involved in this process. PP2B promotes dephosphorylation of the tyrosine phosphatase receptors promotes transcriptional activation through phosphorylation of CREB at Ser133 (ref. 31). Pharmacological or genetic inhibition STEP. PP2B may act directly on STEP as a substrate or through PP1 of adenylyl cyclase or PKA significantly reduces NMDA-induced and inhibitor-1 or DARPP-32 (ref. 38). Either way, dephosphorylation phosphorylation of CREB31. In addition, NMDA receptor activation of STEP via PP2B promotes its activity and interaction with subcan also lead to phosphorylation of CREB through direct activation of strates29. STEP gates NMDA receptor activation and LTP28. The present the RAS/MAP kinase pathway and/or CaMKIV31. data suggest a mechanism by which this occurs and indicate that Amyloid-b regulates activity-dependent CREB phosphorylation32. amyloid-b promotes dephosphorylation and activation of STEP in To test whether this effect is mediated by NMDA receptors, cultured neurons and in the brains of 10-month-old APPSwe mice. In neurons that were cultured for 7–10 d were first treated with tetrodo- addition, STEP regulates amyloid-b–induced endocytosis of NMDA toxin (1 mM) for 2 h to reduce basal CREB phosphorylation and receptors. These findings are consistent with a role for STEP in then for an additional 1 h with tetrodotoxin and either amyloid-b1–42 regulation of NMDA transmission. Although it remains unclear which STEP substrates are essential (1 mM) or control medium. To stimulate CREB phosphorylation, neurons were treated with NMDA (10 mM) or the adenylyl in regulating receptor trafficking, our data indicate that STEP cyclase activator forskolin (100 mM) for 10 min. Treatment with regulates NR2B phosphorylation. Phosphorylation of the NR2B subamyloid-b did not affect basal phosphorylation of CREB (Fig. 7a). unit of the NMDA receptor at Tyr1472 is positively correlated with Treatment with NMDA robustly increased phosphorylation of NMDA currents39. This tyrosine is of interest as it regulates binding CREB, although this effect was reduced by amyloid-b treatment of the NMDA receptor to PSD-95 as well as to the clathrin adaptor (Fig. 7a). In control cultures, NMDA treatment increased CREB protein AP-2, and phosphorylation of this tyrosine may regulate phosphorylation by a factor of 7.1 ± 0.39 over basal amounts, interactions with endocytosis machinery30. Dephosphorylation of whereas in amyloid-b-treated cultures, NMDA treatment increased NR2B may trigger clathrin-coated endocytosis. Future studies should CREB phosphorylation by a factor of 4.20 ± 0.41 over basal address the role of the clathrin-coated machinery in the pathology of amounts (Fig. 7b). In control studies, forskolin increased CREB Alzheimer disease. phosphorylation by a factor of 14.9 ± 1.1 (Fig. 7b). After amyloid-b Alzheimer disease involves multiple neurological changes ranging treatment, forskolin increased CREB phosphorylation by a factor of from plaques and tangles to reduced synapse and neuron density and 13.7 ± 1.2 (n ¼ 4; Fig. 7b). inflammatory responses. Our data indicate that a critical signaling pathway allows amyloid-b to regulate synaptic function and plasticity. DISCUSSION Genetic or pharmacological inhibition of NMDA receptors reduces Despite a wide consensus that amyloid-b is a central causative factor in learning and memory in rodents, indicating that amyloid-b–induced Alzheimer disease, it remains unclear how this peptide causes synaptic loss of surface NMDA receptors may markedly affect memory


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ARTICLES and behavior. Further studies will be necessary to understand precisely how NMDA receptor endocytosis is regulated by amyloid-b and if and how this contributes to dementia. In addition, it will be of great interest to understand how secreted amyloid-b interacts with the amyloid-b that accumulates intracellularly, proximally to synapses. Both secreted and intracellular amyloid-b seem to affect synapses. Further exploration of the interaction of intracellular and extracellular amyloid-b at synapses may lead to a better understanding of Alzheimer disease pathology and may promote new therapeutic approaches for the disease.

ACKNOWLEDGMENTS We thank M. Greenberg for the gift of phospho-NR2B antibody and G. Thinakaran and S. Sisodia for the gift of stably transfected N2A cells. We also thank J. Shepherd and members of the Greengard and Gouras labs for helpful discussions. This work was supported by the Fisher Foundation for Alzheimer’s Research, US National Institutes of Health grant AG09464 (P.G.T. and G.K.G.) and National Institute of Mental Health grant 52711 and 01527 (P.J.L.). COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests.

METHODS Patch-clamp recordings. Whole-cell recordings were made from cortical neuron cultures using procedures described in detail previously14. All experiments were done in accordance with guidelines on animal research of Rockefeller University, University of Toronto or Cornell University. Recordings were made at room temperature (20–22 1C). After attaining the whole-cell configuration, the recorded neurons were voltage clamped using an Axopatch 1-D amplifier to 60 mV, except where indicated otherwise. The neurons were continually perfused with electrophysiological saline (ECS), containing 140 mM NaCl, 1.3 mM CaCl2, 5 mM KCl, 25 mM HEPES, 33 mM glucose, 500 nM tetrodotoxin and 10 mM bicuculline (pH 7.35, osmolarity 330 mOsm)), by a computer-controlled, multibarreled fast perfusion system. NMDA receptor currents were induced by 50 mM NMDA and 1 mM glycine. Data were recorded, digitized with DigiData1200A, filtered (2 kHz) and acquired by the pClamp8.1 program. Recordings in which the series resistance varied by more than 10% were rejected. The intracellular solution contained 20 mM CsCl, 125 mM CsCH3SO3, 2 mM MgCl2, 0.2 mM EGTA, 10 mM HEPES and 4 mM K2ATP, with pH 7.28 and 285 mOsm. Surface biotinylation assay. After treatment, neurons were placed on ice and rinsed in cold PBS. Neurons were then incubated in PBS containing 1.5 mg/ml sulfo-NHS-LC-biotin (Pierce) for 20 min at 4 1C. Neurons were rinsed twice in PBS and then lysed in 200 ml PBS with complete protease inhibitor cocktail (Roche) + 0.1% SDS + 1% Triton X-100. To determine the total protein concentration by immunoblotting, 10% of the cell lysate was removed and diluted in sample buffer. To isolate biotinylated proteins, 80% of the cell lysate was incubated with NeutrAvidin agarose (50 ml; Pierce). Western blots were carried out and data were quantified by comparing the ratio of biotinylated to total protein for a given culture and normalizing to control untreated cultures, unless stated otherwise. Cleavable biotinylation assay. Neurons were rinsed in PBS and then incubated with cold 1.5 mg/ml cleavable biotin reagent in PBS (EZ-Link Sulfo-NHS-SS biotin; Pierce) at 4 1C for 20 min. Cultures were then rinsed in warm medium and incubated at 37 1C in control medium or in medium containing amyloid-b for 15 min. Immediately after treatment, neurons were placed on ice and rinsed in cold stripping buffer (50 mM glutathione, 75 mM NaCl, 75 mM NaOH, 10% FBS, pH 8.5–9.0). Neurons were then lysed in 200 ml PBS with complete protease inhibitor cocktail (Roche) + 0.1% SDS + 1% Triton X-100. Lysates were briefly sonicated and centrifuged to remove insoluble material. Biotinylated proteins were isolated by incubation with NeutrAvidin agarose (50 ml; Pierce). Isolated proteins were rinsed in buffer three times and then boiled in 20 ml sample buffer. Western blots were then carried out. Quantification was done by comparing the densitometric value for internalized biotinylated protein in the presence of amyloid-b to the value in control cultures and normalizing to the value in control cultures. Generation and purification of myc-Tat and Tat-STEP46 S-A/C-S fusion protein. STEP46 S-A/C-S was rendered cell permeable by inserting Tat (YGRKKRRQRRR), the cell membrane transduction domain of HIV type 1 (ref. 40), at the amino terminus using PCR. Tat-STEP46 S-A/C-S (dnSTEP-Tat) was then cloned in the bacterial expression vector pTrcHis2-TOPO (Invitrogen) and transformed into Escherichia coli BL21 for high expression of the fusion protein. The fusion protein was purified using TALON metal affinity resin (Clontech) according to manufacturer’s protocol. The myc-Tat peptide was synthesized by the W.M. Keck Biotechnology Resource Center at Yale University.


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Received 18 April; accepted 22 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Perdahl, E., Wu, W.C., Browning, M.D., Winblad, B. & Greengard, P. Protein III, a neuronspecific phosphoprotein: variant forms found in human brain. Neurobehav. Toxicol. Teratol. 6, 425–431 (1984). 2. Terry, R.D. et al. Physical basis of cognitive alterations in Alzheimer’s disease: synapse loss is the major correlate of cognitive impairment. Ann. Neurol. 30, 572–580 (1991). 3. Takahashi, R.H. et al. Oligomerization of Alzheimer’s b-amyloid within processes and synapses of cultured neurons and brain. J. Neurosci. 24, 3592–3599 (2004). 4. Selkoe, D.J. Alzheimer’s disease is a synaptic failure. Science 298, 789–791 (2002). 5. Hardy, J. & Selkoe, D.J. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297, 353–356 (2002). 6. Chapman, P.F. et al. Impaired synaptic plasticity and learning in aged amyloid precursor protein transgenic mice. Nat. Neurosci. 2, 271–276 (1999). 7. Freir, D.B., Holscher, C. & Herron, C.E. Blockade of long-term potentiation by b-amyloid peptides in the CA1 region of the rat hippocampus in vivo. J. Neurophysiol. 85, 708– 713 (2001). 8. Kim, J.H., Anwyl, R., Suh, Y.H., Djamgoz, M.B. & Rowan, M.J. Use-dependent effects of amyloidogenic fragments of (b)-amyloid precursor protein on synaptic plasticity in rat hippocampus in vivo. J. Neurosci. 21, 1327–1333 (2001). 9. Malenka, R.C. Synaptic plasticity and AMPA receptor trafficking. Ann. NY Acad. Sci. 1003, 1–11 (2003). 10. Naslund, J. et al. Correlation between elevated levels of amyloid b-peptide in the brain and cognitive decline. J. Am. Med. Assoc. 283, 1571–1577 (2000). 11. Kamenetz, F. et al. APP processing and synaptic function. Neuron 37, 925–937 (2003). 12. Snyder, E.M. et al. Internalization of ionotropic glutamate receptors in response to mGluR activation. Nat. Neurosci. 4, 1079–1085 (2001). 13. Roche, K.W. et al. Molecular determinants of NMDA receptor internalization. Nat. Neurosci. 4, 794–802 (2001). 14. Nong, Y. et al. Glycine binding primes NMDA receptor internalization. Nature 422, 302–307 (2003). 15. Scott, D.B., Michailidis, I., Mu, Y., Logothetis, D. & Ehlers, M.D. Endocytosis and degradative sorting of NMDA receptors by conserved membrane-proximal signals. J. Neurosci. 24, 7096–7109 (2004). 16. Mammen, A.L., Huganir, R.L. & O’Brien, R.J. Redistribution and stabilization of cell surface glutamate receptors during synapse formation. J. Neurosci. 17, 7351–7358 (1997). 17. Rao, A. & Craig, A.M. Activity regulates the synaptic localization of the NMDA receptor in hippocampal neurons. Neuron 19, 801–812 (1997). 18. Ehlers, M.D. Reinsertion or degradation of AMPA receptors determined by activitydependent endocytic sorting. Neuron 28, 511–525 (2000). 19. Ehlers, M.D. Activity level controls postsynaptic composition and signaling via the ubiquitin-proteasome system. Nat. Neurosci. 6, 231–242 (2003). 20. Cai, D. et al. Presenilin-1 regulates intracellular trafficking and cell surface delivery of b-amyloid precursor protein. J. Biol. Chem. 278, 3446–3454 (2003). 21. Wang, H.Y. et al. b-Amyloid(1–42) binds to a7 nicotinic acetylcholine receptor with high affinity. Implications for Alzheimer’s disease pathology. J. Biol. Chem. 275, 5626– 5632 (2000). 22. Dineley, K.T. et al. b-amyloid activates the mitogen-activated protein kinase cascade via hippocampal a7 nicotinic acetylcholine receptors: In vitro and in vivo mechanisms related to Alzheimer’s disease. J. Neurosci. 21, 4125–4133 (2001). 23. Levy, R.B. & Aoki, C. a7 nicotinic acetylcholine receptors occur at postsynaptic densities of AMPA receptor-positive and -negative excitatory synapses in rat sensory cortex. J. Neurosci. 22, 5001–5015 (2002). 24. Shi, J., Townsend, M. & Constantine-Paton, M. Activity-dependent induction of tonic calcineurin activity mediates a rapid developmental downregulation of NMDA receptor currents. Neuron 28, 103–114 (2000). 25. Stevens, T.R., Krueger, S.R., Fitzsimonds, R.M. & Picciotto, M.R. Neuroprotection by nicotine in mouse primary cortical cultures involves activation of calcineurin and L-type calcium channel inactivation. J. Neurosci. 23, 10093–10099 (2003). 26. Wang, Y.T. & Salter, M.W. Regulation of NMDA receptors by tyrosine kinases and phosphatases. Nature 369, 233–235 (1994).

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ARTICLES 27. Vissel, B., Krupp, J.J., Heinemann, S.F. & Westbrook, G.L. A use-dependent tyrosine dephosphorylation of NMDA receptors is independent of ion flux. Nat. Neurosci. 4, 587–596 (2001). 28. Pelkey, K.A. et al. Tyrosine phosphatase STEP is a tonic brake on induction of long-term potentiation. Neuron 34, 127–138 (2002). 29. Paul, S., Nairn, A.C., Wang, P. & Lombroso, P.J. NMDA-mediated activation of the tyrosine phosphatase STEP regulates the duration of ERK signaling. Nat. Neurosci. 6, 34–42 (2003). 30. Lavezzari, G., McCallum, J., Lee, R. & Roche, K.W. Differential binding of the AP-2 adaptor complex and PSD-95 to the C-terminus of the NMDA receptor subunit NR2B regulates surface expression. Neuropharmacology 45, 729–737 (2003). 31. Shaywitz, A.J. & Greenberg, M.E. CREB: a stimulus-induced transcription factor activated by a diverse array of extracellular signals. Annu. Rev. Biochem. 68, 821–861 (1999). 32. Tong, L., Thornton, P.L., Balazs, R. & Cotman, C.W. b-amyloid-(1–42) impairs activitydependent cAMP-response element-binding protein signaling in neurons at concentrations in which cell survival is not compromised. J. Biol. Chem. 276, 17301–17306 (2001). 33. Shieh, P.B., Hu, S.C., Bobb, K., Timmusk, T. & Ghosh, A. Identification of a signaling pathway involved in calcium regulation of BDNF expression. Neuron 20, 727–740 (1998).

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34. Tao, X., Finkbeiner, S., Arnold, D.B., Shaywitz, A.J. & Greenberg, M.E. Ca2+ influx regulates BDNF transcription by a CREB family transcription factor-dependent mechanism. Neuron 20, 709–726 (1998). 35. Riccio, A., Ahn, S., Davenport, C.M., Blendy, J.A. & Ginty, D.D. Mediation by a CREB family transcription factor of NGF-dependent survival of sympathetic neurons. Science 286, 2358–2361 (1999). 36. Taubenfeld, S.M., Milekic, M.H., Monti, B. & Alberini, C.M. The consolidation of new but not reactivated memory requires hippocampal C/EBPb. Nat. Neurosci. 4, 813–818 (2001). 37. Yamamoto-Sasaki, M., Ozawa, H., Saito, T., Rosler, M. & Riederer, P. Impaired phosphorylation of cyclic AMP response element binding protein in the hippocampus of dementia of the Alzheimer type. Brain Res. 824, 300–303 (1999). 38. Valjent, E. et al. Regulation of a protein phosphatase cascade allows convergent dopamine and glutamate signals to activate ERK in the striatum. Proc. Natl. Acad. Sci. USA 102, 491–496 (2005). 39. Alvestad, R.M. et al. Tyrosine dephosphorylation and ethanol inhibition of N-methyl-Daspartate receptor function. J. Biol. Chem. 278, 11020–11025 (2003). 40. Schwarze, S.R., Ho, A., Vocero-Akbani, A. & Dowdy, S.F. In vivo protein transduction: delivery of a biologically active protein into the mouse. Science 285, 1569–1572 (1999).

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Mice lacking Dlx1 show subtype-specific loss of interneurons, reduced inhibition and epilepsy Inma Cobos1, Maria Elisa Calcagnotto2, Alex J Vilaythong3, Myo T Thwin1, Jeffrey L Noebels3, Scott C Baraban2 & John L R Rubenstein1 Dlx homeodomain transcription factors are essential during embryonic development for the production of forebrain GABAergic interneurons. Here we show that Dlx1 is also required for regulating the functional longevity of cortical and hippocampal interneurons in the adult brain. We demonstrate preferential Dlx1 expression in a subset of cortical and hippocampal interneurons which, in postnatal Dlx1 mutants, show a time-dependent reduction in number. This reduction preferentially affects calretinin1 (bipolar cells) and somatostatin1 subtypes (for example, bitufted cells), whereas parvalbumin1 subpopulations (basket cells and chandelier cells) seem to be unaffected. Cell transplantation analysis demonstrates that interneuron loss reflects cell-autonomous functions of Dlx1. The decrease in the number of interneurons was associated with a reduction of GABA-mediated inhibitory postsynaptic current in neocortex and hippocampus in vitro and cortical dysrhythmia in vivo. Dlx1 mutant mice show generalized electrographic seizures and histological evidence of seizure-induced reorganization, linking the Dlx1 mutation to delayed-onset epilepsy associated with interneuron loss.

GABAergic interneurons are central to the regulation of cortical and hippocampal intrinsic activity through their direct inhibitory effects on excitatory neurons. Defects in GABAergic function, through either alterations in presynaptic GABA levels or postsynaptic response at GABA receptors, lead to an imbalance in inhibitory and excitatory circuits, which can cause epilepsy1. At the cellular level, GABAergic inhibition is important in regulating local circuit processes (that is, information coding and synaptic plasticity)2 and synchronizing network oscillations (gamma and theta rhythms implicated in cognitive processes)3,4. Cortical inhibition is mediated by a complex set of distinct GABAproducing interneuron subtypes5. Cortical interneurons have been classified according to their axonal or dendritic morphology (for instance, basket, chandelier, bitufted and bipolar cells)6,7 using neurochemical markers such as Ca2+ -binding proteins and neuropeptides8–10 as well as by analyzing their intrinsic neuronal firing properties11 and network interconnections12,13. Approaches that integrate morphological, molecular and physiological characteristics are providing insights into the diversity and functions of interneurons. Most GABAergic interneurons in the telencephalon are derived from subpallial progenitors in the medial ganglionic eminence (MGE) and migrate tangentially to cortex and hippocampus14–18, although in humans there is evidence for a pallial origin as well19. Several transcription factors have been identified that control interneuron development. Mice lacking function of Nkx2.1, a homeobox gene required for MGE specification, form only one-half as many

cortical interneurons as normal mice15,17,18. The Dlx family of homeobox transcription factors (Dlx1, Dlx2, Dlx5 and Dlx6) is expressed in overlapping domains at different stages of cell differentiation in the subpallium and controls differentiation of GABAergic neurons20. Whereas neonatal Dlx single mutants show no overt defects in GABAergic development21,22, tangential migration is blocked in Dlx1/Dlx2 double mutants, and the mutants show a 475% reduction of interneurons in neocortex and 495% reduction in hippocampus20,23. The Arx homeobox transcription factor, which is regulated by Dlx genes24, is also required for migration of interneurons. Mutations in the human ortholog ARX cause X-linked mental retardation and epilepsy25. Although little is known about mechanisms that control later steps of interneuron differentiation, aside from the role of neural activity and neurotrophins26, it is probable that transcription factors (such as Dlx1) expressed in these cells27 participate in their maturation and function. Here, we report that mice lacking Dlx1 function show an agedependent, cell subtype–specific reduction of cortical and hippocampal interneurons. This cell loss is due to apoptotic cell death of subsets of Dlx1-expressing cells. Using transplantations of Dlx1/ interneuron precursors into wild-type neonatal mice, we demonstrate cellautonomous functions of Dlx1 in controlling interneuron maturation and survival. Reduced interneuron numbers are associated with a reduction of GABA-mediated synaptic inhibition in neocortex and hippocampus. As a result, Dlx1/ mice develop behavioral, histological and electrographic signs of epilepsy.

1Nina Ireland Laboratory of Developmental Neurobiology, Department of Psychiatry, University of California San Francisco, San Francisco, California 94158, USA. 2Epilepsy Research Laboratory, Department of Neurological Surgery, University of California San Francisco, San Francisco, California 94143, USA. 3Developmental Neurogenetics Laboratory, Department of Neurology, Baylor College of Medicine, Houston, Texas 77030, USA. Correspondence should be addressed to I.C. ([email protected]) or J.L.R.R. ([email protected]).



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RESULTS Cell subtype–specific expression of Dlx1 in interneurons During forebrain development, the expression of Dlx genes coincides with that of Gad genes Gad1 and Gad2 (also known as Gad67 and Gad65, respectively), which encode the 67- and 65-kDa isoforms, respectively, of glutamate decarboxylase, the enzyme that synthesizes GABA23,27. Here we analyzed expression of Dlx1, the member of the Dlx family with most robust expression in postnatal cortex27,28. Comparison of Dlx1 and Gad67 expression in neocortex and hippocampus showed that not all GABAergic neurons were Dlx1+; rather, only 45% of Gad67+ neurons were Dlx1+ (1-month-old; n ¼ 5; Fig. 1a,b,d,e). To address whether specific subtypes of cortical interneurons express Dlx1, we conducted double-labeling for Dlx1 (detected by in situ hybridization) and either parvalbumin, somatostatin or calretinin (detected by immunohistochemistry; 1-month-old; n ¼ 3; Fig. 1g–j). Parvalbumin+, somatostatin+ and calretinin+ cortical cells are largely nonoverlapping subgroups of interneurons in rodents10,29. We detected Dlx1 expression in B5% of parvalbumin+ interneurons (5.2 7 3.1%). In contrast, we detected Dlx1 expression in the majority of somatostatin+ (90.8 7 5.2%) and calretinin+ interneurons (98.7 7 3%). Neuropeptide Y+ (NPY+) interneurons, some of which are also somatostatin+ (ref. 9), were nearly all Dlx1+ (97.5 7 4.8%). Notably, expression of Lhx6, a LIM-homeobox transcription factor that also regulates cortical interneuron development30, was detected primarily in parvalbumin+ interneurons (93.8 7 5.1%) and a subset of somatostatin+ interneurons (54.8 7 4.8%), and was not detected in NPY+ (3.1 7 2.2%) and calretinin+ neurons (2.2 7 3.7%; Fig. 1c,f,k–n). These cellular expression patterns were maintained in older animals (2–6 months old; data not shown). Thus, in the adult cortex, Dlx1 expression marks calretinin+ and somatostatin+/NPY+ interneurons and is nearly excluded from parvalbumin+ interneurons. Age-dependent reduction of GABAergic neurons in Dlx1/ Homozygous Dlx1 mutant mice have a normal appearance at birth22. We maintained Dlx1/ mice on a mixed genetic background (C57BL/6J;CD1); 50% of the pups had survival rates and weight comparable to wild-type littermates. To study Dlx1 function in interneurons, we analyzed the phenotype of Dlx1 mutants through

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Figure 1 Dlx1 is expressed in subsets of cortical and hippocampal GABAergic interneurons. (a–f) Expression of Gad67 (a,d), Dlx1 (b,e) and Lhx6 (c,f) mRNA in coronal sections through somatosensory cortex (a–c) and hippocampus (d–f) in 1-month-old mice. Roman numerals denote cortical layers. (g–n) Double in situ hybridization and immunohistochemistry staining for either Dlx1 or Lhx6 mRNAs (blue) and either parvalbumin (PV), somatostatin (SOM), neuropeptide Y (NPY) or calretinin (CR; brown) in neocortex of 1-month-old mice. Arrowheads indicate double-positive cells. Abbreviations: DG, dentate gyrus; h, hilus. Scale bars: 250 mm (a–c, d–f); 25 mm (g–n).

n

postnatal stages and adulthood. First, we examined expression of Gad67 (at postnatal day 12 (P12); P20; and 1, 2 and 6 months). At P12, Gad67+ cells appeared normal in Dlx1/ pups, based on number and layer distribution (Supplementary Fig. 1), suggesting that tangential migration of GABAergic precursors from MGE and ability to integrate into the cortical plate was not perturbed. In contrast, the number of Gad67-expressing neurons in neocortex and hippocampus had decreased by the time mice were 1 month old (Fig. 2). Although Dlx1 is also expressed in other regions of the forebrain, including olfactory bulb interneurons, thalamic reticular nucleus and some hypothalamic nuclei27,28, no changes in Gad expression were detected in these locations (Fig. 2a,e; data not shown). The reduction of Gad67 did not show substantial regional differences within the examined cortical areas (cingulate cortex, piriform cortex, somatosensory and visual cortex). We selected somatosensory cortex and hippocampus (dentate gyrus, CA3 and CA1) to quantify the number of Gad67+ neurons in Dlx1/ and wild-type littermates (Fig. 2m). In somatosensory cortex, mutants between 1 and 2 months of age showed a B22% reduction of Gad67+ cells (1 month: 22.3 7 2.1%, P ¼ 0.03, n ¼ 6; 2 months: 22 7 0.8%, P ¼ 0.03, n ¼ 5; Fig. 2f–h,m). In hippocampus, this reduction was 33.6 7 3% in dentate gyrus, 26.4 7 3.5% in CA3 and 29 7 2.7% in CA1 at 2 months of age (P o 0.05, n ¼ 5; Fig. 2i–m). In older mutants (6 months old) the number of Gad+ cells did not show further reductions (somatosensory cortex: 17.4 7 3.3%, P ¼ 0.02; CA1: 26.7 7 3.9%, P ¼ 0.039, n ¼ 5; Fig. 2h,m). GABAergic neuron subtype–specific reduction in Dlx1/ As Dlx1 was specifically detected in distinct neurochemical subtypes of GABAergic neurons, including somatostatin- and calretinin-expressing neurons, we tested the hypothesis that these specific subtypes would be reduced in Dlx1/ mice. As with Gad67, we did not observe significant differences in expression of interneuron markers at early postnatal stages (P12). In contrast, somatostatin+ and calretinin+ interneurons were significantly reduced in animals older than one month (Fig. 3 and Supplementary Figs. 2,3). Somatostatin+ neurons were reduced by B23% in somatosensory cortex and by B33% in CA1 in 1- to 2-month-old mutants (cortex; 1 month: 23 7 2.9%, P ¼ 0.04; 2 months: 24.5 7 3.8%, P ¼ 0.04; CA1; 1 month: 33 7 1.4%, P ¼ 0.01; 2 months: 33.8 7 2.1%, P ¼ 0.001, n ¼ 5; Fig. 3g,p,s).

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ARTICLES Figure 2 Number of GABAergic interneurons is reduced in neocortex and hippocampus of Dlx1/ mice. (a–h) Expression of Gad67 mRNA in coronal sections from 1- to 6-month-old wild-type (a–d) and Dlx1/ (e–h) littermates. Sections (b–d; f–h) correspond to somatosensory cortex (bregma level –0.82 mm); roman numerals denote cortical layers. (i–l) Expression of Gad67 mRNA (10-mm-thick sections) and GABA (40 mm-thick sections) in hippocampus of 2-month-old wild-type and Dlx1/ littermates. (m) Quantification of the number of Gad67+ cells in somatosensory cortex (black) and CA1 field of hippocampus (gray) from P12, P20 and 1-, 2- and 6-month-old mice. Values are normalized to wild-type (white). A, amygdala; DG, dentate gyrus; HT, hypothalamus; RN, reticular nucleus of the thalamus; Cx, neocortex; m, month. Scale bars: 500 mm (a,e); 250 mm (b–d; f–h; i–l).

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Finally, consistent with nearly undetectable Dlx1 expression in the parvalbumin interneuron subclass, the number of parvalbumin+ cells did not change significantly in Dlx1/ mice. Lhx6+ and calbindin+ interneurons, which both label some parvalbumin+ cells8,9, were not affected either (Supplementary Fig. 2). Thus, using a diverse set of interneuron molecular markers we identified a specific reduction of somatostatin+ and calretinin+ subclasses in Dlx1/ mice.

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Apoptotic cell death of GABAergic neurons in Dlx1/ We next investigated whether reduction of interneuron markers in Dlx1/ mice was due to reduced transcription of these markers or to cell death. This is important given that Dlx transcription factors are able to induce Gad expression33. On the other hand, we obtained evidence that Dlx genes do not regulate expression of other markers that were reduced in Dlx1/ mice (Supplementary Fig. 4). To resolve this question, first we analyzed GABA expression in interneurons of Dlx1/ and wild-type littermates (1 month old, Fig. 4a–h). We took advantage of easily discernible laminar organization of the hippocampus, with GABAergic neurons localized in specific layers (for example, stratum oriens), to quantify the numbers of GABA+ profiles among NeuN+ (a general neuronal marker) cells. Whereas the number of both NeuN+ and GABA+ cells was reduced by one-third in Dlx1/ mice, GABA expression was not reduced in NeuN+ cells, as shown by the similar percentage of double-labeled

P11 P20 1 m 2 m 6 m

The number of NPY+ interneurons, some of which are also somatostatin+ (ref. 9), decreased 42.3 7 2.1% in somatosensory cortex and 34.5 7 1.1% in CA1 at 2 months (P o 0.001, n ¼ 5; Fig. 3h,q,s). The enzyme nitric oxide synthase (NOS) is expressed by a small fraction of somatostatin+ interneurons10. In Dlx1/ mice, the number of NOS+ cells was diminished (Fig. 3i). Calretinin+ interneurons, a separate interneuron subclass5,10,29, decreased 30.1 7 3.4% in somatosensory cortex and 52 7 2% in CA1 in 2-month-old mutants (P o 0.05, n ¼ 5; Fig. 3j,r,s). Expression of reelin, which is largely restricted to subsets of GABAergic interneurons that co-express somatostatin/NPY and calretinin in adult neocortex31, was reduced, both at the mRNA (Fig. 3f) and protein level (data not shown). Expression of the helix-loop-helix-PAS transcription factor N-PAS1, which overlaps with calretinin and reelin in cortical interneurSOM ons32, was also diminished (Fig. 3l). These a b reductions were no larger in older mutants (2–6 months; data not shown).

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Figure 3 Subtype-specific reduction of interneurons in Dlx1/ mice. (a–f) Expression of somatostatin (SOM), NPY, nitric oxide synthase (NOS), calretinin (CR), reelin and N-PAS1 in somatosensory cortex of 2-month-old wild-type (a–f) and Dlx1/ (g–l) littermates, shown by either in situ RNA hybridization (SOM, reelin and N-PAS1; 10-mm-thick sections) or immunohistochemistry (NPY, NOS and CR; 40-mm-thick sections). (m–r) Expression of SOM, NPY and CR in hippocampus of 2-month-old wild-type and Dlx1/ littermates. Insets in d, j, o, and r show higher-magnification images from the boxed areas. (s) Number of SOM+, NPY+ and CR+ cells in somatosensory cortex (black) and CA1 field of hippocampus (gray) in P12 and 1- and 2-month-old mice. Values are normalized to wild-type (white). Scale bars: 250 mm (a–l; m–r).


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GABA/NeuN+ cells in the mutant and control conditions (Fig. 4g,h), suggesting that neuronal loss, rather than reduction of GABA expression, accounts for the reduction in number of interneurons. To assess programmed neuronal death in Dlx1/ mice we performed two different apoptosis assays, TUNEL staining and anti–active caspase-3 immunohistochemistry (P20–P60; Fig. 4i–s). TUNEL+ and active caspase-3+ profiles were rarely observed in neocortex of wild-type mice. In contrast, the number of TUNEL+ nuclei was roughly fivefold greater in P20–P30 Dlx1/ mice than in wild-type littermates (Fig. 4r and Supplementary Fig. 5). Similarly, active caspase-3+ profiles increased approximately fourfold (Fig. 4s). Animals older than P30 did not show a significant increase in apoptosis (data not shown). At least some of the cells that underwent apoptosis in Dlx1/ mice were interneurons, as shown by TUNEL or anti–active caspase-3 labeling along with anti-NeuN fluorescence immunohistochemistry, in hippocampus (stratum radiatum; Fig. 4i–n), and by TUNEL and anti-NPY immunohistochemistry in neocortex (Fig. 4o–q). Thus, these results show increased levels of GABAergic neuron cell death in Dlx1/ mice during the period when there is a reduction in Gad67+ interneurons. Cell-autonomous loss of GABAergic neurons in Dlx1/ To determine whether interneuron loss in Dlx1/ mice was due to cell autonomous defects, we performed transplantations of GFP-expressing interneuron precursors from Dlx1/ embryos into wild-type neonatal brains (Fig. 5). Grafted interneuron precursors from embryonic MGE are able to migrate to neocortex and differentiate into distinct GABAergic neuron suptypes16. We quantified the percentage of neurons that differentiated into GABA-, parvalbumin-, somatostatin- and NPY-expressing cells after transplants from Dlx1/ and Dlx1+/+ littermate donors (Fig. 5a–d). In adult brains (2–6 months old), approximately 75% of GFP-expressing cells were immunoreactive for GABA for both Dlx1+/+ and Dlx1/ transplants. Parvalbumin-expressing cells represented nearly half of GFP+ cells from both donors. In contrast, somatostatin-expressing neurons were reduced by about one-third and NPY-expressing cells were reduced B60% in grafted cells from Dlx1/ transplants, as compared with Dlx1+/+ transplants (Dlx1/: somatostatin, 23.88 7 2.32%; NPY, 3.2 7 0.3%; Dlx1+/+: somatostatin, 37.45 7 2.9%, P ¼ 0.01; NPY: 8.2 7 0.6%, P ¼ 0.005; Fig. 5d). Brains analyzed 2–3 weeks after transplantations did not show significant differences (data

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Figure 4 The reduction of GABAergic neurons in Dlx1/ mice is due to apoptotic cell death. (a–f) Confocal immunofluorescence images of antiNeuN and anti-GABA staining in CA1 of 1-month-old Dlx1/ and wild-type littermates. Arrows in c,f indicate double-positive cells. (g) Total number of NeuN+ cells and total number of GABA+ cells in stratum oriens (so) is lower in Dlx1/ mice (NeuN: 16.56 7 1.16; GABA: 15.11 7 1.02) than in controls (NeuN: 23.33 7 1.52, P o 0.01; GABA: 22.67 7 1.62, P o 0.01). (h) Percentage of GABA/NeuN+ cells in Dlx1/ mice did not change compared with controls (mutant: 92.23 7 4.8%; control: 97.94 7 5.3%; P ¼ 0.38). (i–k) Double fluorescence–labeled interneurons shown by TUNEL or with anti-active caspase-3 immunohistochemistry combined with anti-NeuN and anti-NPY staining from 1-month-old Dlx1/ mice. i–n correspond to stratum radiatum of hippocampus; o–q correspond to neocortex. (r,s) Number of TUNEL+ and active caspase-3+ profiles in neocortex from 1-month-old Dlx1/ and wild-type littermates. Values are normalized to wild-type. Student’s t-test shows a significant increase in apoptotic figures in Dlx1/ mice compared with controls (TUNEL: 4.74 7 0.34, P o 0.001; caspase-3: 3.74 7 0.43, P o 0.001). Abbreviations: so, stratum oriens, sp, stratum pyramidale. Scale bars: 50 mm (a–f); 10 mm (i–q).

not shown). These data are consistent with a cell-autonomous defect of somatostatin+/NPY+ interneurons that affects their survival. To further characterize deficits in transplanted somatostatin+/NPY+ interneurons, we analyzed the morphology of bitufted cells (somatostatin+) at early stages after transplantation (10 d), when the number of interneurons was unaffected. Dendritic arborization of grafted bitufted cells was apparent in relatively isolated interneurons in neocortex (Fig. 5e–j). Quantification of dendrite morphology showed that mutant bitufted cells have poorly differentiated dendrites. Notably, total interneuron branch length was reduced B45% and total number of branches was reduced B40% in mutant bitufted cells compared with wild-type donors (Dlx1/: total interneuron branch length, 282.07 7 17 mm; number of branches: 8.68 7 0.57; Dlx1+/+: total interneuron branch length, 510.13 7 24.36 mm, P o 0.001; number of branches, 14 7 0.74, P o 0.001; Fig. 5k–n). In adult brains (2–6 months), few cells with clear bitufted morphology were observed in grafts from Dlx1/ donors. In contrast, Dlx1/ donor cells differentiated, like wild-type donors, into basket and chandelier cells, both of which are parvalbumin+ (Fig. 5o–q). Taken together, these data are consistent with a cell-autonomous role of Dlx1 in controlling dendritic maturation and survival of subsets of cortical interneurons. Reduction of GABA-mediated synaptic inhibition in Dlx1/ To determine whether fewer GABA-producing neurons and/or interneurons with poorly differentiated dendrites would result in a functional change, we compared whole-cell inhibitory postsynaptic currents (IPSCs) from Dlx1/ and wild-type littermates. We first compared the kinetic properties of spontaneous and miniature IPSCs (sIPSCs and mIPSCs) recorded from neocortical layer II/III and hippocampal CA3 pyramidal neurons and found that 10 mM bicuculline abolished IPSCs (n ¼ 30), confirming the involvement of GABAA receptors. Recordings were made at a holding potential of 0 mV (the reversal potential for glutamate-mediated currents) in artificial cerebrospinal fluid (ACSF) containing glutamate receptor antagonists34 (20 mM CNQX or DNQX plus 50 mM AP5). Spontaneous IPSC analysis showed significant reductions in frequency and amplitude in 2-monthold mutants. Average sIPSC frequency was reduced in neocortical (B50%; n ¼ 37) and CA3 pyramidal cells (B60%; n ¼ 21) when compared with controls (n ¼ 16, 21); amplitude was reduced to B70% of control for neocortical (and B65% of control for CA3) pyramidal cells (Fig. 6 and Supplementary Fig. 6). To further characterize the

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Figure 5 Cell transplantation experiments show a cell-autonomous role for Dlx1 in controlling maturation and survival of subsets of cortical interneurons. (a–c) Neocortical interneurons differentiated from GFPexpressing Dlx1/ precursors, as shown by double immunofluorescence with either anti-PV, anti-SOM or anti-NPY along with anti-GFP antibodies. (d) Percentage of double-labeled cells (GFP+GABA, GFP+PV, GFP+SOM, GFP+NPY) in neocortex of 2- to 6-month-old mice grafted with Dlx1+/+ (white) and Dlx1/ (black) cells. (e–j) Morphology of bitufted interneurons in neocortex of early postnatal animals with grafts from control (e–g) and mutant (h–j) cells, as shown by anti-GFP immunohistochemistry. (k–n) Quantification of dendrite branching of bitufted interneurons differentiated from Dlx1+/+ (white) and Dlx1/ (black) grafts. (o–q) Morphology of grafted neocortical interneurons in 2-month-old mice, as shown by anti-GFP immunohistochemistry: basket cell (o) and chandelier cell (p) differentiated from mutant interneuron precursors (inset: highermagnification image of area in box; note typical vertical axons of these cells (arrows)); bitufted cell (q) differentiated from wild-type graft. Scale bars: 50 mm (a–c; e–j); 100 mm (o–q).

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Behavioral and histological signs of epilepsy in Dlx1/ Interneuron loss and reduction in synaptic inhibition may contribute to a hyperexcitable and epileptic phenotype35. Loss of NPY-containing and somatostatin-containing interneurons could lead to further functional deficit as these neuropeptides exert endogenous antiepileptic properties36. Therefore, we observed Dlx1/ mice for seizure activity. Seizures were reliably induced in animals over 2 months of age by mild stressors, such as noise or handling (n ¼ 25). To assess the severity of seizures, we exposed 19 mutants to noise and handling (30 s) and scored behavioral seizure activity on a five-stage scale, as described previously37. Fourteen mice (73.7%) showed seizure-like behavior; four showed stage III seizures, three stage IV, and seven stage V. Two of these seven mice (10.5%) died following a generalized tonicclonic seizure. Seizures are often associated with specific changes in immediateearly gene expression35. To determine whether similar changes occur in


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reduction in GABA-mediated synaptic inhibition, tetrodotoxin (1 mM) was added to the ACSF to isolate mIPSCs. Significant decreases in mIPSC frequency were observed in 1-month-old Dlx1 mutants, in neocortical (B60%) and CA3 pyramidal neurons (B70%). In 2month-old mutants, mIPSC frequencies in both cell types were reduced by B50% (Fig. 6d,f and Supplementary Fig. 6). Cumulative probability plots and Kolmogorov-Smirnov statistical analysis further confirmed reductions in IPSC amplitude or frequency (Fig. 6c–j). Histograms of sIPSC amplitudes for all cells showed a shift to smallamplitude events in Dlx1/ mice (Fig. 6h,j). Finally, to assess selective defects in interneurons that potentially innervate dendrites of excitatory neurons (that is, somatostatin+ interneurons5,29) we analyzed the kinetics of individual mIPSCs. Reductions in the relative number of slow-decay, small-amplitude IPSC events, characteristic of dendriteinnervating interneurons, were not detected (Supplementary Fig. 7). On the other hand, no significant changes in sIPSC decay time constant or 10–90% rise time were noted, suggesting that GABA receptor or transporter function is not altered in these mice (Supplementary Table 1). Consistent with this, analysis of evoked GABAmediated inhibitory postsynaptic currents (eIPSC) showed no differences in amplitude, 10–90% rise time or decay time constant between mutant and control neurons (n ¼ 20; data not shown). Thus, decreased IPSC frequency with no change in eIPSCs suggests a reduction in inhibitory synaptic input in neocortex and hippocampus of Dlx1/ mice; this is consistent with histological observations of a reduction in the number of GABAergic interneurons.

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Dlx1/ mice, four animals that had stress-induced tonic-clonic stage V seizures were killed 90 min after one episode and were immunoassayed for expression of c-Fos, a calcium-dependent immediate-early gene product. Consistent with seizure activity, c-Fos expression in the hippocampus was elevated in pyramidal cells of CA1 and CA3 and was most intense in dentate granule cells (Fig. 7a–c). Epilepsy is often associated with complex seizure-induced histological changes in cerebral cortex and hippocampus (for example, neuronal death; increased levels of Gad, somatostatin and NPY in interneurons; ectopic expression of NPY in projecting neurons and axonal sprouting)35,36. Many of these histological changes were detected in Dlx1 mutants that were at least 2 months old (Fig. 7d– h). We found increased NPY immunoreactivity in hippocampus, neocortex, piriform cortex and amygdala (Fig. 7d,e). Notably, in hippocampus, ectopic NPY immunoreactivity was detected in mossy fibers of dentate granule cells (DGC; Fig. 7g,h). This was observed in 10 out of 12 mutants, both in animals with and without observed seizures. Ectopic NPY immunoreactivity was also detected in the inner molecular layer of the dentate gyrus in two of these mutants (Fig. 7h). This ectopic NPY expression corresponded to sprouting of mossy fibers, as shown by their labeling with Timm’s staining (Fig. 7i,j). Neither ectopic

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NPY immunoreactivity in DGC mossy fibers nor mossy fiber sprouting was detected in 1-month-old Dlx1 mutants (n ¼ 6), consistent with the absence of seizures at this age. Cortical dysrhythmia and epilepsy in Dlx1/ Because these histological, electrophysiological and behavioral studies are consistent with a hypothesis that aged Dlx1/ mice may develop a spontaneous epileptic phenotype, we monitored four animals (6–10 months old) using a video electroencephalogram (EEG) system. Background cortical activity recorded in Dlx1/ mice showed an approximately twofold increase in theta rhythm amplitudes during exploratory activity compared with wild-type littermates (Fig. 8a,b). These rhythms, shaped by inhibitory interneuron firing patterns in response to novel environments, are a normal feature of hippocampal function in the behaving rodent; however, they are weakly expressed in neocortex38. A second abnormality was the occurrence of generalized interictal synchronous discharges at rates from 0.5 to 20 min1 (not shown).

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Figure 6 GABAergic synaptic inhibition is decreased in neocortex and hippocampus of Dlx1/ mice. Recordings obtained in ACSF containing DNQX and AP5. (a, b) Representative traces of sIPSCs and mIPSCs from cortical layer II/III and CA3 pyramidal cells of 2-month-old Dlx1+/+ and Dlx1/ mice. (c–f) Cumulative probability plots of sIPSCs and mIPSCs interevent intervals from neocortical and CA3 pyramidal cells show lower IPSC frequencies for Dlx1/ mice (Dlx1/, red; Dlx1+/+; black; Kolmogorov-Smirnov test, P o 0.001). Average sIPSC and mIPSC frequencies (inset) were lower in neocortical and CA3 pyramidal neurons from Dlx1/ mice (sIPSC: neocortex, 1.2 7 0.3 Hz; CA3, 1.5 7 0.2 Hz; mIPSC: neocortex, 1.1 7 0.1 Hz; CA3, 1.3 7 0.2 Hz) than in controls (sIPSC neocortex, 3.2 7 0.4 Hz; CA3; 4.2 7 0.7 Hz; mIPSC neocortex: 2.4 7 0.2 Hz; CA3, 2.9 7 0.2 Hz). (g,i) Cumulative probability plots of sIPSC amplitude from neocortical and CA3 pyramidal cells show lower IPSC amplitudes for mutants (Dlx1/, red; Dlx1+/+, black; Kolmogorov-Smirnov test, P o 0.001). Average sIPSC amplitude (inset) was lower in mutants (neocortex, 12.8 7 1.4 pA; CA3, 11.3 7 1.4 pA) than in controls (neocortex, 20 7 0.6 pA; CA3; 21 7 0.6 pA). (h,j) Distribution of sIPSC amplitudes from neocortical and CA3 pyramidal cells. Dlx1+/+: black (n ¼ 5); Dlx1/: red (n ¼ 5). Error bars: s.e.m. *P o 0.01; ANOVA.

Two distinct spontaneous seizure types were repeatedly observed during monitoring of Dlx1/ mice. The first was characterized by a rapid onset of generalized spike and slow spike-wave discharges, gradually increasing in frequency until the abrupt termination of the ictal event, typically lasting 20–40 s (Fig. 8c). This type of seizure showed no associated behavioral component, and the mutants consistently showed normal exploratory behaviors throughout the synchronous activity. The early stage of the second seizure type resembled the first but then progressed to higher spike discharge frequencies, at which point the EEG seizures were accompanied by sustained behavioral arrest, myoclonic movements and Straub tail. These seizures lacked any tonic posturing and the mouse rapidly resumed normal behavior. Notably, no thalamocortical spike-wave absence seizures were observed in Dlx1/ mice. These seizures

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a Figure 7 Dlx1/ mice have histological changes associated with seizures. (a–c) c-Fos immunoreactivity in hippocampus of a 4-month-old wild-type mouse (a), a Dlx1/ mouse analyzed 90 min after a stress-induced epileptic episode (b) and an unhandled Dlx1/ mouse (c). Granule cells from the mutant mouse with induced seizure show strong c-Fos expression. (d–h) NPY immunoreactivity in 4-month-old wild-type mice (d,f) and Dlx1/ mice with recurrent seizures (e,g,h). In hippocampus of Dlx1/ mice, NPY is ectopically expressed by mossy fibers (arrowheads in g and h). A subset of mutants show ectopic NPY expression in the inner molecular layer (iml) of dentate gyrus (DG) (arrows in h). (i,j) High magnifications of dentate gyrus from the brains shown in g and h, respectively, stained with Timm’s method (black) and counterstained with cresyl violet. Timm’s labeling in the iml (j) demonstrates mossy fiber sprouting. A, amygdala; Cx, cortex; gc, granule cells; iml, inner molecular layer; mf, mossy fibers; PiCx, piriform cortex. Scale bars: 250 mm (a–c; f–h); 500 mm (d,e); 50 mm (i,j).

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are believed to reflect altered inhibitory signaling from the thalamic nucleus reticularis, the histology of which appears normal in Dlx1/ mice. DISCUSSION We demonstrate that the Dlx1 transcription factor is preferentially expressed in distinct interneuron subtypes, including the somatostatin+ and calretinin+ subtypes. By analyzing Dlx1/ mice, we show that Dlx1 is required for regulating the functional longevity of these interneurons. Dlx1/ mice demonstrate an age-dependent reduction of somatostatin+ and calretinin+ interneurons in neocortex and hippocampus. This interneuron loss is attributable at least in part to apoptotic cell death. Furthermore, using a cell transplantation assay, we demonstrate cell-autonomous functions of Dlx1 in the control of interneuron maturation and survival. Finally, we show that the decrease in interneuron number is associated with decreased synaptic inhibition in neocortex and hippocampus and cortical dysrhythmia. Dlx1/ mice develop behavioral, histological and electrographic signs of epilepsy. Dlx1 expression is maintained in subsets of interneurons Although Dlx1 is expressed by distinct subpopulations of mature GABAergic interneurons, we suggest that all mouse cortical interneuron subtypes originate from Dlx+ precursors and that subsets of their derivatives maintain Dlx1 expression, on the basis of the following lines of evidence. First, the expression of Dlx genes coincides with that of Gad during forebrain development23,27,33. Second, b-galactosidase expression from a Dlx5/Dlx6 enhancer is present in virtually all interneurons migrating from the MGE to cortex, and this expression persists after lacZ mRNA expression wanes in virtually all mature cortical interneurons27. Third, newborn Dlx1/Dlx2/ mice lack the majority of cortical interneurons, including somatostatin+ and NPY+ subtypes17,23. Because these mutants die at P0, one cannot assess their in vivo expression of parvalbumin and calretinin in interneurons, which begins postnatally. However, primary


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culture experiments from Dlx1/Dlx2/ cortices demonstrate that parvalbumin interneurons are reduced and calretinin interneurons are absent in Dlx1/Dlx2 mutants17. There is evidence that both parvalbumin and somatostatin/NPY interneuron subtypes derive from the MGE, whereas calretinin interneurons derive from the CGE (caudal ganglionic eminence)17,39. For instance, in Nkx2.1/ mice, in which the MGE fails to form and the CGE is less affected15, parvalbumin and somatostatin+/NPY+ interneurons are absent and calretinin interneurons are present. Calretinin interneurons are absent in Dlx1/ Dlx2/ mice, in which both MGE and CGE are abnormal17. These data are consistent with a model in which parvalbumin and somatostatin+/NPY+ interneurons originate from MGE (where Nkx2.1, Lhx6 and Dlx are expressed), and calretinin interneurons originate from CGE (where neither Nkx2.1 nor Lhx6 is expressed, but Dlx is expressed). MGE-derived interneurons turn off Nkx2.1 as they migrate to cortex18. As the cortex matures, Dlx1 expression is maintained in somatostatin/NPY and calretinin cells and is downregulated in parvalbumin cells, and Lhx6 is maintained in parvalbumin cells and a subset of somatostatin cells. Dlx function in forebrain GABAergic neurons Previous studies have demonstrated that Dlx genes regulate differentiation of progenitors that produce GABAergic and dopaminergic neurons18,20–23,40. Until now, the requirement for Dlx genes in postmitotic neurons has been unknown. Here we show that Dlx1/ mice have a progressive loss of molecular markers expressed in GABAergic neurons (somatostatin, NPY, NOS, calretinin, reelin, N-PAS1). Although it is possible that reductions in Gad and other markers might be due to reduced transcription of these genes, either directly or indirectly because of loss of Dlx1 function, we suggest that this reduction is primarily due to apoptotic death of interneurons, on the basis of the following lines of evidence. First, a gain-of-function assay has shown that Dlx1 is weak in inducing Gad expression (compared with Dlx2 and Dlx5)33. Second, we found reduction of seven interneuron markers in Dlx1 mutants. In contrast to Gad, several lines of experimentation suggest that some of these markers are not regulated by Dlx genes. For instance, in the gainof-function assay, Dlx genes did not induce somatostatin or NPY expression33, and Dlx1/ Dlx2/ mutants show preserved expression of somatostatin and NPY in cells that fail to migrate to cortex (Supplementary Fig. 5). Third, using TUNEL and anti-active caspase-3 immunohistochemistry assays, we detected increased neuronal death in neocortex and hippocampus of Dlx1/ mice. Furthermore, our cell transplantation analysis demonstrates that the loss of somatostatin+/NPY+ interneurons in Dlx1/ mice reflects cellautonomous functions of Dlx1. Notably, analysis of the morphology of bitufted interneurons (somatostatin+) from Dlx1/ precursors showed defects in dendrite morphogenesis. Although at this point we do not know why interneurons die in Dlx1 mutants, dendrite morphogenesis deficits in mutant cells might result in insufficient trophic support from synaptic partners, resulting in their apoptosis.

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ARTICLES The relatively late onset of GABAergic deficits observed in Dlx1/ mice might be explained by redundant functions of Dlx1 with other Dlx genes. Indeed, the distribution of Dlx1, Dlx2 and Dlx5 is very similar in early postnatal cortex27,28. The subsequent downregulation of Dlx2 and Dlx5 (after the second postnatal week) in both wild-type and Dlx1 mutants temporally correlates with the onset of GABAergic deficits (Supplementary Fig. 8). On the other hand, distinct functions for individual Dlx genes have been observed21,22. For instance, Dlx2/ mice have a reduction in tyrosine hydroxylase expression in interneurons of the olfactory bulb periglomerular layer21. Although the majority of somatostatin/NPY+ and calretinin+ interneurons express Dlx1, these cell subtypes showed only a partial loss in Dlx1/ mice, suggesting the existence of molecular properties that distinguish which Dlx1+ interneurons survive in the mutants. For example, our data suggest the existence of two molecularly distinct subtypes of somatostatin+ cells, one expressing both Dlx1 and Lhx6, and the other one expressing only Dlx1. The latter was selectively reduced in Dlx1/ mice. Loss of GABAergic neurons and epilepsy in Dlx1/ Many known mutations that cause epilepsy in humans and mice reduce the efficiency of GABAergic signaling. For instance, mutations that decrease presynaptic GABA availability (Gad65 mutants) or postsynaptic GABA responses (GABARa1 or GABARb3 mutants) result in epileptic phenotypes1. Defects in development of GABAergic neurons can also be epileptogenic. For example, mice homozygous for a mutation in urokinase plasminogen activator receptor (uPAR, also known as Plaur), which encodes a regulator of hepatocyte growth factor (also known as scatter factor) function, demonstrate myoclonic seizures41. uPAR is required for the migration of GABAergic interneurons to neocortex; in uPAR/ mice, interneurons (primarily parvalbumin+) are reduced41. Finally, mutation of ARX in humans, which is also required for migration of GABAergic interneurons in rodents, causes epilepsy25. A loss of interneurons is a common pathological feature in human and experimental animal models, although it is not clear whether this loss precedes or follows the onset of seizures35,42–44. Dlx1/ mice are unique in this regard, because the interneuron loss occurs during early adulthood and precedes the onset of seizures by several weeks. In Dlx1/ mice, there are reduced numbers of cells (such as somatostatin+ interneurons) with projections primarily innervating dendrites29. A simple reduction in only these neurons and subsequent loss of exclusively dendritic input could eliminate primarily smallamplitude, slow-decay IPSCs45. However, our analysis of IPSC kinetics does not support a model in which GABAergic inhibition to dendrites is selectively reduced but rather is more consistent with a general reduction in GABA tone that affects soma and dendrites of pyramidal cells. This result could arise through the following three mechanisms: first, subsets of interneurons expressing somatostatin, NPY and calretinin are reported to make somatic and axo-axonic synapses5,46,47. Second, Dlx1, through its expression in most or all immature interneurons, may have an early role in the differentiation of parvalbumin+ somatic-innervating interneurons. Likewise, although we do not readily detect Dlx1 mRNA expression in mature parvalbumin+ interneurons, Dlx1 expression may persist and be important for their function, even if not for their survival. Finally, age-dependent deafferentation in Dlx1/ mice is likely to be associated with pre- and postsynaptic reorganization that complicates mechanistic interpretations of physiological data. Irrespective of their precise synaptic defects, Dlx1/ mice show a reduction in GABA-mediated inhibition that is consistent with the observed seizure phenotype.

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Notably, interneuron loss precedes the onset of seizure expression by B4 weeks, suggesting that additional mechanisms may serve a compensatory role for the initial loss of interneurons. Several mechanisms have been suggested to compensate for hyperexcitability, including increased excitatory synaptic input on surviving interneurons (increased feedback inhibition), increased expression of GABAA receptors per synapse, decreased paired-pulse depression of IPSCs in principal cells and sprouting of surviving interneurons35,44. These mechanisms might be unable to control hyperexcitation when the inhibitory synaptic input is reduced to a critical level. In addition, plastic changes associated with hyperexcitation, including changes in neurotransmitter receptors, immediate early genes, transcription factors, neurotrophic factors and axon guidance molecules, may in turn contribute to epileptogenesis and permanent alterations leading to recurrent seizure activity35,44. Investigation of the electrophysiological and molecular adaptive mechanisms involved in epileptogenesis in Dlx1/ mice will be the subject of future experiments. Besides contributing to epilepsy, loss of interneurons could also contribute to alterations in the development and function of neural systems underlying cognition, memory and affect. We observed increased amplitude of cortical theta rhythms, an indication of altered network synchronization. Shifts in these rhythms could be associated with neuropsychiatric disorders. Indeed, it has been postulated that defects in cortical inhibition underlie the etiology of autism and schizophrenia48,49. As such, Dlx1/ mice could serve as a model for poorly understood neurological disorders. METHODS Animals. Mutant mice lacking Dlx1 were generated previously in our laboratory as described22. Homozygous Dlx1 mice, maintained on a C57BL/ 6J background, were viable and had normal appearance at birth, but B90% of them were smaller than their littermates and died within the first three postnatal weeks for unknown reasons. To circumvent this early lethality the mice were crossed with the CD1 outbred strain. All Dlx1/ mice used in this study were the F2 generation of C57BL/6J CD1 crossings. On this mixed genetic background, 50% of Dlx1/ pups had weight and survival rates comparable to wild-type littermates. Pups that were 425% smaller that littermates were not studied. Wild-type littermate mice were used as controls for all experiments (histology, electrophysiology and in vivo physiology). Transgenic mice expressing green fluorescent protein (GFP) mice on a CD1 background were mated to Dlx1+/ C57BL/6J mice to generate Dlx1+/ GFP+/ animals (F1). Matings of F1 F1 mice were used to generate the Dlx1/ GFP+/ (that is, either GFP+/ or GFP+/+) and Dlx1+/ GFP+/ embryos that served as donors for transplantations. Mouse colonies were maintained at the University of California, San Francisco, in accordance with National Institutes of Health and UCSF guidelines. Histology. Mouse pups (P5–P21) and adult mice (1–6 months) were deeply anesthetized with Avertin (Sigma; 0.2 ml/10 g body weight) and perfused intracardially with 4% paraformaldehyde (PFA) in phosphate-buffered solution (PB 0.1 M, pH 7.4). The brains were removed, cut through the sagittal midline, postfixed overnight in the same fixative and cryoprotected by immersion in 30% sucrose. One hemibrain was sectioned at a thickness of 40 mm on a sliding microtome and used for free-floating immunohistochemistry. The other hemibrain was embedded in Tissue-Tek OCT compound (Sakura), cut at a thickness of 10 mm on a cryostat and mounted on Fisher Superfrost/Plus slides for in situ RNA hybridization, double in situ hybridization, immunohistochemistry staining, apoptosis assays and Timm’s staining. Details of these techniques are available online in Supplementary Methods. Cell counting methods used to compare the number of neuronal bodies stained by immunohistochemistry or in situ RNA hybridization in Dlx1/ and Dlx1+/+ littermate mice are described in detail in Supplementary Methods.

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Transplantation of interneuron precursors. Cell transplantations of interneuron precursors from GFP-expressing Dlx1/ and Dlx1+/+ embryos into wild-type neonates were performed as described previously16. Embryos aged E14.5 from Dlx1+/;GFP+/ Dlx1+/;GFP+/ crossings were used as donors. Dissections of the ventricular and subventricular zones from the anterior part of the medial ganglionic eminences (MGE) were performed. MGE cells were dissociated and transplanted into the parietal cortex of P2–P3 wild-type pups. Details of the transplantation method and analysis of the transplanted mice are available in Supplementary Methods. Dendrite analysis. Quantification of dendritic morphology was performed in GFP-expressing interneurons differentiated from Dlx1/ and Dlx1+/+ interneuron precursors grafted into wild-type neonates after 10 d of survival. We selected interneurons with bitufted morphology in layers II/III of the somatosensory cortex, because these neurons are selectively lost at later stages in Dlx1/ mice. Bitufted cells have ovoid somata and primary dendrites emerging from opposite poles; their axons produce radially oriented plexuses with some horizontal spans6. We sampled 50 interneurons whose processes could be clearly distinguished from those of other GFP+ cells and whose dendritic trees were entirely confined within the sections (100 mm thick). For dendrite quantifications of bitufted cells, the dendrites were drawn using a camera lucida. The drawings were scanned and the electronic files were exported to Image J (with the Neuron J plugin; National Institutes of Health) to trace and quantify dendritic arbors. Sampling and data analysis was performed while the investigator was blind to genotype. Total dendritic length, total number of branches (filopodia longer than 3 mm were considered dendritic branch tips), average dendritic length and length of longest dendrite were determined for each cell. To compare results between mutant and control cells, the Student’s t-test was used. P o 0.05 was considered significant. Electrophysiology. Acute brain slices were prepared from Dlx1/ and Dlx1+/+ mice (1 and 2 months old). Briefly, the mice were decapitated, and the brain was rapidly removed in ice-cold oxygenated slicing artificial CSF (sACSF) consisting of (in mM) 220 sucrose, 3 KCl, 1.25 NaH2PO4, 2 MgSO4, 26 NaHCO3, 2 CaCl2, and 10 dextrose (295–305 mOsm). Horizontal hippocampal or coronal cortical (300- mm-thick) slices were cut in 4 1C oxygenated (95% O2/5% CO2) sACSF. The slices were immediately transferred to a holding chamber where they remained submerged in oxygenated recording ACSF consisting of (in mM) 124 NaCl, 3 KCl, 1.25 NaH2PO4, 2 MgO4, 26 NaHCO3, 2 CaCl2, and 10 dextrose (295–305 mOsm). Slices were held at 37 1C for 45 min and then at B22 1C. Whole-cell voltage-clamp recordings were obtained from visually identified neurons using an infrared differential interference contrast (IR-DIC) video microscopy system. Patch electrodes (3–7 MO) were pulled from borosilicate glass capillary tubing (World Precision Instruments), coated with Sylgard (Dow Corning) and fire polished. Intracellular patch pipette solution contained (in mM) 120 Cs-gluconate, 10 HEPES, 11 EGTA, 11 CsCl2, 1 MgCl2, 1.25 QX314, 2 Na2-ATP, and 0.5 Na2-GTP, pH 7.25 (285–290 mOsm). To isolate GABAergic currents, slices were perfused with ACSF containing either 20 mM 6-ciano-7dinitroquinoxaline-2,3-dione (CNQX) or 6,7-dinitroquinoxaline-2,3-dione (DNQX), and 50 mM D-(–)-2-amino-5-phosphonovaleric acid (D-AP5). Whole-cell voltage-clamp data were low-pass filtered at 1 kHz (3 dB, eightpole Bessel), digitally sampled at 10 kHz, and monitored with pClamp software (Axon Instruments) running on a Pentium PC (Dell Computer). Whole-cell access resistance was carefully monitored throughout the recording, and cells were rejected if values changed by 425% (or exceeded 20 MO); only recordings with stable series resistance of o20 MO were used for analysis. Spontaneous IPSCs were analyzed using Mini Analysis 5.6.28 software (Synaptosoft). Each event was manually selected based on rise time, amplitude, and decay properties. Between 100 and 200 individual events were analyzed for each cell. Kinetic analysis of the IPSCs was performed with a single-exponential function. Results are presented as mean 7 s.e.m. To compare the results between different cell types, we used the Student’s t-test. Similar data were obtained using a one-way ANOVA. P o 0.05 was considered significant. Chronic electroencephalographic (EEG) recordings. Adult Dlx1/ and Dlx1+/+ littermate mice (aged 6–10 months) were implanted for chronic EEG


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recordings. For that, mice were anesthetized with Avertin (1.25% tribromoethanol/amyl alcohol solution, intraperitoneal) using a dose of 0.02 ml/g. Tefloncoated silver wire electrodes (0.005-inch diameter) soldered to a microminiature connector were implanted bilaterally into the subdural space over frontal, central, parietal, and occipital cortices. Digital EEG activity was monitored daily for up to 2 weeks during prolonged overnight and random 2-h sample recordings (Stellate Systems, Harmonie v. 5.0b). A digital video camera was used to simultaneously monitor behavior during the EEG recording periods. All recordings were carried out at least 24 h after surgery on mice freely moving in the test cage. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We thank R. Nicoll for physiological advice. I.C. thanks J. Palop and U. Borello for helpful discussions, M. Alvarez-Dolado for advice in cell transplantations, and the L. Mucke laboratory (Gladstone Institute of Neurological Disease, UCSF) for sharing the BioQuant Image Analysis. This work was supported by funds to J.L.R.R. (Nina Ireland, National Institute of Mental Health RO1 MH49428 and K05 MH065670), I.C. (National Alliance for Research on Schizophrenia and Depression Young Investigator Award), S.C.B. (US National Institutes of Health RO1 NS40272 and Citizens United for Research in Epilepsy) and J.L.N. (National Institute of Neurological Disorders and Stroke NS 29709 and National Institute of Child Health and Human Development HD24064, Baylor Mental Retardation and Developmental Disabilities Research Center). COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 15 March; accepted 13 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Noebels, J.L. The biology of epilepsy genes. Annu. Rev. Neurosci. 26, 599–625 (2003). 2. Paulsen, O. & Moser, E.I. A model of hippocampal memory encoding and retrieval: GABAergic control of synaptic plasticity. Trends Neurosci. 21, 273–278 (1998). 3. Whittington, M.A. & Traub, R.D. Interneuron diversity series: inhibitory interneurons and network oscillations in vitro. Trends Neurosci. 26, 676–682 (2003). 4. Freund, T.F. Interneuron Diversity series: Rhythm and mood in perisomatic inhibition. Trends Neurosci. 26, 489–495 (2003). 5. Markram, H. et al. Interneurons of the neocortical inhibitory system. Nat. Rev. Neurosci. 5, 793–807 (2004). 6. Ramon y Cajal, S. Histology of the Nervous System. (Oxford University Press, New York, 1911). 7. Jones, E.G. Varieties and distribution of non-pyramidal cells in the somatic sensory cortex of the squirrel monkey. J. Comp. Neurol. 160, 205–267 (1975). 8. DeFelipe, J. Neocortical neuronal diversity: chemical heterogeneity revealed by colocalization studies of classic neurotransmitters, neuropeptides, calcium-binding proteins, and cell surface molecules. Cereb. Cortex 3, 273–289 (1993). 9. Kubota, Y., Hattori, R. & Yui, Y. Three distinct subpopulations of GABAergic neurons in rat frontal agranular cortex. Brain Res. 649, 159–173 (1994). 10. Gonchar, Y. & Burkhalter, A. Three distinct families of GABAergic neurons in rat visual cortex. Cereb. Cortex 7, 347–358 (1997). 11. McBain, C.J. & Fisahn, A. Interneurons unbound. Nat. Rev. Neurosci. 2, 11–23 (2001). 12. Gupta, A., Wang, Y. & Markram, H. Organizing principles for a diversity of GABAergic interneurons and synapses in the neocortex. Science 287, 273–278 (2000). 13. Klausberger, T. et al. Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature 421, 844–848 (2003). 14. Lavdas, A.A., Grigoriou, M., Pachnis, V. & Parnavelas, J.G. The medial ganglionic eminence gives rise to a population of early neurons in the developing cerebral cortex. J. Neurosci. 19, 7881–7888 (1999). 15. Sussel, L., Marin, O., Kimura, S. & Rubenstein, J.L. Loss of Nkx2.1 homeobox gene function results in a ventral to dorsal molecular respecification within the basal telencephalon: evidence for a transformation of the pallidum into the striatum. Development 126, 3359–3370 (1999). 16. Wichterle, H., Garcia-Verdugo, J.M., Herrera, D.G. & Alvarez-Buylla, A. Young neurons from medial ganglionic eminence disperse in adult and embryonic brain. Nat. Neurosci. 2, 461–466 (1999). 17. Xu, Q., Cobos, I., De La Cruz, E., Rubenstein, J.L. & Anderson, S.A. Origins of cortical interneuron subtypes. J. Neurosci. 24, 2612–2622 (2004). 18. Marin, O., Anderson, S.A. & Rubenstein, J.L. Origin and molecular specification of striatal interneurons. J. Neurosci. 20, 6063–6076 (2000). 19. Letinic, K., Zoncu, R. & Rakic, P. Origin of GABAergic neurons in the human neocortex. Nature 417, 645–649 (2002). 20. Panganiban, G. & Rubenstein, J.L. Developmental functions of the Distal-less/Dlx homeobox genes. Development 129, 4371–4386 (2002).

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ARTICLES 21. Qiu, M. et al. Null mutation of Dlx-2 results in abnormal morphogenesis of proximal first and second branchial arch derivatives and abnormal differentiation in the forebrain. Genes Dev. 9, 2523–2538 (1995). 22. Qiu, M. et al. Role of the Dlx homeobox genes in proximodistal patterning of the branchial arches: mutations of Dlx-1, Dlx-2, and Dlx-1 and -2 alter morphogenesis of proximal skeletal and soft tissue structures derived from the first and second arches. Dev. Biol. 185, 165–184 (1997). 23. Anderson, S.A., Eisenstat, D.D., Shi, L. & Rubenstein, J.L. Interneuron migration from basal forebrain to neocortex: dependence on Dlx genes. Science 278, 474–476 (1997). 24. Cobos, I., Broccoli, V. & Rubenstein, J.L. The vertebrate ortholog of Aristaless is regulated by Dlx genes in the developing forebrain. J. Comp. Neurol. 483, 292–303 (2005). 25. Kitamura, K. et al. Mutation of ARX causes abnormal development of forebrain and testes in mice and X-linked lissencephaly with abnormal genitalia in humans. Nat. Genet. 32, 359–369 (2002). 26. Marty, S., Berzaghi Mda, P. & Berninger, B. Neurotrophins and activity-dependent plasticity of cortical interneurons. Trends Neurosci. 20, 198–202 (1997). 27. Stuhmer, T., Puelles, L., Ekker, M. & Rubenstein, J.L. Expression from a Dlx gene enhancer marks adult mouse cortical GABAergic neurons. Cereb. Cortex 12, 75–85 (2002). 28. Saino-Saito, S., Berlin, R. & Baker, H. Dlx-1 and Dlx-2 expression in the adult mouse brain: relationship to dopaminergic phenotypic regulation. J. Comp. Neurol. 461, 18– 30 (2003). 29. Kawaguchi, Y. & Kubota, Y. GABAergic cell subtypes and their synaptic connections in rat frontal cortex. Cereb. Cortex 7, 476–486 (1997). 30. Alifragis, P., Liapi, A. & Parnavelas, J.G. Lhx6 regulates the migration of cortical interneurons from the ventral telencephalon but does not specify their GABA phenotype. J. Neurosci. 24, 5643–5648 (2004). 31. Alcantara, S. et al. Regional and cellular patterns of Reelin mRNA expression in the forebrain of the developing and adult mouse. J. Neurosci. 18, 7779–7799 (1998). 32. Erbel-Sieler, C. et al. Behavioral and regulatory abnormalities in mice deficient in the NPAS1 and NPAS3 transcription factors. Proc. Natl. Acad. Sci. USA 101, 13648– 13653 (2004). 33. Stuhmer, T., Anderson, S.A., Ekker, M. & Rubenstein, J.L. Ectopic expression of the Dlx genes induces glutamic acid decarboxylase and Dlx expression. Development 129, 245–252 (2002). 34. McBain, C.J., Eaton, J.V., Brown, T. & Dingledine, R. CNQX increases spontaneous inhibitory input to CA3 pyramidal neurones in neonatal rat hippocampal slices. Brain Res. 592, 255–260 (1992).

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35. Morimoto, K., Fahnestock, M. & Racine, R.J. Kindling and status epilepticus models of epilepsy: rewiring the brain. Prog. Neurobiol. 73, 1–60 (2004). 36. Baraban, S.C. & Tallent, M.K. Interneuron Diversity series: Interneuronal neuropeptides–endogenous regulators of neuronal excitability. Trends Neurosci. 27, 135–142 (2004). 37. Racine, R.J. Modification of seizure activity by electrical stimulation. II. Motor seizure. Electroencephalogr. Clin. Neurophysiol. 32, 281–294 (1972). 38. Buzsaki, G. Theta oscillations in the hippocampus. Neuron 33, 325–340 (2002). 39. Nery, S., Fishell, G. & Corbin, J.G. The caudal ganglionic eminence is a source of distinct cortical and subcortical cell populations. Nat. Neurosci. 5, 1279–1287 (2002). 40. Yun, K. et al. Modulation of the notch signaling by Mash1 and Dlx1/2 regulates sequential specification and differentiation of progenitor cell types in the subcortical telencephalon. Development 129, 5029–5040 (2002). 41. Powell, E.M. et al. Genetic disruption of cortical interneuron development causes regionand GABA cell type-specific deficits, epilepsy, and behavioral dysfunction. J. Neurosci. 23, 622–631 (2003). 42. Kobayashi, M. & Buckmaster, P.S. Reduced inhibition of dentate granule cells in a model of temporal lobe epilepsy. J. Neurosci. 23, 2440–2452 (2003). 43. Cossart, R. et al. Dendritic but not somatic GABAergic inhibition is decreased in experimental epilepsy. Nat. Neurosci. 4, 52–62 (2001). 44. Cossart, R., Bernard, C. & Ben-Ari, Y. Multiple facets of GABAergic neurons and synapses: multiple fates of GABA signalling in epilepsies. Trends Neurosci. 28, 108– 115 (2005). 45. Maccaferri, G., Roberts, J.D., Szucs, P., Cottingham, C.A. & Somogyi, P. Cell surface domain specific postsynaptic currents evoked by identified GABAergic neurones in rat hippocampus in vitro. J. Physiol. (Lond.) 524, 91–116 (2000). 46. Gonchar, Y., Turney, S., Price, J.L. & Burkhalter, A. Axo-axonic synapses formed by somatostatin-expressing GABAergic neurons in rat and monkey visual cortex. J. Comp. Neurol. 443, 1–14 (2002). 47. Wang, Y. et al. Anatomical, physiological and molecular properties of Martinotti cells in the somatosensory cortex of the juvenile rat. J. Physiol. (Lond.) 561, 65–90 (2004). 48. Levitt, P., Eagleson, K.L. & Powell, E.M. Regulation of neocortical interneuron development and the implications for neurodevelopmental disorders. Trends Neurosci. 27, 400–406 (2004). 49. Horike, S., Cai, S., Miyano, M., Cheng, J.F. & Kohwi-Shigematsu, T. Loss of silentchromatin looping and impaired imprinting of DLX5 in Rett syndrome. Nat. Genet. 37, 31–40 (2005).

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Activation of p75NTR by proBDNF facilitates hippocampal long-term depression Newton H Woo1, Henry K Teng2, Chia-Jen Siao2, Cristina Chiaruttini1, Petti T Pang1, Teresa A Milner3, Barbara L Hempstead2 & Bai Lu1 Pro- and mature brain-derived neurotrophic factor (BDNF) activate two distinct receptors: p75 neurotrophin receptor (p75NTR) and TrkB. Mature BDNF facilitates hippocampal synaptic potentiation through TrkB. Here we report that proBDNF, by activating p75NTR, facilitates hippocampal long-term depression (LTD). Electron microscopy showed that p75NTR localized in dendritic spines, in addition to afferent terminals, of CA1 neurons. Deletion of p75 NTR in mice selectively impaired the NMDA receptor–dependent LTD, without affecting other forms of synaptic plasticity. p75 NTR2/2 mice also showed a decrease in the expression of NR2B, an NMDA receptor subunit uniquely involved in LTD. Activation of p75NTR by proBDNF enhanced NR2B-dependent LTD and NR2B-mediated synaptic currents. These results show a crucial role for proBDNF-p75NTR signaling in LTD and its potential mechanism, and together with the finding that mature BDNF promotes synaptic potentiation, suggest a bidirectional regulation of synaptic plasticity by proBDNF and mature BDNF.

Persistent modifications of synapses, also known as long-term synaptic plasticity, are believed to be a fundamental mechanism for information storage and processing in the brain. These modifications include either strengthening or weakening of synaptic connections, respectively termed long-term potentiation (LTP) and long-term depression (LTD). An emerging concept is that synaptic plasticity is tightly controlled by neurotrophic factors, which themselves are produced and secreted in an activity-dependent manner1,2. Brain-derived neurotrophic factor (BDNF) is the best-studied neurotrophic protein that elicits diverse and profound effects on central synapses, including the regulation of hippocampal LTP3–5. Biological actions of BDNF are mediated by two separate receptors, the TrkB receptor tyrosine kinase and p75NTR. Like other neurotrophins, BDNF is first synthesized as a precursor (proBDNF), which is proteolytically cleaved to form mature BDNF (mBDNF)6–9. Mature BDNF interacts preferentially with TrkB to activate its intrinsic tyrosine kinase activity, which in turn triggers multiple intracellular signaling pathways10,11. In contrast, pro-neurotrophins bind p75NTR with high affinity12. Although p75NTR lacks intrinsic enzymatic activity, it can trigger signaling transduction through its association with adaptor proteins distinct from Trk signaling cascades10,11. The finding that pro-neurotrophins serve as signaling molecules rather than inactive precursors has brought a new dimension of complexity to neurotrophin function12–14. Indeed, a number of recent studies showed that pro-neurotrophins, by activating p75NTR, promote apoptosis in the peripheral nervous system12,15–18. This is in marked contrast to mature neurotrophins, which act to enhance neuronal

survival. As a member of the tumor necrosis factor receptor family, p75NTR encodes a type II death domain and is known to promote apoptosis, a function opposite to that of Trk receptors16,19,20. Thus, pro- and mature neurotrophins may elicit diametrically opposite cellular responses, through two distinct receptor-signaling systems. Recently, studies have shown that endogenous proBDNF is secreted from neuronal cells18,21 and accounts for a substantial proportion of total BDNF secreted extracellularly8,22,23. Although p75NTR, a receptor for pro-neurotrophins, has been thought to be involved in cell death, the relative paucity of changes in cell death in brains of mice that lack full-length p75NTR suggests that proBDNF-p75NTR interaction may mediate neuronal functions other than apoptosis24. Recently, extracellular cleavage of proBDNF has been shown to be crucial for the expression of late-phase LTP in the hippocampus25. Because a major function of BDNF in the brain is to regulate hippocampal LTP, we asked whether proBDNF, if uncleaved, modulates synaptic plasticity through p75NTR. In this study, we show that proBDNF, signaling through p75NTR, selectively facilitates NMDA receptor–dependent LTD in the mammalian hippocampus. Furthermore, we show that this enhancement of LTD by proBDNF-p75NTR is mediated through an upregulation of NR2B, an NMDA receptor subtype uniquely involved in LTD26,27. RESULTS Normal hippocampal synaptic properties in p75 NTR/ mice As an initial step toward characterizing p75 NTR/ mice, we examined basal synaptic function in hippocampal area CA1. We observed no difference in the input-output curves in p75 NTR+/+ and p75 NTR/

1Section on Neural Development and Plasticity, LCSN, NICHD, Porter Neuroscience Research Center, 35 Lincoln Drive, Bethesda, Maryland 20892-3714, USA. 2Division of

Hematology, Department of Medicine, Weill Medical College of Cornell University, 1300 York Avenue, New York, New York 10021, USA. 3Department of Neurology and Neuroscience, Weill Medical College of Cornell University, 411 East 69th Street, New York, New York 10021, USA. Correspondence shold be addressed to B.L. ([email protected]). Published online 17 July 2005; doi:10.1038/nn1510


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synapses (Fig. 1a), suggesting that the deletion of p75 NTR does not alter basal synaptic transmission. Similarly, paired-pulse facilitation at various interstimulus intervals, a commonly used method to infer changes in probability of neurotransmitter release, was virtually identical in both genotypes (Fig. 1b). We next examined the readily releasable pool of synaptic vesicles by applying a brief train of highfrequency stimulation (HFS; 100 Hz, 100 pulses) to the CA1 afferents in the presence of AP5, an NMDA receptor antagonist (50 mM). Field

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excitatory postsynaptic potential (fEPSP) slopes showed a continuous decline over time, indicative of a gradual depletion of docked vesicles, with no obvious differences between mutant and control slices (Fig. 1c). We also recorded synaptic responses to a prolonged train of repetitive stimulation (14 Hz, 300 pulses) in the presence of AP5 to determine the size of the reserve pool of vesicles28. Again we observed no difference between p75 NTR+/+ and p75 NTR/ slices (Fig. 1d). Thus deletion of p75 NTR does not alter basic properties of CA1 synapses.

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Figure 1 Intact presynaptic properties in CA1 synapses of p75 NTR/ mice. Field recordings were performed in hippocampal slices derived from p75 NTR+/+ and p75 NTR/ animals. (a) Normal input-output curves in p75 NTR/ slices. We plotted fEPSP slopes against their corresponding presynaptic fiber volley amplitude and found no difference in the distribution of values obtained from p75 NTR/ and age-matched controls. (b) Normal paired-pulse facilitation (PPF). We calculated PPF from the ratio of the second fEPSP slope to the first fEPSP and plotted it against different interstimulus intervals. There was no significant difference between p75 NTR/ and p75 NTR+/+ mice at all interstimulus intervals tested. (c) Normal synaptic responses to brief, HFS (100 Hz, 100 pulses) at p75 NTR/ synapses. Top, representative recordings of EPSP traces from p75 NTR+/+ (black) and p75 NTR/ (gray) hippocampi; bottom, summary results. (d) Normal synaptic responses to prolonged repetitive stimulation (14 Hz, 300 pulses) in p75 NTR/ mice, as compared with wild-type hippocampal slices. Time course of the effects of the stimulus trains is shown. Experiments in c and d were performed in the presence of AP5. Error bars, s.e.m.




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Figure 2 Selective deficit for NMDA receptor–dependent LTD in p75 NTR/ mice. (a) Lack of LTD induced by LFS in p75 NTR/ synapses. LFS (1 Hz, 15 min) was applied to the Schaeffer collaterals. Sample traces are shown at indicated time points labeled ‘i’ and ‘ii’. Scale bars, 5 mV and 5 ms. (b) Blockade of LTD in p75 NTR+/+ mice by REX antibody. Hippocampal slices were incubated in REX during recovery and was also present throughout the experiment as indicated. (c) Summary bar graph depicting the lack of NMDA receptor–mediated LTD in p75 NTR/ animals. (d) Lack of LTD induced by NMDA perfusion in p75 NTR/ slices. NMDA was applied to slices, as indicated by the gray bar. (e) Intact NMDA receptor–independent LTD in p75 NTR/ slices. Paired stimulation (50 ms interval) was applied to the Schaeffer collaterals at low frequency (1 Hz, 15 min). (f) Normal LTP in p75 NTR/ slices. Two trains of HFS (100 Hz, 1 s) were applied. Error bars, s.e.m.

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p75 NTR/ mice lack NMDA receptor–dependent LTD To test the hypothesis that p75NTR may have an opposing role to TrkB in LTP, we monitored the induction of LTD by applying a prolonged train of low-frequency stimulation (LFS; 1 Hz, 15 min) to hippocampal slices from juvenile p75 NTR+/+ and p75 NTR/ mice (3–4 weeks old). LFS applied to the Schaeffer collaterals elicited robust LTD in slices derived from p75 NTR+/+ mice (Fig. 2a). In marked contrast, slices from aged-matched p75 NTR/ mice did not show LTD. LFS induced an initial decrease in fEPSP slopes, which subsequently recovered back to baseline (Fig. 2a). Immediately after LFS, mean fEPSP slopes were 58 ± 2% and 65 ± 4% (P 4 0.5), whereas those 60 min after LFS were 70 ± 4% and 95 ± 3% (P o 0.05) for p75 NTR+/+ and p75 NTR/ mice, respectively. To test whether p75NTR has an indispensable role in LTD under genetically unmodified conditions, hippocampal slices from p75 NTR+/+ mice were perfused with REX function-blocking antibody, a reagent known to block p75 NTR function29. In slices that were incubated in REX antibody (50 mg/ml, 2 h), LFS did not induce LTD (Fig. 2b). In both genotypes, LFS-induced LTD was completely blocked by the general antagonist of NMDA receptor, AP5, suggesting that this form of LTD depends on the NMDA receptor (Fig. 2c and Supplementary Fig. 1 online). Consistent with previous reports26,27, application of ifenprodil (10 mM), an antagonist of NR2B involved in LTD, selectively blocked this form of LTD without affecting LTP in slices prepared from p75 NTR+/+ mice (Fig. 2c and Supplementary Fig. 1). The NMDA receptor–dependent form of LTD can also be induced by bath application of NMDA. As in the case of LFS-induced LTD, LTD elicited by brief perfusion of NMDA was also impaired in juvenile p75 NTR/ mice (Fig. 2d). Application of NMDA (20 mM) for a period of 10 min induced LTD that lasted for the duration of the recording in p75 NTR+/+ slices, and this LTD was not observed


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Figure 3 Localization of p75NTR immunoreactivity in mouse hippocampus. (a,b) By light microscopy, we found p75NTR immunoreactivity in fine, varicose fibers that were dense near stratum pyramidale (SP) and scattered throughout stratum radiatum (SR) of the hippocampal CA1 region. The number of p75NTR-immunoreactive processes seemed greater in the hippocampi of 2-week-old than 8-week-old p75 NTR+/+ mice. (c) p75NTR immunoreactivity was absent in the hippocampi of p75 NTR/ mice. All photographs from sections labeled with the R & D antibody. Scale bar, 100 mm. (d) Western blot showing the levels for p75NTR protein. Measurements of protein levels were taken from hippocampal lysates prepared from young p75 NTR+/+ (3 weeks old), mature p75 NTR+/+ (8 weeks old) and p75 NTR/ (3 weeks old) mice. We observed an age-dependent increase in p75NTR protein levels, with young mice having higher levels than the mature mice. p75NTR protein was absent in p75 NTR/ mice. (e) Quantification of p75NTR protein levels normalized to an actin control. *P o 0.05. (f–i) Expression of p75NTR in dendrites of hippocampal cultured neurons. Punctate staining of (f) p75NTR and (g) PSD95 was observed in cultured hippocampal neurons (day 14) prepared from E16 mice and were often colocalized in the soma and dendrites (h,i). Error bars, s.e.m.

in p75 NTR/ slices (Fig. 2d). In both genotypes, complete suppression of synaptic transmission occurred shortly after NMDA application. But fEPSP slopes slowly recovered to baseline values of 96 ± 7% in p75 NTR/ slices, whereas in p75 NTR+/+ slices the response remained depressed at a mean value of 62 ± 5% (P o 0.01). Coapplication of AP5 with NMDA blocked this form of LTD (data not shown). In addition to NMDA receptor–dependent LTD, the young hippocampus expresses an NMDA receptor–independent form of LTD, which is induced by a twin-pulse LFS protocol30,31. Notably, the NMDA receptor–independent form of LTD was not altered in young juvenile p75 NTR/ mice. A 15-min train of twin pulses (50 ms apart) at 1 Hz elicited a robust and long-lasting depression in both genotypes (Fig. 2e). The mean fEPSP slope values recorded 60 min after the application of this protocol were 74 ± 4% and 72 ± 3% in wild-type and p75 NTR/ slices (P 4 0.2), respectively. In agreement with previous studies32, this twin-pulse LFS protocol induced a form of LTD that was independent of NMDA receptor activation. Perfusion of 50 mM AP5, which blocked the expression of LTD induced by 1 Hz, 15 min (Fig. 2c), did not affect the expression of LTD elicited by twinpulse LFS stimulation (Supplementary Fig. 1). Finally, we examined whether p75 NTR/ regulates NMDA receptor–dependent LTP. Application of tetanic stimulation (100 Hz, 1 s, 2 trains separated by 20 s) induced almost identical LTP in slices from p75 NTR+/+ and p75 NTR/ mice, suggesting that deletion of p75 NTR does not affect either induction or expression of LTP (Fig. 2f). Immediately after tetanus, the mean fEPSP slopes were 259 ± 17% and 283 ± 12% (P 4 0.5) in p75 NTR+/+ and p75 NTR/ mice, respectively. At 60 min after HFS, fEPSP slopes remained potentiated above baseline with mean values of 167 ± 6% and 177 ± 14% (P 4 0.5) for wild-type and p75 NTR/ mice, respectively. These results show a

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Figure 4 Electron microscopic localization of p75NTR immunoreactivity in CA1 region of the p75 NTR+/+ mouse. (a) Within stratum pyramidale, we found p75NTR immunoreactivity (arrowhead) in an axon terminal that contained numerous small synaptic vesicles and abuted a pyramidal cell perikaryon (py). (b) A p75NTR-immunoreactive axon terminal with a preterminal axon was found in the neuropil of stratum radiatum. (c) An aggregate of p75NTR immunoreactivity (arrowhead) was found near the plasma membrane of a dendritic shaft (D). (d–f) Within stratum radiatum, p75NTR immunoreactivity was detected in dendritic spines that received contacts (curved arrows) from unlabeled terminals (uT). (e) p75NTR immunoreactivity was denser near the synapse. Scale bars for a–c, 500 nm. Scale bars for d–f, 250 nm.

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selective role for p75NTR in one form of hippocampal synaptic plasticity: the NMDA receptor–dependent form of LTD. Expression of p75NTR in the mouse hippocampus To assess whether p75NTR could directly mediate these effects, we sought to localize p75NTR immunoreactivity in the mouse hippocampus, using an antibody that detects the extracellular domain of p75NTR. Light microscopic analysis of sections showed p75NTR immunoreactivity in very fine varicose fibers throughout the hippocampus (Fig. 3a,b), which was absent in the p75 NTR/ mouse (Fig. 3c). Within the CA1 region, p75NTR-immunoreactive fibers were concentrated near stratum pyramidale and were more evenly dispersed in strata oriens and radiatum. Side-by-side comparison showed that sections of hippocampi from young juvenile mice (postnatal day (P) 14; Fig. 3a) seemed to express greater p75NTR immunoreactivity than did older juvenile mice (P60; Fig. 3b). Similar results were obtained using an antibody against the intracellular domain of p75NTR (data not shown). Western

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blot analysis confirmed that p75NTR expression levels are inversely related to age (Fig. 3d). Quantitative analysis indicated that younger mice (P21) had significantly higher p75NTR receptor levels than did older mice (P60; Fig. 3e). These results are consistent with the observation that robust LTD is induced more readily in younger juvenile hippocampus33,34. To determine the subcellular localization of p75NTR, we performed double staining on mouse hippocampal neurons derived from embryonic day 16 (E16) wild-type mice, using antibodies against p75NTR and a dendritic spine marker PSD95. After 14 d in vitro, we observed p75NTR immunoreactivity as punctate staining around the cell body as well as dendrites (Fig. 3f), with distribution very similar to that of PSD95 immunoreactivity (Fig. 3g). The majority of p75NTR immunoreactivity was colocalized with PSD95 immunoreactivity in the dendrites of hippocampal neurons, suggesting their localization in spines (Fig. 3h,i). To firmly establish that p75NTR is localized at CA1 synapses, we performed immunoelectron microscopy in stratum radiatum of the hippocampal CA1 region. In agreement with a previous study in adult rats35, we observed p75NTR immunoreactivity in axons and axon terminals (Fig. 4a,b). Axon terminals (0.4–0.6 mm in diameter) contained numerous small synaptic vesicles and often abutted pyramidal cell perikarya (Fig. 4a). But many CA1 pyramidal neurons also expressed p75NTR immunoreactivity. We observed the immunoreactive profiles in dendritic shafts (Fig. 4c), spines (Fig. 4d–f) and glial profiles (data not shown). Within dendritic profiles, p75NTR immunoreactivity was usually aggregated near the plasma membrane, and was denser in the spine head near the synaptic specialization. Additional examples of p75NTR-labeled dendritic spines are shown in Supplementary Figure 2. Labeling of axon, terminal and spine profiles was absent in the p75 NTR/ mice. Taken together, our immunoelectron microscopy experiments raise the possibility that activation of p75NTR on the CA1


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Figure 5 Enhancement of NMDA receptor–dependent LTD by proBDNF. (a) Lack of effect on basal transmission. Application of proBDNF, a ligand for p75NTR, did not induce synaptic depression. (b) Effect of proBDNF on the expression of NMDA receptor–dependent LTD. Hippocampal slices were incubated with purified, cleavage-resistant proBDNF for at least 1 h before recording. proBDNF enhanced LTD in young p75 NTR+/+ hippocampal slices as compared with vehicle control, but not in p75 NTR/ slices. (c) Pairing proBDNF with a weak LFS protocol did not induce LTD. (d) Opposing actions of mBDNF on LTD. Incubation of mBDNF inhibited the expression of LTD. Error bars, s.e.m.

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Figure 6 Enhancement of hippocampal LTD by proBNDF is mediated by p75NTR and NR2B. (a) Pronounced enhancement of LTD by proBDNF in mature mice (7–8 weeks old). Hippocampal slices derived from older mice that normally expressed attenuated levels of LTD showed robust LTD in the presence of proBDNF. (b,c) Inhibition of proBDNF-mediated enhancement of LTD by blocking p75NTR or NR2B function. (b) Incubation of hippocampal slices in REX (50 mg/ml) blocked the effects of proBDNF. (c) Ifenprodil blocked the enhancement of LTD normally observed with proBDNF. (d) Facilitation of LTD by proBDNF is not dependent on the cholinergic system. Atropine (5 mM) did not affect LTD or the enhancement of LTD by proBDNF. Error bars, s.e.m.

pyramidal-cell dendrites or their afferents contributes to the expression of NMDA receptor–dependent LTD. Facilitation of NMDA receptor–dependent LTD by proBDNF Because proBDNF is a high-affinity ligand for p75NTR that can be secreted from hippocampal neurons22, we tested whether activation of p75NTR by proBDNF regulates NMDA-dependent LTD. Perfusion of a cleavage-resistant form of proBDNF (2 ng/ml) to hippocampal slices had no effect on basal synaptic transmission recorded over an extended period of time (Fig. 5a). Next, we treated the hippocampal slices from p75 NTR+/+ mice with proBDNF for more than 1 h before inducing LTD. In young juvenile slices that already showed pronounced LTD, treatment with proBDNF, but not vehicle, resulted in a small but notable increase in LTD (Fig. 5b). The mean values of fEPSP slopes 60 min after the application of LFS for vehicle- and proBDNF- treated slices were 70 ± 7%, and 56 ± 3%, respectively. Moreover, application of proBDNF to slices from p75 NTR/ mice elicited little effect, suggesting that proBDNF facilitated LTD through activation of p75NTR (Fig. 5b; fEPSP slope at 60 min after LFS, 96 ± 8%). Application of proBDNFcontaining perfusates collected at the end of several hippocampal slice experiments, but not control perfusates, to cultured neuromuscular

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synapses resulted in a marked reduction in synaptic transmission. This suggests that proBDNF in the slice-recording chamber remains intact and biologically active for many hours (data not shown). To determine whether proBDNF reduced the threshold of LTD induction, we stimulated hippocampal slices using a weaker stimulation protocol (1 Hz, 5 min) in the presence of proBDNF. This protocol did not induce LTD in vehicle-treated slices, and treatment with proBDNF had little effect (Fig. 5c; fEPSP slope at 60 min in control and proBDNFtreated slices were 100 ± 13% and 90 ± 5%, respectively). In contrast to proBDNF, incubation of hippocampal slices with mBDNF attenuated LTD expression (Fig. 5d). This is consistent with a previous study that examined the modulation of hippocampal LTD by mBDNF36. In older juvenile slices in which LTD is attenuated, incubation of slices in proBDNF elicited a stronger facilitatory effect on LTD than it did in young juvenile slices (Fig. 6a). The mean values of fEPSPs 60 min after LFS were 94 ± 7% and 71 ± 2% for slices that received vehicle control and those that received proBDNF, respectively. Moreover, pretreatment with the p75NTR-blocking REX antibody completely prevented the effect of proBDNF on LFS-induced LTD (Fig. 6b), indicating the effect of proBDNF is mediated by p75NTR. In slices treated with proBDNF and the NR2B antagonist ifenprodil

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Figure 7 Relationship between p75NTR and NR2B at hippocampal CA1 synapse. (a) Reduced expression of NR2B-mediated synaptic currents in p75 NTR/ mice. Evoked whole-cell responses were recorded from CA1 pyramidal neurons in the presence of AHPA receptor antagonist DNQX and GABA receptor antagonist bicuculline. Application of ifenprodil selectively decreased NMDA-mediated synaptic currents recorded from p75 NTR+/+ but not in p75 NTR/ hippocampal slices. Arrowheads indicate timepoints of sample NMDA-mediated current traces during baseline (black), after ifenprodil application (red) and after final AP5 application (green), which verified that evoked synaptic currents were mediated by NMDA receptors. (b) Summary plot depicting the sensitivity of NMDA currents to ifenprodil is dependent on p75NTR. Normalized averaged traces depicted a slower decay rate of NMDA receptor–mediated EPSC in p75 NTR+/+ than p75 NTR/ mice. (c) Recruitment of NR2B by proBDNF-p75NTR. Application of proBDNF rapidly enhanced NMDA receptor–mediated currents in slices derived from p75 NTR+/+ but not in p75 NTR/ animals. In the presence of ifenprodil, the potentiation of NMDA receptor currents by proBDNF was inhibited. Scale bars, 50 pA and 40 ms. Error bars, s.e.m.


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(10 mM), LFS no longer induced LTD (Fig. 6c), suggesting that proBDNF regulates NR2B-mediated LTD. Because a previous report showed that application of carbachol facilitates LTD37, we tested whether proBDNF enhances LTD by regulating cholinergic inputs to the hippocampus. In the presence of the muscuranic receptor antagonist atropine (5 mM), proBDNF still facilitated LTD (Fig. 6d). Thus, it is less likely that proBDNF enhanced LTD by regulating cholinergic inputs. Finally, proBDNF selectively regulated LTD without affecting LTP. When hippocampal slices were incubated with proBDNF and subsequently subjected to two trains of HFS, LTP was readily induced and was not different from slices that were only incubated with the vehicle control (Supplementary Fig. 3). In addition, proBDNF also had no effect on late-phase LTP, induced either with long theta burst stimulation (Supplementary Fig. 3) or four trains of tetanic stimulation (4 100 Hz, 1 s; data not shown). These results suggest that the proBDNF selectively facilitates hippocampal LTD through the activation of p75NTR. Regulation of NR2B expression by proBDNF-p75NTR An emerging concept in the field of hippocampal plasticity is that LTP and LTD are differentially controlled by two different subtypes of NMDA receptors: NR2A and NR2B, respectively26,27. Given that the NMDA-dependent LTD, but not LTP, was selectively impaired in the p75 NTR/ mice, we tested whether proBDNF-p75NTR regulated specific subtypes of NMDA receptors by performing whole-cell voltageclamp recordings of CA1 pyramidal neurons. Resting membrane potential and input resistance of CA1 neurons were not different between p75 NTR/ and p75 NTR+/+ mice (data not shown). We stimulated Schaffer collaterals in the presence of AMPA and GABA receptor antagonists to induce synaptic NMDA currents. We observed a marked difference in the subunit composition of NMDA receptors between the two genotypes. Application of ifenprodil at a concentration that blocked LTD expression reduced isolated synaptic NMDA currents by more than 50% in slices derived from p75 NTR+/+ young juvenile mice (Fig. 7a,b). In contrast, application of ifenprodil had little or no effect on synaptic NMDA currents in age-matched p75 NTR/ slices (Fig. 7a,b). When we applied a high concentration of AP5, a

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Figure 8 Attenuated levels of NR2B expression in p75 NTR/ mice. (a,b) Western blot showing the levels for NR2B and NR2A protein. NR2B levels were substantially higher in hippocampal tissues taken from young animals than in older animals. Furthermore, NR2B probed in young p75 NTR/ tissue samples showed significantly lower levels (P o 0.05). (c,d) Quantification of protein levels of NR2B and NR2A normalized to an actin control. Error bars, s.e.m.

general antagonist for all subtypes of NMDA receptors, the NMDAmediated excitatory postsynaptic currents (EPSCs) were eliminated in both p75 NTR+/+ and p75 NTR/ slices (Fig. 7a). Thus, although the NR2B-containing NMDA receptor accounts for a substantial proportion of total NMDA channels at the p75 NTR+/+ CA1 synapses, which is made evident by the ifenprodil sensitivity and by the slower decay rate of the NMDA receptor–mediated EPSC (Fig. 7b), p75 NTR/ mice primarily express NMDA receptors that contain subunits other than NR2B. To investigate whether proBDNF directly regulates NR2B-mediated synaptic currents, we applied proBDNF to hippocampal slices. Such application markedly potentiated the NMDA currents at the CA1 synapses (Fig. 7c). The mean amplitude of the NMDA current after proBDNF treatment was 147 ± 12% when normalized to the baseline. In two extended recordings, the amplitude of the NMDA currents returned to near baseline levels after application of ifenprodil (data not shown). When the slices were pretreated with ifenprodil, application of proBDNF no longer potentiated the NMDA currents (Fig. 7c). Similarly, proBDNF did not enhance NMDA currents when applied to slices derived from p75 NTR/ mice. These results suggest that proBDNF through p75NTR selectively potentiates the NR2B component of the NMDA currents. We next examined the changes in the expression of NMDA receptor subtypes by immunohistochemistry and western blot analysis. Immunostaining showed that in the CA1 area, the NR2B staining of soma and apical dendrites seemed to be reduced in sections derived from young juvenile p75 NTR/ mice as compared with slices from p75 NTR+/+ mice of the same age (Supplementary Fig. 4). Older juvenile p75 NTR+/+ mice also seemed to show lower levels of NR2B immunoreactivity (Supplementary Fig. 4). Western blots confirmed this developmental decrease of NR2B, paralleling the developmental decrease in LTD expression (Fig. 8a). As a comparison, we also probed NR2A expression and observed that it was higher in younger juvenile (3-week-old) than in older juvenile (8-week-old) mice (Fig. 8b). Quantitative analysis showed the level of NR2B in p75 NTR/ hippocampus was significantly lower than that in wild-type hippocampus (Fig. 8c). But there was no difference in the level of NR2A protein between p75 NTR+/+ and p75 NTR/ mice (Fig. 8d; P 4 0.5). These results suggest that p75NTR mutation selectively alters the expression of NR2B-containing NMDA receptors in hippocampal CA1. DISCUSSION Recent studies suggest that pro-neurotrophins serve as signaling molecules rather than inactive precursors. Several studies have indicated that proBDNF, rather than mBDNF, is the major form secreted from CNS neurons8,22,23. But whether proBDNF has any biological function in synaptic plasticity remains unknown. The fact that p75 NTR/ mice have impairments in several learning and memory tasks38,39 and findings in a recent study showing a lack of LTD40 suggest that proBDNF may have a role in hippocampal synaptic plasticity. Here we provide evidence that proBDNF, signaling through p75NTR, is important for NMDA receptor–dependent LTD in the hippocampus.

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ARTICLES Our electrophysiology experiments showed that deletion of p75 NTR in mice selectively impaired the NMDA receptor–dependent form of LTD, without affecting other forms of synaptic plasticity tested. As p75NTR is known to interact with Nogo66, myelin-associated glycoprotein, oligodendrocyte myelin glycoprotein, pro–nerve growth factor (proNGF) and proBDNF41, it is important to identify the endogenous ligand that activates p75NTR under physiological conditions. Here, application of the p75NTR-blocking antibody REX virtually abolished LTD in wild-type mice, probably by inhibiting the interaction between endogenous proBDNF with p75NTR. Moreover, application of proBDNF to hippocampal slices enhanced LTD. Such potentiating effects were absent in p75 NTR/ mice, and were prevented by the REX antibody. Thus, we have identified proBDNF as an endogenous ligand that activates p75NTR to promote LTD. Growing evidence now supports the notion that LTP and LTD in the hippocampus are mediated by the NR2A and NR2B subunits of NMDA receptor, respectively26,27. We have shown that deletion of p75NTR selectively impaired, and proBDNF selectively enhanced, the NMDA receptor–dependent form of LTD. Neither p75NTR mutation nor proBDNF affected the NMDA receptor–dependent LTP. In parallel, the p75 NTR/ mice showed not only a selective decrease in NR2B (but not NR2A) expression in the hippocampus, but also a marked reduction in NR2B-mediated currents at the CA1 synapse. Notably, application of proBDNF potentiated the NR2B-mediated currents at CA1 synapses, suggesting that activation of p75NTR by proBDNF increased NR2B at the synapses. The enhancement of LTD by proBDNF was prevented by the NR2B antagonist ifenprodil. These results provide strong support for the idea that endogenously secreted proBDNF, by acting on p75NTR, promotes NMDA-dependent LTD by enhancing the expression of NR2B at CA1 synapses. To fully establish a causal link, however, it must still be shown that expression of NR2B in the hippocampus rescues the LTD impairment in p75 NTR/ slices. Exactly how proBDNF signals through p75NTR to regulate NR2B remains to be established. Immunostaining and western blotting experiments showed a substantial reduction in NR2B, but not NR2A, throughout the hippocampus of the p75 NTR/ mice, suggesting that proBDNF-p75NTR controls the expression of NR2B. This could possibly be achieved through activation of c-Jun kinase42 or NF-kB43, which are both expressed in hippocampal neurons. On the other hand, application of exogenous proBDNF enhanced NR2B-mediated synaptic currents in a p75NTR-dependent manner. Because the increase in NR2B currents occurred fairly rapidly after proBDNF application, this effect is less likely to be the result of p75NTR-mediated transcription and translation. It is possible that proBDNF facilitates the membrane insertion, trafficking into synapses or the channel properties of NR2B, all of which could, in theory, enhance LTD. Further investigation is necessary to distinguish these possibilities. Another finding that sheds light on the mechanisms of proBDNF regulation of LTD is the localization of p75NTR in CA1 synapses. It has long been believed that p75NTR protein in the hippocampus is primarily derived from basal forebrain cholinergic afferents44,45. It is possible that proBDNF is acting at p75NTR on the cholinergic afferents to induce the release of acetylcholine, which would also facilitate LTD37. But we have shown that atropine, a cholinergic antagonist, did not significantly alter the effect of proBDNF on LTD. Rather than an indirect mechanism, the enhancement of LTD may be the result of proBDNF directly binding to p75NTR expressed by CA1 hippocampal neurons. In support of this notion, immunohistochemistry at light and electron microscopic levels showed robust p75NTR expression in CA1 dendritic spines in addition to the afferent terminals


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in the hippocampus. Moreover, double staining conducted on cultured hippocampal neurons showed that p75NTR is colocalized with PSD95, a marker for postsynaptic density often localized in dendritic spines. Collectively, these results raise the possibility that proBDNF regulates hippocampal LTD by acting directly on p75NTR in the dendritic spines of CA1 neurons. Our study has several important implications. First, we have identified a new and specific function for proBDNF-p75NTR signaling in synaptic plasticity, which is in marked contrast to the conventional view of pro-neurotrophins and p75NTR in regulating neuronal apoptosis. Second, we have provided some insights into the mechanisms by which proBDNF controls hippocampal LTD. Our results suggest that proBDNF is an endogenous ligand for p75NTR receptors, which are localized on CA1 dendritic shafts and spines. Moreover, proBDNF promotes hippocampal LTD by regulating the expression of the NR2B subunit. Finally, our study suggests a bidirectional control of hippocampal plasticity by BDNF. Our recent work showed that tissue plasminogen activator, by activating the extracellular protease plasmin, converts the precursor proBDNF to the mBDNF, and such conversion is required for late-phase LTP in the hippocampus25. We now show that proBDNF, if not cleaved, enhances hippocampal LTD. These results support a provocative ‘yin-yang’ hypothesis46: uncleaved proBDNF enhances LTD through p75NTR, whereas activation of TrkB by mBDNF facilitates LTP and also inhibits LTD. Thus, proteolysis of the precursor form of BDNF becomes an important control mechanism for the direction of hippocampal plasticity. METHODS Mice. p75NTR/ mice, as characterized previously47, were backcrossed onto a C57BL/6 background for more than five generations. All animal procedures conformed to the US National Institutes of Health animal welfare guidelines. Electrophysiological recording. We prepared transverse hippocampal slices (400 mm) from p75 NTR/ and age-matched wild-type mice that were young (3–4 weeks old) or mature (8–10 weeks old). We maintained slices in an interface chamber exposed to a humidified atmosphere of 95% O2 and 5% CO2. After a minimum recovery period of at least 2 h, we recorded fEPSPs using an Axoclamp-2B amplifier (Axon Instruments) with an artificial cerebral spinal fluid (ACSF; composition was as previously described25)–filled glass microelectrode (1–3 MO) positioned in the stratum radiatum of hippocampal area CA1. We applied tetanic stimulation or LFS after stable baseline was established. Stimulus intensity was adjusted to evoke fEPSP approximately 40% of the maximum. We induced LTP by two trains of HFS (100 Hz, 1 s, separated by 20 s), whereas we induced LTD by either single (for NMDA receptor– dependent LTD) or twin pulses (for NMDA receptor–independent LTD, 50 ms interstimulus interval) applied at a rate of 1 Hz for 15 min. We made whole-cell recordings from CA1 pyramidal neurons of hippocampal slices using the blind patch method. We filled recording electrodes (5–8 MO) with intracellular solution containing (in mM): 130 K-gluconate, 10 HEPES, 2 Mg2ATP, 0.5 Na3GTP, 11 EGTA, 10 phosphocreatine and 5 QX314. We evoked EPSCs at a rate of 0.05 Hz by a placing a stimulating electrode in the stratum radiatum. We monitored access resistance throughout experiments, and it ranged from 10–25 MO. We discarded data when access resistance changed by 420% during an experiment. To isolate NMDA-mediated EPSCs, we voltage clamped neurons at –50 mV in the presence of 20 mM DNQX and 10 mM bicuculline methiodide. We recorded signals using an Axopatch 200B, filtered them at 5 kHz and digitized them at 10 kHz. We initially prepared NMDA (Tocris) and the antagonists atropine (Sigma), ifenprodil (Sigma), AP5 (Sigma), NMDA (Sigma), DNQX (Sigma) and bicuculline (Sigma) as concentrated stock solutions and diluted them with ACSF to the specified concentrations before each experiment. We added 1% BSA to proBDNF25 before perfusion. The vehicle control consisted of 1% BSA and the proteinase inhibitors. We incubated hippocampal slices with either mBDNF or proBDNF for at least 1 h before experiments.

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ARTICLES p75NTR immunohistochemistry and electron microscopy. We deeply anesthetized mice (n ¼ 5) and perfused them through the ascending aorta sequentially with 1,000 units/ml heparin in normal saline followed by 40 ml of a mixture of 3.75% acrolein and 2% paraformaldehyde in 0.1 M phosphate buffer (pH 7.4). We removed brains and postfixed them for 30 min, and then cut them into 40 mm sections using a Vibratome and collected them in phosphate buffer. We transferred free-floating sections to 1% sodium borohydride for 30 min and washed them extensively. We then then transferred them to 0.1 M Tris-saline (TS, pH 7.6) and incubated them sequentially in: (i) 0.5% BSA, 30 min; (ii) p75-specific antibody (Promega, 1:1,000; R&D Systems, 1: 400) in 0.1% BSA and 0.25% Triton X-100, 48 h; (iii) biotinylated rabbit-specific goat antibody or goat-specific rabbit antibody (Vector Laboratories) at 1:400 in 0.1% BSA, 30 min; (iv) avidin-biotin complex (VectaStain Elite kit, 30 min); (v) diaminobenzidine and H2O2, 8 min. Finally, we mounted sections onto slides previously coated with 1% gelatin, dried them and dehydrated them through an alcohol series into xylenes, and put them on coverslips using DPX (Aldrich). We took photographs using a Nikon Eclipse 80i microscope and a Photometrix digital camera. For electron microscopy, we prepared sections as previously described48. We counterstained ultrathin hippocampal sections containing CA1 with uranyl acetate and Reyonold lead citrate. We examined final preparations using a Tecnai Biotwin electron microscope (FEI). We identified hippocampal processes as neuronal using previously described criteria49. In particular, dendritic profiles contained regular microtubular arrays and were usually postsynaptic to axon terminal profiles. Terminal profiles had minimal diameters greater than 0.2 mm, contained numerous small synaptic vesicles and often contacted other neuronal profiles. Cleavage-resistant proBDNF. We purified the histidine-tagged, cleavageresistant proBDNF as previously described25. We introduced point mutations into the proconvertase cleavage site of proBDNF to convert the Arg-Arg (amino acid positions 129,130) to Ala-Ala. In vitro experiments showed that this proBDNF is resistant to cleavage by plasmin. We dialyzed the protein against ACSF, and stored it in small aliquots at 801C until use. p75NTR and PSD95 immunocytochemistry in cultured neurons. We cultured mouse hippocampal neurons as previously described50. Briefly, we dissected hippocampi from embryonic day 16 (E16) mice, dissociated them in tyrosine solution and plated them on coverslips coated with polylysine and laminin at 5,000 cells/coverslip. We grew cells in serum-free medium Neurobasal plus B27 (Life Technologies) at 371C, 5% CO2 incubator. After 14 d in vitro, we fixed the cells in 4% paraformaldehyde, permeabilized them with 0.1% Triton X-100 and incubated them with a p75NTR-specific rabbit antibody (Promega, 1:1,000 dilution), PSD95-specific mouse antibodies (1:300, Cell Signaling) in 3% BSA, followed by incubation with and Alex Fluor 488 (green for PSD95)– and Alex Fluor 546 (red for p75NTR)–conjugated secondary antibodies (Molecular Probes). We obtained images with a Zeiss confocal laser-scanning microscope using a 60 and a 100 (NA 1.40) objective. NMDA receptor immunohistochemistry. We anesthetized mice and transcardially perfused them with saline, then fixed them with 4% paraformaldehyde in PBS. We removed intact brains, post-fixed them in 4% paraformaldehyde for an additional 2 h, and placed them in 30% sucrose cryoprotectant solution for 48 h. Then we embedded the brains in OCT medium and stored them at 801C. We then sectioned frozen brains coronally at 40 mm using a Leica cryotome. For immunolabeling experiments, we blocked the prepared sections in normal serum, incubated them with NR2B-specific antibody (Chemicon) overnight at 41C and then incubated them with biotinylated secondary antibody. Next we processed sections using an immunoperoxidasebased Vectastain system. Western blot. We separated proteins from homogenized hippocampal tissues electrophoresis, and transferred them to PVDF membranes. After blocking using 5% BSA, we then incubated membranes with a rabbit polyclonal antibody against one of the following: NR2B (Chemicon 1:500); 9992 p75NTR-specific antibody (generated in the laboratory of B.L.H.; 1:1,000); or b-actin (ABCAM; 1:10,000) followed by a peroxidase-labeled rabbit-specific goat IgG. We processed blots and developed them using a chemilumininescent

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substrate (ECL plus). We scanned developed blots at high resolution and analyzed them using ImageJ software gel analyzer. We used band intensity normalized to an actin loading control to assess the protein levels. Statistical analysis. We used a Student t-test (two groups) or an analysis of variance (ANOVA) with a Tukey-Kramer post-test (three or more groups) for statistical comparisons of mean fEPSP slopes, with a significance level of P o 0.05. All values shown are mean ± s.e.m., with n ¼ number of slices. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS This work is supported by funds from National Institute of Child Health and Human Development intramural program (to B.L.), and US National Institutes of Health grants NS30658 (to B.L.H.) and HL18974 (to T.A.M.). N.H.W. is supported by fellowships from Alberta Heritage Foundation for Medical Research and Natural Sciences and Engineering Research Council of Canada. We would like to thank K. Sakata, J. Chang and K. Pelkey for advice and assistance. We also thank L. Tessarollo for providing p75 NTR/ mice and L. Reichardt for the p75NTR-blocking REX antibody. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 16 May; accepted 28 June 2005 Published online at http://www.nature.com/natureneuroscience/

1. Lu, B. BDNF and activity-dependent synaptic modulation. Learn. Mem. 10, 86–98 (2003). 2. Poo, M.M. Neurotrophins as synaptic modulators. Nat. Rev. Neurosci. 2, 24–32 (2001). 3. Korte, M. et al. Hippocampal long-term potentiation is impaired in mice lacking brain-derived neurotrophic factor. Proc. Natl. Acad. Sci. USA 92, 8856–8860 (1995). 4. Figurov, A., Pozzo-Miller, L., Olafsson, P., Wang, T. & Lu, B. Regulation of synaptic responses to high-frequency stimulation and LTP by neurotrophins in the hippocampus. Nature 381, 706–709 (1996). 5. Patterson, S.L. et al. Recombinant BDNF rescues deficits in basal synaptic transmission and hippocampal LTP in BDNF knockout mice. Neuron 16, 1137–1145 (1996). 6. Lessmann, V., Gottmann, K. & Malcangio, M. Neurotrophin secretion: current facts and future prospects. Prog. Neurobiol. 69, 341–374 (2003). 7. Lu, B. Pro-region of neurotrophins: role in synaptic modulation. Neuron 39, 735–738 (2003). 8. Mowla, S.J. et al. Biosynthesis and post-translational processing of the precursor to brain-derived neurotrophic factor. J. Biol. Chem. 276, 12660–12666 (2001). 9. Seidah, N.G., Benjannet, S., Pareek, S., Chretien, M. & Murphy, R.A. Cellular processing of the neurotrophin precursors of NT3 and BDNF by the mammalian proprotein convertases. FEBS Lett. 379, 247–250 (1996). 10. Kaplan, D.R. & Miller, F.D. Neurotrophin signal transduction in the nervous system. Curr. Opin. Neurobiol. 10, 381–391 (2000). 11. Huang, E.J. & Reichardt, L.F. Trk receptors: roles in neuronal signal transduction. Annu. Rev. Biochem. 72, 609–642 (2003). 12. Lee, R., Kermani, P., Teng, K.K. & Hempstead, B.L. Regulation of cell survival by secreted proneurotrophins. Science 294, 1945–1948 (2001). 13. Chao, M.V. & Bothwell, M. Neurotrophins: to cleave or not to cleave. Neuron 33, 9–12 (2002). 14. Ibanez, C.F. Jekyll-Hyde neurotrophins: the story of proNGF. Trends Neurosci. 25, 284–286 (2002). 15. Nykjaer, A. et al. Sortilin is essential for proNGF-induced neuronal cell death. Nature 427, 843–848 (2004). 16. Beattie, M.S. et al. ProNGF induces p75-mediated death of oligodendrocytes following spinal cord injury. Neuron 36, 375–386 (2002). 17. Harrington, A.W. et al. Secreted proNGF is a pathophysiological death-inducing ligand after adult CNS injury. Proc. Natl. Acad. Sci. USA 101, 6226–6230 (2004). 18. Teng, H.K. et al. ProBDNF induces neuronal apoptosis via activation of a receptor complex of p75NTR and sortilin. J. Neurosci. 25, 5455–5463 (2005). 19. Dechant, G. & Barde, Y.A. The neurotrophin receptor p75(NTR): novel functions and implications for diseases of the nervous system. Nat. Neurosci. 5, 1131–1136 (2002). 20. Barker, P.A. p75NTR is positively promiscuous: novel partners and new insights. Neuron 42, 529–533 (2004). 21. Lou, H. et al. Sorting and activity-dependent secretion of BDNF require interaction of a specific motif with the sorting receptor carboxypeptidase e. Neuron 45, 245–255 (2005). 22. Mowla, S.J. et al. Differential sorting of nerve growth factor and brain-derived neurotrophic factor in hippocampal neurons. J. Neurosci. 19, 2069–2080 (1999). 23. Chen, Z.-Y. et al. Variant brain-derived neurotrophic factor (BDNF) (Met66) alters the intracellular trafficking and activity-dependent secretion of wild-type bdnf in neurosecretory cells and cortical neurons. J. Neurosci. 24, 4401–4411 (2004). 24. Lee, K.F. et al. Targeted mutation of the gene encoding the low affinity NGF repector p75 leads to deficits in the peripheral sensory nervous system. Cell 69, 737–749 (1992).

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ARTICLES 25. Pang, P.T. et al. Cleavage of proBDNF by tPA/plasmin is essential for long-term hippocampal plasticity. Science 306, 487–491 (2004). 26. Liu, L. et al. Role of NMDA receptor subtypes in governing the direction of hippocampal synaptic plasticity. Science 304, 1021–1024 (2004). 27. Massey, P.V. et al. Differential roles of NR2A and NR2B-containing NMDA receptors in cortical long-term potentiation and long-term depression. J. Neurosci. 24, 7821–7828 (2004). 28. Cabin, D.E. et al. Synaptic vesicle depletion correlates with attenuated synaptic responses to prolonged repetitive stimulation in mice lacking alpha-synuclein. J. Neurosci. 22, 8797–8807 (2002). 29. Mischel, P.S. et al. The extracellular domain of p75NTR is necessary to inhibit neurotrophin-3 signaling through TrkA. J. Biol. Chem. 276, 11294–11301 (2001). 30. Oliet, S.H., Malenka, R.C. & Nicoll, R.A. Two distinct forms of long-term depression coexist in CA1 hippocampal pyramidal cells. Neuron 18, 969–982 (1997). 31. Hempstead, B.L. The many faces of p75NTR. Curr. Opin. Neurobiol. 12, 260–267 (2002). 32. Kemp, N. & Bashir, Z.I. Induction of LTD in the adult hippocampus by the synaptic activation of AMPA/kainate and metabotropic glutamate receptors. Neuropharmacology 38, 495–504 (1999). 33. Mulkey, R.M. & Malenka, R.C. Mechanisms underlying induction of homosynaptic long-term depression in area CA1 of the hippocampus. Neuron 9, 967–975 (1992). 34. Dudek, S.M. & Bear, M.F. Homosynaptic long-term depression in area CA1 of hippocampus and effects of N-methyl-D-aspartate receptor blockade. Proc. Natl. Acad. Sci. USA 89, 4363–4367 (1992). 35. Dougherty, K.D. & Milner, T.A. Cholinergic septal afferent terminals preferentially contact neuropeptide Y-containing interneurons compared to parvalbumin-containing interneurons in the rat dentate gyrus. J. Neurosci. 19, 10140–10152 (1999). 36. Ikegaya, Y., Ishizaka, Y. & Matsuki, N. BDNF attenuates hippocampal LTD via activation of phospholipase C: implications for a vertical shift in the frequency-response curve of synaptic plasticity. Eur. J. Neurosci. 16, 145–148 (2002). 37. Kirkwood, A., Rozas, C., Kirkwood, J., Perez, F. & Bear, M.F. Modulation of long-term synaptic depression in visual cortex by acetylcholine and norepinephrine. J. Neurosci. 19, 1599–1609 (1999).


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38. Wright, J.W., Alt, J.A., Turner, G.D. & Krueger, J.M. Differences in spatial learning comparing transgenic p75 knockout, New Zealand Black, C57BL/6, and Swiss Webster mice. Behav. Brain Res. 153, 453–458 (2004). 39. Peterson, D.A., Dickinson-Anson, H.A., Leppert, J.T., Lee, K.F. & Gage, F.H. Central neuronal loss and behavioral impairment in mice lacking neurotrophin receptor p75. J. Comp. Neurol. 404, 1–20 (1999). 40. Rosch, H., Schweigreiter, R., Bonhoeffer, T., Barde, Y.A. & Korte, M. The neurotrophin receptor p75NTR modulates long-term depression and regulates the expression of AMPA receptor subunits in the hippocampus. Proc. Natl. Acad. Sci. USA 102, 7362– 7367 (2005). 41. Bandtlow, C. & Dechant, G. From cell death to neuronal regeneration, effects of the p75 neurotrophin receptor depend on interactions with partner subunits. Sci. STKE 2004, pe24 (2004). 42. Davis, R.J. Signal transduction by the JNK group of MAP kinases. Cell 103, 239–252 (2000). 43. O’Neill, L.A. & Kaltschmidt, C. NF-kappa B: a crucial transcription factor for glial and neuronal cell function. Trends Neurosci. 20, 252–258 (1997). 44. Yan, Q. & Johnson, E.M., Jr. An immunohistochemical study of the nerve growth factor receptor in developing rats. J. Neurosci. 8, 3481–3498 (1988). 45. Van der Zee, C.E., Ross, G.M., Riopelle, R.J. & Hagg, T. Survival of cholinergic forebrain neurons in developing p75NGFR-deficient mice. Science 274, 1729–1732 (1996). 46. Lu, B., Pang, P.T. & Woo, N.H. The yin and yang of neurotrophin action. Nat. Rev. Neurosci. (in the press). 47. Lee, K.F., Bachman, K., Landis, S. & Jaenisch, R. Dependence of the p75 innervation of some sympathetic targets. Science 263, 1447–1449 (1994). 48. Dougherty, K.D. & Milner, T.A. p75NTR immunoreactivity in the rat dentate gyrus is mostly within presynaptic profiles but is also found in some astrocytic and postsynaptic profiles. J. Comp. Neurol. 407, 77–91 (1999). 49. Peters, A., Palay, S.L. & Webster, H.deF. The Fine Structure of the Nervous System (Oxford University Press, New York, 1991). 50. Ji, Y., Pang, P.T., Feng, L. & Lu, B. Cyclic AMP controls BDNF-induced TrkB phosphorylation and dendritic spine formation in mature hippocampal neurons. Nat. Neurosci. 8, 164–172 (2005).

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Norepinephrine triggers release of glial ATP to increase postsynaptic efficacy Grant R J Gordon1, Dinara V Baimoukhametova1, Sarah A Hewitt1, W R A Kosala J S Rajapaksha2, Thomas E Fisher2 & Jaideep S Bains1 Glial cells actively participate in synaptic transmission. They clear molecules from the synaptic cleft, receive signals from neurons and, in turn, release molecules that can modulate signaling between neuronal elements. Whether glial-derived transmitters can contribute to enduring changes in postsynaptic efficacy, however, remains to be established. In rat hypothalamic paraventricular nucleus, we demonstrate an increase in the amplitude of miniature excitatory postsynaptic currents in response to norepinephrine that requires the release of ATP from glial cells. The increase in quantal efficacy, which likely results from an insertion of AMPA receptors, is secondary to the activation of P2X7 receptors, an increase in postsynaptic calcium and the activation of phosphatidylinositol 3-kinase. The gliotransmitter ATP, therefore, contributes directly to the regulation of postsynaptic efficacy at glutamatergic synapses in the CNS.

Astrocytes1–4 and Schwann cells5 can respond to and influence neuronal signals by releasing glial-derived substances (gliotransmitters). However, until very recently3, the most ubiquitous gliotransmitter, ATP, had been categorized almost exclusively as a paracrine messenger responsible for inter-glial propagation of calcium waves6–8. There is now growing support for the idea that activation of neuronal purinergic receptors can affect synaptic plasticity9–11. Until now, the majority of the characterized actions of ATP on excitatory synaptic transmission, however, have been short-term, presynaptic changes in neurotransmitter release, with little evidence for enduring, postsynaptic changes. Given that ATP-gated P2X channels are calcium permeable12 and that the P2X7 receptor is linked directly to phosphatidylinositol 3-kinase (PI3K)13, an intracellular signaling molecule that is crucial for the insertion of AMPA receptors14 and the expression of LTP in the hippocampus15,16 and amygdala17, it seems plausible to hypothesize that ATP can induce enduring changes in postsynaptic efficacy. To study the putative contributions of glial-derived ATP to postsynaptic changes in synaptic strength, we examined glutamatergic synapses onto magnocellular neurosecretory cells (MNCs) in the paraventricular nucleus (PVN). The glial cells that surround the MNCs and their synaptic contacts show a notable degree of anatomical plasticity. In response to physiological challenges, they undergo a remodeling process that results in a decrease in the astrocytic coverage of synaptic contacts18,19. Taking advantage of this propensity of glial cells to retract when the animal is physiologically challenged, we can study synaptic function during conditions in which there is either a relative paucity or relative abundance of glial cells surrounding the

MNCs. This allows us to address directly the question of glia and, by extension, gliotransmitters in the regulation of synaptic function. Important for the study of ATP and long-term synaptic plasticity in this system is the demonstration that the MNCs have several subtypes of P2X receptors that are permeable to calcium12, the critical trigger for enduring changes in postsynaptic efficacy20. Furthermore, ATP receptors are critical for the increases in activity observed in MNCs in response to physiological perturbations that selectively recruit noradrenergic fibers21 and for facilitating hormone release in response to norepinephrine22. As a large fraction of catecholaminergic (and, more specifically, noradrenergic) terminals in the brain lack postsynaptic contacts23, this raises the possibility that signaling in this vital homeostatic circuit may require dynamic glial-neuronal interactions. Here, we demonstrate that norepinephrine increases the amplitude of miniature excitatory postsynaptic currents (mEPSCs) in MNCs through the release of ATP from glial cells. ATP acts at postsynaptic P2X7 receptors to promote the insertion of AMPA receptors through a mechanism requiring the calcium-dependent activation of PI3K. These data demonstrate a new mechanism by which glial cells can affect synaptic strength at excitatory synapses. RESULTS We examined changes in mEPSC amplitude as a measure of synaptic strength because of the compelling evidence that mEPSCs are important for information transfer in a number of vertebrate preparations24–26. Changes in mEPSC amplitude directly translate into changes in the firing patterns of CNS neurons, and, in particular, the MNCs27.

1Hotchkiss

Brain Institute and the Department of Physiology and Biophysics, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Canada T2N 4N1. of Physiology, College of Medicine, University of Saskatchewan, 107 Wiggins Road, Saskatoon, Saskatchewan, Canada S7N 5E5. Correspondence should be addressed to J.B. ([email protected]).

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Norepinephrine permanently increases mEPSC amplitude Bath application of norepinephrine (5 min, 200 mM) elicited three sequential changes in mEPSC amplitude. These were, in temporal order, a small enhancement followed by a robust increase lasting approximately 15 min, which in turn relaxed to a new mean and remained elevated even during our longest whole-cell recordings (which exceeded 90 min in length). This manuscript focuses on the enduring increase in mEPSC amplitude and not the initial increases during agonist application. In each cell, control mEPSC amplitudes were compared with those 30 min after treatment (gray demarcations in Fig. 1a). A minimum 5-min recording segment was used for the analysis. The enduring increase in mEPSC amplitude was 1.22 ± 0.05 (P o 0.01, n ¼ 20; Fig. 1a–d); all values are expressed as a fraction or multiple of the control condition. For the remainder of the manuscript, we often use the terms ‘increase in synaptic strength’ or ‘synaptic potentiation’ interchangeably with ‘enduring increase in mEPSC amplitude’. The a1 adrenoceptor mediates the excitatory effects of norepinephrine on MNCs28–31. Here, the a1-adrenoceptor agonist phenylephrine (5 min, 200 mM) effectively mimicked the effects of norepinephrine (1.23 ± 0.08, P o 0.01, n ¼ 5; Fig. 1d), whereas the a1-adrenoceptor antagonist prazosin (10 mM) attenuated them (0.99 ± 0.05, P 4 0.05, n ¼ 6; Fig. 1d). To rule out the possibility that the enduring increase in synaptic strength resulted from a slow washout of the agonist, prazosin was added to the bath immediately after norepinephrine application was terminated. This did not attenuate the enduring increase in synaptic strength (1.22 ± 0.09, P o 0.05, n ¼ 4, Fig. 1d). These data collectively suggest that transient activation of a1-adrenoceptors triggers a robust and enduring enhancement of mEPSC amplitude. This increase in synaptic strength is reminiscent of activitydependent changes in postsynaptic receptor function responsible for long-term potentiation (LTP) at cortical synapses20. Consequently,


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we investigated whether norepinephrine increased the postsynaptic response to exogenous AMPA application. The response to focal application of AMPA (see Methods) directly onto MNCs (mean: 197.4 ± 28.9 pA) was significantly increased after norepinephrine application (1.41 ± 0.09, P o 0.05, n ¼ 5; Fig. 1e,f). Norepinephrine triggers AMPA receptor insertion We used peak-scaled non-stationary noise analysis (PSNA)32 to investigate whether the increase in synaptic strength was associated with an increase in AMPA channel conductance33. To ensure that the fluctuation in mEPSC decay arose mostly from stochastic channel properties, we examined mEPSCs in the control condition and after norepinephrine treatment and confirmed there was no strong relationship between the rise time and decay time of the mEPSCs32 (control: 10– 90 rise-time versus decay-time r2 ¼ 0.15 ± 0.02; 30 min post– norepinephrine treatment: 10–90 rise-time versus decay-time r2 ¼ 0.11 ± 0.03, P 4 0.05, n ¼ 6). To establish that PSNA yielded unitary currents that were linearly related to voltage and predicted the reversal potential of the channel (approximately 0 mV), cells were voltage clamped at different potentials, and unitary current values satisfying these criteria were obtained (40 mV: 1.73 ± 0.29 pA; 60 mV: 2.61 ± 0.39 pA; 80 mV: 3.32 ± 0.44 pA; channel reversal: 4.4 mV, n ¼ 5; Fig. 2a,b). Next, we determined that there was no change in the unitary AMPA conductance upon application of a low dose of the AMPA receptor blocker DNQX (500 nM); this decreases mEPSC amplitude by completely blocking a fraction of AMPA receptors (control: 16.82 ± 2.85 pS; DNQX: 16.35 ± 2.81 pS, P 4 0.05, n ¼ 6; Fig. 2c,d). The mEPSC amplitude in DNQX was 0.73 ± 0.08, P o 0.05, n ¼ 7. The unitary conductance of mEPSCs in the control condition was not different from that after norepinephrine (control: 20.02 ± 3.63 pS; post-norepinephrine: 18.22 ± 2.69 pS, P 4 0.05, n ¼ 7; Fig. 2e,f). These values are consistent with those reported previously for excitatory synapses onto MNCs in the supraoptic nucleus (SON) of the hypothalamus34. It is widely accepted that the insertion of postsynaptic AMPA receptors is a mechanism by which synapses increase their strength20. We tested for this possibility by targeting SNARE-dependent vesicle exocytosis. Inclusion in our patch pipette of botulinum toxin C (5 mg/ ml), which proteolytically cleaves the tSNARE syntaxin35, completely blocked the enduring increase in quantal amplitude caused by norepinephrine (0.96 ± 0.04, P 4 0.05, n ¼ 7; Fig. 3a). Consistent with previous observations20, we found that this exocytotic process requires increases in postsynaptic calcium, as the inclusion of EGTA (10 mM) in

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our internal solution completely blocked the effects of norepinephrine (1.03 ± 0.02, P 4 0.05, n ¼ 6, Fig. 3b). Finally, we examined the cellular signals required for the insertion of AMPA receptors by targeting PI3K, which is important in the expression of LTP in the hippocampus14–16. Inclusion of either of two different PI3K inhibitors in the patch pipette (wortmannin (100 nM) or LY294002 (10 mM)) blocked the effects of norepinephrine on mEPSC amplitude (wortmannin: 1.02 ± 0.02, P 4 0.05, n ¼ 4; LY294002: 1.01 ± 0.02, P 4 0.05, n ¼ 5, Fig. 3c). Collectively, these data suggest that norepinephrine promotes the calcium-dependent, postsynaptic insertion of AMPA receptors through the activation of PI3K. Norepinephrine does not use postsynaptic receptors To examine the possibility that activation of the postsynaptic Gq-coupled a1-adrenoceptor directly increases mEPSC amplitude, we targeted two separate points on the a1-adrenoceptor intracellular

Figure 3 The enduring increase in mEPSC amplitude requires SNARE-dependent exocytosis, an increase in postsynaptic calcium and activation of PI3K. (a) Top: average mEPSCs before and after norepinephrine application with postsynaptic botulinum toxin C (5 mg/ml) to block SNARE-dependent exocytosis. Bottom: cumulative probability plot of mEPSC amplitudes (P 4 0.05) from the same cell. (b) Top: average mEPSCs before and after norepinephrine with postsynaptic EGTA (10 mM) to chelate calcium. Bottom: cumulative fraction plot (P 4 0.05) from the same cell. (c) Top: average mEPSCs before and after norepinephrine with postsynaptic LY294002 (10 mM) to block PI3K activation. Bottom: cumulative fraction plot (P 4 0.05) from the same cell. Scale bars 10 pA, 5 ms.

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cascade. First, we introduced thapsigargin (5 mM), which depletes calcium stores, into our patch electrode. This treatment did not block the norepinephrine-mediated increase in quantal amplitude (1.22 ± 0.05, P o 0.01, n ¼ 8, Fig. 4a). Second, we targeted the Gq-protein directly with intracellular perfusion of GDP-bs (1 mM). This experimental manipulation had no impact on the enduring increase in mEPSC amplitude after norepinephrine treatment (1.19 ± 0.02, P o 0.01, n ¼ 6, Fig. 4b). To confirm the validity of this negative result, we conducted an additional experiment in which we bath applied the glucocorticoid receptor agonist, dexamethasone (50 mM, 3 min). Activation of postsynaptic glucocorticoid receptors decreases glutamate release through a mechanism that requires the production of endocannabinoids36. Consistent with this report, dexamethasone decreased mEPSC frequency (0.49 ± 0.04, P o 0.01 compared with control condition, n ¼ 3). This was attenuated when GDP-bs was included in the internal solution (0.86 ± 0.13, P o 0.05 compared with dexamethasone alone, n ¼ 3). Collectively, these data suggest that postsynaptic a1-adrenoceptors are not responsible for the enduring increase in mEPSC amplitude. We have previously shown that norepinephrine transiently increases the frequency of glutamate release through a presynaptic a1-adrenoceptor–mediated mechanism31. This enhanced period of release may activate NMDA and/or metabotropic glutamate receptors (mGluRs) leading to a postsynaptic increase in synaptic strength. Although activation of NMDA receptors is crucial for hippocampal plasticity20, blockade of these receptors (with 100 mM D-L-AP5) did not affect the ability of norepinephrine to increase quantal amplitude (1.25 ± 0.05, P o 0.01, n ¼ 5, Fig. 4c). Although the experiments in which postsynaptic inclusion of GDP-bs and thapsigargin (above) would argue against a role for postsynaptic mGluRs, we directly tested for

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a1-adrenoceptors are colocalized with a glial marker Glial cells possess receptors for norepinephrine38, and in the PVN, a large fraction of noradrenergic terminals lack postsynaptic contacts23, leaving norepinephrine free to activate these cells. As the enduring enhancement of quantal amplitude is independent of glutamate

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P2X7 receptor activation is necessary and sufficient The excitatory effects of norepinephrine on MNC firing observed in vivo are attenuated by blockade of purinergic receptors21. We tested the hypothesis that direct activation of ATP-gated P2X receptors in our

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their contribution by applying norepinephrine in the presence of the group I mGluR antagonist MCPG (200 mM). Under these conditions, norepinephrine still increased synaptic strength (1.21 ± 0.01, P o 0.01, n ¼ 5, Fig. 4d). Collectively, these observations argue against a role for postsynaptic a1-adrenoceptors, NMDA receptors or group I mGluRs in mediating the enduring increase in mEPSC amplitude.

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slice preparation would effectively mimic the effects of norepinephrine on synaptic strength. Our experiments targeting postsynaptic G protein signaling argue against the metabotropic P2Y receptors, but MNCs possess a variety of functional P2X receptors capable of passing calcium12. We first tested ATP directly. Bath application of 30 mM ATP elicited a sustained increase in mEPSC amplitude (1.15 ± 0.02, P o 0.05, n ¼ 7). As ATP can be rapidly broken down by ectonucleotidases, this effect may be an underestimation. We repeated the experiment with BzATP, an analogue that is not readily degraded and can also activate several P2X channels, including P2X1, P2X3 and P2X7 (ref. 37). BzATP (30 mM, 3 min) increased mEPSC amplitude (1.17 ± 0.02, P o 0.01, n ¼ 8, Fig. 5a–c). We next tested the hypothesis that activation of P2X7 receptors was necessary for the norepinephrineinduced increase in synaptic strength. In the continuous presence of brilliant blue G (BBG, 1 mM) a P2X receptor antagonist that blocks P2X7 at the concentration used here37, norepinephrine failed to cause an enduring increase in mEPSC amplitude (1.04 ± 0.02, P 4 0.05, n ¼ 5, Fig. 5d–f). BBG also blocked the increase in synaptic strength induced by BzATP (1.03 ± 0.03, P 4 0.05, n ¼ 5, Fig. 5f). These data indicate that ATP-gated P2X7 receptor activation is both necessary and sufficient for increasing mEPSC amplitude.


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Figure 4 The enduring increase in mEPSC amplitude does not involve postsynaptic a1-adrenoceptors or glutamate signaling. (a) Top: average mEPSCs before and after norepinephrine application with postsynaptic thapsigargin (5 mM) to deplete calcium stores. Bottom: summary of effects of thapsigargin (1.22 ± 0.05, P o 0.01, n ¼ 8). (b) Top: average mEPSCs before and after norepinephrine application with postsynaptic GDP-bs (1 mM) to block G protein signaling. Bottom: summary of effects of GDP-bs (1.19 ± 0.02, P o 0.01, n ¼ 6). (c) Top: average mEPSCs before and after norepinephrine application with the NMDA receptor antagonist AP5 (100 mM). Bottom: summary of effects of AP5 (1.25 ± 0.05, P o 0.01, n ¼ 5). (d) Top: average mEPSCs before and after norepinephrine with the mGluR antagonist MCPG (200 mM). Bottom: summary of effects of MCPG (1.21 ± 0.01, P o 0.01, n ¼ 5). Scale bars: 10 pA, 5 ms. Error bars: s.e.m.

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Figure 6 Norepinephrine targets glial cells to release ATP. (a) Slice immunohistochemistry for the glial marker GFAP (top) and for the a1-adrenoceptor (middle). Overlaid confocal images show colocalization (bottom). Each picture comprises a series of stacked images, and each column is an example from a different rat. (b) Top: summary of relative increase in ATP release in response to norepinephrine (10–50 mM) from cultured glial cells (peak ATP release: 2.39 ± 0.17, P o 0.01, n ¼ 18). Bottom: summary demonstrating that norepinephrine-induced release of ATP is blocked in the presence of the fluorocitric acid (1.02 ± 0.07, P 4 0.05, n ¼ 7). Data represent the pooled responses from four separate glial culture systems: pituicytes, neonatal hypothalamus, hippocampus and neocortex. Error bars: s.e.m.

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receptors and postsynaptic G protein signaling, yet requires the activation of a1-adrenoceptors, we tested the hypothesis that the observed effect in response to norepinephrine was secondary to the activation of glial cells. We first tested for the presence of a1-adrenoceptors on glial cells in PVN using immunohistochemical techniques. Astrocytes were identified with glial fibrillary acidic protein (GFAP) staining, and long astrocytic processes were clearly labeled in the PVN (Fig. 6a, top). In addition, a primary antibody directed against the a1a-adrenoceptor subunit resulted in both punctate staining and staining characterized by long thin sections (Fig. 6a, middle). Although it is clear that a1-adrenoceptors are not localized exclusively to glial cells, confocal images showed a strong colocalization between the signal for the a1a-antibody and GFAP in the glial processes (Fig. 6a, bottom).

structural reorganization similar to that seen with SON and PVN glia in response to dehydration, parturition and lactation39. Using an ATP bioluminescence assay, we observed an increase in the ATP concentration in the surrounding saline in response to norepinephrine (10–50 mM). We then confirmed the ubiquitous nature of this phenomenon in three separate culture systems in which glial cells were isolated from the neonatal hypothalamus, hippocampus or the neocortex. Again, in each of these preparations, norepinephrine robustly increased the concentration of ATP in the surround media. As the increases in extracellular ATP were qualitatively similar across cultures, the data were pooled. During the first five minutes after norepinephrine application, ATP levels increased 2.39 ± 0.17–fold over the control condition (P o 0.01, n ¼ 18, Fig. 6b, top). We then used a pharmacological tool, fluorocitric acid (100 mM), to examine whether the norepinephrine effect could be abated when the glial Krebs cycle was blocked40. Cultures were incubated for a minimum of 2 h in fluorocitric acid before norepinephrine was applied. Under these conditions, norepinephrine did not trigger the release of ATP (1.02 ± 0.07, P 4 0.05, n ¼ 7, Fig. 6b, bottom).

Norepinephrine releases ATP from cultured glial cells We next investigated whether norepinephrine would elicit the release of ATP from cultured glial cells. To test this directly we used a system of cultured pituicytes. These glial cells engulf the neuropeptide-secreting terminals of the MNCs in the posterior pituitary and undergo

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Figure 7 Glial cells are necessary for the enduring increase in mEPSC amplitude triggered by a1-adrenoceptor activation. (a) Top: inward current at the onset of the norepinephrine effect (18.6 ± 3.4 pA, P o 0.01, n ¼ 8). The inward current was blocked when P2X channels were blocked with BBG (2.3 ± 3.6 pA, P 4 0.05, n ¼ 6; middle) and when slices were incubated for 42 h with fluorocitric acid (3.6 ± 1.0 pA, P 4 0.05, n ¼ 6; bottom). (b) Top: average mEPSC traces from control condition and post–norepinephrine treatment after fluorocitric acid incubation. Bottom: cumulative fraction plot of mEPSC amplitudes (P 4 0.05) from the same cell. (c) Top: average mEPSC traces from control condition and post–norepinephrine treatment after a 7- to 10-d dehydration protocol that elicits reduced glial coverage of synaptic contacts. Bottom: cumulative fraction plot of mEPSC amplitudes (P 4 0.05) from the same cell. (d) Top: average mEPSC traces from control condition and post–BzATP treatment in the dehydrated state. Bottom: cumulative fraction plot of mEPSC amplitudes (P o 0.01) from the same cell. Scale bars, a: 40 pA, 30 s; b,c,d: 10 pA, 5 ms.

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Glial cells are necessary for the norepinephrine effect We next used several different tactics to determine whether the ATP responsible for the norepinephrine-induced plasticity in brain slices was derived from glia. First, we tested for the possibility that ATP, released from nerve terminals in our preparation, gates fast purinoceptor-mediated synaptic transmission41. To maximize the likelihood of detecting ATP-mediated synaptic events, AMPA receptors were blocked (DNQX, 10 mM), and norepinephrine was applied. We did not detect any currents with kinetic features consistent with the rapid activation of ligand-gated ionotropic channels in response to synaptically released ATP41 (data not shown). We next examined our data for a slower, more prolonged inward current that might be indicative of a neuronal response to diffuse activation of membrane receptors. Both norepinephrine and BzATP elicited a slow inward current that preceded the increase in mEPSC amplitude (norepinephrine: 18.6 ± 3.4 pA, n ¼ 8; Fig. 7a, top; BzATP: 8.8 ± 1.5 pA, n ¼ 8). Furthermore, the inward current induced by norepinephrine was abolished by BBG (2.3 ± 3.6 pA, n ¼ 6; Fig. 7a, middle), suggesting that this response is P2X7 mediated. Notably, the transient increases in both frequency and amplitude elicited by norepinephrine were unaffected by BBG (Fig. 7a). To test the hypothesis that ATP in the slice is derived from glial cells, we again used fluorocitric acid to inhibit the glial Krebs cycle40. Similar to the culture systems, slices were incubated for a minimum of 2 h in fluorocitric acid before norepinephrine treatment. Under these conditions, norepinephrine did not increase the amplitude of mEPSCs (0.98 ± 0.02, P 4 0.05, n ¼ 6, Fig. 7b). Notably, the basal amplitude of mEPSCs from slices incubated in fluorocitric acid was not different from that in slices incubated in control solution (control: 28.15 ± 2.25 pA; fluorocitric acid: 27.10 ± 2.40 pA, P 4 0.05, n ¼ 10). We also did not observe an inward current in response to norepinephrine (3.6 ± 1.0 pA, P 4 0.05, n ¼ 6, Fig. 7a, bottom), yet the transient increases in mEPSC frequency and amplitude at the commencement of norepinephrine application were unaltered.


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Figure 8 A general rise in calcium in glial cells does not mimic the enduring increase in mEPSC amplitude observed in response to norepinephrine. (a) Left: average mEPSC traces showing no change in current amplitude after the bath application of 50 mM K+ in osmotically normal ACSF (2 min). Right: cumulative fraction plot of mEPSC amplitudes (P 4 0.05) from the same cell. (b) Left: average mEPSC traces showing that the GABAB receptor agonist baclofen (20 mM, 3 min) does not increase mEPSC amplitude. Right: cumulative fraction plot of mEPSC amplitudes (P 4 0.05) from the same cell. (c) Left: average mEPSC traces showing no change in current amplitude after bath application of caffeine (5 mM, 3 min). Right: cumulative fraction plot of mEPSC amplitudes (P 4 0.05) from the same cell. Scale bars: 10 pA, 5 ms.

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Finally, we used a physiological tool to assess the putative contribution of glial cells to the norepinephrine-induced synaptic potentiation. Glial coverage of synapses in the magnocellular neurosecretory nuclei can be decreased markedly by physiological challenges, such as parturition, lactation and dehydration18,19. Such dynamic changes in the physical relationship between neurons and glial cells increase glutamate spillover and increase presynaptic autoinhibition42. To test the hypothesis that synaptic glial processes are necessary for the norepinephrineinduced synaptic strengthening, we used an established dehydration protocol to cause glial retraction from synaptic contacts43. In these experiments, norepinephrine did not cause an enduring increase in the mEPSC amplitude (1.04 ± 0.02, P 4 0.05, n ¼ 12; Fig. 7c). Finally, to confirm that this effect is due to the absence of glial investiture (and hence availability of ATP) and not due to changes in postsynaptic P2X receptor expression or signaling, we applied BzATP directly to these slices and observed that the enduring increase in mEPSC amplitude could still be induced (1.16 ± 0.02, P o 0.01, n ¼ 6; Fig. 7d). It is important to note that in six additional cells, BzATP had no effect on amplitude. Taken together, these findings support the assertion that the norepinephrine-induced enduring increase in synaptic strength requires the release of ATP from surrounding glial cells. Although the precise mechanism of ATP release from glial cells remains controversial, there is increasing support for the idea that the process may be calcium independent7,44,45. To examine whether the release of ATP from hypothalamic glial cells is consistent with these observations, we used several strategies to increase the calcium concentration in glia and assessed their impact on mEPSC amplitude. First, we bath applied 50 mM K+ in iso-osmotic artificial cerebrospinal fluid (ACSF; 2 min)38. This resulted in a pronounced inward current as well as an increase in mEPSC frequency that washed out completely (data not shown) but did not elevate mEPSC amplitude (0.97 ± 0.01, P 4 0.05, n ¼ 5; Fig. 8a). Second, we applied the GABAB receptor agonist baclofen (20 mM, 3 min)2 which also did not increase mEPSC amplitude (0.99 ± 0.01, P 4 0.05, n ¼ 7; Fig. 8b). A decrease in the frequency of mEPSCs, consistent with the activation of GABAB receptors on glutamatergic terminals, was always observed, indicating that baclofen was reaching its target (data not shown). Although mGluRs can also increase calcium in glia46, this receptor, like the a1-adrenoceptor, is Gq-coupled and thus did not allow us to discriminate between the contribution of calcium from intracellular stores and that of other second messengers (such as diacylglycerol or IP3/IP4) in promoting the release of ATP. Instead, we applied caffeine (5 mM, 3 min), which liberates calcium from intracellular stores. Caffeine, however, did not increase mEPSC amplitude (1.01 ± 0.06, P 4 0.05, n ¼ 5; Fig. 8c). Finally, we either depleted intracellular calcium stores by incubating slices in thapsigargin (5 mM, 45 min) or blocked calcium release with a high dose of ryanodine (100 mM, 20 min) before testing with norepinephrine. These experimental manipulations did not block the norepinephrine-induced increase in mEPSC amplitude (thapsigargin

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+ norepinephrine: 1.22 ± 0.06, P o 0.01, n ¼ 8; ryanodine + norepinephrine: 1.21 ± 0.04, P o 0.01, n ¼ 5). These results are consistent with previous demonstrations suggesting that ATP release from glial cells occurs through a calcium-independent mechanism7,44,45. DISCUSSION The data presented here support the conclusion that ATP, released from glial cells in response to activation of a1-adrenoceptors, increases synaptic strength at glutamatergic synapses by promoting the postsynaptic insertion of AMPA receptors. Our findings further expand the role of glial cells in regulating the efficacy at excitatory synapses in the CNS1,3,4,42,47,48. The assertion that glia are the source of the ATP is consistent with both anatomical findings describing catecholaminergic terminals that lack direct postsynaptic contacts23 and physiological findings that norepinephrine can directly activate astrocytes38. Although it is clear that a1-adrenoceptors, in addition to being present on glial processes, are also present on non–GFAP-positive elements throughout the PVN, our inability to affect the expression of synaptic potentiation by either interfering with postsynaptic G protein function or depleting postsynaptic intracellular calcium stores argues against a direct postsynaptic action of norepinephrine. ATP may also be released in a vesicular fashion from presynaptic terminals in PVN. ATP-mediated synaptic currents have been reported in the CNS41, but we did not see any evidence for fast synaptic currents in the absence of glutamatergic signaling. We did, however, observe a slow, inward P2X7-mediated current in response to either norepinephrine or BzATP, which may be indicative of a slow increase in the concentration of a transmitter in the extracellular space, as might be predicted if ATP were released some distance from the postsynaptic cell. Although not on the same time scale, slow inward currents mediated by the activation of extrasynaptic NMDA receptors in response to glial glutamate have been recently described in hippocampal CA1 pyramidal neurons46. We were also able to block the increase in synaptic strength in response to norepinephrine by either pharmacologically compromising glial cells40 or using physiological manipulations that decrease the astrocytic coverage of synapses in the magnocellular neurosecretory system18,43. Finally, we demonstrate that application of norepinephrine directly onto neuronfree glial cultures increases the release of ATP. The norepinephrinedriven ATP release from glial cells provides a mechanism by which glia can respond to, and exert influence over, synaptic activity. Glia are known to respond to norepinephrine with increases in intracellular calcium38. Whether an increase in intraglial calcium can stimulate, or is even necessary for, ATP release is contentious. Both calcium-dependent49 and calcium-independent7,44,45 mechanisms have been described. We have found that increasing calcium either non-specifically (high K+) by activating a membrane-bound G protein–coupled receptor (baclofen) or by promoting release from intracellular stores (with caffeine) does not mimic the effects of norepinephrine on synaptic strength; this is most consistent with the idea that ATP release is not intimately linked to an increase in intraglial calcium. Our results also indicate that the key intracellular signaling molecules, postsynaptic calcium and PI3K14,20, that have been linked to the insertion of new AMPA receptors in other brain regions are conserved during the ATP-mediated increase in postsynaptic efficacy described here. Although the initial trigger for activation of this cascade in MNCs is different from that in a region such as the hippocampus, the ATPgated P2X7 receptor essentially serves as a surrogate for the NMDA receptor. The increase in mEPSC amplitude is blocked by buffering postsynaptic calcium with EGTA, interfering with PI3K signaling or by preventing vesicular fusion, all critical requirements for the insertion of

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new AMPA receptors into the postsynaptic membrane14,20. Our findings also support previous reports of P2X7 coupling to the PI3K/Akt pathway13. Although we cannot explicitly rule out the involvement of heteromeric P2X receptors or a contribution of P2Y receptors, our observations indicate that activation of the P2X7 receptor alone is sufficient for the calcium entry and that PI3K activation is necessary for the enduring increase in mEPSC amplitude in our preparation. In addition to advancing our understanding of the codependent interactions between glia and neurons, our findings also offer insights into a form of plasticity that may not be synapse specific (like LTP)20. Rather, it may be a new mechanism through which a single-point activation of interconnected glial networks may lead to changes in the synaptic strength of spatially distributed neuronal circuits and may contribute to the synchronization of firing activity in populations of cells that are not synaptically coupled46. METHODS Electrophysiology. Hypothalamic coronal slices (300 mm) containing PVN were prepared from male Sprague-Dawley rats (postnatal day (P) 21–28; Charles River). To promote retraction of glial cells, we used a dehydration protocol in which a solution of 2% NaCl was substituted for tap water for 7–10 d43. Animal use protocols were approved by the University of Calgary Animal Care and Use Committee. Animals were anesthetized (sodium pentobarbital 0.1 ml/100 g body weight) and decapitated, and brains were removed into ice-cold slicing solution for 3 min containing (in mM) NaCl 87, KCl 2.5, NaHCO3 25, CaCl2 0.5, MgCl2 7, NaH2PO4 1.25, glucose 25, sucrose 75, saturated with 95% O2/5% CO2. The brain was blocked and mounted on a vibrating slicer (Leica Instruments) submerged in ice-cold slicing solution. Slices were incubated at 32.5 1C in ACSF containing (in mM) NaCl 126, KCl 2.5, NaHCO3 26, CaCl2 2, MgCl2 2, NaH2PO4 1.25, glucose 10, saturated with 95% O2/5%CO2, for a minimum of 60 min. Using an upright microscope (Zeiss AxioskopII FS Plus) fitted with infrared differential interference contrast, whole-cell recordings were obtained from magnocellular PVN neurons (as confirmed by their distinct morphology and electrophysiological characteristics). All experimental recordings were obtained at 32.5 1C in voltage-clamp mode and were accepted barring changes in access resistance of 415%. The intracellular solution contained (in mM) potassium gluconate 123, MgCl2 2, NaCl 8, potassium EGTA 1, potassium ATP 4, and sodium GTP 0.3 buffered with KHCO3 16. In experiments in which drugs were introduced to the postsynaptic cell through the patch electrode, a minimum of 20 min was allowed for intracellular diffusion. For experiments with thapsigargin, a minimum diffusion time of 30 min was given. When GDP-bs was included in the internal solution, GTP was removed. The perfusate always contained picrotoxin (100 mM) to block GABAA channels and tetrodotoxin (1 mM) to block voltagegated Na+ channels. Cells were held at –80 mV to increase ionic driving force and to block the contribution of NMDA receptors to the synaptic response. In experiments using focal administration of AMPA (3-ms pulse, 100 mM, 25 psi), puffs were performed once every minute in the control, norepinephrine and wash conditions using a Picospritzer 2 (General Valve Corporation). The spritzing tips (resistance 3–6 mO) were placed directly over the soma of the patched cell. The response elicited was validated with 5 mM DNQX, which completely blocked the response (n ¼ 3). Immunohistochemistry. Male Sprague-Dawley rats (P21–28; Charles River) were anesthetized with sodium pentobarbital and perfused transcardially with cold phosphate buffered saline (PBS) followed by 4% paraformaldehyde. The brains were harvested and post-fixed in 4% paraformaldehyde overnight and then cryoprotected in 30% sucrose for another 24 h. Sections were cut on a cryostat to 30 mM and floated in PBS. The sections were washed in 0.2% Tween-20 in PBS for 10 min, followed by 30 min in 1% hydrogen peroxide to clear excess peroxidases. Sections were then washed three times before blocking (3% donkey serum, 0.2% Tween-20 and 2% dimethylsulfoxide (DMSO) in PBS) for 1 h. Subsequently, sections were incubated at 20–22 1C for 24 h with an affinity-purified rabbit polyclonal antibody against the a1a-adrenoceptor (Sigma, 1:250 in blocking buffer) followed by three washes

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ARTICLES (0.2% Tween-20, 2% DMSO in PBS) before incubation for two hours with Alexa Fluor 488 donkey anti-rabbit (Molecular Probes, 1:250 in blocking buffer). Sections were washed again three times (0.2% Tween-20, 2% DMSO in PBS) followed by a second 24-h incubation with a mouse monoclonal GFAP antibody conjugated with Cy3 (Sigma, 1:500 in blocking buffer). Sections were subsequently washed and mounted onto chrom alum–coated slides, coverslipped with Vectashield (Vector Labs) and visualized on a confocal microscope (Olympus, BX-51). Each image in Figure 6 comprises 12 sequential 1-mm plane images stacked together. Colocalization of GFAP and a1-adrenoceptor was also verified on a single plane occurring within the uppermost section of the glial process. Glial cell culture. Brains of two-day-old neonatal Wistar rats were removed after decapitation and were dissected using a dissecting microscope to separate hippocampus and cortex. These were separately mashed through an 80-mm Nitex mesh using a metal rod under aseptic conditions, as described50. All steps were carried out on ice. The collected cell suspension was cultured in 35-mm culture dishes in DMEM medium (Invitrogen) containing 10% fetal calf serum and was maintained at 37 1C in a humidified atmosphere containing 5% CO2. The medium was changed every 3–4 d. The cultures were used for the ATP assay after 10 d. For the pituicyte culture, posterior pituitaries were separated from decapitated adult Long-Evans rats using a dissecting microscope. The tissue was cut into eight pieces, each of which was attached to the bottom of a 35-mm culture dish in a fibrin clot and cultured under the conditions described above. The cells were used for the ATP assay after 14 d. For the ATP assay, the cell medium was replaced with physiological saline containing (in mM) NaCl 120, KCl 4, MgCl2 1.2, glucose 10, CaCl2 2, HEPES 10, pH 7.35. During the experiment, the saline was replaced every 2 min and an aliquot was used to measure ATP using an ATP bioluminescent assay kit (Sigma) and a 1251 luminometer (LKB Wallac) at room temperature. The light output was measured 1 min after the beginning of the luciferase reaction. During the two exchanges indicated, the saline also contained 10–50 mM norepinephrine. Data collection and statistics. Signals were amplified with the Multiclamp 700A amplifier (Axon Instruments), low-pass filtered at 1 kHz and digitized at 10 kHz using the Digidata 1322 (Axon Instruments). Data were collected (pClamp, Axon Instruments) and stored on computer for offline analysis using software designed to detect miniature synaptic events using a variable threshold (MiniAnalysis, Synaptosoft). The amplitude of mEPSCs was obtained during the control condition and 30 min after the cessation of norepinephrine or BzATP, where a minimum of 5 min (up to 10 min) of recording was taken for analysis. In each experiment, the change in mEPSC amplitude was assessed as a fraction of one. All cells in a given experimental set were averaged and are presented as mean ± s.e.m. Statistical analyses were performed using a twotailed Student’s t-test when comparing two groups, an analysis of variance (ANOVA) with a post-hoc Newman-Keuls test for comparisons across multiple groups and a Kolmogorov-Smirnov test for comparing two cumulative distributions. P o 0.05 was accepted as statistically significant (*, P o 0.05; **, P o 0.01). Peak-scaled non-stationary noise analysis (PSNA). The stochastic gating properties of AMPA receptors were assessed with PSNA using Synaptosoft Minianalysis software. In brief, 100–200 mEPSCs were selected with rise times o1 ms, aligned at steepest rise and then averaged. The mean mEPSC waveform was scaled to each individual mEPSC and subtracted to obtain the difference decay current. The variance was calculated between all difference currents, and a correction for post-mEPSC baseline variance was made. A parabolic relationship was obtained from the decay variance versus mean decay current plot and a regression line was fit to the first 50% of the data points back-calculated from the end-of-decay baseline. The slope of this relationship represents the weighted mean single-channel current, and the conductance is calculated from Ohm’s law, g ¼ i / E–Ex, where i represents the unitary current, and E–Ex is the driving force (80 mV). Drugs. Norepinephrine (1-[3,4-dihydroxyphenyl]-2-aminoethanol), phenylephrine ((R)-(-)-1-(3-hydroxyphenyl)-2-methylaminoethanol hydrochloride), prazosin (1-[4-amino-6,7-dimethoxy-2-quinazolinyl]-4-[2-furanylcarbonyl]piperazine), DNQX (6,7-dinitroquinoxaline-2,3(1H,4H)-dione), AMPA,


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LY294002 (2-(4-morpholinyl)-8-phenyl-1(4H)-benzopyran-4-one hydrochloride), wortmannin, BBG, BzATP (2¢-3¢-o-(4-benzoylbenzoyl)adenosine 5¢-triphosphate triethylammonium salt), ATP, picrotoxin, GDP-bs (guanosine 5¢-[b-thio]diphosphate trilithium salt), MCPG (a-methyl-(4-carboxyphenyl)glycine)), fluorocitric acid (D,L-fluorocitric acid, barium salt), baclofen ((±)-b(aminomethyl)-4-chlorobenzenepropanoic acid), thapsigargin and ryanodine (ryanodol 3-(1H-pyrrole-2-carboxylate), Ryania speciosa) were purchased from Sigma. Tetrodotoxin was purchased from Alomone Labs. Botulinum toxin C was purchased from Calbiochem. Picrotoxin, wortmannin and LY294002 were dissolved in DMSO (final concentration o0.1%). Prazosin was dissolved in methanol (final bath concentration o0.05%). MCPG was dissolved in 0.1 M NaOH. Fluorocitric acid was dissolved in ACSF with 15 min of sonication. ACKNOWLEDGMENTS We thank C. Sank for technical assistance and for conducting the immunohistochemistry experiments. We are also grateful to Q. Pittman for assistance with the dehydration protocol and for comments on an earlier version of the manuscript and to S. Oliet and B. MacVicar for helpful discussions. This work was supported by operating grants to J.S.B. from the Canadian Institutes of Health Research (CIHR) and T.E.F. from the Heart and Stroke Foundation of Saskatchewan. G.R.J.G. is supported by a studentship from the Natural Sciences and Engineering Research Council. J.S.B. is a CIHR New Investigator and an Alberta Heritage Foundation for Medical Research Scholar. T.E.F. is a CIHR/ Regional Partnership Program New Investigator. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 24 May; accepted 9 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Parpura, V. et al. Glutamate-mediated astrocyte-neuron signalling. Nature 369, 744–747 (1994). 2. Kang, J., Jiang, L., Goldman, S.A. & Nedergaard, M. Astrocyte-mediated potentiation of inhibitory synaptic transmission. Nat. Neurosci. 1, 683–692 (1998). 3. Zhang, J.M. et al. ATP released by astrocytes mediates glutamatergic activity-dependent heterosynaptic suppression. Neuron 40, 971–982 (2003). 4. Beattie, E.C. et al. Control of synaptic strength by glial TNFa. Science 295, 2282–2285 (2002). 5. Robitaille, R. Modulation of synaptic efficacy and synaptic depression by glial cells at the frog neuromuscular junction. Neuron 21, 847–855 (1998). 6. Guthrie, P.B. et al. ATP released from astrocytes mediates glial calcium waves. J. Neurosci. 19, 520–528 (1999). 7. Wang, Z., Haydon, P.G. & Yeung, E.S. Direct observation of calcium-independent intercellular ATP signaling in astrocytes. Anal. Chem. 72, 2001–2007 (2000). 8. Cotrina, M.L., Lin, J.H., Lopez-Garcia, J.C., Naus, C.C. & Nedergaard, M. ATP-mediated glia signaling. J. Neurosci. 20, 2835–2844 (2000). 9. Khakh, B.S. Molecular physiology of P2X receptors and ATP signalling at synapses. Nat. Rev. Neurosci. 2, 165–174 (2001). 10. Shigetomi, E. & Kato, F. Action potential-independent release of glutamate by Ca2+ entry through presynaptic P2X receptors elicits postsynaptic firing in the brainstem autonomic network. J. Neurosci. 24, 3125–3135 (2004). 11. Armstrong, J.N., Brust, T.B., Lewis, R.G. & MacVicar, B.A. Activation of presynaptic P2X7-like receptors depresses mossy fiber-CA3 synaptic transmission through p38 mitogen-activated protein kinase. J. Neurosci. 22, 5938–5945 (2002). 12. Shibuya, I. et al. Evidence that multiple P2X purinoceptors are functionally expressed in rat supraoptic neurones. J. Physiol. (Lond.) 514, 351–367 (1999). 13. Jacques-Silva, M.C. et al. P2X7 receptors stimulate AKT phosphorylation in astrocytes. Br. J. Pharmacol. 141, 1106–1117 (2004). 14. Man, H.Y. et al. Activation of PI3-kinase is required for AMPA receptor insertion during LTP of mEPSCs in cultured hippocampal neurons. Neuron 38, 611–624 (2003). 15. Sanna, P.P. et al. Phosphatidylinositol 3-kinase is required for the expression but not for the induction or the maintenance of long-term potentiation in the hippocampal CA1 region. J. Neurosci. 22, 3359–3365 (2002). 16. Raymond, C.R., Redman, S.J. & Crouch, M.F. The phosphoinositide 3-kinase and p70 S6 kinase regulate long-term potentiation in hippocampal neurons. Neuroscience 109, 531–536 (2002). 17. Lin, C.H. et al. A role for the PI-3 kinase signaling pathway in fear conditioning and synaptic plasticity in the amygdala. Neuron 31, 841–851 (2001). 18. Tweedle, C.D. & Hatton, G.I. Ultrastructural changes in rat hypothalamic neurosecretory cells and their associated glia during minimal dehydration and rehydration. Cell Tissue Res. 181, 59–72 (1977). 19. Theodosis, D.T. & Poulain, D.A. Activity-dependent neuronal-glial and synaptic plasticity in the adult mammalian hypothalamus. Neuroscience 57, 501–535 (1993). 20. Malinow, R. & Malenka, R.C. AMPA receptor trafficking and synaptic plasticity. Annu. Rev. Neurosci. 25, 103–126 (2002). 21. Day, T.A., Sibbald, J.R. & Khanna, S. ATP mediates an excitatory noradrenergic neuron input to supraoptic vasopressin cells. Brain Res. 607, 341–344 (1993).

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ARTICLES 22. Kapoor, J.R. & Sladek, C.D. Purinergic and adrenergic agonists synergize in stimulating vasopressin and oxytocin release. J. Neurosci. 20, 8868–8875 (2000). 23. Sawyer, C.H. & Clifton, D.K. Aminergic innervation of the hypothalamus. Fed. Proc. 39, 2889–2895 (1980). 24. Carter, A.G. & Regehr, W.G. Quantal events shape cerebellar interneuron firing. Nat. Neurosci. 5, 1309–1318 (2002). 25. Sharma, G. & Vijayaraghavan, S. Modulation of presynaptic store calcium induces release of glutamate and postsynaptic firing. Neuron 38, 929–939 (2003). 26. Zucker, R.S. Can a synaptic signal arise from noise? Neuron 38, 845–846 (2003). 27. Kombian, S.B., Hirasawa, M., Mouginot, D., Chen, X. & Pittman, Q.J. Short-term potentiation of miniature excitatory synaptic currents causes excitation of supraoptic neurons. J. Neurophysiol. 83, 2542–2553 (2000). 28. Armstrong, W.E., Gallagher, M.J. & Sladek, C.D. Noradrenergic stimulation of supraoptic neuronal activity and vasopressin release in vitro: mediation by an alpha 1-receptor. Brain Res. 365, 192–197 (1986). 29. Randle, J.C., Bourque, C.W. & Renaud, L.P. Alpha 1-adrenergic receptor activation depolarizes rat supraoptic neurosecretory neurons in vitro. Am. J. Physiol. 251, R569– R574 (1986). 30. Daftary, S.S., Boudaba, C., Szabo, K. & Tasker, J.G. Noradrenergic excitation of magnocellular neurons in the rat hypothalamic paraventricular nucleus via intranuclear glutamatergic circuits. J. Neurosci. 18, 10619–10628 (1998). 31. Gordon, G.R. & Bains, J.S. Priming of excitatory synapses by alpha1 adrenoceptormediated inhibition of group III metabotropic glutamate receptors. J. Neurosci. 23, 6223–6231 (2003). 32. Traynelis, S.F., Silver, R.A. & Cull-Candy, S.G. Estimated conductance of glutamate receptor channels activated during EPSCs at the cerebellar mossy fiber-granule cell synapse. Neuron 11, 279–289 (1993). 33. Benke, T.A., Luthi, A., Isaac, J.T. & Collingridge, G.L. Modulation of AMPA receptor unitary conductance by synaptic activity. Nature 393, 793–797 (1998). 34. Stern, J.E., Galarreta, M., Foehring, R.C., Hestrin, S. & Armstrong, W.E. Differences in the properties of ionotropic glutamate synaptic currents in oxytocin and vasopressin neuroendocrine neurons. J. Neurosci. 19, 3367–3375 (1999). 35. O’Connor, V. et al. Disruption of syntaxin-mediated protein interactions blocks neurotransmitter secretion. Proc. Natl. Acad. Sci. USA 94, 12186–12191 (1997).

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36. Di, S., Malcher-Lopes, R., Halmos, K.C. & Tasker, J.G. Nongenomic glucocorticoid inhibition via endocannabinoid release in the hypothalamus: a fast feedback mechanism. J. Neurosci. 23, 4850–4857 (2003). 37. North, R.A. Molecular physiology of P2X receptors. Physiol. Rev. 82, 1013–1067 (2002). 38. Duffy, S. & MacVicar, B.A. Adrenergic calcium signaling in astrocyte networks within the hippocampal slice. J. Neurosci. 15, 5535–5550 (1995). 39. Tweedle, C.D. & Hatton, G.I. Morphological adaptability at neurosecretory axonal endings on the neurovascular contact zone of the rat neurohypophysis. Neuroscience 20, 241–246 (1987). 40. Clarke, D.D. Fluoroacetate and fluorocitrate: mechanism of action. Neurochem. Res. 16, 1055–1058 (1991). 41. Edwards, F.A., Gibb, A.J. & Colquhoun, D. ATP receptor-mediated synaptic currents in the central nervous system. Nature 359, 144–147 (1992). 42. Oliet, S.H., Piet, R. & Poulain, D.A. Control of glutamate clearance and synaptic efficacy by glial coverage of neurons. Science 292, 923–926 (2001). 43. Miyata, S., Nakashima, T. & Kiyohara, T. Structural dynamics of neural plasticity in the supraoptic nucleus of the rat hypothalamus during dehydration and rehydration. Brain Res. Bull. 34, 169–175 (1994). 44. Leybaert, L., Paemeleire, K., Strahonja, A. & Sanderson, M.J. Inositol-trisphosphatedependent intercellular calcium signaling in and between astrocytes and endothelial cells. Glia 24, 398–407 (1998). 45. Anderson, C.M., Bergher, J.P. & Swanson, R.A. ATP-induced ATP release from astrocytes. J. Neurochem. 88, 246–256 (2004). 46. Fellin, T. et al. Neuronal synchrony mediated by astrocytic glutamate through activation of extrasynaptic NMDA receptors. Neuron 43, 729–743 (2004). 47. Araque, A., Parpura, V., Sanzgiri, R.P. & Haydon, P.G. Glutamate-dependent astrocyte modulation of synaptic transmission between cultured hippocampal neurons. Eur. J. Neurosci. 10, 2129–2142 (1998). 48. Bezzi, P. & Volterra, A. A neuron-glia signalling network in the active brain. Curr. Opin. Neurobiol. 11, 387–394 (2001). 49. Coco, S. et al. Storage and release of ATP from astrocytes in culture. J. Biol. Chem. 278, 1354–1362 (2003). 50. Bekar, L.K. et al. Complex expression and localization of inactivating Kv channels in cultured hippocampal astrocytes. J. Neurophysiol. 93, 1699–1709 (2005).

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Synchronized retinal oscillations encode essential information for escape behavior in frogs Hiroshi Ishikane1,2, Mie Gangi1, Shoko Honda1 & Masao Tachibana1 Synchronized oscillatory activity is generated among visual neurons in a manner that depends on certain key features of visual stimulation. Although this activity may be important for perceptual integration, its functional significance has yet to be explained. Here we find a very strong correlation between synchronized oscillatory activity in a class of frog retinal ganglion cells (dimming detectors) and a well-known escape response, as shown by behavioral tests and multi-electrode recordings from isolated retinas. Escape behavior elicited by an expanding dark spot was suppressed and potentiated by intraocular injection of GABAA receptor and GABAC receptor antagonists, respectively. Changes in escape behavior correlated with antagonist-evoked changes in synchronized oscillatory activity but not with changes in the discharge rate of dimming detectors. These antagonists did not affect the expanding dark spot–induced responses in retinal ganglion cells other than dimming detectors. Thus, synchronized oscillations in the retina are likely to encode escape-related information in frogs.

Synchronized activity accompanied by g-range (B20 to B80 Hz) oscillations is frequently observed in various nervous systems, and this neural activity may be related to perception, attention and memory1–13. In the visual system, synchronized oscillatory activity is found in various regions, such as the retina14,15, the lateral geniculate nucleus14,15, the primary visual cortex1,2,16 and the posteromedial lateral suprasylvian sulcus17. Furthermore, synchronized oscillatory activity is found not only among neurons located within one region but also among neurons in different regions17,18. The synchronized oscillatory activity depends on certain stimulus features such as continuity and direction of motion2,19,20, and thus it may serve to integrate spatially distributed features1,2,14,15,21,22. However, its functional significance remains unclear. Frogs jump away when a predator approaches, and the characteristic stimulus that elicits escape behavior is a looming or expanding dark object23,24. In the frog retina, ganglion cells are categorized into four classes on the basis of their response properties: sustained contrast detectors, net convexity detectors, moving-edge detectors and dimming detectors25. A large darkening or dimming light evokes off-sustained spike discharges in the dimming detector but elicits only a few spike discharges transiently in other cell classes (the non-dimming detector classes)25. Of these cell classes, the dimming detectors are of note, as it has been reported that pharmacological blockade of their activity selectively suppresses escape behavior without affecting prey-catching behavior24. However, it is not evident how dimming detectors encode escape-related information, although coding by discharge rate is commonly assumed. A possible candidate is synchronized oscillatory spike discharge, which is gener-

ated among dimming detectors when a large retinal area is stimulated by a dimming light26. As we have already shown in the frog retina, the g-range oscillations induced in dimming detectors by a large dimming stimulus are suppressed by a GABAA receptor (GABAAR) antagonist, bicuculline26,27, whereas these activities are enhanced by a GABACR antagonist, (1,2,5,6-tetrahydropyridin-4-yl)methylphosphinic acid (TPMPA)27. In the present study, using these GABAR antagonists as a tool, we examined the relationship between visually guided behaviors and light-evoked spike discharges of ganglion cells in isolated retinas. Our results indicate that synchronized oscillatory activity among retinal dimming detectors may have an important role in escaperelated visual information processing in frogs. RESULTS Suppression of escape behavior by a GABAAR antagonist An expanding dark spot that emulated the shadow of an approaching predator evoked escape behavior in frogs (Fig. 1a). The escape rate (number of escape trials / total number of trials) increased with increasing expansion speed (Fig. 1b; final spot diameter, 551) and final diameter (Fig. 1c; expansion speed, 431 s1) of the dark spot. When we presented a dark spot expanding from 01 to 551 at a speed of 431 s1, the escape rate reached B0.85 (Fig. 1c), and the reaction time for escape was 1.01 7 0.03 s (mean 7 s.e.m., n ¼ 5 frogs) from the start of spot expansion. Notably, escape behavior was elicited neither by an expanding bright spot nor by an expanding dark ring (n ¼ 3 frogs), stimuli which activate the non-dimming detector classes25 (see Supplementary Fig. 1 online). These behavioral tests support

1Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. 2Present address: Laboratory for Neuroinformatics, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan. Correspondence should be addressed to M.T. ([email protected]).



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ARTICLES times) with the expanding dark spot, the parameters of which were similar to those 1.0 used for the behavioral test (from 01 to 601 at the speed of 431 s1; Fig. 1d). We recorded 0.5 0.5 spike discharges from various cell classes, the receptive fields of which were located within 0.0 0.0 the stimulated area. Then we constructed peri10 20 30 40 50 60 0 20 40 60 Spot diameter (deg) Speed of expansion (deg/s) stimulus time histograms (PSTHs, 50-ms bin width) and autocorrelograms (2-ms bin width) to analyze the temporal pattern of d e spike discharges (Fig. 2). ** ** Dimming detectors generated sustained 1.0 1.0 discharges to the expanding dark spot (Fig. 2a, top). Autocorrelation analysis 0.5 0.5 showed a pattern with periodic peaks at regular intervals. The power spectrum, 0.0 0.0 which is the Fourier transform of the autoControl Std Washout Control Bic Washout correlation function, showed a clear peak at 32.15 7 1.28 Hz (mean 7 s.e.m., n ¼ 13 Figure 1 Bicuculline suppressed escape behavior in response to the expanding dark spot. (a) Visually elicited escape behavior of a frog was examined with an expanding dark spot presented on a computercells), indicating the presence of g-range oscilcontrolled display. (b) Relationship between the expansion speed of a dark spot and the escape rate lations. Bicuculline suppressed the periodic (mean 7 s.e.m., n ¼ 6 frogs). (c) Relationship between the final diameter of an expanding dark spot peaks in the autocorrelogram and the peak in and the escape rate (mean 7 s.e.m., n ¼ 5 frogs). (d) Suppression of escape behavior by intraocular the g range (Fig. 2a, bottom), indicating the injection of a GABAAR antagonist, bicuculline. Behavioral experiments were performed before (Control), suppression of g-range oscillations. 2 h after (‘Bic’) and 1 d after (Washout) injection. The dark spot expanded from 01 to 551 at the Both sustained contrast and/or net convexexpansion speed of 431 s1. The escape rate was normalized to the value obtained before injection ity detectors and moving-edge detectors (Control). Mean 7 s.e.m., n ¼ 5 frogs. **P o 0.01. (e) Effect of intraocular injection of the standard saline without bicuculline (mean 7 s.e.m., n ¼ 5 frogs). The experimental procedure was the same as evoked transient discharges to the expanding that employed in d. dark spot (1.73 7 0.42 spikes/trial in 11 sustained contrast and/or net convexity detectors and 2.72 7 0.46 spikes/trial in the hypothesis that dimming detectors may be critical in eliciting 14 moving edge detectors; Fig. 2b,c, top). The autocorrelograms and power spectra do not indicate any detectable g-range oscillations in escape behavior24. The oscillatory discharges that are evoked by a large dimming these non-dimming detector classes (Fig. 2b,c). Bicuculline did not stimulus in dimming detectors of frog’s retinas are suppressed by induce any obvious changes in the profiles of PSTHs, autocorrelograms GABAAR antagonists26,27. Thus, we injected bicuculline into both eyes or power spectra (Fig. 2b,c, bottom). Among all cell classes, only under anesthesia and allowed the frogs to recover (B2 h). We tested dimming detectors showed a significant increase in the number of spike escape behavior with an optimal expanding dark spot (expansion discharges (P o 0.05, t-test, n ¼ 7 cells; Fig. 2d, left) and a significant speed, 431 s1; final spot diameter, 551; Fig. 1b,c). This pharmaco- decrease in the oscillation index (see Methods; P o 0.01, t-test, logical treatment significantly suppressed escape behavior (P o 0.01, n ¼ 7 cells; Fig. 2d, right) in response to bicuculline. Thus, behavioral repeated-measures ANOVA followed by Tukey’s method, n ¼ 5 frogs; changes induced by intraocular injection of bicuculline may not Fig. 1d). The suppressive effect of bicuculline was recovered 1 d after be ascribed to changes in the activity of cell classes other than bicuculline injection (Fig. 1d). Intraocular injection of physiological dimming detectors. Applying a planar multi-electrode array to the isolated retinas29, saline without bicuculline did not change escape behavior (P ¼ 0.46, repeated-measures ANOVA, n ¼ 5 frogs; Fig. 1e), indicating that we closely examined the effects of bicuculline on the activities of suppression of escape behavior (Fig. 1d) could not be ascribed to dimming detectors. We mapped each receptive field center of recorded experimental artifacts such as the effect of anesthesia. dimming detectors using a small flashing spot (Fig. 3a). Then we projected a dark spot that expanded from 01 (0 s) to 601 (1.4 s) on the Effects of bicuculline on retinal ganglion cells retina (Fig. 3a,b). Figure 3c (top) illustrates an example of the spike To examine how bicuculline affected the responses induced by the trains simultaneously recorded from seven dimming detectors during a expanding dark spot in retinal ganglion cells, we recorded spike single presentation of the expanding dark spot. In the control condidischarges extracellularly from isolated frog retinas. Each ganglion cell tion, when the spot diameter exceeded B401 (B0.9 s after stimulus class was identified as follows: cells that generated off-sustained spike onset), the inter-spike intervals became regular, and spike discharges discharges to a full-field stimulus (44 mm in diameter on the retina) were phase-locked across dimming detectors. Notably, for each dimwere identified as dimming detectors, cells that generated transient ming detector the latency of the first spike as well as the emergence of spike discharges at the onset and offset of the full-field stimulus as regular inter-spike intervals after the start of dark spot expansion varied moving-edge detectors, and cells that evoked transient spike discharges from trial to trial (Supplementary Fig. 2). A PSTH (50-ms bin width) to a small flashing spot (B100 mm in diameter) but no spike discharges was constructed from the simultaneous spike trains recorded from to the full-field stimulus as sustained contrast and/or net convexity seven dimming detectors during the single stimulus presentation detectors. The sustained contrast and/or net convexity detectors were (Fig. 3c). The number of spikes/bin increased as the dark spot categorized as one group because these cells respond similarly to a expanded. The profile of PSTH seemed similar before (Fig. 3c) and moving dark stimulus28. We stimulated the retinas repeatedly (100 during application of bicuculline (Fig. 3d). However, the regularity of

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Figure 2 Effects of bicuculline on the activities of retinal ganglion cells. (a–c) Spikes were recorded during 100 repetitive trials from dimming detectors (a), sustained contrast and/or net convexity detectors (b), and moving-edge detectors (c). The dark spot expanded from 01 (0 s) to 601 (1.4 s) at the speed of 431 s1 and then was maintained for 3 s. The PSTHs (left; 50-ms bin width), autocorrelograms (middle; 2-ms bin width) and power spectra (right) were calculated before (control) and during application of 10 mM bicuculline. In this and the following figures, the number shown in each autocorrelogram indicates the peak value at zero time shift. (d) Summary of the effects of bicuculline on the number of spikes (left) and the oscillation index (right). Mean 7 s.e.m. Data obtained from seven dimming detectors, six sustained contrast and/or net convexity detectors (SC/NC detectors), and seven moving-edge detectors (ME detectors). *P o 0.05, **P o 0.01.

oscillations of each dimming detector (see Fig. 2a, control autocorrelogram and power spectrum) were phase-locked or synchronized. To demonstrate the synchrony of oscillations plainly, we extracted a synchronized event (Fig. 4b, top) where spikes were generated within 2 ms in multiple (Z2) dimming detectors (Fig. 4b, inset), and we calculated the autocorrelation (Fig. 4b, bottom left) and power spectrum (Fig. 4b, bottom right) from the synchronized event train.

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Figure 3 Spike trains evoked by an expanding dark spot in multiple dimming detectors in the isolated retina. (a) Map of receptive field centers of the seven recorded dimming detectors. The dark spot started expanding from the receptive field center of cell #1. Scale bar indicates 1.0 mm, which corresponds to B101 of subtense. (b) Changes in spot size (diameter) with time. (c) A single-trial record of simultaneous spike trains in the control condition. Top: the raster plots of discharges simultaneously recorded from seven cells shown in a. Bottom: the peri-stimulus time histogram (PSTH, 50-ms bin width) calculated from the simultaneous spike trains shown above. (d) The raster plots (top) and PSTH (bottom) obtained from the same cells in the presence of 10 mM bicuculline.

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inter-spike intervals (Fig. 3c, top) seemed to be obscured by bicuculline (Fig. 3d, top). To analyze the temporal pattern of spike trains, we created an ensemble spike train from the simultaneous spike trains recorded from several dimming detectors during repetitive presentations of the expanding dark spot. In the control condition, an autocorrelogram of the ensemble spike train showed a pattern with periodic peaks at regular intervals (Fig. 4a, left), and the power spectrum of the autocorrelation function showed a clear peak at B40 Hz (Fig. 4a, right). Because the response period of each dimming detector was mostly overlapping during each stimulus presentation (Fig. 3c, top), these results indicate that the g-range

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ARTICLES each; t-test, n ¼ 5 retinas; Fig. 4e; see Methods). However, blockade of inhibitory inter1,000 actions mediated by GABAARs increased 40 40 500 the number of spike discharges (P o 0.05), 20 20 resulting in an increase in the number of synchronized events (P o 0.05). These 0 0 0 0 0 100 200 150 –150 0 –150 0 150 0 100 200 results strongly suggest that the bicucullineTime shift (ms) Frequency (Hz) Time shift (ms) Frequency (Hz) induced suppression of escape behavior (Fig. 1d) may be caused by impairment of b d the synchronized g-range oscillations among 1. 1. ... ... dimming detectors. ... ... .. .. To clarify the relationship between the 7 7 synchronized oscillation and the distance between dimming detectors, we calculated 1.5 1.0 1.5 1.0 cross-correlations for each pair of dimming Time (s) detectors before and during application of bicuculline (Fig. 5a). In the control condition, cross-correlograms demonstrated a pattern with a central peak and periodic side peaks 1.42 1.44 1.46 (Fig. 5a, top), indicating the presence of 100 538 394 synchronization (the central peak) accompa0.5 0.5 50 nied by oscillations (the side peaks). The shift predictors were almost flat (Fig. 5a, top, inset), indicating that the synchronization 0 0 0 0 and oscillations had a neural origin. During –150 0 150 0 100 200 –150 0 150 0 100 200 bicuculline application the oscillations disapTime shift (ms) Frequency (Hz) Time shift (ms) Frequency (Hz) peared in all cell pairs (Fig. 5a). However, the e synchronization still remained in near-cell * 1.5 * Figure 4 Bicuculline impaired the synchronized pairs (0 to 0.5 mm; Fig. 5a) whereas it was oscillations among dimming detectors. (a) Analysis obscured in remote-cell pairs (0.5 to 1.0 of the ensemble spike train. Data were obtained 1 mm, and 41 mm; Fig. 5a). We found from seven dimming detectors shown in Figure 3a ** that during bicuculline application, the ** during ten repetitive presentations of the expanding 0.5 synchronization index (see Methods) did dark spot. Autocorrelogram of the ensemble spike not change in near-cell pairs (0 to 0.5 mm, train (left) and its power spectrum (right). (b) Top: 0.0 a part of the simultaneous spike trains shown in n ¼ 9 pairs; Fig. 5b) but became significantly # Spikes Osci # Sync OS Figure 3c and the extracted synchronized event train small in remote-cell pairs (0.5 to 1 mm, (‘Sync event’). Inset, the simultaneous spike trains n ¼ 11 pairs; 41 mm, n ¼ 49 pairs; P o were grouped in 2-ms bins (vertical lines) and the synchronized events were extracted. Bottom: 0.01 each, t-test; Fig. 5b). These results sugautocorrelogram of the synchronized event train (left) and its power spectrum (right). (c) Effects of gest that suppression of oscillations by bicuculline (10 mM) on the ensemble spike train. Autocorrelogram of the ensemble spike train (left) and bicuculline may impair the long-range synits power spectrum (right). (d) Top: a part of the simultaneous spike trains in the presence of bicuculline shown in Figure 3d and the extracted synchronized events. Bottom: effects of bicuculline on the chrony of spike discharges without affecting synchronized event train. Autocorrelogram of the synchronized event train (left) and its power spectrum the local synchrony. (right). (e) Effects of bicuculline on the number of spikes (‘# Spikes’), the oscillation index (‘Osci’), the We also calculated time-resolved slidingnumber of synchronized events (‘# Sync’), and the oscillatory synchronization index (‘OS’). Each value window cross-correlograms (200-ms time was normalized to the control condition. Mean 7 s.e.m., n ¼ 5 retinas. *P o 0.05, **P o 0.01. window, 20-ms sliding steps; see Methods) to examine how the synchronization and oscillations developed with increasing spot size These analyses indicate that the synchronized event occurred in (Fig. 5c, bottom). In the control condition, for both near- and remote-cell pairs, a clear striped pattern was observed along the time oscillation (39.84 7 3.36 Hz, n ¼ 5 retinas). Bicuculline impaired the oscillations (Fig. 4c) and the oscillatory axis (4B1 s), indicating the presence of synchronization (the horsynchronization (Fig. 4d). Periodic peaks disappeared both in the izontal center line at zero time shift) and oscillations (horizontal lines autocorrelogram calculated from the ensemble spike train (Fig. 4c, left) nearly parallel to the center line). With time the inter-stripe width and in that from the synchronized event train (Fig. 4d, bottom left). In became wider, suggesting that the frequency of oscillations decreased the power spectra there was no clear peak in the g-range frequency gradually. Bicuculline obscured the striped pattern in both pairs, (Fig. 4c, right and 4d, bottom right). Note that under this condition indicating the suppression of oscillations. However, the center line both spikes and synchronized events were generated with random (indicating synchronization) remained in the near-cell pair, whereas it intervals because the number of coincidences in the autocorrelograms disappeared in the remote-cell pair. was almost constant besides the central peak (Fig. 4c, left and 4d, Potentiation of escape behavior by a GABACR antagonist bottom left). Bicuculline significantly decreased both the oscillation index and the It is critical to know whether escape behavior is potentiated when oscillatory synchronization index of dimming detectors (P o 0.01 for retinal synchronized oscillatory activity is enhanced. 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Effects of TPMPA on retinal ganglion cells To examine the effects of TPMPA on the activities of retinal ganglion cells, we recorded spike discharges extracellularly from various cell classes within a retinal area that was stimulated by a dark spot expanding from 01 to 301. TPMPA (10 mM) increased the number of spike discharges and enormously enhanced the g-range oscillations in dimming detectors (Fig. 6b), whereas TPMPA did not change the profiles of PSTHs, autocorrelograms and power spectra in sustained contrast and/or net convexity detectors (Fig. 6c) or in moving-edge detectors (Fig. 6d). TPMPA induced a significant increase in the number of spike discharges and in the oscillation index only in dimming detectors (P o 0.01 each, t-test, n ¼ 6 cells; Fig. 6e). Applying a multi-electrode array to the isolated retinas, we simultaneously recorded the responses of several dimming detectors to a dark spot expanding from 01 to 301, and we calculated autocorrelations from the ensemble spike train (Fig. 7a) and the synchronized event train (Fig. 7b). These analyses showed that TPMPA (10 mM) enhanced synchronized oscillatory activity. Power spectrum analysis indicated that TPMPA markedly increased

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shown that the oscillations evoked by a large dimming stimulus in dimming detectors are enhanced by a GABACR antagonist, TPMPA27. It is probable that blockade of the GABACR-mediated negative feedback from amacrine cells to bipolar cells increases glutamate release from bipolar cells30,31. In contrast to injection of bicuculline, intraocular injection of TPMPA potentiated escape behavior in response to the expanding dark spot (n ¼ 5 frogs) (Fig. 6a). Frogs responded to smaller dark spots with a higher escape rate B2 h after TPMPA injection (Fig. 6a, filled squares) than in the control condition (Fig. 6a, open circles). The TPMPA-induced potentiation of escape behavior recovered 1 d after injection (Fig. 6a, open triangles). TPMPA shifted the relationship between the final spot diameter and the escape rate along the abscissa, suggesting that GABACRs in the retina may contribute to controlling the sensitivity to escape behavior.


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Figure 5 Effects of bicuculline on synchronization and oscillations. Cross-correlograms were calculated from spike discharges recorded from a pair of dimming detectors during ten repetitive presentations of the expanding dark spot. The spot size was increased from 01 (0 s) to 601 (1.4 s) at the speed of 431 s1 and then was maintained for 3 s. (a) Examples of crosscorrelograms and shift predictors (inset) obtained from three pairs of dimming detectors before (top) and during (bottom) application of bicuculline. Distance between receptive field centers of dimming detectors was categorized into three groups (top). (b) Distance-dependent suppression of the synchronization by bicuculline. The synchronization index in the presence of bicuculline was normalized to that in the control condition. Mean 7 s.e.m., n ¼ 5 retinas. **P o 0.01. (c) Left: sliding-window cross-correlograms obtained from the near-cell pair shown in a (0–0.5 mm) before (Control) and during application of bicuculline. Right: sliding window cross-correlograms obtained from the remote-cell pair shown in a (41.0 mm). The vertical and horizontal axes indicate time shift (ms) and the time course of stimulus presentation, respectively. Gray scale bar (right) indicates the number of coincidences normalized by the mean value of the corresponding shift predictor.

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the peak power of g-range oscillations without changing their peak frequency (Fig. 7a,b). TPMPA significantly increased the oscillation index, the oscillatory synchronization index, the number of spike discharges and the occurrence of synchronized events in dimming detectors (P o 0.05 each, t-test, n ¼ 5 retinas; Fig. 7c). Examination of these results and the bicuculline results (Fig. 4) suggests that the oscillation index and the oscillatory synchronization index seem to be good predictors of changes in escape behavior. Effects of GABAR antagonists on optokinetic behavior One may argue that GABAR antagonists might cause nonspecific disruption of retinal function. However, this seems unlikely. We examined the effects of GABAR antagonists on optokinetic responses to horizontally drifting stripes (Fig. 8a). Frogs pursued reciprocating motion of stripes by rotating their head. Approximately 2 h after intraocular injection of bicuculline, the frogs did not escape in response to the expanding dark spot (Fig. 1d), but the same frogs displayed optokinetic responses to the drifting stripes (Fig. 8b). The maximal angle of optokinetic head rotation did not change significantly (P ¼ 0.98, repeated-measures ANOVA, n ¼ 5 frogs). Furthermore, intraocular injection of TPMPA did not affect optokinetic responses (P ¼ 0.30, repeated-measures ANOVA, n ¼ 5 frogs; Fig. 8c). Therefore, the retinal system that was required to induce optokinetic responses was still functioning after the pharmacological treatments that markedly changed escape behavior. DISCUSSION In the present study, we examined the relationship between visually guided behavior and the activity of retinal ganglion cells in frogs. Intraocular injection of GABAAR and GABACR antagonists caused suppression and potentiation of escape behavior, respectively, in response to an expanding dark spot (Figs. 1d and 6a). The changes in escape behavior were not correlated with the discharge rate of ganglion cells but rather with changes in the synchronized oscillatory

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activity of dimming detectors (Figs. 2–7). We also found that both the escape rate of frogs (Fig. 1b,c) and the oscillatory activities of dimming detectors (Supplementary Fig. 3) were similarly affected by the expansion speed and final diameter of the dark spot in the control condition (that is, without pharmacological treatment). Furthermore, escape behavior was strongly modified by the GABAR antagonists, whereas other behaviors, such as optokinetic responses to the drifting

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Figure 6 Effects of a GABACR antagonist on escape behavior and the activities of retinal ganglion cells. (a) Relationship between the escape rate and the final spot diameter before (open circles), 2 h after (filled squares) and 1 d after (open triangles) intraocular injection of TPMPA. R2 values of the Weibull function fitted to the data (solid and dotted lines) were 0.985 (control), 0.996 (TPMPA) and 0.985 (washout). (b–d) Effects of bath-applied TPMPA (10 mM) on the activities of dimming detectors (b), sustained contrast and/or net convexity detectors (c) and moving-edge detectors (d). The PSTHs (left; 50-ms bin width), autocorrelograms (middle; 2-ms bin width) and power spectra (right) were calculated from spikes that occurred during 100 repetitive presentations of the expanding dark spot (from 01 to 301 at an expansion speed of 431 s1). (e) Effects of TPMPA on the number of spikes (left) and the oscillation index (right). Mean 7 s.e.m. Data were obtained from six dimming detectors, eight sustained contrast and/or net convexity detectors (SC/NC detectors) and four moving-edge detectors (ME detectors). **P o 0.01.

stripes, were not (Fig. 8). These results, therefore, suggest a strong tie between synchronized oscillatory activity among dimming detectors and escape behavior. Although these results are strongly suggestive, they are not unequivocal. Proving that the synchronized oscillations in dimming detectors are responsible for escape behavior would require one of two things: (i) a demonstration that the GABAR antagonists we used to perturb escape behavior does not affect cell classes other than the dimming detector, or (ii) a demonstration that the dimming detector is the only cell class involved in this particular behavioral response. If the latter is the case, then effects of GABAR antagonists on other cell classes become irrelevant. It is difficult to prove either of these, and thus we have gathered substantial evidence in both directions. First, we have shown that the firing patterns of the non-dimming detector classes were not changed by the GABAR antagonists (Figs. 2 and 6), as measured by changes in the profiles of the PSTHs, autocorrelograms and power spectra. (For this analysis we used firing patterns produced by an expanding dark spot, as this was the stimulus that evoked the escape behavior. However, this stimulus might not be optimal for detecting the effects of GABAR antagonists on the activities of the non-dimming detector classes because it has been reported that responses to bright light stimuli were modified by GABAR antagonists in frog retinal ganglion cells32.) Second, we have shown that the firing patterns of the non-dimming detector classes were not as tightly linked to escape behavior as the firing patterns of dimming detectors. The non-dimming detector classes generated significantly stronger transient responses to the expanding dark ring than to the expanding dark spot, but the former stimulus did not elicit escape behavior (Supplementary Fig. 1). However, in dimming detectors both the number of spike discharges and the oscillation index were significantly reduced for the expanding dark ring than for the expanding dark spot (Supplementary Fig. 1). Thus, the non-dimming detector classes may have some role in escape behavior, but it is likely to be a lesser role than that of dimming detectors, whose responses are tightly correlated with the expanding dark spot stimulus. In remote pairs of dimming detectors bicuculline suppressed both oscillations and synchronization (Fig. 5). However, in nearby pairs of dimming detectors bicuculline suppressed the oscillations but did not impair synchronization, perhaps because adjacent dimming detectors may have received excitatory common inputs and/or electrically coupled inputs26,27,33. The synchrony of spike discharges that occurred randomly in multiple local regions would be insufficient to evoke escape behavior. The g-range oscillations may serve to adjust the local synchronizations in phase and to establish the synchronization between dimming detectors widely across the retina26,34. The long-range lateral

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Figure 7 TPMPA enhanced the synchronized oscillatory activity among dimming detectors. Autocorrelograms were calculated from spike discharges recorded during ten repetitive presentations of the expanding dark spot (from 01 to 301 at the expansion speed of 431 s1). (a) Enhancement of the oscillations by bathapplied TPMPA (10 mM). Analysis of the ensemble spike train obtained from seven simultaneously recorded dimming detectors before (control) and during application of TPMPA as shown by autocorrelograms (top) and power spectra (bottom). (b) Enhancement of the oscillatory synchronization by TPMPA. Analysis of the synchronized event train before (Control) and during application of TPMPA as shown by autocorrelograms (top) and power spectra (bottom). (c) Effects of TPMPA on the number of spikes (‘# Spikes’), the oscillation index (‘Osci’), the number of synchronized events (‘# Sync’) and the oscillatory synchronization index (‘OS’). Each value was normalized to that in the control condition. Mean 7 s.e.m., n ¼ 5 retinas. *P o 0.05.

interactions between dimming detectors may be mediated by Na+ spikes because blockade of Na+ channels by tetrodotoxin suppresses oscillatory synaptic inputs to dimming detectors27. Na+ spikes trigger the release of GABA from amacrine cells35,36, and thus GABAergic amacrine cells may be important in the network that generates oscillations in the inner retina. Oscillatory activity among dimming detectors was suppressed by bicuculline, an antagonist specific to GABAARs, whereas this activity was enhanced by TPMPA, an antagonist specific to GABACRs. Both GABARs exist in the inner plexiform layer37–39. GABACRs are expressed mostly at the axon terminals of bipolar cells39. It has been suggested that the GABACRmediated negative feedback from amacrine cells to bipolar cells may be used to control the gain of glutamatergic transmission30,31. Therefore, blockade of GABACRs may increase the release of glutamate from bipolar cells and enhance the direct excitatory input to dimming detectors and/or the inhibitory activity of amacrine cells, resulting in enhancement of the oscillatory activities of dimming detectors. When picrotoxin, which blocks both GABAARs and GABACRs in the frog retina38, is applied, the oscillatory activity of dimming detectors is

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suppressed26. It is likely that GABAARs may be essential for generating the oscillatory activities in the inner retina, whereas GABACRs may have a different role, such as gain control. After blockade of GABACRs, frogs show escape behavior in response to small spots that elicit little or no escape behavior under control condition (Fig. 6a). Activation of GABACRs in the retina may attenuate the oscillatory activity of dimming detectors and may optimize the stimulus size tuning for eliciting escape behavior. Such adjustment may be useful to avoid unnecessary escape from tiny prey or a distant predator. Synchronized oscillations among dimming detectors in a wide retinal area seems to convey essential escape-related visual information to the frog’s brain. However, it is not evident which aspect of this activity is analyzed by central visual neurons such as neurons in the tectum40. There may be at least three possibilities: (i) synchronization, (ii) synchronization accompanied by g-range oscillations and (iii) g-range oscillations. In the first case, central visual neurons may behave as coincidence detectors. These neurons respond only to synchrony of discharges from many dimming detectors without taking into account oscillations. The function of oscillations may be limited only to establishing the synchronization of discharges among dimming detectors widely across the retina. Coincidence detection with a narrow time window may improve both noise tolerance and input discriminability41–43. In the second case, central visual neurons may fire only when synchronized events arrive repetitively at regular (B20 to B30 ms) intervals. Such a mechanism may improve input discriminability and prevent false alarms. However, the probability of falling victim to predators would increase if central neurons responded only after the arrival of a large number of synchronized events at periodic intervals. A few synchronized events should trigger spikes in central neurons to elicit escape behavior. In the third case, central neurons may be tuned to a specific frequency of g-range oscillations. These neurons would be

Figure 8 Effects of GABAR antagonists on optokinetic responses. (a) Horizontally drifting stripes (square wave) were presented on two displays in front of a frog. (b) The maximum angle of head rotation before (Control), 2 h after (‘Bic’) and 1 d after (Washout) intraocular injection of bicuculline (mean 7 s.e.m., n ¼ 5 frogs). (c) The maximum angle of head rotation before (Control), 2 h after (TPMPA) and 1 d after (Washout) intraocular injection of TPMPA (mean 7 s.e.m., n ¼ 5 frogs).

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METHODS Bullfrogs (Rana catesbeiana) were used for behavioral and electrophysiological experiments in accordance with the guidelines for the care and use of animals (The University of Tokyo and The Physiological Society of Japan). Intraocular injection and behavioral experiments. Frogs were deeply anesthetized with ethyl 3-aminobenzoate methanesulfonate (3 g/l; MS-222, Sigma) before intraocular injection of GABA receptor antagonists. Bicuculline or TPMPA (500 mM; both from Tocris) dissolved in the standard solution (see ‘Electrophysiology’) was intravitreously injected into both eyes by a syringe (60 ml/eye). The final drug concentration in each eye was estimated to be B50 mM. After sufficient recovery from anesthesia, we started behavioral experiments (B2 h after injection). To evaluate experimental artifacts, the standard solution without GABAR antagonists was injected into both eyes of a different group of frogs with the same protocol. Behavioral experiments were performed in a dark box (65 72 75 cm), and behavior of a frog placed in a transparent acrylic dome (30 cm in diameter) was monitored by a video camera under infrared illumination. For the test of escape behavior, a liquid crystal display (LCD, NANAO) was positioned 28.5 cm away from either eye (+1351 (right eye) or 1351 (left eye) from the median plane, 451 elevation from the horizontal; the plane of LCD was slanted off the horizontal), and an expanding dark spot (stimulus contrast, spot:background ¼ 1:17) was presented (Fig. 1a). When the final spot diameter was changed, the spot diameter was increased from 01 to a final size (101 to 551 of subtense) at the speed of 431 s1 and then maintained for 1 s during each trial. When the expansion speed was changed in the range between 51 s1 and 501 s1, the final spot diameter was fixed to 551. Two sessions were performed under each condition (Fig. 1b: eight trials per session, Figs. 1c and 6a: 12 trials per session, Fig. 1d,e: six trials per session). To prevent habituation, a 460-s pause was inserted between trials and a 15-min pause between sessions, and the stimulus was presented alternately to each eye. The escape rate under each condition was the ratio of the number of trials where escape behavior was elicited to the total number of trials. The relationship between the spot diameter and the escape rate could be fitted with Weibull function by the Levenberg-Marquardt algorithm using Origin (OriginLab) software (Fig. 6a). For the test of optokinetic head rotation, two LCDs (Mitsubishi Electronics) were positioned in front of a frog (Fig. 8a). Vertical stripes (contrast ¼ 0.89; spatial frequency of the square wave 0.1 cycles/degree, 50% duty cycle) were moved horizontally at a sinusoidally modulated speed (0.067 Hz, maximum speed +161 s1 (right), 161 s1 (left)). The reciprocating motion of the vertical stripes was presented for two cycles per trial, and three trials were performed under each condition. The maximum angle of head rotation in three trials was measured from digital video images with Matlab (Mathworks) software. Electrophysiology. Experimental procedures and equipment has been described previously in detail26. Briefly, under a dim red light, a frog was double pithed and eyes were enucleated. The eyeball was hemisected, and the cornea and lens were separated from the posterior part. The eyecup was cut into several pieces and the retina was isolated carefully from the pigment epithelium. The isolated retina was transferred onto a planar multi-electrode array with the ganglion cell layer facing down and was superfused with a standard solution. The standard solution contained (in mM) 100.0 NaCl, 2.5 KCl, 1.6 MgCl2, 1.0 CaCl2, 18.0 NaHCO3 and 10.0 D-glucose and was bubbled with 95% O2/5% CO2. To hold the ganglion cell bodies near the electrode surface, a Teflon ring frame holding a tightly stretched sheet of transparent dialysis membrane (50-kDa exclusion limit) was inserted into the recording chamber over the retina. Bicuculline (10 mM) or TPMPA (10 mM) was dissolved in the standard solution and bath-applied. Light-evoked spike discharges from ganglion cells were picked up by a multi-electrode array (8 8 array, electrode size 50 50 mm, interpolar distance 300 mm, MED-P5305, Alpha MED Sciences). The signals were amplified by a multi-channel

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differential amplifier and stored on a digital audio tape at a 24-kHz sampling rate. The spikes originating from an arbitrary ganglion cell were sorted by the template-matching technique26. Light stimuli presented on a cathode-ray tube display (Iiyama) were projected onto the retina through optics. Parameters of light stimuli used for electrophysiological experiments were similar to those for behavioral experiments. Using a laser beam, we confirmed experimentally that 101 of subtense corresponded to B1.0 mm on the retina. Each time we used a new piece of isolated retina, we first examined receptive field positions and cell types from light-evoked spike discharges based on a previously described method45. Spike analyses. After spike sorting, peri-stimulus time histograms (PSTHs) were constructed, and auto- and cross-correlations were calculated with a bin width of 2 ms in a 7160 ms range. Shift predictors were computed to evaluate correlations from stimulus-locked coordination. The pattern of shift predictors was almost flat in all cases (Fig. 5a, inset). To investigate the temporal profile of spike trains simultaneously recorded from multiple ganglion cells, an ensemble spike train was created by superimposing the simultaneous spike trains. The strength of oscillations was assessed from the power spectrum, which was the fast Fourier transform (FFT) of the autocorrelogram calculated from the ensemble spike train. An oscillation index was defined as the ratio of the peak power in the g range (20 to 60 Hz) to the mean power between 150 and 250 Hz in the power spectrum, because the power spectrum showed no peaks beyond 150 Hz46 (Figs. 2,4,6 and 7). We extracted the synchronized event where spikes were generated within 2 ms in multiple (Z2) dimming detectors and created the synchronized event train. The occurrence time of the synchronized event was defined as the center of the bin that included multiple spikes. The autocorrelogram and power spectrum were calculated from the synchronized event train. An oscillatory synchronization index was defined as the peak power in the g range to the mean power between 150 and 250 Hz in the power spectrum. A synchronization index was defined as the ratio of the number of coincidences at zero time shift in the raw cross-correlogram to the mean value of the shift predictor (7160 ms) for each cell pair. In time-resolved slidingwindow cross-correlograms, the number of coincidences of the raw crosscorrelogram for each window (200-ms width) was normalized to the mean number of coincidences of the shift predictor for the corresponding window to avoid the effect of changes in discharge rate, and the window was moved in 20-ms steps. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS We thank L.H. Pinto, T. Takahashi, I. Arai and J. Hasegawa for discussion and comments and Y. Horiuchi for excellent technical assistance. This work was supported by Grant-in-Aid for Scientific Research (12053212 and 17022014 to M.T., 14710040 and 17730424 to H.I., 1610444 to M.G.) and the Special Coordination Funds for Promoting Science and Technology (The Neuroinformatics Research in Vision Project to M.T.) from the Ministry of Education, Science, Sports and Culture. M.G. is a research fellow of the Japan Society for Promotion of Science. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 3 March; accepted 8 June 2005 Published online at http://www.nature.com/natureneuroscience/

1. Eckhorn, R. et al. Coherent oscillations: a mechanism of feature linking in the visual cortex? Multiple electrode and correlation analyses in the cat. Biol. Cybern. 60, 121– 130 (1988). 2. Gray, C.M., Ko¨nig, P., Engel, A.K. & Singer, W. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338, 334–337 (1989). 3. Wehr, M. & Laurent, G. Odour encoding by temporal sequences of firing in oscillating neural assemblies. Nature 384, 162–166 (1996). 4. Fries, P., Roelfsema, P.R., Engel, A.K., Ko¨nig, P. & Singer, W. Synchronization of oscillatory responses in visual cortex correlates with perception in interocular rivalry. Proc. Natl. Acad. Sci. USA 94, 12699–12704 (1997). 5. Stopfer, M., Bhagavan, S., Smith, B.H. & Laurent, G. Impaired odour discrimination on desynchronization of odour-encoding neural assemblies. Nature 390, 70–74 (1997).

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ARTICLES 6. Laurent, G. A systems perspective on early olfactory coding. Science 286, 723–728 (1999). 7. Rodriguez, E. et al. Perception’s shadow: long-distance synchronization of human brain activity. Nature 397, 430–433 (1999). 8. Castelo-Branco, M., Goebel, R., Neuenschwander, S. & Singer, W. Neural synchrony correlates with surface segregation rules. Nature 405, 685–689 (2000). 9. Patel, A.D. & Balaban, E. Temporal patterns of human cortical activity reflect tone sequence structure. Nature 404, 80–84 (2000). 10. Engel, A.K., Fries, P. & Singer, W. Dynamic predictions: oscillations and synchrony in top-down processing. Nat. Rev. Neurosci. 2, 704–716 (2001). 11. Engel, A.K. & Singer, W. Temporal binding and the neural correlates of sensory awareness. Trends Cogn. Sci. 5, 16–25 (2001). 12. Fell, J. et al. Human memory formation is accompanied by rhinal-hippocampal coupling and decoupling. Nat. Neurosci. 4, 1259–1264 (2001). 13. Fries, P., Reynolds, J.H., Rorie, A.E. & Desimone, R. Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291, 1560–1563 (2001). 14. Neuenschwander, S. & Singer, W. Long-range synchronization of oscillatory light responses in the cat retina and lateral geniculate nucleus. Nature 379, 728–733 (1996). 15. Castelo-Branco, M., Neuenschwander, S. & Singer, W. Synchronization of visual responses between the cortex, lateral geniculate nucleus, and retina in the anesthetized cat. J. Neurosci. 18, 6395–6410 (1998). 16. Gray, C.M. & Singer, W. Stimulus-specific neuronal oscillations in orientation columns of cat visual cortex. Proc. Natl. Acad. Sci. USA 86, 1698–1702 (1989). 17. Engel, A.K., Kreiter, A.K., Ko¨nig, P. & Singer, W. Synchronization of oscillatory neuronal responses between striate and extrastriate visual cortical areas of the cat. Proc. Natl. Acad. Sci. USA 88, 6048–6052 (1991). 18. Engel, A.K., Ko¨nig, P., Kreiter, A.K. & Singer, W. Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex. Science 252, 1177–1179 (1991). 19. Engel, A.K., Ko¨nig, P. & Singer, W. Direct physiological evidence for scene segmentation by temporal coding. Proc. Natl. Acad. Sci. USA 88, 9136–9140 (1991). 20. Kreiter, A.K. & Singer, W. Stimulus-dependent synchronization of neuronal responses in the visual cortex of the awake macaque monkey. J. Neurosci. 16, 2381–2396 (1996). 21. Engel, A.K., Ko¨nig, P., Kreiter, A.K., Schillen, T.B. & Singer, W. Temporal coding in the visual cortex: new vistas on integration in the nervous system. Trends Neurosci. 15, 218–226 (1992). 22. Singer, W. & Gray, C.M. Visual feature integration and the temporal correlation hypothesis. Annu. Rev. Neurosci. 18, 555–586 (1995). 23. Waldeck, R.F. & Gruberg, E.R. Studies on the optic chiasm of the leopard frog. I. Selective loss of visually elicited avoidance behavior after optic chiasm hemisection. Brain Behav. Evol. 46, 84–94 (1995). 24. King, J.G., Lettvin, J.Y. & Gruberg, E.R. Selective, unilateral, reversible loss of behavioral responses to looming stimuli after injection of tetrodotoxin or cadmium chloride into the frog optic nerve. Brain Res. 841, 20–26 (1999). 25. Lettvin, J.Y., Maturana, H.R., McCulloch, W.S. & Pitts, W.H. What the frog’s eye tells the frog’s brain. Proc. Inst. Radio Eng. 47, 1940–1951 (1959). 26. Ishikane, H., Kawana, A. & Tachibana, M. Short- and long-range synchronous activities in dimming detectors of the frog retina. Vis. Neurosci. 16, 1001–1014 (1999).


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27. Arai, I., Yamada, Y., Asaka, T. & Tachibana, M. Light-evoked oscillatory discharges in retinal ganglion cells are generated by rhythmic synaptic inputs. J. Neurophysiol. 92, 715–725 (2004). 28. Ba¨ckstro¨m, A.C., Hemila¨, S. & Reuter, T. Directional selectivity and colour coding in the frog retina. Med. Biol. 56, 72–83 (1978). 29. Meister, M., Pine, J. & Baylor, D.A. Multi-neuronal signals from the retina: acquisition and analysis. J. Neurosci. Methods 51, 95–106 (1994). 30. Dong, C.J. & Werblin, F.S. Temporal contrast enhancement via GABAC feedback at bipolar terminals in the tiger salamander retina. J. Neurophysiol. 79, 2171–2180 (1998). 31. Matsui, K., Hasegawa, J. & Tachibana, M. Modulation of excitatory synaptic transmission by GABAC receptor-mediated feedback in the mouse inner retina. J. Neurophysiol. 86, 2285–2298 (2001). 32. Bonaventure, N., Wioland, N. & Jardon, B. Anisotropic inhibition in the receptive field surround of the frog retinal ganglion cells, evidenced by bicuculline and SR 95103, a new GABA antagonist. Eur. J. Pharmacol. 121, 327–336 (1986). 33. Brivanlou, I.H., Warland, D.K. & Meister, M. Mechanisms of concerted firing among retinal ganglion cells. Neuron 20, 527–539 (1998). 34. Ko¨nig, P., Engel, A.K. & Singer, W. Relation between oscillatory activity and long-range synchronization in cat visual cortex. Proc. Natl. Acad. Sci. USA 92, 290–294 (1995). 35. Watanabe, S., Koizumi, A., Matsunaga, S., Stocker, J.W. & Kaneko, A. GABA-Mediated inhibition between amacrine cells in the goldfish retina. J. Neurophysiol. 84, 1826– 1834 (2000). 36. Shields, C.R. & Lukasiewicz, P.D. Spike-dependent GABA inputs to bipolar cell axon terminals contribute to lateral inhibition of retinal ganglion cells. J. Neurophysiol. 89, 2449–2458 (2003). 37. Wa¨ssle, H., Koulen, P., Brandsta¨tter, J.H., Fletcher, E.L. & Becker, C.M. Glycine and GABA receptors in the mammalian retina. Vision Res. 38, 1411–1430 (1998). 38. Du, J.L. & Yang, X.L. Subcellular localization and complements of GABAA and GABAC receptors on bullfrog retinal bipolar cells. J. Neurophysiol. 84, 666–676 (2000). 39. Vitanova, L. et al. Immunocytochemical and electrophysiological characterization of GABA receptors in the frog and turtle retina. Vision Res. 41, 691–704 (2001). 40. Gru¨sser, O.J. & Gru¨sser-Cornehls, U. Neurophysiology of the anuran visual system. in Frog Neurobiology (eds. Llina´s, R. & Precht, W.) 297–385 (Springer, Berlin, 1976). 41. Ko¨nig, P., Engel, A.K. & Singer, W. Integrator or coincidence detector? The role of the cortical neuron revisited. Trends Neurosci. 19, 130–137 (1996). 42. Salinas, E. & Sejnowski, T.J. Impact of correlated synaptic input on output firing rate and variability in simple neuronal models. J. Neurosci. 20, 6193–6209 (2000). 43. Perez-Orive, J., Bazhenov, M. & Laurent, G. Intrinsic and circuit properties favor coincidence detection for decoding oscillatory input. J. Neurosci. 24, 6037–6047 (2004). 44. Hutcheon, B. & Yarom, Y. Resonance, oscillation and the intrinsic frequency preferences of neurons. Trends Neurosci. 23, 216–222 (2000). 45. Gru¨sser, O.J. & Gru¨sser-Cornehls, U. Comparative physiology of movement-detecting neuronal systems in lower vertebrates (Anura and Urodela). Bibl. Ophthalmol. 82, 260– 273 (1972). 46. Molotchnikoff, S., Shumikhina, S. & Moisan, L.E. Stimulus-dependent oscillations in the cat visual cortex: differences between bar and grating stimuli. Brain Res. 731, 91– 100 (1996).

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Continuous flash suppression reduces negative afterimages Naotsugu Tsuchiya & Christof Koch Illusions that produce perceptual suppression despite constant retinal input are used to manipulate visual consciousness. Here we report on a powerful variant of existing techniques, continuous flash suppression. Distinct images flashed successively at ~10 Hz into one eye reliably suppress an image presented to the other eye. The duration of perceptual suppression is at least ten times greater than that produced by binocular rivalry. Using this tool we show that the strength of the negative afterimage of an adaptor was reduced by half when it was perceptually suppressed by input from the other eye. The more completely the adaptor was suppressed, the more strongly the afterimage intensity was reduced. Paradoxically, trial-to-trial visibility of the adaptor did not correlate with the degree of reduction. Our results imply that formation of afterimages involves neuronal structures that access input from both eyes but that do not correspond directly to the neuronal correlates of perceptual awareness.

The question of the neuronal correlates of conscious perception has seen renewed interest over the last decade1. One powerful tool in this area is illusions that give rise to effects that are measurable, yet are not, or are only occasionally, consciously seen2–5. In backward masking6, inattentional blindness7, motion-induced blindness8, binocular rivalry9–16 and flash suppression11,17–19, an image is presented to one or both eyes of the observer yet is not seen. Binocular rivalry is a popular method to determine if a visual aftereffect occurs before or after the neuronal site for the suppression of rivalry2,20–23. In binocular rivalry, two different images are shown to the two eyes, and the subject’s percept alternates between one and the other image24. The strength of the aftereffect when the adaptor is presented to one eye and is plainly visible throughout the adaptation period is compared with the aftereffect when the adaptor is suppressed by the input to the other eye. However, the duration and timing of perceptual suppression are difficult to control because of the stochastic nature of rivalry. Flash suppression11,17–19 provides better control over the timing of suppression, but at the price of shorter periods of suppression, too brief to produce strong aftereffects. Furthermore, flash suppression requires a pre-adapting period, preventing complete unawareness of the adaptor. Here we combine aspects of both binocular rivalry and flash suppression into a potent procedure we term continuous flash suppression (CFS). We continuously flash different images rapidly into one eye while the input to the corresponding location in the other eye remains the same (see demonstration at http://www.klab.caltech.edu/~naotsu/ CFSdemo.html). Most observers do not see the image in one eye even though it is present for a long time, sometimes for several minutes. We used CFS to examine the neuronal site for negative afterimages. These are vivid percepts that demonstrate the tenuous link between

physical stimuli and their associated subjective percepts. A variety of evidence supports their origin among neurons in the retina25–31 or lateral geniculate nucleus (LGN)32. In particular, negative afterimages do not transfer across eyes, nor is their strength reduced by suppression of the inducing image by pressure blinding20,33 (but see ref. 29). Neither binocular rivalry20 nor motion-induced blindness (MIB)5 reduces either the duration or the strength of afterimages. All of these observations suggest that afterimages are retinal phenomena. However, both binocular rivalry and MIB suppress the adaptor only intermittently. By using CFS, we asked what happens when the adapting stimulus is completely suppressed from awareness. We found that when an adaptor was reliably suppressed by CFS, the intensity of the negative afterimage of the adaptor was reduced by half. Our results imply that formation of afterimages involves neuronal structures that access input from both eyes but that do not correspond directly to the neuronal correlates of perceptual awareness. RESULTS Prolonged invisibility by continuous flash suppression We first compared the initial duration of stimulus suppression in CFS and binocular rivalry without pre-exposure to the suppressed image. While a constant, gray image was presented to one eye, CFS stimuli composed of different Mondrians were presented at the corresponding location in the other eye (Fig. 1). Each Mondrian was replaced by a different pattern every 100 ms. Seventeen naive subjects pressed a button as soon as any part of the gray figure became visible. The mean initial suppression time in 16 trials was 4.3 s for binocular rivalry and 56.0 s for CFS (13 times longer than for binocular rivalry; paired t-test, t-score ¼ 4.81, d.f. ¼ 16, P o 0.001). In 40 out of 272 CFS trials, no part of the gray image was seen at all for the full 3-min trial. As we treated those

Computation and Neural Systems Program, California Institute of Technology, M/s 139-74, 1200 East California Boulevard, Pasadena, California 91125, USA. Correspondence should be addressed to N.T. ([email protected]). Published online 3 July 2005; doi:10.1038/nn1500

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Figure 1 Continuous flash suppression. A stationary gray stimulus was presented in one eye (left) while different, colored Mondrian patterns were flashed in the other eye (center) every 100 ms. Subjects fixated the central cross and pressed a button to report when the gray figure started to become visible. Initial suppression duration in CFS was more than ten times longer than in binocular rivalry, using the same stimulus but with a stationary Mondrian pattern.

Random flashed patterns in the other eye Typical percept Flash interval

trials’ suppression time as 180 s, we underestimated the true duration of the initial period during which the adaptor remains invisible. Pilot experiments on afterimage reduction We next examined if CFS interferes with the formation of negative afterimages. These experiments were partly motivated by the observation that only a single subject in one out of 40 trials reported a negative afterimage of the gray figure. We did not expect this, given that the image was present for 3 min on the retina. In a second experiment, we presented two isoluminant Gabor patches in one eye to the left and right of fixation for 5 s (Fig. 2, left). At the same time, suppressing CFS stimuli were continuously flashed only to one side of the other eye (Fig. 2, center). CFS in one eye effectively renders the Gabor patch at the corresponding location in the other eye invisible (Fig. 2, right). Sixteen naive subjects verbally described their percepts after a 5-s adaptation in two trials (Supplementary Table 1 online). Subjects usually reported that the adaptor suppressed by CFS produced a weaker afterimage (87% in the two-trial experiment and 83% in the 30-trial experiment). No subjects reported seeing an afterimage of the Mondrians. This consistency was notable, given the known variability in the strength of afterimages across trials, subjects and hemifields5,27,34. Under the retinal origin hypothesis, input from the other eye should not influence afterimage formation. As adaptation at the retina is the same for both visible and suppressed locations, the weakened afterimage must be due to interference from sites at or beyond binocular convergence.

(pegged at a subjective rating of 10). Any putative afterimage of the Mondrian would interfere with the afterimage of the Gabor in both synchronous and asynchronous CFS locations. If CFS had to be presented simultaneously with the adaptors to weaken afterimage amplitude, the afterimages should be equally strong for the control and the asynchronous CFS locations and should be weaker for the synchronous CFS location. Each of six naive subjects performed 20 trials, rating the subjective intensity of the afterimages induced by the synchronously and asynchronously suppressed Gabor adaptors relative to the control, which received a rating of 10 (Fig. 3, bottom). The mean afterimage rating from the asynchronous CFS location was 11.1 7 1.13 (s.e.m.), which was not significantly different from 10 (two-tailed t-test, P 4 0.35, t-score ¼ 0.98, d.f. ¼ 5). The mean rating from the synchronous CFS location was 5.85 7 1.63, a reduction of 47% (one-tailed paired t-test on the rating between synchronous and asynchronous, P o 0.02). We conclude that the Mondrians themselves did not reduce the afterimage, and that coincidence of the adaptor with CFS was key to reduction of the afterimage. Reliable suppression reduces afterimage intensity Why does CFS reduce the intensity of the afterimage, whereas previous studies have shown that perceptual suppression does not influence the duration or the intensity of the afterimage using binocular rivalry20 or MIB5? One notable difference is that CFS suppressed adaptors more consistently and completely than either of the other techniques; most One eye

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Ruling out nonspecific effects of the flashes Although no subjects reported seeing afterimages of the ever-changing Mondrians, such dynamic and luminance-equated patterns could have created afterimages29. Though their contrast may have been too low to perceive, they may nevertheless have interfered with the afterimage from the Gabor adaptor35. In a third experiment, we tested for this possibility. We compared the subjective ratings of the afterimage intensity from three intermittently presented adaptors (2 s ‘on’ and 2 s ‘off’ for 30 s, Fig. 3). One eye was stimulated by three separate Gabor patches while the other eye was stimulated at two of these three locations with Mondrians in such a way that this pattern synchronously coincided for 2 s with one of the Gabor patches but was asynchronously delayed by 2 s from the other Gabor pattern. A third location was never suppressed by Mondrians but received a Gabor patch intermittently for 2 s and served as a control for the strength of the afterimage

5 s (Exp. 2 and 5) or 3 s (Exp. 4) of adaptation

Typical afterimage

Figure 2 CFS suppresses a Gabor patch and reduces its afterimage. Left: two isoluminant Gabor patches, at 30% contrast and 0.6 cpd spatial frequency, were presented to the left and right of fixation in one eye for 5 s. Center: different Mondrian patterns that changed every 100 ms were projected in one-half of the visual field (here, the right side) of the other eye. Right: typically, subjects saw a Gabor on one side and flickering Mondrians on the other, not perceiving the Gabor on the right. In experiment 2, subjects verbally described their percepts at the end of the adaptation period (‘What do you see?’). In experiment 4, subjects reported which afterimage was stronger and whether they saw the suppressed adaptor during a 3-s adaptation in a two-alternative forced choice. In experiment 5, subjects pressed and held a key whenever the suppressed adaptor was visible during the 5-s adaptation period and then reported which afterimage was stronger.

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subjects did not see the suppressed stimuli at all throughout the adaptation period. In a fourth experiment, we tested the extent to which complete invisibility is necessary to weaken afterimage strength. We measured the reduction in the afterimage while manipulating the reliability of suppression of the Gabor patches by changing the stimulus properties of both adaptors and Mondrians. In preliminary experiments, we found that complete suppression occurred less frequently as the spatial frequency of adaptors was increased. Furthermore, as the contrast of adaptors increased, the suppression became less reliable, whereas increasing the contrast of Mondrians resulted in more reliable suppression. We used five different spatial frequencies for the adaptors and three combinations of adaptor and Mondrian contrast to manipulate the reliability of suppression. With the same setup as in Figure 2 (except for a 3-s adaptation period), subjects indicated which side had the stronger afterimage and whether they saw the Gabor adaptor at the

Figure 4 Relationship between afterimage reduction and the reliability of suppression. We used two different dichoptic suppression protocols: CFS (as in Fig. 3, except that the adaptation period was shortened to 3 s) and binocular rivalry with moving stimuli. Subjects reported which of the afterimages was stronger and whether or not they saw the suppressed Gabor patch during adaptation. To modulate the reliability of suppression, three combinations of contrasts for adaptors and Mondrians were used: 30% and 100% (triangles), 100% and 100% (circles) or 100% and 5% (squares). The Gabor had one of five different spatial frequencies. Subjects compared the intensity of the afterimage from two adaptors with the same contrast and spatial frequency. Increasing symbol size represents increasing spatial frequency of the adaptors: 0.60 through 0.84, 1.2, 1.7, to 2.5 cpd. In total, 30 different experimental conditions were evaluated. Filled symbols represent data obtained from CFS and open symbols, data from binocular rivalry. Each data point represents the average across five subjects. The y-axis is the proportion of trials in which the afterimage from the suppressed adaptor was weaker than the afterimage from the plainly visible Gabor patch, representing the degree of afterimage reduction. The x-axis is the fraction of trials during which any part of the adaptor was visible, representing the reliability of complete suppression in a statistical sense. The data clearly show that for both CFS and binocular rivalry, the less frequently the adapting stimulus is seen, the weaker its associated afterimage.

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CFS location during adaptation. We also used binocular rivalry to suppress the inducing image for comparison with the efficiency of CFS methods. The results (Fig. 4) are unambiguous: the less the Gabor patch was visible during adaptation, the weaker the associated afterimage (for CFS, r2 ¼ 0.82, P o 1 105; for binocular rivalry, r2 ¼ 0.76, P o 1 104). If suppression was sufficiently reliable (in a statistical sense), the intensity of the afterimage was reduced. Trial-by-trial visibility and afterimage intensity CFS-induced suppression may reduce the afterimage either by eliminating the afterimage entirely on some fraction of trials or by lowering the afterimage intensity uniformly on all trials. In a fifth experiment, we tried to distinguish between these hypotheses. We repeated three of the conditions from the fourth experiment more extensively to estimate the matching contrast. In the low–spatial frequency condition (Fig. 4, small filled triangle), the contrast of a test Gabor patch that matched the 60% contrast Gabor patch suppressed by CFS was 42.7% 7 7.1% (n ¼ 5, t-score ¼ 2.45, P o 0.05, one-tailed t-adaptor visibility duration was 0.51 7 0.24 s during the 5-s adaptation period (Fig. 5b). Subjects did not report seeing any part of the Gabor in 61.8 7 15.2% of trials (Fig. 5c). In the high–spatial frequency

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Figure 3 Mondrian flashes themselves do not reduce the afterimage of the Gabor. Left: three adaptors were presented to the left, upper right and lower right of fixation during 2-s ‘on’ periods and were removed during 2-s ‘off’ periods. The contrast of the adaptors was 50%. The position of the adaptors and Mondrians was balanced between top and bottom and between left and right across 20 trials (five trials for each configuration). Center: Mondrian flashes were presented synchronously with the adaptors during 2-s ‘on’ periods at the lower right and asynchronously during 2-s ‘off’ periods at the upper right. Right: during 2-s ‘on’ periods, subjects perceived two adaptors and a stream of Mondrians at the lower right, whereas during 2-s ‘off’ periods they saw only a stream of asynchronous Mondrians at the upper right. Bottom: after 30 s of adaptation, subjects rated the intensity of the afterimage relative to that at the left visible location (control), which was pegged at 10. Next to the expected afterimage, the time course of adaptors and Mondrians is shown for each location. Filled squares indicate the eight 2-s ‘adaptor-on’ periods, and open squares denote the 2-s ‘CFS-on’ periods.

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condition (Fig. 4, large filled triangle), the matching contrast was 62.8 7 6.1%; that is, there was no reduction of afterimage intensity (n ¼ 4, t-score ¼ 0.46, P 4 0.6). The mean adaptor visibility duration was 1.73 7 0.38 s, and complete suppression occurred in 18.6 7 10.9% of trials. To evaluate the effect of adaptor visibility, we sorted the 60 trials with the high–spatial frequency patches at each test contrast into ten bins according to the duration of the visibility of the adaptor. Figure 5d shows each data point averaged across four subjects and psychometric curves fitted for each of ten bins. Matching contrast was independent of adaptor visibility duration (Fig. 5e, r2 ¼ 0.18, P ¼ 0.22). Although it did not reach significance, the slope is slightly negative (2.9% s1), contrary to the prediction that only invisible trials contribute to afterimage reduction. We obtained similar results using low–spatial frequency Gabor patches and low-contrast Mondrians (n ¼ 5; the matching contrast was 61.2 7 1.8%, the mean adaptor visible duration was 2.03 7 0.38 s and complete suppression occurred in 4.12 7 10.9% of trials). Again, we did not find any correlation between matching contrast and the adaptor visibility duration (r2 ¼ 0.23, P ¼ 0.16; slope of the regression line was slightly negative: 3.2% s1). Dividing trials into two or three bins did not change the results. For a given stimulus setting, trial-by-trial variability in the visibility of the adaptor did not change the intensity of the afterimage. This is consistent with previous studies of afterimages5,20 but was contrary to the suppression of high-level aftereffects21,23. Since the statistical reliability of suppression is correlated with the reduction of the afterimage, the visibility of the adaptor seems only indirectly related to the percepts of the associated afterimage. DISCUSSION We have identified dichoptic visual stimuli that, for at least ten times longer than existing techniques, reliably suppress from conscious


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Figure 5 Visibility and afterimage reduction. We repeated three conditions of the fourth experiment. Subjects reported the visibility of the suppressed Gabor by holding a key during the 5-s adaptation period and then compared the afterimage intensity. (a–c) We used low– (0.6 cpd, left) and high–spatial frequency (2.0 cpd, right) Gabor patches. (a) Matching contrast (estimated by the method of constant stimuli), showing a significant reduction of contrast in the low spatial frequency condition (error bars represent s.e.m.). (b) Mean duration that the adaptor was visible. (c) Proportion of trials where subjects did not see the adaptor at all. (d) We divided 60 trials at each test contrast for each subject into ten bins based on the adaptor visibility duration in the high spatial frequency condition (a–c, right). Six trials from each of four subjects were pooled to fit a Weibull function, which was used to estimate the matching contrast for which the afterimage (AI) induced by the test adaptor was stronger than the afterimage induced by a suppressed Gabor adaptor in 50% of trials (vertical lines in d). (e) The duration for which the adaptor was visible was weakly but negatively correlated (one-tailed t-test; P ¼ 0.22) with the matching contrast. Different colors in d and e represent different durations of mean adaptor visibility.

perception salient figures presented to one eye. With CFS as a tool, vivid images can be rendered invisible for long periods with excellent control of timing. This suppression of a continuously presented stimulus at the fovea dissociates physical stimuli from their associated subjective percepts. CFS does not require pre-adaptation, a key aspect of flash suppression15,17,19,23, to achieve reliable disappearance. This property makes CFS attractive for studies that require complete unawareness. CFS extends the total duration for which Mondrians are perceived by prolonging their period of dominance without shortening their period of suppression (Supplementary Note online). In binocular rivalry, strong stimuli shorten each period of suppression of the strong stimuli, with little effect on their period of dominance24,36,37 (but see ref. 38). Thus, CFS is not simply a stronger version of binocular rivalry. This observation is compatible with the hypothesis that CFS involves a repetitive flash suppression component, in addition to binocular suppression. Indeed, we present a simple model (Supplementary Note) that combines aspects of flash suppression and binocular rivalry and describes the measured periods of CFS dominance and suppression in a quantitative manner. We applied CFS to ascertain the extent to which dichoptic inhibition interferes with the formation of negative afterimages. Though it is widely believed that afterimages originate among retinal neurons20,25–31,33, some experiments imply that cortical processing can modulate39–42 or possibly even create34,43 negative afterimages. Our results are consistent with these latter studies, and notably, they imply that such cortical components may be necessary for the formation of afterimages. Dichoptic inhibition that underlies the afterimage reduction has been found as early as the LGN44. The possibility that latent afterimages from the Mondrians interfered with the afterimage of the Gabor pattern was ruled out by the third experiment. Asynchronously presented Mondrian patterns did not reduce the intensity of the afterimage, whereas synchronously presented Mondrians reduced it by about 50%. This suggests that the peculiarity of CFS (that is, continuously present transient signals) is not sufficient for the reduction of the afterimage. Rather, the adaptor has to be suppressed strongly by stimuli presented simultaneously to the other eye. We found that the degree of afterimage reduction correlated with how reliably adaptors are suppressed. This relationship exists for both binocular rivalry and CFS (Fig. 4), implying that the inconsistency between our results and previous studies20 arises from the strong suppression induced by CFS. Although cortical neurons may adapt under partial suppression, they seem to adapt less under reliable

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ARTICLES suppression. In an analogy with lesion studies, partial suppression techniques can be compared with ‘unilateral lesions’ and CFS with ‘bilateral lesions’; often, bilateral, but not unilateral, lesions result in behavioral deficits. Partial suppression by binocular rivalry and MIB may leave sufficient residual activity to produce full-blown adaptation and an afterimage. Furthermore, in this study, we replicated previous findings from our laboratory5 that afterimage intensity was not influenced by trial-bytrial variability in adaptor visibility, indicating the cortical component for the afterimage is only indirectly related to neuronal correlates of awareness. Can we explain our results by the total lack of attention to the adaptor owing to complete suppression? Attending to adaptors during adaptation weakens the afterimage41,42. If one assumes that lack of attention to an object is equivalent to not being aware of it45, one would expect that both would cause the same effects on the afterimage. However, lack of attention enhances afterimages, while complete invisibility reduces afterimages. These results support the view that attention and awareness involve different mechanisms1,46. A reduction of 50% in the strength of the afterimage when the inducing image is present on the retina but not seen by the observer seems to be at odds with the fact that afterimages do not transfer across eyes; when the subject closes the adapted eye, no afterimage is seen. It is known that the binocular components of afterimages have access to the direction of gaze40. Likewise, these mechanisms may have access to the overall brightness from the eye and, if it is closed, may reduce or even eliminate afterimages, resulting in no transfer of afterimages. The involvement of a cortical suppression mechanism is supported by patients with cortical lesions who report abnormally long afterimages that transfer across eyes47,48. This may reflect the disruption of cortical mechanisms for afterimage reduction. If normal observers open both eyes during the test period, the inter ocular transfer effect, albeit weak, can be measured psychophysically in detection or discrimination procedures49. In summary, dichoptic suppression by means of CFS significantly reduces the strength of the negative afterimage. This reduction was correlated with the reliability of suppression of the adaptors, but not with trial-by-trial visibility. One implication of our finding is that failure of interocular transfer and failure of reduction of afterimage intensity by partial suppression does not imply that structures that have access to information from both eyes, such as visual cortex, are not involved in the formation of negative afterimages. METHODS Subjects were recruited from the California Institute of Technology campus and gave informed written consent. Experiments were approved by the Institutional Review Board (Committee for the Protection of Human Subjects) of the California Institute of Technology. They had normal or corrected eyesight and normal stereo vision. Subjects observed the display through a set of mirrors. The distance between the eyes and the display was 92 cm. To stabilize fixation, a headrest and chinrest were used. We used Matlab 6.5 under Windows 98, Matlab 5.2.1 under Mac OS and the Psychophysics Toolbox50. The Mondrian images consisted of randomly generated squares of random colors (experiment 1) or white, black and gray squares (the other experiments) superimposed onto each other. Twenty distinct Mondrians were generated before each session. Experiment 1. Seventeen naive subjects participated. They were instructed to hit a space bar when any part of a gray image became visible and to describe it verbally to the experimenter. The time to key press was taken as the duration of initial suppression. One of four types of gray images was used in each trial: a 451 left-tilted Gabor patch of 30% contrast, a 451 right-tilted Gabor patch of 60% contrast, an angry face and a blurred angry face. Spatial frequency and s.d. of the Gabor patches were 0.5 cpd and 11, respectively. Each type of image

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appeared once in a block of four trials. In total, four blocks of 16 trials were run. The images were presented at the fovea and extended 6 61. Experiment 2. Sixteen naive subjects participated. Isoluminant Gabor patches (spatial frequency, 0.6 cpd; s.d., 0.831) were used as afterimage inducers. The green level was equated with pink (CIE [x, y] ¼ [0.389,0.205]; luminance 18.7 cd/mm2) using a flicker minimization for each subject. The average green level was [x, y] ¼ [0.201,0.278]. The contrast of the isoluminant Gabor patch was defined as the contrast modulation of the red or the green intensity, Contrast ¼

maxðred; greenÞ minðred; greenÞ : maxðred; greenÞ + minðred; greenÞ

Peaks of the red intensity coincided with troughs of the green. The luminance for black and white was 0.028 and 67.6 cd/mm2, respectively. Three crosses on a rectangle with random texture (0.481 4.81) stabilized binocular fusion. Subjects fixated the middle cross. Each of two Gabor patches of 30% contrast was presented within an imaginary 4.81 4.81 square, with the center of the square 2.61 away from the fixation (Fig. 2, left). The phase and orientation of the adaptor were randomized for each trial. The Mondrians flashed at 10 Hz were presented in the corresponding square (Fig. 2, center). After 5 s of adaptation, the adaptors and Mondrians were replaced with a uniform gray background to induce negative afterimages, and subjects described their percepts (Supplementary Table). Experiment 3. Six naive subjects performed 20 trials. Three 50% contrast Gabor adaptors were presented spaced apart (Fig. 3). One visible control adaptor was placed to the left (or right) of fixation (3.61 square, with its center location 21 from fixation); two other adaptors were placed at the top or bottom right (or left) from the fixation (3.61 square, 1.81 above or below fixation). Three adaptors appeared simultaneously for 2 s and were turned off for 2 s, repeating for seven cycles and ending with a 2-s ‘on’ period. After 30 s of adaptation, subjects rated the intensity of the afterimage on a linear scale relative to the control, which was pegged at 10. If no afterimage was visible, the rating was 0. A rating of 5 (or 20) was given when the intensity was half (or twice) as strong as the afterimage from the control adaptor. Experiment 4. Four naive subjects and the first author participated. Subjects compared the intensity of afterimages produced by a pair of adaptors with the same contrast and spatial frequency. Different spatial frequencies (0.60, 0.84, 1.2, 1.7 and 2.5 cpd) and two types of dichoptic suppression (CFS and binocular rivalry) were randomly interleaved within a block. The contrast of adaptors and Mondrians was constant in one block of 100 trials. Each subject completed at least 30 trials for each combination of the suppression protocol, the spatial frequency of adaptors, and contrasts of adaptors and Mondrians (30% versus 100%, 100% versus 100%, 100% versus 5%). We created motion binocular rivalry stimuli by sliding the right and left half of the texture at 0.711 s1 to converge at the midline (see demonstration at http://www.klab. caltech.edu/~naotsu/CFSdemo.html). The motion binocular rivalry stimulus was randomly created before each trial. Experiment 5. Four experienced (but naive to the hypothesis of this experiment) subjects and the first author participated. Subjects pressed a key to indicate if the suppressed Gabor became visible during a 5-s adaptation period and then reported on which side the afterimage was stronger. The spatial frequency of Gabor was either 0.6 or 2.0 cpd, and the contrast of Mondrian was either 100% or 2–4%. In the low–spatial frequency and high–Mondrian contrast condition, the test contrast was adjusted either from 10% to 50% or from 15% to 100% in five linear steps, depending on the matching contrast for each subject. In one block of 50 trials (ten trials at each of five contrast levels), test contrasts were randomized. Each subject completed at least two blocks. In other conditions, the test contrast was adjusted from 15% to 100% in five linear steps, and six blocks were conducted. To estimate the matching contrast for the test adaptor, we fitted a Weibull function to the data. For the correlation analysis, 60 trials at each test contrast were sorted according to the adaptor visibility duration: the six trials with the shortest visibility duration were categorized in the first bin, the six trials with the next shortest visibility duration in the second bin, and so on.

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ACKNOWLEDGMENTS We thank R. Kanai, C. Hofstoetter, D.A. Wu, F. Moradi, R. Van Rullen and S. Shimojo for discussion. This research was funded by grants from the US National Institute of Mental Health, the US National Science Foundation, the Keck Foundation and the Moore Foundation.


COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 5 April; accepted 16 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Koch, C. The Quest for Consciousness: A Neurobiological Approach (Roberts, Greenwood Village, Colorado, 2004). 2. Blake, R. & Fox, R. Adaptation to invisible gratings and the site of binocular rivalry suppression. Nature 249, 488–490 (1974). 3. He, S., Cavanagh, P. & Intriligator, J. Attentional resolution and the locus of visual awareness. Nature 383, 334–337 (1996). 4. Rajimehr, R. Unconscious orientation processing. Neuron 41, 663–673 (2004). 5. Hofstoetter, C., Koch, C. & Kiper, D.C. Motion-induced blindness does not affect the formation of negative afterimages. Conscious. Cogn. 13, 691–708 (2004). 6. Macknik, S.L. & Martinez-Conde, S. Dichoptic visual masking reveals that early binocular neurons exhibit weak interocular suppression: implications for binocular vision and visual awareness. J. Cogn. Neurosci. 16, 1049–1059 (2004). 7. Rees, G., Russell, C., Frith, C.D. & Driver, J. Inattentional blindness versus inattentional amnesia for fixated but ignored words. Science 286, 2504–2507 (1999). 8. Bonneh, Y.S., Cooperman, A. & Sagi, D. Motion-induced blindness in normal observers. Nature 411, 798–801 (2001). 9. Logothetis, N.K. & Schall, J.D. Neuronal correlates of subjective visual perception. Science 245, 761–763 (1989). 10. Leopold, D.A. & Logothetis, N.K. Activity changes in early visual cortex reflect monkeys’ percepts during binocular rivalry. Nature 379, 549–553 (1996). 11. Sheinberg, D.L. & Logothetis, N.K. The role of temporal cortical areas in perceptual organization. Proc. Natl. Acad. Sci. USA 94, 3408–3413 (1997). 12. Lumer, E.D., Friston, K.J. & Rees, G. Neural correlates of perceptual rivalry in the human brain. Science 280, 1930–1934 (1998). 13. Tong, F., Nakayama, K., Vaughan, J.T. & Kanwisher, N. Binocular rivalry and visual awareness in human extrastriate cortex. Neuron 21, 753–759 (1998). 14. Polonsky, A., Blake, R., Braun, J. & Heeger, D.J. Neuronal activity in human primary visual cortex correlates with perception during binocular rivalry. Nat. Neurosci. 3, 1153–1159 (2000). 15. Pasley, B.N., Mayes, L.C. & Schultz, R.T. Subcortical discrimination of unperceived objects during binocular rivalry. Neuron 42, 163–172 (2004). 16. Williams, M.A., Morris, A.P., McGlone, F., Abbott, D.F. & Mattingley, J.B. Amygdala responses to fearful and happy facial expressions under conditions of binocular suppression. J. Neurosci. 24, 2898–2904 (2004). 17. Wolfe, J.M. Reversing ocular dominance and suppression in a single flash. Vision Res. 24, 471–478 (1984). 18. Kreiman, G., Fried, I. & Koch, C. Single-neuron correlates of subjective vision in the human medial temporal lobe. Proc. Natl. Acad. Sci. USA 99, 8378–8383 (2002). 19. Wilke, M., Logothetis, N.K. & Leopold, D.A. Generalized flash suppression of salient visual targets. Neuron 39, 1043–1052 (2003). 20. Lack, L.C. Selective Attention and the Control of Binocular Rivalry 117–169 (Mouton, The Hague, The Netherlands, 1978).


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21. Wiesenfelder, H. & Blake, R. The neural site of binocular rivalry relative to the analysis of motion in the human visual system. J. Neurosci. 10, 3880–3888 (1990). 22. Blake, R. Psychoanatomical strategies for studying human visual perception. in Early Vision and Beyond (eds. Papathomas, T.V., Chubb, C., Gorea, A., & Kowler, E.) 17–25 (M.I.T. Press, Cambridge, Massachusetts, 1995). 23. Moradi, F., Koch, C. & Shimojo, S. Face adaptation depends on seeing the face. Neuron 45, 169–175 (2005). 24. Blake, R. & Logothetis, N.K. Visual competition. Nat. Rev. Neurosci. 3, 13–21 (2002). 25. Alpern, M. & Barr, L. Durations of the after-images of brief light flashes and the theory of the Broca and Sulzer phenomenon. J. Opt. Soc. Am. 52, 219–221 (1962). 26. Brindley, G.S. Two new properties of foveal after-images and a photochemical hypothesis to explain them. J. Physiol. (Lond.) 164, 168–179 (1962). 27. Loomis, J.M. The photopigment bleaching hypothesis of complementary after-images: a psychophysical test. Vision Res. 12, 1587–1594 (1972). 28. Loomis, J.M. Complementary afterimages and the unequal adapting effects of steady and flickering light. J. Opt. Soc. Am. 68, 411–416 (1978). 29. Virsu, V. & Laurinen, P. Long-lasting afterimages caused by neural adaptation. Vision Res. 17, 853–860 (1977). 30. Sakitt, B. Psychophysical correlates of photoreceptor activity. Vision Res. 16, 129–140 (1976). 31. Wilson, H.R. A neural model of foveal light adaptation and afterimage formation. Vis. Neurosci. 14, 403–423 (1997). 32. Kelly, D.H. & Martinez-Uriegas, E. Measurements of chromatic and achromatic afterimages. J. Opt. Soc. Am. A 10, 29–37 (1993). 33. Craik, K.J.W. Origin of visual after-images. Nature 145, 512 (1940). 34. Shimojo, S., Kamitani, Y. & Nishida, S. Afterimage of perceptually filled-in surface. Science 293, 1677–1680 (2001). 35. Breese, B.B. On Inhibition. Psychol. Monogr. 3, 1–65 (1899). 36. Levelt, W.J.M. On Binocular Rivalry (Institute for Perception RVO-TNO, Soesterberg, The Netherlands, 1965). 37. Fox, R. & Rasche, F. Binocular rivalry and reciprocal inhibition. Percept. Psychophys. 5, 215–217 (1969). 38. Bossink, C.J., Stalmeier, P.F. & De Weert, C.M. A test of Levelt’s second proposition for binocular rivalry. Vision Res. 33, 1413–1419 (1993). 39. Anstis, S., Rogers, B. & Henry, J. Interactions between simultaneous contrast and coloured afterimages. Vision Res. 18, 899–911 (1978). 40. Hayhoe, M.M. & Williams, D.R. Disappearance of afterimages at ‘impossible’ locations in space. Perception 13, 455–459 (1984). 41. Suzuki, S. & Grabowecky, M. Attention during adaptation weakens negative afterimages. J. Exp. Psychol. Hum. Percept. Perform. 29, 793–807 (2003). 42. Lou, L. Effects of voluntary attention on structured afterimages. Perception 30, 1439– 1448 (2001). 43. Weiskrantz, L. An unusual case of after-imagery following fixation of an ‘imaginary’ visual pattern. Q. J. Exp. Psychol. 2, 170–175 (1950). 44. Sengpiel, F., Blakemore, C. & Harrad, R. Interocular suppression in the primary visual cortex: a possible neural basis of binocular rivalry. Vision Res. 35, 179–195 (1995). 45. O’Regan, J.K. & Noe, A. A sensorimotor account of vision and visual consciousness. Behav. Brain Sci. 24, 939–73 (2001). 46. Lamme, V.A. Why visual attention and awareness are different. Trends Cogn. Sci. 7, 12– 18 (2003). 47. Chan, D., Crutch, S.J. & Warrington, E.K. A disorder of colour perception associated with abnormal colour after-images: a defect of the primary visual cortex. J. Neurol. Neurosurg. Psychiatry 71, 515–517 (2001). 48. Weiskrantz, L. Prime-sight and blindsight. Conscious. Cogn. 11, 568–581 (2002). 49. Schiller, P.H. & Dolan, R.P. Visual aftereffects and the consequences of visual system lesions on their perception in the rhesus monkey. Vis. Neurosci. 11, 643–665 (1994). 50. Brainard, D.H. The Psychophysics Toolbox. Spat. Vis. 10, 433–436 (1997).

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Visual field maps and stimulus selectivity in human ventral occipital cortex Alyssa A Brewer1, Junjie Liu2, Alex R Wade4 & Brian A Wandell1,3 Human visual cortex is organized into distinct visual field maps whose locations and properties provide important information about visual computations. There are two conflicting models of the organization and computational role of ventral occipital visual field maps. We report new functional MRI measurements that test these models. We also present the first coordinated measurements of visual field maps and stimulus responsivity to color, objects and faces in ventral occipital cortex. These measurements support a model that includes a hemifield map, hV4, adjacent to the central field representation of ventral V3. In addition, the measurements demonstrate a cluster of visual field maps in ventral occipital cortex (VO cluster) anterior to hV4. We describe the organization and stimulus responsivity of two new hemifield maps, VO-1 and VO-2, within this cluster. The maps and stimulus responsivity support a general organization of visual cortex based on clusters of maps that serve distinct computational functions.

Human visual cortex is organized into a set of distinct visual field maps; these are cortical regions in which nearby neurons analyze the properties of nearby points in the visual field. Knowledge of the properties of these visual field maps and the stimulus selectivity of the neurons within these maps is the foundation for understanding visual computations. Although there is consensus on the properties of several human maps, including V1, V2 and V3 (refs. 1–4), there are disputes about the organization of maps in other portions of human visual cortex5. One of the disputed regions is the ventral occipital surface adjacent to V3 (refs. 6,7). There has been no consensus on the properties of visual field maps in this region despite several attempts to understand their organization and role in visual perception6–15. Here we report new measurements of eccentricity maps, angular maps and stimulus responsivity in ventral occipital cortex. These measurements discriminated between two models of the visual field maps. The data supported a model containing a hemifield map, hV4, adjacent and anterior to the ventral portion of V3. In addition, these measurements demonstrated a cluster of visual field maps containing at least two new hemifield maps, VO-1 and VO-2, anterior to hV4 on the fusiform gyrus. To clarify the perceptual function of the neurons in these maps, we describe the first coordinated measurements of color, face and object selectivity within these visual field maps. The stimulus selectivity differed across the hV4 and VO maps. The field maps hV4, VO-1 and VO-2 responded well to color stimulus exchanges. The VO-1 and VO-2 maps responded preferentially to objects compared to faces, but the hV4 map did not. In addition, the stimulus-response patterns in hV4, VO-1 and VO-2 differed from cortex lateral to these maps.

RESULTS Visual field map models We compared two models of the visual field maps on the ventral surface adjacent to ventral V3 (Figs. 1 and 2). One, the hV4 (human V4) model, was proposed by Wade et al.15 (see also Kastner et al.10 and McKeefry et al.8). The second, the V8 model, was proposed by Hadjikhani et al.6. Both models agree that there are several maps representing the upper part of the visual field in a single hemisphere beginning in the calcarine sulcus and extending onto the ventral surface (Fig. 1a): V2-ventral (green), V3-ventral (blue) and an upper quarterfield (red) adjacent and anterior to V3v. All of these quarterfield maps share a common eccentricity profile, with the foveal representation centered slightly lateral to the occipital pole and the peripheral representation extending onto the ventral surface toward the collateral sulcus. The models diverge in the region of cortex adjacent to these quarterfield maps in the location denoted by the dotted yellow outline. The hV4 model15 suggests that the upper quarter-field adjacent to V3v is part of a hemifield map that extends into the dotted yellow region. The red region and outlined region together form hV4. This hemifield map has an eccentricity representation parallel to that of V1/2/3. The V8 model proposes that the upper quarter-field adjacent to V3v, named V4v, has no corresponding lower quarter-field representation16. Adjacent to V4v, in the area bounded by the dotted yellow line (Fig. 1a), the model proposes a visual area, V8, that represents a hemifield and whose eccentricity map is rotated 901 with respect to the red region6. The peripheral representation of V8 abuts the horizontal meridian representation in V4v, and the foveal representation of V8 is distinct and anterior to that of V1/2/3.

1Neurosciences

Program, 2Applied Physics and 3Department of Psychology, Stanford University, Stanford, California 94305, USA. 4Smith-Kettlewell Eye Research Institute, San Francisco, California 94115, USA. Correspondence should be addressed to A.A.B. ([email protected]).


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ARTICLES Figure 1 Ventral occipital visual field map The hV4 model 4 models. (a) Top: locations of ventral portions of V2 (green), V3 (blue) and the undisputed quarterV3v V3v field representation (red), derived from automatic 2 atlas-fitting procedures (0–31 eccentricity3). The hV4 hV4 PO-S dotted yellow line and white circles denote the region of cortex in which the hV4 and V8 models Cal-S diverge. Inset at lower left: region of cortex under 0 1 2 3 study. PO-S: Parietal-occipital sulcus. Cal-S: Disk Calcarine sulcus. Col-S: Collateral sulcus. Fu-G: Angle Fusiform gyrus. (b) The hV4 model specifies a Eccentricity hemifield map adjacent and anterior to ventral V3. Col-S The colors in the cartoon maps represent the The V8 model 4 Fu-G visual field position that would produce the strongest response at that cortical location (see V3v V3v color legends). Measurements at the positions hV4 hV4 2 indicated by the white circles (corresponding to the locations of the white circles in a) should have a constant angular representation and a varying V8 V8 eccentricity representation. These predictions are 0 1 2 3 illustrated in the graph at the right, which shows Disk the expected traveling wave phases in response to rotating wedge (angle) and expanding ring (eccentricity) stimuli. (c) The V8 model includes only a quarter-field map adjacent to the ventral portion of V3. Adjacent to this quarter-field map, the model proposes a rotated hemifield representation. The V8 model predicts that measurements at the white circle positions will have a varying angular representation and a constant eccentricity representation. These predictions are shown in the graph at the right, which can be contrasted with the predictions for the hV4 model.

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The hV4 and V8 models predict different response patterns at the locations indicated by the white circles (Fig. 1). In the hV4 model, measurements along the white circles should represent a constant angular direction and changing eccentricity. In contrast, the V8 model predicts a constant eccentricity representation and a varying angular direction. The contrasting predictions from these two models are illustrated in the graphs in Figure 1b,c. Testing the models We measured the visual field representation in the disputed region using traveling wave stimuli (Fig. 2). These stimuli were confined within the central 31 and contained relatively high–spatial frequency patterns. The angular and eccentricity measurements are shown as pseudocolor maps in Figure 2a,b, respectively (see Figs. 3–5 for additional examples). The white lines denote the boundary between V2v/V3v and the anterior boundary of V3v. These boundaries as well as

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the horizontal meridian of the undisputed quarter-field were defined by atlas-fitting procedures3. The white circles indicate three measurement regions comprising 3-mm-radius disks. These were positioned (i) in the disputed portion of cortex, (ii) parallel to the horizontal meridian of the undisputed upper field representation and (iii) with a spacing of approximately 1 cm center-to-center. In all nine observers, the angular representation in these three regions was approximately constant (Fig. 2c). The eccentricity representation varied from fovea to periphery, paralleling that of the V2/V3 eccentricity maps. Hence, the data were consistent with the hV4 model but inconsistent with the V8 model. In previous reports that included measurements of visual field maps in ventral occipital cortex, investigators used stimuli that spanned a much larger portion of the visual field6,8,10,15. Although we found that data were consistent across 201 and 31 measurements, concentrating the measurements in the central 31 provided a clearer view. This may be explained by the strong cortical magnification present in the region around hV4 and on the ventral surface in general17. This foveal emphasis is consistent with anatomical labeling in macaque that shows foveal receptive fields dominating the ventral pathways and dorsal pathways receiving predominantly peripheral input18.

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Figure 2 The data support the hV4 model. (a) Angular map measurements using 31 rotating wedge stimuli. The pseudocolor overlay represents the visual field position that produces the strongest response at each cortical location (see color legend). The measurements shown are restricted to lie within the boundaries of V2v, V3v and hV4, as derived from automatic atlas fitting procedures3. The white lines mark the boundary between V2v and V3v as well as at the anterior boundary of V3v. The white circles show the three measurement positions (3-mm-radius disks) in the disputed region. (b) Eccentricity map measurements using a 31 expanding ring stimulus; otherwise as in a. (c) Measurements from nine subjects showing the traveling wave phases in the 3-mm radius disks at the white circle positions (most foveal disk is #1). For clarity, the left hemisphere angular phases have been shifted up by p radians to align with the right hemisphere angular phases. Subject 1 in a,b. Coherence Z 0.30. Other details as in Figure 1.

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Figure 3 The VO cluster. (a,b) Eccentricity maps in ventral occipital cortex of two subjects measured using expanding ring stimuli (31; see color legend). Two distinct foveal representations (red/yellow) are present. The posterior representation is at the confluence of the V1/V2/V3/hV4 maps. These share a common eccentricity representation that expands in a semicircle from the foveal representation. The second foveal representation is located in the fusiform gyrus and also forms a semicircular eccentricity map. The two maps meet at the blue boundary. Measurement planes were located posterior to the dotted line. For clarity, only responses near the fusiform gyrus are shown. (c) BOLD time series and response amplitudes in a 3-mm-radius disk located at the arrow in b. The normalized response amplitude at the signal frequency (Sf, red) with respect to the distribution of non-stimulus frequencies is 16.77. These stimulus-driven signals are substantially above statistical threshold. Subjects S2, S3. Coherence Z 0.25 (S1) or 0.20 (S6). Other details as in Figure 2.

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HV4 and the VO cluster In human cortex, we have proposed that visual field maps are organized into several clusters as exemplified by the V1/2/3/hV4 cluster5. These clusters share a common eccentricity representation and can be subdivided into multiple maps by reversals in their angular representations. In addition to the cluster near V1, there are established clusters near V3A/V3B and motion selective cortex (hMT+). We suspect that each cluster contains one or more groups of maps with similar computational functions. Eccentricity measurements (31 expanding ring) in ventral occipital cortex revealed another cluster of maps anterior to hV4 (Fig. 3a,b). The foveal (red/yellow) representation of the V1 cluster can be seen at the occipital pole. The peripheral boundary of this cluster is also evident (cyan/blue/purple). In more anterior ventral cortex, along the fusiform gyrus and collateral sulcus, there was a distinct semicircular eccentricity map (dotted white line) on the fusiform gyrus15. We refer to this region as the ventral occipital (VO) cluster. We measured complete eccentricity maps in this region in all subjects. Anterior to the VO cluster, we

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where F() is the Fourier transform operator and | | is the amplitude operator. By computing the harmonic amplitudes at each voxel before averaging, we compared response strength independent of the phase differences between the voxels. The peak response frequency coincided with the stimulus alternation frequency (red). The response modulations were substantially higher than common statistical significance levels (P { 0.001). New visual field maps in the VO cluster Beyond hV4, there were at least two hemifield maps in the VO cluster, VO-1 and VO-2 (Fig. 4). The lower vertical meridian representation of the VO-1 map (magenta; posterior white line) abutted the peripheral representation of hV4 and extended to the peripheral representation of V3v. VO-1 and VO-2 shared an upper vertical meridian representation (cyan/blue; anterior white line).

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observed additional responses to the traveling wave stimuli in many subjects, but these will not be further described here. The blood oxygenation level-dependent (BOLD) response is strong and reliable across the boundary between hV4 and the VO cluster (Fig. 3b, arrow). The curve on the left (Fig. 3c) measures the mean of the BOLD time series ri(t). The curve on the right measures the mean of the harmonic response amplitudes across the region of interest. For a collection of time series ri(t) at voxels i ¼ 1,N in the region of interest, the mean of the harmonic amplitudes is 1 X Aðf Þ ¼ jFðri ðtÞ; f Þj N i¼1;N

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Figure 4 The definitions of VO-1 and VO-2. The solid green and blue regions in the images denote V2v and V3v (0–161) derived from the automatic atlasfitting procedures described in Methods3. The color overlays show measurements of the visual field position that most effectively stimulates each cortical location (see color legends). The inset shows the right ventral occipital region under study. (a) Angular map measurements using 31 rotating wedge stimuli. The white lines indicate the boundaries between hV4 and VO-1 and between VO-1 and VO-2. For clarity, data are restricted to hV4, VO-1 and VO-2 maps, as defined by the atlas fitting procedures. (b) Eccentricity map measurements using a 31 expanding ring stimulus; otherwise as in a. (c,d) The response amplitudes as a function of temporal frequency measured in two 3-mm-radius disks located in VO-1 and VO-2 (arrows). The responses for both angular (c) and eccentricity (d) data are significantly greater at the stimulus repetition frequency (6 cycles/scan, shown in red) than other temporal frequencies. Normalized response amplitude at the signal frequency (Sf, red) with respect to the distribution of non-stimulus frequencies are 12.14, 12.37 (VO-1, wedge and ring) and 17.55, 8.54 (VO-2, wedge and ring). Subject S2. Coherence Z 0.25. Other details as in Figure 2.

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The VO-1 and VO-2 eccentricity maps began in the large distinct foveal representation used to define the VO cluster. Much like the V3A/ V3B maps, the eccentricity representation formed a semicircular pattern. The eccentricity map became increasingly peripheral as it extended medially across the collateral sulcus and approached the peripheral representation of V3v. The arrows in Figure 4a indicate the location of two regions of interest (3-mm-radius disks). The harmonic amplitudes of BOLD responses in these two regions are shown in the graphs at the bottom (Fig. 4c,d). Again, the response modulations were substantially higher than common statistical significance levels (P { 0.001). The same basic pattern of visual field maps is shown in three additional subjects (Fig. 5). An angular map representing the complete VO-1 and VO-2 hemifield was present in all subjects measured (n ¼ 9), although the precise orientation with respect to the sulcal and gyral patterns varied across subjects. Because the relatively anterior location of VO-2 within visual cortex was at the limit of the volume that could be imaged by our posterior surface coil, the signal coherence within VO-2 was lower than the coherence in more posterior regions in some subjects. The maps in this region occupied small amounts of cortical surface area, so that with current fMRI spatial resolution (2.5 mm), the maps depend on measurements in only a few dozen spatial samples, and these samples might not be completely independent. Because of the limited spatial resolution of the measurements, it is important to make additional measurements of stimulus selectivity to clarify the presence (or absence) of a visual field map boundary. In the next section, we describe coordinated measurements of color, object and face responsivity within these maps and adjacent regions to further clarify the properties and functional significance of these maps.

cause selective loss of color, face or object perception19–23. There are significant fMRI responses in these regions as subjects engage in a wide range of tasks involving color, faces, or objects9,24–27. Using the same set of subjects as in the visual field mapping experiments, we measured stimulus-exchange responses in this ventral region in order to clarify the relationship between the visual field maps in this region and the responses to these stimuli. We identified nine regions of interest (ROIs) for measurements spanning hV4 (red), VO-1 (yellow), VO-2 (magenta) and nearby lateral cortex (white circles in Fig. 6). Each ROI within the maps was centered over a 3-mm-radius disk as measured on the cortical surface; the lateral ROIs had a 6 mm radius. The hV4 (circles labeled 1 and 2), VO-1 (circles 3,4), and VO-2 (circles 5,6) ROIs were placed approximately on the horizontal meridian in foveal and peripheral representations. We measured the responses in these nine ROIs during colorluminance exchange experiments (Fig. 7a) and object-face exchange experiments (Fig. 7b). In these exchange experiments, we expected the responses across voxels in an ROI to occur in a common temporal phase. Hence, we measured the response by first computing the average time series of all the voxels in the region of interest and then calculating the amplitude spectrum of this average. That is, for a response time series ri(t) at voxels i ¼ 1,N in the region of interest, we calculated the amplitude spectrum as ! 1 X ri ðtÞ; f Aðf Þ ¼ F N i¼1;N We summarized the response during the exchange experiment by computing the normalized response amplitude. This quantity was computed from the BOLD response amplitude at the stimulus exchange frequency, A(fS), the mean amplitude at noise frequencies,

Stimulus selectivity near hV4, VO-1 and VO-2 Cortical computations in ventral occipital cortex are important for many types of visual recognition processes. Lesions in this region can

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Figure 6 Stimulus selectivity measurement locations. The solid colored regions denote ventral visual maps fit by the automatic atlas fitting procedures3: V2 (green, 0–161), V3 (blue, 0–161), hV4 (red), VO-1 (yellow) and VO-2 (magenta). The white circles show the nine measurement locations. The regions in hV4, VO-1 and VO-2 are 3-mm-radius disks; those lateral to these maps are 6-mm radius. Each map contains a relatively central and peripheral measurement region near the horizontal meridian representation. PO-S: parietal-occipital sulcus. Cal-S: calcarine sulcus. Col-S: collateral sulcus. Fu-G: fusiform gyrus.


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hfN i (frequencies other than fS and 2fS) and the s.d. of the amplitude at the noise frequencies, sh fN i . P Aðfs Þ N1 AðfN Þ hfN i R¼ shfN i We assigned the normalized response a positive or negative value to indicate which of the stimulus phases aligned with the response phase (for example, positive BOLD responses in synchrony with object or face presentations). The normalized response amplitudes in each of the nine ROIs during the color-luminance exchange experiments are shown in Figure 7a. There was a significant response in synchrony with the color stimulus in all three maps; the response amplitude was significantly greater in the central than peripheral portions of the maps. We were surprised to find that there was a significant right/left hemisphere difference in the responses lateral to VO-1 (ROI 8). There were powerful color responses in the right, but not left, hemisphere of all five subjects. (All five subjects were right-handed.) No other differences in lateralization were observed. The normalized response amplitudes in each of the nine ROIs during the object-face exchange experiments are shown in Figure 7b. There was no preferential response in either the central or peripheral ROIs of hV4. In additional measurements, we found that the upper and lower field representations of hV4 were consistent in both the color-luminance and object-face experiments, supporting the grouping of the upper and lower quarter-field representations within hV4 into a single hemifield representation. In both VO-1 and VO-2, there was a stronger preference for objects, particularly in the peripheral portions of these maps. Responses in phase with the face presentations were observed in the

regions lateral to hV4 and VO-2. These ROIs were near the Talairach coordinates of two commonly cited face-responsive regions: the fusiform face area27,28 and the occipital face area24. The Talairach coordinates for the parahippocampal place area were anterior and slightly lateral to VO-2 (ref. 29). An example of the spatial distribution of color, face and object responses in relation to visual field maps is shown for one subject in Supplementary Figure 1. In summary, the stimulus selectivity properties of hV4, the VO cluster maps, and the lateral regions all differed from one another. DISCUSSION To investigate the visual computations in ventral occipital cortex, we made measurements of visual field maps coordinated with selectivity for color, faces and objects. Visual field maps Figure 8a summarizes the ventral maps beyond V1. The ventral portions (0–161) of the V2 and V3 maps both represented the upper visual field. The hV4, VO-1 and VO-2 maps spanned a hemifield. The relatively central representations of the V2, V3 and hV4 maps were confluent with the V1 central representation. The central representations for V1, V2 and V3 extended onto the lateral surface (data not shown), but the hV4 central representation remained ventral. The VO-1 and VO-2 maps shared a central representation that was separated from the V1/2/3/hV4 fovea and located primarily along the fusiform gyrus. When measured using a 31 radius stimulus, the hV4 map covered a surface area of about 500–750 mm2 (Fig. 8b). The VO-1 and VO-2 maps were both slightly smaller than hV4 (400–700 mm2). Like V1, the surface area of each of these maps varied across subjects3. Individual map sizes for V1, hV4, VO-1 and VO-2 are described in Supplementary Table 1. When measuring V1 with the same 31 stimulus, the

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Figure 8 Summary of hV4, VO-1 and VO-2 field map properties. (a) The positions of the ventral-occipital visual field maps V2v (green, 0–161), V3v (blue, 0–161), hV4 (red), VO-1 (yellow) and VO-2 (magenta) are shown. The + and – indicate upper and lower visual field representations, respectively. The asterisk indicates the most central visual field representation within each map. PO-S: parietal-occipital sulcus. Cal-S: calcarine sulcus. Col-S: collateral sulcus. Fu-G: fusiform gyrus. (b) The surface area of each map was defined by a 31 expanding ring stimulus and measured along the cortical manifold. The left and right hemispheres correspond to the left and right bars. Error bars: ± 1 s.d.

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Figure 7 Stimulus selectivity measurements. The normalized response amplitudes in nine ROIs during the color-luminance (a) and object-face (b) experiments are shown. The top and middle panels show the responses in the central (1,3,5) and peripheral (2,4,6) ROIs (numbers in parentheses indicate ROI numbers; see Fig. 6). The bottom panel shows the responses in the three regions lateral to the maps (7,8,9). The circles represent the normalized responses for individual subjects (n ¼ 5, two hemispheres per subject) and are colored by subject. The dark vertical bars represent the median response. The shaded regions represent a significance level P 4 0.001 (uncorrected). The dotted oval indicates measurements from the right hemisphere. Subjects S1, S2, S4, S5, S6.

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ARTICLES cortical surface area spanned approximately 600–1600 mm2. When measured using a 161 stimulus, the responding surface area of V1 expanded considerably along the calcarine sulcus, but the hV4, VO-1 and VO-2 maps expanded very little or not at all. These ventral maps appeared to respond more powerfully to central visual stimuli throughout their extent, consistent with the strong cortical magnification described in human and macaque ventral cortex17,18. These data are the first report in the literature on human hemifield maps in the positions occupied by VO-1 and VO-2. The VO cluster occupies the same position as the object-responsive region that Halgren et al. refer to as posterior collateral30 and the building-responsive region that Malach et al. refer to as collateral sulcus (see Figure 3 in ref. 11). Halgren et al. describe this region as non-retinotopic cortex; Malach et al. describe it as having only a peripheral eccentricity bias and no angular representation. In contrast to both studies, we found two visual field maps (VO-1, VO-2) in this region with detailed eccentricity and angular maps that were primarily central. The visual field maps measured here can be compared with several other reports in the literature. We have already described the differences between our hV4 measurements and the V8 model6. Our hV4 measurements are consistent with those of Kastner et al.10, who describe a hemifield adjacent to V3v and find no evidence for the V8 visual field map. Tootell et al.16 (subsequent to Halgren et al.) have reported data consistent with a full visual hemifield map adjacent to V3v (see Figures 5 in refs. 16,31). The organization of the ventral maps was secondary to those papers, and the authors did not discuss this aspect of their measurements. McKeefry and Zeki8 have also demonstrated a hemifield map in the ventral region. In subsequent measurements, this group identified a V4 complex (V4; V4a) that overlaps with hV4 and the VO cluster9. They did not measure visual field maps near this region, such as V2 and V3, leaving open how their activations are positioned with respect to those maps. The region anterior to hV4 on the fusiform gyrus, which overlaps with the VO cluster, has also been discussed by Kastner et al.10,32. They call this region TEO based on its position and a guess about homology with macaque. While they show that this region responds to stimuli across the contralateral hemifield, they find no separation between the upper and lower visual field representation and do not measure eccentricity maps. We have considered the relationship between the model we present here and the V8 model proposed by Hadjikhani et al.6. One way to coordinate these models is to suppose that Hadjikhani et al. missed the second quarter-field in hV4, but that VO-1 is the visual field map they identified as V8. We call this a quarter-field-insertion model. According to this model the VO-1 visual field map should have (i) a peripheral representation that abuts the hV4 lower vertical meridian and (ii) an angular representation that runs parallel to the hV4 eccentricity map (Fig. 1). It would not be expected that VO-1 would reach V3v. In contrast, the VO-1 map we measured was located near the peripheral representation of hV4, nestled between that map and the peripheral representation of V3. Hence, the quarter-field-insertion model does not fit the VO-1 data, and VO-1 cannot be the same as V8. Further, the anatomical location and object-selectivity of VO-1 correlates with the object-responsive region named posterior collateral, not V8, in data from the same group30. A variant of the quarter-field-insertion model would allow that VO-1 is new and differs from V8, but that V8 still exists at the location abutting the lower vertical meridian representation of hV4 (see ROIs 7–8 in Fig. 6). We have not been able to find evidence for a V8 visual field map in this location, although we acknowledge that such evidence might be found with other stimuli or experimental designs. We do see a


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strong color response in position 8, lateral to VO-1, but only in the right hemisphere. The Talairach coordinates of the hV4, VO-1 and VO-2 field maps are described in Supplementary Table 2. The basic arrangement of visual field maps was consistent, but across individuals there was variability on the order of 1 cm in the Talairach coordinates of these maps. Given that the maps themselves are on the order of 2–3 cm, such variability suggests that averaging across subjects would obscure the presence of these maps. Although many aspects of human visual field maps in early visual areas parallel those in macaque, we found significant differences beyond V3v/VP. The visual field map adjacent to V3v represents a hemifield confined entirely to the ventral surface in human (hV4), while the same region in macaque (V4) continues to follow the V1/2/3 pattern of splitting into dorsal and ventral quarter-fields. The human hV4 map may be homologous to macaque V4 despite the ventral placement of the full hemifield, or hV4 may not have an exact counterpart in macaque15,33. The VO maps occupied a position with respect to V3v and hV4 that was similar to the position of macaque VTF30,34,35. Although both macaque VTF and the human VO maps are responsive to more complex visual stimuli like objects, presently there is no strong evidence linking these regions36. Stimulus selectivity The patterns of stimulus selectivity in the hV4 and the VO maps differed, and these patterns both differed from those in the regions lateral to these maps. The central hV4 ROI responded powerfully to color, and no part of the map responded preferentially to faces or objects. The VO cluster maps responded strongly to color in the central portion of the map and preferentially to objects compared with faces, particularly in the peripheral representation. In contrast, cortex slightly lateral to these maps responded preferentially to faces compared to objects. This differential stimulus selectivity across this ventral region supports our definitions of the hV4, VO-1 and VO-2 visual field maps. There is consensus that ventral occipital cortex is essential for normal color perception. However, there is a dispute about the localization of color processing with respect to individual maps6–9,37,38. McKeefry and Zeki8 describe a V4 complex as the essential region for color perception, while Hadjikhani et al.6 propose that V8 is the essential map. Both groups identify essential color signals by measuring the response while alternating two stimuli. However, these stimulus pairs are not comparable. McKeefry and Zeki use a spatial pattern comprised of a set of rectangles whose average luminance contrast is constant between blocks and whose chromatic contrast is modulated. Hadjikhani et al. use harmonic patterns that alternate between a 95% contrast monochrome pattern and an isoluminant chromatic pattern (unspecified contrast level); in these experiments neither luminance nor chrominance are held constant. These two types of stimulus alternations should not produce identical cortical responses. For example, the McKeefry and Zeki stimulus would produce no modulation in regions that respond only to luminance, whereas the Hadjikhani et al. stimulus would. The color-luminance exchange measurements performed here used the same approach as McKeefry and Zeki8 and produce responses in hV4, VO-1 and VO-2. In separate experiments, we have also used the Hadjikhani et al.6 design, and we found that the spatial distribution of responses in phase with the color stimulus was nearly identical in both experiments. Hence, we believe that the Hadjikhani et al. color responses are in the same cortical locations as described by McKeefry and Zeki8 and colleagues9,37,39.

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Neither group comments on the right lateralization of the color responses, which we observed using both types of color-luminance exchange methods. In addition, our color responses were not confined to a single visual field map, in contrast to reports from Hadjikhani et al.6. Before drawing strong conclusions about the functional role of these responses in color perception, a variety of additional factors, such as the spatial inhomogeneity of the retinal encoding of signals and better stimulus control, must be accounted for (for example, see refs. 4,15,40). Visual clusters In human, we find several distinct eccentricity maps that include one or more angular maps (Figs. 3–5). We have named such regions visual field map clusters5. The V1/V2/V3/hV4 maps form one cluster; the V3A/V3B maps form another; the maps near hMT+ form another cluster; and we propose that VO-1 and VO-2 are part of a VO cluster. We suspect that maps within each cluster share common computational resources, such as short-term information storage or timing circuitry41. It may also be that perceptual specializations are organized around these clusters rather than within single visual field maps, as is seen in the common motion selectivity in the hMT+ cluster. The data presented here show common object and color selectivity across the VO cluster. The visual cluster model differs from the model of human visual cortex developed by Levy et al.12–14,42. According to that model, visual cortex begins with precise visual field maps in V1, V2, and V3. Anterior to these regions, however, the maps degrade, so that ‘‘orderly representations of the visual field meridians are absent’’ (ref. 12, p. 533). The contiguous eccentricity map present in the early visual areas degrades to become simply a bias toward central and peripheral responses14. These eccentricity biases are posited as the driving force for organization in higher order visual cortex. The eccentricity bias theory does not allow for the detailed eccentricity and angular maps as seen in VO-1 and VO-2. We disagree with their model because (i) no computational principle has been identified to suggest why neurons would be arranged with orderly eccentricity responses, but no angular maps, and (ii) we observe organized eccentricity and angular maps in ventral cortex (see ref. 5 for an extended critique). Hence, we propose exploring the alternative hypothesis that clusters of maps, each devoted to a different computational function, are a basis for the organization of human visual cortex. METHODS Subjects. Nine subjects participated in this study (visual field mapping: S1–S9; stimulus selectivity: S1, S2, S4–S6). All subjects had normal color vision and a corrected acuity of 20/20 or better. Informed written consent was obtained from all subjects. Visual display. Stimuli were presented on an LCD (NEC 2080UX; spatial resolution 800 600, refresh rate 60 Hz). The display was inside an electrically shielded box with conductive glass on the front side. The intensity and spectral characteristics of the display were calibrated (PhotoResearch PR-650). The display primary intensities were controlled using a 10-bit digital-to-analog card (ATI Radeon). Cone excitations were estimated using conventional methods43,44. Stimuli were presented in one of two display configurations. (i) The visual field mapping studies were performed with the LCD positioned at the rear of the magnet bore, behind the subject’s head. The viewing distance was 2.8 m. Subjects viewed the LCD through an angled front surface mirror placed close to the eyes. The mirror was included in the optical path during the display calibration procedure. The maximum stimulus radius subtended 31 of visual angle. (ii) The stimulus selectivity studies (faces, objects, and color) were performed with the display at the foot of the patient table. In this configuration subjects viewed the screen through binoculars as well as the mirror. The

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binoculars were adjusted to ensure that the stimulus was centered in the visual field and no vignetting occurred. The monitor was 4.3 m from the subject, so the approximately eightfold magnification of the binoculars yielded an effective viewing distance of 0.54 m. In this configuration, the maximum stimulus radius subtended 161 of visual angle. FMRI data acquisition. FMRI measurements were performed on a 3-T General Electric scanner with a custom-designed surface coil (Nova Medical) for anatomical, visual field mapping and color scans or with a custom-built volume head coil for the object-face scans. Subjects were supine in the scanner bore, with the coil placed near visual cortex. Head movements were minimized by padding and tape. Functional MR data were acquired with a spiral pulse sequence45,46 with 21–30 slices oriented coronally, axially or perpendicularly to the calcarine sulcus. Slice orientation had no significant effect on results. The effective inter-frame sampling interval of BOLD signals was 2.4 s (field mapping) or 3 s (stimulus selectivity), and the voxel size of functional data was 2.5 2.5 3 mm. A set of two-dimensional fast SPGR anatomy images was acquired before the series of functional scans. These T1-weighted slices were physically in register with the functional slices and were used to align the functional data with the high-resolution anatomy data via a semi-automated three-dimensional (3D) coregistration algorithm47. Data analysis. We analyzed fMRI data using custom software (http://white. stanford.edu/software/). Data in each fMRI session were analyzed voxel-byvoxel with no spatial smoothing. The acquired BOLD signal from each voxel was divided by its mean to derive a time series of percent modulation. Baseline drifts were removed from the time series by high-pass temporal filtering. Head movements across scans were examined by comparing the mean value maps of the BOLD signals; most scans had minimal head motion (less than one voxel). Motion artifacts within each scan were also monitored. Fewer than 10% of the scans had significant motion artifacts; these scans were discarded. No motioncorrection algorithm was applied. Anatomical pre-processing. Anatomical images were acquired on a GE 1.5-T Signa LX scanner using a 3D SPGR pulse sequence (1 echo, minimum TE, 151 flip angle, 2 excitations). Sagittal slices were acquired with an inplane voxel size 0.94 0.94 mm and 1.2 mm slice thickness. We acquired 1–3 whole brain T1-weighted anatomical data sets for each subject. These images were averaged and re-sampled into a 1 1 1 mm resolution three-dimensional anatomical volume that was corrected for inhomogeneity and linearly transformed (with no rescaling or distortion) to align with the Talairach reference brain. These operations were performed using tools from the FMRIB software library (http://www.fmrib.ox.ac.uk/fsl/). Gray and white matter were segmented from the anatomical volume using custom software and then hand-edited to minimize segmentation errors48. Data analysis was restricted to the gray matter. The surface at the white/gray boundary was rendered as a smoothed three-dimensional surface using VTK software (http://www.vtk.org/). Analyses were also performed on a flattened two-dimensional map of the cortical surface40. Visual field mapping methods. We measured visual field maps using expanding rings and rotating wedges. Stimuli were high contrast dartboard patterns4,49. The patterns were 5 cycles per degree (31 stimuli) or 1 cycle per degree (161 stimuli) in the radial direction, 12 cycles per 2p radians in the angular direction, and reversed contrast at a temporal frequency of 2 Hz. The expanding ring contrast pattern covered 25% of the 0–31 or 0–161 eccentricity range and changed position every 2.4 s. The wedge angle was 451 and stepped 361 clockwise every 2.4 s. For both stimuli, a full display cycle comprised 24 s, and the data include at least 25 cycles from repeated scans of each type of stimulus. Subjects maintained fixation on a central cross throughout all scans. Atlas fitting procedures. We used an automated atlas fitting procedure to identify visual areas3. The algorithm simultaneously fits both angle and eccentricity maps. With this approach, we obtain objective estimates of the boundaries of hemifield and quarter-field visual angle representations. Stimulus selectivity methods: color. Color responses were measured using a block design in which 12-s blocks of achromatic stimuli alternated with 12-s

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ARTICLES blocks of chromatic stimuli (24-s period). Subjects viewed a series of patterns comprised of an array of 8 8 rectangular patches spanning 241 of visual angle. During each 12-s block a new pattern was presented every 2 s. Stimulus color was specified in terms of relative L, M and S-cone excitations. In the first 12-s block the patterns had only achromatic (luminance scaling) contrast. In this block, (L + M)- and S-cone contrasts were set equal, and (L – M)-cone contrast was zero. The (L + M)-and S-cone contrasts were selected randomly and uniformly from a range of ±17%. In the second 12-s block, the (L + M)- and S-cone contrasts were equal and selected the same way as in the first block. The (L – M)-cone contrast was selected randomly and uniformly from a contrast range of ±6%. The two contrast ranges (17% for (L + M)-cone and S-cone compared with 6% for (L – M) chromatic) were chosen to approximately equate for V1 responses50. To control attention, subjects were required to detect the orientation of a superimposed ‘C’ shape. The shape was created by adding a small amount of L + M signal to seven of the rectangles. The additional mean signal was very slight and was adjusted so that subjects scored about 80% correctly in identifying the orientation of the target. Stimulus selectivity methods: faces and objects We measured fMRI responses to stimuli by alternating between blocks containing images of faces and blocks containing a variety of objects. A new grayscale picture within one category (for example, face) was presented every 2 s during a 36-s block. All photographs were scaled to subtend 12 121 of visual angle, matched in mean luminance, and centered in the visual field. These stimuli were similar to those used by Kanwisher and colleagues in studies examining face and object representations26,27. Throughout each scan, subjects maintained fixation on a 0.21 cross that was centered in the field of view. To control for attention, the subjects were asked to perform a one-back matching task in which they compared the present picture to the stimulus presented two frames prior. One or two pictures per block were repeated. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS Supported by National Eye Institute RO1 EY03164 and National Institute of Neurological Disorders and Stroke 5 F30 NS44759. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 18 May; accepted 27 June 2005 Published online at http://www.nature.com/natureneuroscience/

1. Sereno, M.I., McDonald, C.T. & Allman, J.M. Analysis of retinotopic maps in extrastriate cortex. Cereb. Cortex 4, 601–620 (1994). 2. DeYoe, E.A. et al. Mapping striate and extrastriate visual areas in human cerebral cortex. Proc. Natl. Acad. Sci. USA 93, 2382–2386 (1996). 3. Dougherty, R.F. et al. Visual field representations and locations of visual areas V1/2/3 in human visual cortex. J. Vis. 3, 586–598 (2003). 4. Engel, S.A., Glover, G.H. & Wandell, B.A. Retinotopic organization in human visual cortex and the spatial precision of functional MRI. Cereb. Cortex 7, 181–192 (1997). 5. Wandell, B.A., Brewer, A.A. & Dougherty, R.F. Visual field map clusters in human cortex. Phil. Trans. R. Soc. Lond. B 360, 693–707 (2005). 6. Hadjikhani, N., Liu, A.K., Dale, A.M., Cavanagh, P. & Tootell, R.B.H. Retinotopy and color sensitivity in human visual cortical area V8. Nat. Neurosci. 1, 235–241 (1998). 7. Zeki, S., McKeefry, D.J., Bartels, A. & Frackowiak, R.S. Has a new color area been discovered? Nat. Neurosci. 1, 335–336 (1998). 8. McKeefry, D.J. & Zeki, S. The position and topography of the human colour centre as revealed by functional magnetic resonance imaging. Brain 120, 2229–2242 (1997). 9. Bartels, A. & Zeki, S. The architecture of the colour centre in the human visual brain: new results and a review. Eur. J. Neurosci. 12, 172–193 (2000). 10. Kastner, S. et al. Modulation of sensory suppression: implications for receptive field sizes in the human visual cortex. J. Neurophysiol. 86, 1398–1411 (2001). 11. Malach, R., Levy, I. & Hasson, U. The topography of high-order human object areas. Trends Cogn. Sci. 6, 176–184 (2002). 12. Levy, I., Hasson, U., Avidan, G., Hendler, T. & Malach, R. Center-periphery organization of human object areas. Nat. Neurosci. 4, 533–539 (2001). 13. Hasson, U., Levy, I., Behrmann, M., Hendler, T. & Malach, R. Eccentricity bias as an organizing principle for human high-order object areas. Neuron 34, 479–490 (2002).


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14. Hasson, U., Harel, M., Levy, I. & Malach, R. Large-scale mirror-symmetry organization of human occipito-temporal object areas. Neuron 37, 1027–1041 (2003). 15. Wade, A.R., Brewer, A.A., Rieger, J.W. & Wandell, B.A. Functional measurements of human ventral occipital cortex: retinotopy and colour. Phil. Trans. R. Soc. Lond. B 357, 963–973 (2002). 16. Tootell, R.B. & Hadjikhani, N. Where is ‘dorsal V4’ in human visual cortex? Retinotopic, topographic and functional evidence. Cereb. Cortex 11, 298–311 (2001). 17. Ejima, Y. et al. Interindividual and interspecies variations of the extrastriate visual cortex. Neuroreport 14, 1579–1583 (2003). 18. Baizer, J.S., Ungerleider, L.G. & Desimone, R. Organization of visual inputs to the inferior temporal and posterior parietal cortex in macaques. J. Neurosci. 11, 168–190 (1991). 19. Meadows, J. Disturbed perception of colours associated with localized cerebral lesions. Brain 97, 615–632 (1974). 20. Meadows, J.C. The anatomical basis of prosopagnosia. J. Neurol. Neurosurg. Psychiatry 37, 489–501 (1974). 21. Damasio, A., Yamada, T., Damasio, H., Corbett, J. & McKee, J. Central achromatopsia: behavioral, anatomic, and physiologic aspects. Neurology 30, 1064–1071 (1980). 22. Damasio, A.R., Damasio, H. & Van Hoesen, G.W. Prosopagnosia: anatomic basis and behavioral mechanisms. Neurology 32, 331–341 (1982). 23. James, T.W., Culham, J., Humphrey, G.K., Milner, A.D. & Goodale, M.A. Ventral occipital lesions impair object recognition but not object-directed grasping: an fMRI study. Brain 126, 2463–2475 (2003). 24. Gauthier, I., Skudlarski, P., Gore, J.C. & Anderson, A.W. Expertise for cars and birds recruits brain areas involved in face recognition. Nat. Neurosci. 3, 191–197 (2000). 25. Ishai, A., Ungerleider, L.G., Martin, A. & Haxby, J.V. The representation of objects in the human occipital and temporal cortex. J. Cogn. Neurosci. 12, 35–51 (2000). 26. Grill-Spector, K., Knouf, N. & Kanwisher, N. The fusiform face area subserves face perception, not generic within-category identification. Nat. Neurosci. 7, 555–562 (2004). 27. Kanwisher, N., McDermott, J. & Chun, M.M. The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci. 17, 4302–4311 (1997). 28. Grill-Spector, K. et al. Differential processing of objects under various viewing conditions in the human lateral occipital complex. Neuron 24, 187–203 (1999). 29. Epstein, R. & Kanwisher, N. A cortical representation of the local visual environment. Nature 392, 598–601 (1998). 30. Halgren, E. et al. Location of human face-selective cortex with respect to retinotopic areas. Hum. Brain Mapp. 7, 29–37 (1999). 31. Sasaki, Y. et al. Local and global attention are mapped retinotopically in human occipital cortex. Proc. Natl. Acad. Sci. USA 98, 2077–2082 (2001). 32. Kastner, S., De Weerd, P., Desimone, R. & Ungerleider, L.G. Mechanisms of directed attention in the human extrastriate cortex as revealed by functional MRI. Science 282, 108–111 (1998). 33. Gattass, R., Sousa, A.P. & Gross, C.G. Visuotopic organization and extent of V3 and V4 of the macaque. J. Neurosci. 8, 1831–1845 (1988). 34. Boussaoud, D., Desimone, R. & Ungerleider, L.G. Visual topography of area TEO in the macaque. J. Comp. Neurol. 306, 554–575 (1991). 35. Van Essen, D.C. Organization of visual areas in macaque and human cerebral cortex. in The Visual Neurosciences (eds. Chalupa, L.M. & Werner, J.S.) 507–521 (Bradford Books, Boston, 2003). 36. Rosa, M.G. & Tweedale, R. Brain maps, great and small: lessons from comparative studies of primate visual cortical organization. Phil. Trans. R. Soc. Lond. B 360, 665– 691 (2005). 37. Zeki, S. & Bartels, A. The clinical and functional measurement of cortical (in)activity in the visual brain, with special reference to the two subdivisions (V4 and V4 alpha) of the human colour centre. Phil. Trans. R. Soc. Lond. B 354, 1371–1382 (1999). 38. Beauchamp, M.S., Haxby, J.V., Jennings, J.E. & DeYoe, E.A. An fMRI version of the Farnsworth-Munsell 100-Hue test reveals multiple color-selective areas in human ventral occipitotemporal cortex. Cereb. Cortex 9, 257–263 (1999). 39. Zeki, S. et al. A direct demonstration of functional specialization in human visual cortex. J. Neurosci. 11, 641–649 (1991). 40. Wandell, B.A., Chial, S. & Backus, B. Visualization and measurement of the cortical surface. J. Cogn. Neurosci. 12, 739–752 (2000). 41. Wandell, B.A., El Gamal, A. & Girod, B. Common principles of image acquisition systems and biological vision. Proc. IEEE 90, 5–17 (2002). 42. Levy, I., Hasson, U., Harel, M. & Malach, R. Functional analysis of the periphery effect in human building related areas. Hum. Brain Mapp. 22, 15–26 (2004). 43. Brainard, D.H. & Colorimetry in Handbook of the Optical Society Vol. 1. (ed. Bass, M.) 26.1–26.54 (McGraw-Hill, New York, 1995). 44. Wandell, B.A. Foundations of Vision (Sinauer, Sunderland, MA,, 1995). 45. Glover, G.H. & Lai, S. Self-navigated spiral fMRI: interleaved versus single-shot. Magn. Reson. Med. 39, 361–368 (1998). 46. Glover, G.H. Simple analytic spiral K-space algorithm. Magn. Reson. Med. 42, 412–415 (1999). 47. Nestares, O. & Heeger, D.J. Robust multiresolution alignment of MRI brain volumes. Magn. Reson. Med. [In Process Citation] 43, 705–715 (2000). 48. Teo, P.C., Sapiro, G. & Wandell, B.A. Creating connected representations of cortical gray matter for functional MRI visualization. IEEE Trans. Med. Imaging 16, 852–863 (1997). 49. Wandell, B.A. Computational neuroimaging of human visual cortex. Annu. Rev. Neurosci. 22, 145–173 (1999). 50. Engel, S., Zhang, X. & Wandell, B. Colour tuning in human visual cortex measured with functional magnetic resonance imaging. Nature 388, 68–71 (1997).

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Erratum: Heterogeneity in synaptic transmission along a Drosophila larval motor axon Giovanna Guerrero, Dierk F Rieff, Gautam Agarwal, Robin W Ball, Alexander Borst, Corey S Goodman & Ehud Y Isacoff Nat. Neurosci., 8, 1188–1196 (2005)


In the version of this article initially published online, the second author’s name was misspelled. The correct spelling is Dierk F Reiff.

Erratum: Notch signaling in the mammalian central nervous system: insights from mouse mutants Keejung Yoon & Nicholas Gaiano Nat. Neurosci., 8, 709 – 715 (2005) The version of this article that was published contained typographical errors in some gene names. On page 710, in the right column, third paragraph, the fourth sentence should have read as follows: “That study examined the expression both of pathway components such as Hes1, Hes5 and Delta-like 1 (Dll1) and of early differentiation markers such as Math4A (also known as Neurog2), NeuroD and NSCL-1 (also known as Nhlh1).” The last sentence of that paragraph should have read as follows: “This notion is supported by previous findings that Hes1 can be upregulated in PC12 cells cultured in the growth factors NGF, FGF2 or EGF64 and in postnatal cerebellar granule cells cultured in Sonic hedgehog65.” The fourth and fifth sentences in the second paragraph, right column, on page 713 should have read as follows: “These studies found that Notch activation reduced neurite extension, but presumed signaling blockade (via expression of Numb, Numbl or Dx) could promote neurite extension. Subsequent studies have found that Numb deletion disrupts neuronal maturation in the developing cerebellum31, whereas deletion of Numb and Numbl disrupts axonal arborization in sensory ganglia in vivo32.” In addition, on page 712, in the right column, top line, the authors would like to revise the sentence to read as follows: “Third, several reports have identified ErbB2 as a Notch target that has a role during mammalian radial glial maintenance91,92.”

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Corrigendum: Visual field maps and stimulus selectivity in human ventral occipital cortex Alyssa A Brewer, Junjie Liu, Alex R Wade & Brian A Wandell Nat. Neurosci., 8, 1102-1109 (2005) The discussion section contains an incorrect citation. In the 3rd paragraph on page 1107, “Tootell et al. 16 (subsequent to Halgren et al.)” should read: “Tootell et al. 16 (subsequent to Hadjikhani et al.)”. The authors regret the error

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Stimulus context modulates competition in human extrastriate cortex Diane M Beck & Sabine Kastner When multiple stimuli appear simultaneously in the visual field, they are not processed independently, but rather interact in a mutually suppressive way, suggesting that they compete for neural representation in visual cortex. The biased competition model of selective attention predicts that the competition can be influenced by both top-down and bottom-up mechanisms. Directed attention has been shown to bias competition in favor of the attended stimulus in extrastriate cortex. Here, we show that suppressive interactions among multiple stimuli are eliminated in extrastriate cortex when they are presented in the context of pop-out displays, in which a single item differs from the others, but not in heterogeneous displays, in which all items differ from each other. The pop-out effects seemed to originate in early visual cortex and were independent of attentional top-down control, suggesting that stimulus context may provide a powerful influence on neural competition in human visual cortex.

Natural visual scenes are cluttered and contain many different objects that cannot all be processed at once due to the limited processing capacity of the visual system1, suggesting that multiple objects present at the same time in the visual field compete for neural representation2,3. Neural correlates for competitive interactions among multiple stimuli have been found in the visual cortex in single-cell physiology and functional brain imaging studies, showing that multiple stimuli presented in nearby locations are not processed independently from each other, but interact in a mutually suppressive way4–8. These sensory suppressive interactions occur most strongly at the level of the receptive field5,9 and are therefore prominent in extrastriate areas where receptive fields are large enough to encompass multiple stimuli4–8. According to the biased competition model of selective attention2,3,10, competition among multiple stimuli can be influenced both by top-down processes related to the selection of information that is relevant to current behavioral goals and by bottom-up, stimulusdriven processes. For example, if one directs attention to a particular location in a cluttered scene, processing of information at the attended location will be facilitated and processing of unwanted information from nearby irrelevant objects (distracters) will be suppressed11, suggesting that competition is biased in favor of the attended stimulus. On the other hand, if a salient stimulus is present in a cluttered scene, it will be effortlessly and quickly detected regardless of the number of distracters12, suggesting that competition is biased in favor of the salient stimulus. At the neural level, evidence in support of the biased competition model has been found in studies showing that spatially directing attention to one of multiple stimuli eliminates or reduces the suppressive influences of nearby stimuli in extrastriate cortical areas, consistent with the idea that selective attention biases the competition among multiple stimuli in favor of the attended stimulus

by counteracting suppressive interactions5–7,9,13. These mechanisms that operate in the visual cortex seem to be controlled by a distributed network of higher-order areas in frontal and parietal cortex, which generate top-down signals that are transmitted through feedback connections to the visual system14–16. Here, we asked how bottomup influences related to stimulus context of a visual display in which a single, salient stimulus pops out from a homogeneous background affect suppressive interactions among multiple stimuli competing for neural representation in human visual cortex using functional magnetic resonance imaging (fMRI). Unlike selective attention, which relies on top-down signals from frontoparietal sources14–16, a contextual effect like pop-out depends on factors present in the display, including simple feature properties such as the color of the stimulus12, perceptual grouping of stimulus features by Gestalt principles17–19 and the dissimilarity between the stimulus and nearby distracters20,21. Neural correlates of pop-out have been found as early as in area V1. Responses of V1 neurons to a single item presented in a receptive field surrounded by a homogeneous array of items presented outside the receptive field are stronger when the surround differs from the receptive field stimulus than when the two are identical22–24, suggesting that neural responses depend on the context in which the stimuli are shown. These context-dependent effects do not seem to rely on top-down control, as they are demonstrated in awake as well as anesthetized animals23,24. Here, we assessed suppressive interactions among multiple stimuli present at the same time in nearby locations across human visual cortex using two display types: pop-out displays, in which a single item differed from the others (Fig. 1a), and heterogeneous displays, in which all items differed from each other (Fig. 1b). We predicted that bottomup signals related to pop-out could weaken suppressive interactions

Department of Psychology and the Center for the Study of Brain, Mind, and Behavior, Princeton University, Green Hall, Princeton, New Jersey 08544, USA. Correspondence should be addressed to D.M.B. ([email protected]). Published online 10 July 2005; doi:10.1038/nn1501

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among stimuli appearing in the context of pop-out relative to heterogeneous displays, similar to the way in which top-down attention can counteract suppressive interactions among multiple stimuli5–7,9,13. However, in accordance with the biased competition theory, although neural signals related to the encoding of pop-out may originate early in the visual cortex, we predicted that these signals would affect the outcome of competitive interactions among multiple stimuli that typically take place in later extrastriate areas such as V2 and V4, where receptive fields are sufficiently large to encompass multiple stimuli4–8. RESULTS Four colored Gabor stimuli were presented in randomized order in four nearby locations within the upper right quadrant of the visual field under two presentation conditions: sequential and simultaneous. In the sequential condition, each of the stimuli was presented alone in one of the four locations (Fig. 1c). In the simultaneous condition, the stimuli appeared together in all four locations (Fig. 1d). Integrated over time, the physical stimulation parameters in each of the four locations were identical under the two presentation conditions. However, as shown previously7,8, suppressive interactions among the stimuli could take place only in the simultaneous, but not in the sequential, presentation condition. The influence of pop-out on competitively interacting stimuli was studied by probing two different display type conditions, heterogeneous and pop-out, in addition to the sequential and simultaneous presentation conditions. In the heterogeneous display condition, all four stimuli differed in orientation and color (Fig. 1b). In the pop-out display condition, one stimulus differed in color and orientation from the other three (Fig. 1a). The display type conditions were equated such that, integrated over time, the physical stimulation parameters in each location were identical, and only the context in which the four stimuli were presented was varied. The subject’s task was to detect target letters presented in a rapid stream of letters, digits and keyboard symbols at fixation during all conditions. The fixation task ensured proper fixation and effectively prevented subjects from covertly attending to the peripheral stimuli. Two versions of the fixation task were tested in the fMRI experiments: one in which subjects (n ¼ 6) made no overt motor response and simply counted the number of targets; and one in which subjects (n ¼ 6) pressed a button as soon as they detected a target letter. These two experiments yielded very similar


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results (Supplementary Fig. 1 online); therefore, the data from the two experiments were combined for the following fMRI analyses. Gabor stimuli, compared with blank presentations, evoked significant activity in areas V1, V2, VP and V4 in all subjects, as determined on the basis of retinotopic mapping. As the border between V2 and VP could not be distinguished unequivocally in some of the subjects, the two areas were combined for all analyses. The locations of the activations were in the ventral parts of these areas in the left hemisphere, consistent with the locations of stimuli in the upper right visual field. Experiment 1: heterogeneous versus pop-out displays For the heterogeneous display condition, we predicted that the fMRI signals evoked by simultaneously presented stimuli would be smaller than those evoked by sequentially presented stimuli in the extrastriate cortex due to the mutual suppression induced by competitively interacting stimuli7,8. In support of our hypothesis, an analysis of the fMRI time series and the mean signal changes averaged across all subjects showed that simultaneous presentations evoked less response than sequential presentations in areas V2/VP and V4 (V2/VP, t9 ¼ 5.33, P o 0.001; V4, t9 ¼ 6.98, P o 0.001; Figs. 2a and 3a). The difference in activations between sequential and simultaneous presentations increased gradually from V1 to V4 (interaction of area and presentation condition: F2,18 ¼ 30.37, P o 0.001); response differences in area V1 were not significant (t o 1). This effect is also reflected in the sensory suppression index (SSI), which quantifies the differences in responses to sequential and simultaneous presentations (main effect of area on SSI for heterogeneous display type (SSIHet), F2,18 ¼ 43.89, P o 0.001;

a

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Figure 1 Experimental design and stimuli. Four Gabor stimuli were presented in four nearby locations in the periphery of the upper right quadrant as popout displays (a), in which a single item differed in color and orientation from the others, or heterogeneous displays (b), in which all four stimuli differed in color and orientation. These stimuli were presented either sequentially (c) or simultaneously (d). (c,d) A stimulation period of 1 s, which was repeated in blocks of 18 s, is shown for a heterogeneous display. Stimuli were presented for 250 ms, followed by a blank period of 750 ms, on average, in each location. During all conditions, subjects detected target letters at fixation (illustrated in lower left corner of each display).

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Figure 2 Time series of fMRI signals in visual cortex (experiment 1). Group analysis (n ¼ 10). Solid curves indicate activity evoked by sequential (Seq) presentations and dashed curves indicate activity evoked by simultaneous (Sim) presentations for heterogeneous displays (a) and pop-out displays (b).

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ARTICLES the effects on suppressive interactions obtained with pop-out displays were due to 0.1 the salient item, the surrounding homoge* * neous items or a combination of both. We * * * carried out a second experiment in which * pop-out displays were compared with homogeneous displays instead of heterogeneous 0.0 displays. Neither pop-out nor homogeneous displays induced a significant suppression effect in areas V1, V2/VP or V4, suggesting that the homogeneous surround did indeed –0.1 0.5 V1 V2/VP V4 V1 V2/VP V4 contribute to the weaker sensory suppression found with the pop-out displays. This result is Figure 3 Mean signal changes and SSIs in visual cortex (experiment 1). (a) Mean signal changes for each compatible with predictions from biased area and each of the four conditions were averaged across subjects (n ¼ 10). For each subject, mean competition theory2 and from behavioral signal change was defined as the average of the nine peak intensities of the fMRI signal obtained during data19,20, suggesting that competitive interacvisual presentations. *, significantly different, P o 0.05. (b) SSIs were derived from the data shown in a. tions should occur between rather than within Vertical bars indicate s.e.m. Het, heterogeneous; Pop, pop-out; Seq, sequential; Sim, simultaneous. perceptual groups. However, simultaneous pop-out displays evoked significantly more V1 versus V2/VP, t9 ¼ 6.46, P o 0.001; V2/VP versus V4, t9 ¼ 2.64, activity than simultaneous homogenous displays in area V4 (t5 ¼ P o 0.05). The gradual increase in magnitude of the SSIHet from V1 to 2.68, P o 0.05; Fig. 4), indicating that the neural responses evoked by V4 (Fig. 3b) suggests that suppressive interactions were scaled to the pop-out displays were not driven entirely by the homogeneous surincreasing receptive field sizes of neurons in areas along the ventral round, but also depended on the presence of the salient stimulus in the display. This result renders it unlikely that the observed stimulus visual pathway in accordance with previous results7,8. For the pop-out display condition, we predicted that the differences display effects on suppressive interactions resulted from the relative in responses evoked by sequential and simultaneous presentations homogeneity or heterogeneity of the displays. According to such an would be smaller than those obtained with the heterogeneous displays account, one would predict the pop-out displays (containing two item due to a presumed bottom-up contextual effect related to pop-out. In types) to produce a suppressive effect somewhere in between those support of our hypothesis, a repeated measures analysis of variance produced by the homogeneous and heterogeneous displays. Yet this (ANOVA) revealed a significant interaction of presentation (sequential was not the case. A similar pattern of results was observed in areas versus simultaneous) and display type condition (pop-out versus V2/VP, but the difference was not significant. These findings suggest heterogeneous) in areas V2/VP (F1,9 ¼ 18.34, P o 0.01) and V4 that the effects on sensory suppression associated with pop-out displays (F1,9 ¼ 18.63, P o 0.01), such that the response differences evoked by were a function of both the salient item and the surrounding homosequential and simultaneous presentations were indeed smaller for geneous items in the display, consistent with the fact that pop-out is a pop-out displays than for heterogeneous displays (Figs. 2 and 3a). In contextual effect, and the perceptual salience of an item is determined fact, in areas V2/VP and V4, there was no significant difference between by the surrounding items in the display. activity evoked by simultaneous and sequential presentations in the pop-out condition (Fig. 2b). The interaction of presentation and Bottom-up versus top-down modulation display type condition can be seen most clearly in comparing the SSI Thus far, we have presented evidence that pop-out displays induced less computed for heterogeneous and pop-out display conditions (Fig. 3b), sensory suppression among multiple competing stimuli than did which differed significantly in areas V1 (t9 ¼ 2.35, P o 0.05), V2/VP heterogeneous displays in extrastriate cortex and that both the salient (t9 ¼ 3.97, P o 0.01) and V4 (t9 ¼ 5.03, P o 0.001). Indeed, in V2/VP item and the surrounding items contributed to this effect. Because the and V4, the SSI for the pop-out display type (SSIPop) was not different from zero. In V1, the SSIPop was significantly different from zero Hom seq Pop seq (t9 ¼ 3.75, P o 0.01), but it was reversed (negative), indicating that Hom sim Pop sim simultaneous presentations evoked more activity than sequential pre* sentations (Fig. 3b). The reversal of the presentation condition effect 2.0 with the pop-out, but not with the heterogeneous display condition, is consistent with single-cell physiology studies showing that neural correlates of pop-out can be found as early as in area V1 (refs. 22–24). Indeed, such a result is suggestive that V1 may be the source of the signal that modulates the suppressive interactions among multiple stimuli at subsequent stages of processing, consistent with the idea that competitive interactions in extrastriate cortex can be modulated by stimulus context in a bottom-up manner. Pop seq

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Experiment 2: homogeneous versus pop-out displays Due to the spatial resolution limits of fMRI, we were unable to isolate the activity of any one item in the display. Instead, the activity evoked in the pop-out condition represents the summed activity evoked by all items in the display integrated over time. Therefore, we asked whether

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Figure 4 Mean signal changes in visual cortex (experiment 2). Mean signal changes, defined as described in Fig. 3, were averaged across subjects (n ¼ 6) for each presentation condition of the homogeneous and pop-out displays. *, significantly different, P o 0.05.

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500 (21) 493 (20)

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503 (17) 501 (20)

13 (1) 11 (1)

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subject’s attention was engaged in a demanding task at fixation, this effect on sensory suppression presumably occurred in a stimulusdriven, or bottom-up, fashion. However, it is possible that pop-out displays captured attention25 more than the heterogeneous displays, which would imply that the effects were mediated by top-down rather than bottom-up factors related to visual salience. This issue was addressed in two ways. First, we assessed whether performance on the fixation task differed as a function of the peripheral stimulus condition. If attention was drawn to the pop-out displays and away from the fixation task, then performance on the fixation task should be worse during the pop-out condition than during the other conditions. Second, we compared activity evoked by simultaneously presented pop-out and heterogeneous displays to identify brain regions outside the visual cortex that were more activated during the pop-out display than the heterogeneous display condition across subjects. If attention was disproportionately captured by the pop-out displays, then we might expect this comparison to result in greater activation in parietal areas associated with attentional capture26–28 or spatial shifts of attention15,16. Behavioral data were acquired in the scanner by requiring subjects to press a button upon detection of a target letter at fixation. Subjects missed 13% of the targets on average, but no differences in misses across the four block types were obtained (F3,12 ¼ 1.30, nonsignificant; Table 1). An analysis of subjects’ reaction times to correctly detected targets also showed no differences across the four block types (F3,12 ¼ 1.39, nonsignificant; Table 1). Because the simultaneous heterogeneous and simultaneous pop-out conditions evoked different neural responses in the fMRI experiment, behavioral performance in these conditions was of particular interest. There were no differences in miss rates or reaction times between these two conditions (t4 ¼ 0.14, nonsignificant, t4 ¼ 1.77, nonsignificant, respectively). Thus, the behavioral results did not support the idea that the pop-out displays attracted more attention than the heterogeneous displays. A similar conclusion can be drawn from the fMRI data analyses of parietal areas. Using the same statistical procedures applied to identify visual areas, a comparison of simultaneous pop-out and simultaneous heterogeneous displays did not demonstrate any significantly activated voxels anywhere in the parietal cortex, including the superior parietal Figure 5 Effects of pop-out and directed attention on suppressive interactions in human visual cortex. SSIs obtained for areas V1, V2/VP and V4 are plotted for the current study, probing bottom-up effects of pop-out on suppressive interactions (open symbols), and for a previous study that probed the top-down effects of directed attention on suppressive interactions7 (filled symbols). The horizontal axis represents the SSIs obtained for heterogeneous display conditions from the two studies, when the peripheral stimuli were unattended. The vertical axis represents the SSIs obtained for the pop-out display condition from the present study and the directed attention condition from the previous study7 to directly compare the top-down and bottom-up effects on suppressive interactions. The dashed line represents the points at which the two indices are equal, indicating no modulation of suppressive interactions by top-down or bottom-up influences.


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areas or the temporal parietal junction, which have been previously associated with attentional capture and spatial shifts of attention15,16,26–28. Moreover, a group analysis of the six subjects who were tested in the version of the fixation task requiring motor responses did not show any significant parietal activity (Supplementary Methods). Together, our results from behavioral and fMRI studies suggest that the effects on sensory suppression observed for pop-out displays was not mediated by top-down processes but instead reflected a bottom-up effect of stimulus context related to visual salience. Finally, we directly compared the top-down effects on sensory suppression described previously7 with the bottom-up effects found here by plotting the SSIs from both studies (Fig. 5). In both studies, sensory suppression among four heterogeneous stimuli was assessed across the visual cortex when attention was directed away from the display (Fig. 5, horizontal axis) and in the presence of either a top-down or a bottom-up factor (attention or pop-out, respectively; Fig. 5, vertical axis). The SSIs from both studies fall below the dashed line in Figure 5, indicating that both pop-out and directed attention conditions led to weaker suppressive interactions relative to the unattended condition. The data probing top-down effects on sensory suppression all fall significantly above zero on the vertical axis, indicating that some suppressive interactions remained when attention was directed to a stimulus and that competition was not fully resolved by directed attention. The data from our study fall on or below zero, consistent with the possibility that competitive interactions were eliminated with the pop-out displays. However, it should be noted that this difference is only suggestive because the data from the attention study7 also fall to the right of the data from our study, indicating that the complex stimuli used in that study induced stronger suppressive interactions than those induced by the simpler Gabor stimuli used here. In accord with the central tenets of biased competition theory, this comparison suggests that the competition among multiple stimuli for neural representation can be influenced by means of both bottom-up and top-down mechanisms operating at intermediate processing stages of human visual cortex. DISCUSSION Here we have reported evidence for modulation of competitive interactions among multiple stimuli by stimulus context in the human extrastriate cortex. Sensory suppression among multiple stimuli was observed in areas V2/VP and V4 when the stimuli were presented in the context of heterogeneous displays, in accordance with previous studies7,8, but was eliminated when the same stimuli were presented in the context of pop-out displays.

V1 attend V1 pop-out V2/VP attend V2/VP pop-out

SSI: attend/pop-out

Table 1 Error rates and reaction times for behavioral letter detection tasks (n ¼ 5)

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SSI: heterogeneous

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ARTICLES Our results complement previous studies suggesting that sensory suppressive interactions reflect competition among multiple stimuli for neural representation, using the same experimental procedure of sequential and simultaneous stimulus presentations. As in previous studies7,8, the suppressive interactions obtained in the heterogeneous display condition increased gradually from V1 to V4, suggesting that they were scaled to the increasing receptive field size of neurons in these areas, and supporting the notion that suppressive interactions among multiple stimuli occur most strongly at the level of the receptive field. This idea is further corroborated by previous findings that when the spatial separation among the competing stimuli is increased, suppressive interactions are found in more anterior extrastriate areas with larger receptive fields8. The effects of spatial separation on the outcome of competitive interactions, together with the effects of display type found in our study, rule out the possibility that fewer stimulus onsets in the simultaneous versus sequential presentation condition might account for the smaller activity evoked by simultaneously presented heterogeneous displays. Suppressive interactions among multiple stimuli depend either on the distance between the stimuli8 or on the context (that is, display type) in which the stimuli appeared, despite the fact that the relative number of onsets was unchanged. These findings are consistent with the predictions that competition among multiple stimuli for neural representation can be affected by several factors including the spatial layout of stimuli in a display and the context of stimulus presentations. Our findings constitute important evidence in support of the biased competition model of selective visual attention, which postulates that competitive interactions among multiple stimuli for neural representation can be biased by not only top-down allocation of attention, but also bottom-up, stimulus-driven influences. Evidence for top-down modulation of competitive interactions has been provided by singlecell physiology5,6,9,13 and functional brain-imaging studies7 in which directing attention to one of multiple heterogeneous stimuli presented at the same time results in weaker suppressive interactions in areas V4 and TEO, relative to a condition in which the same stimuli are unattended. Here, we have demonstrated a similar effect on suppressive interactions among multiple simultaneously presented stimuli that occurred when attention was directed away from the peripheral stimuli and instead stimulus context rendered one of the stimuli salient. This context-dependent effect eliminated suppressive interactions among the stimuli in extrastriate cortex. These findings suggest that both topdown mechanisms related to spatially selective attention and bottomup mechanisms related to stimulus context operate by resolving competitive interactions at intermediate processing stages in visual cortex, although in keeping with single-cell recording22–24 and computational models29 of pop-out it seems that these stimulus context effects may have their origin in early visual cortex. It should be noted that, given the spatial resolution of fMRI, it is possible that our results obtained with the pop-out displays were the sum of two separate neural processes generated within the same area (for example, V4) but from different subpopulations of neurons that did not interact with each other: one subpopulation coding suppressive interactions due to the ongoing competition among the stimuli and another subpopulation coding signals related to pop-out. It is possible, for example, that the reduction of suppression depended entirely on the homogeneous surround and that the increased activity associated with the pop-out displays simply reflected a separate but additive influence of visual salience. However, there is evidence for an interaction of visual salience and competitive processes at the level of single neurons30 that is consistent with the interpretation that competitive interactions may depend on the entire display, including the salient item. Suppressive

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interactions in V4 neurons are biased toward the more salient (highcontrast) of a pair of stimuli presented in the receptive field of the neuron. Such a conception is also consistent with winner-take-all models of visual salience31, in which the more salient stimulus dominates neural responses and thereby wins the competition. We considered the possibility that the effects on sensory suppression demonstrated with pop-out displays were mediated to some degree by spatially directed attention, given that several models of pop-out have assumed that attention is automatically directed to salient objects in the visual field28,32,33. Although visually salient items do not necessarily capture attention34, it is possible that attention was captured to a greater degree by the pop-out displays than by the heterogeneous displays in our study. If so, the effects on suppressive interactions among the stimuli were not mediated by the context of the display but rather by directed attention, similar to those found previously7. However, our behavioral data and additional analyses of the fMRI data did not favor such an interpretation. There was no effect of display type on the ability of subjects to rapidly detect target letters, suggesting that the different display types did not differ in their ability to capture attention. Simultaneously presented pop-out displays evoked no more activity than heterogeneous displays in regions of the parietal cortex known to be activated by displays capturing attention26–28 or by spatial shifts of attention15,16. Finally, the contextual effects of pop-out on sensory suppression seemed to be stronger than the top-down influences of directed attention (Fig. 5), making it unlikely that the effects observed with the pop-out displays resulted from some small misdirection of attention to the salient stimuli that we were unable to detect in our behavioral studies. Unlike the pop-out displays, directed attention reduces, but does not eliminate, the suppression induced by nearby stimuli7. Rather, it seems that pop-out is a powerful bottom-up process that overcomes competitive interactions among multiple stimuli for neural representation and operates independently of attentional topdown control, consistent with the classical notion that visual salience is processed in a preattentive mode35. The conception of pop-out as a similar but separate mechanism from top-down attention for modulating competitive interactions among multiple stimuli at intermediate processing stages is in agreement with lesion studies in humans and monkeys. A human subject with an isolated V4 lesion36 and monkeys with lesions of areas V4 and TEO show discrimination deficits when targets must be selected among distracters37, suggesting that the filtering mechanisms associated with top-down attention may critically depend on the integrity of extrastriate areas such as V4. Notably, however, the deficit associated with V4 lesions can be ameliorated by increasing the salience of the target stimulus36–38, suggesting that visual salience constitutes a separate filtering mechanism than the one mediated by top-down signals from attention. Although subjects’ attention was drawn away from the peripheral stimuli and engaged in a demanding task at fixation, under natural viewing conditions bottom-up and top-down mechanisms are free to interact, allowing the biasing mechanisms to reinforce each other39–41. Moreover, visual salience may be just one example of several bottomup contextual effects instrumental in scene segmentation and guiding attention to object-based selections17,18,42–44 that may influence competition for neural representation in visual cortex. METHODS Subjects, visual stimuli and experimental design. In all, 12 subjects (seven females; aged 21–34 years; normal or corrected-to-normal visual acuity) gave informed written consent for participation in the study, which was approved by the Institutional Review Panel of Princeton University.

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ARTICLES Visual stimuli were four Gabor patches (wavelength, 0.471; s.d. of Gaussian envelope, 0.731; each approximately 2 21 in size) presented in four nearby locations (2.51 from the center of one Gabor to its nearest neighbor) in the upper right quadrant of the visual field, with the Gabor closest to and furthest from fixation centered at 9.51 and 13.51 from fixation, respectively. The stimuli were red, blue, green or cyan and had an orientation of 01 (vertical), 601, 901 (horizontal) and 1501, respectively (Fig. 1). All stimuli were presented on a dark background. Stimuli were generated on a Power Mac G4 using Matlab software (Mathworks) and the Psychophysical Toolbox45. The stimuli were shown under two presentation conditions: sequential and simultaneous. In the sequential presentation condition, each of the four Gabor stimuli was shown alone in one of the four locations for 250 ms (Fig. 1c). In the simultaneous presentation condition, the same four stimuli appeared together for 250 ms (Fig. 1d). The order of stimuli and of locations was randomized. Stimulation periods (Fig. 1c,d) were repeated in blocks of 18 s. Integrated over time, the physical stimulation parameters in each of the four locations were identical for sequential and simultaneous presentations. In addition to the two presentation conditions, two display type conditions were probed in the main scanning experiment: heterogeneous and pop-out. In the heterogeneous display condition, all four stimuli differed in both orientation and color (Fig. 1b). In the pop-out display condition, three of the stimuli were identical, and the fourth differed in both orientation and color from the others (Fig. 1a). However, in both display type conditions, the same colors and orientations occurred with equal probability in each location, so that integrated across presentation blocks, the stimulation parameters in each location were identical for pop-out and heterogeneous display conditions, and only the context in which the stimuli appeared changed. Specifically, a particular Gabor stimulus (for example, green-horizontal; Fig. 1a,b) was designated the singleton in the pop-out displays throughout a block, and that singleton was presented in the exact same locations as the identical item (for example, green-horizontal) in a heterogeneous display block from the same scanning run. For each display within a pop-out presentation block, the homogeneous surround was drawn at random from the remaining three colors, with the constraint that each of the three colors was presented exactly six times in a block. The remaining three colors in the heterogeneous displays were also presented randomly in each of the remaining three locations. During a given scan, presentation (sequential versus simultaneous) and display type conditions (pop-up versus heterogeneous) were combined to produce four blocks of visual stimulation (sequential pop-up, sequential heterogeneous, simultaneous pop-up, simultaneous heterogeneous) that were interleaved with blank periods of 18 s each. Each scan began with a block of visual stimulation that was discarded from further analysis and ended with a blank period of 18 s for an overall scan duration of 180 s. Presentation conditions were presented in the sequence sequential-simultaneous-simultaneous-sequential, with the sequence of display type conditions counterbalanced across scans. Subjects were engaged in detecting target letters presented in a rapid stream (4 Hz) of letters, digits and keyboard symbols (720 per scan; 0.5 deg in size) presented at fixation for 250 ms each. Because it has been shown that motor responses can modulate activity in the occipital cortex46, the experiment was undertaken with two versions of the letter detection task. In one, subjects (n ¼ 6) made no overt motor response and simply counted the number of targets (presented at random with a 17.6% probability), reporting the number at the end of the scan. In the second, subjects (n ¼ 6) pressed a button as quickly as possible whenever they detected a target letter, which appeared in 20% of the trials. In this version of the experiment, half of the target letters appeared synchronously with the simultaneous displays and half appeared in the intervening intervals between simultaneous displays but during a simultaneous block. These two versions of the experiment yielded very similar fMRI results (Supplementary Fig. 1); therefore, the fMRI data were combined, yielding ten data sets, as two subjects participated in both versions of the experiment. Before being scanned, subjects participated in a training session outside the scanner to ensure that they were able to perform the tasks while maintaining fixation for several minutes. Experiment 2 compared the pop-out display condition used in experiment 1 with a homogeneous display condition. In the homogeneous display condition,


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four identical stimuli were presented in each of the four locations. Display conditions were equated such that, integrated over time, physical stimulation parameters were identical in pop-out and homogeneous display type conditions and, as in the main experiment, only the context of the four stimuli was varied. Visual stimuli and experimental design were as described for the counting version of experiment 1 except for the length of visual presentation blocks, which were 12 s, and that of the interleaved blank periods, which were 16 s. Data acquisition and analysis. Data were acquired in 18 scan sessions with a 3-T head scanner (Allegra, Siemens) using a standard head coil. In addition, retinotopic mapping was performed for all subjects in a separate scan session. Functional images were taken with a gradient echo, echoplanar sequence (TR ¼ 2s; TE ¼ 30 ms; flip angle ¼ 901; matrix: 64 64). Twenty coronal slices were acquired in an interleaved fashion starting from the posterior pole (3 mm thickness, 1 mm gap, 2.5 2.5 mm in-plane resolution) in 12 series of 90 images each. Echoplanar images were compared with a coaligned, high-resolution anatomical scan of the same partial brain volume (FLASH; TR ¼ 184 ms; TE ¼ 4.6 ms, flip angle ¼ 901; matrix, 256 256; field of view, 160 160 mm) for scan sessions testing the counting version of the fixation task and with a high-resolution anatomical scan of the whole brain (MPRAGE; TR ¼ 2.5 s; TE ¼ 4.38 ms, flip angle ¼ 81; matrix, 256 256; field of view, 256 256 mm) for scan sessions testing the motor response version of the fixation task. Functional images were motion-corrected47. The US National Institutes of Health functional imaging data analysis program (FIDAP) software was used to perform a multiple regression48. Square-wave functions matching the time course of the experimental design contrasted (i) visual stimulation versus blank periods and (ii) sequential versus simultaneous presentations. These squarewave functions were convolved with a Gaussian model of the hemodynamic response (lag, 4.8 s; dispersion, 1.8 s) to generate idealized response functions, which were used as regressors in the multiple regression model. Additional regressors were included in the model to factor out between-run changes in mean intensity and within-run linear drifts. Statistical maps were thresholded at a Z-score of 2.33 (P o 0.01, corrected for multiple comparisons). Activated voxels in visual cortex obtained during visual stimulation versus blank periods were subsequently assigned to retinotopically organized areas. For each subject, mean signals were computed by averaging across peak intensity values obtained in a given condition and visual area and are given as percentage signal change, which was computed relative to the mean signal obtained during blank presentations. These values were further quantified by defining a sensory suppression index (SSI ¼ (RSeq RSim) / (RSeq + RSim); R, response computed as mean signal change; Seq, sequential presentation condition; Sim, simultaneous presentation condition), which was computed separately for the different display type conditions (SSIHet, SSIPop). The SSI quantifies the differences in responses to sequential and simultaneous presentations. Positive values indicate stronger responses to sequential than to simultaneous presentations; negative values indicate the opposite, and values around 0 indicate the absence of response differences. Statistical significance of SSIs and mean signal changes were assessed using repeated measures ANOVAs and paired t-tests with the subject as the random variable. To investigate whether regions in the parietal cortex were differentially activated by the pop-out or heterogeneous displays, both individual subject and group analyses were carried out by comparing activity evoked by simultaneous pop-out and simultaneous heterogeneous displays using AFNI (http://afni. nimh.nih.gov/afni; Supplementary Methods). Mapping visual areas. Retinotopic mapping was carried out for each subject in a separate scanning session using established procedures49 and was used to assign activated voxels to visual areas (Supplementary Methods). Behavioral data analysis. Reaction times to correctly identify targets by means of a button press in the scanner were computed relative to the onset of the target stimulus as a function of block type for each subject. Correct responses were defined as responses occurring between 250 and 1,000 ms after the onset of the target. The reaction time analysis was restricted to the four counterbalanced visual stimulation blocks from each run (that is, the first visual stimulation block and blank blocks were excluded from each run). In one

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ARTICLES subject, detections were likely overestimated due to a computer error. Consequently, the data from this subject were excluded from further analysis. Note: Supplementary information is available on the Nature Neuroscience website.


ACKNOWLEDGMENTS We thank A. Treisman and H.-C. Nothdurft for discussions. This work was supported by grants from the US National Institute of Mental Health (RO1 MH-64043, P50 MH-62196) and the Whitehall Foundation. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 16 May; accepted 21 June 2005 Published online at http://www.nature.com/natureneuroscience/ 1. Broadbent, D.E. Perception and Communication (Pergamon, London, 1958). 2. Desimone, R. & Duncan, J. Neural mechanisms of selective visual attention. Annu. Rev. Neurosci. 18, 193–222 (1995). 3. Duncan, J. Converging levels of analysis in the cognitive neuroscience of visual attention. Phil. Trans. R. Soc. Lond. B 353, 1307–1317 (1998). 4. Miller, E.K., Gochin, P.M. & Gross, C.G. Suppression of visual responses of neurons in inferior temporal cortex of the awake macaque by addition of a second stimulus. Brain Res. 616, 25–29 (1993). 5. Reynolds, J.H., Chelazzi, L. & Desimone, R. Competitive mechanisms subserve attention in macaque areas V2 and V4. J. Neurosci. 19, 1736–1753 (1999). 6. Recanzone, G.H. & Wurtz, R.H. Effects of attention on MT and MST neuronal activity during pursuit initiation. J. Neurophysiol. 83, 777–790 (2000). 7. Kastner, S., De Weerd, P., Desimone, R. & Ungerleider, L.G. Mechanisms of directed attention in the human extrastriate cortex as revealed by functional MRI. Science 282, 108–111 (1998). 8. Kastner, S. et al. Modulation of sensory suppression: Implications for receptive field sizes in the human visual cortex. J. Neurophysiol. 86, 1398–1411 (2001). 9. Moran, J. & Desimone, R. Selective attention gates visual processing in the extrastriate cortex. Science 229, 782–784 (1985). 10. Bundesen, C. A theory of visual attention. Psychol. Res. 97, 523–547 (1990). 11. Posner, M.I. Orienting of attention. Q. J. Exp. Psychol. 32, 3–25 (1980). 12. Treisman, A.M. & Gelade, G. A feature-integration theory of attention. Cognit. Psychol. 12, 97–136 (1980). 13. Luck, S.J., Chelazzi, L., Hillyard, S.A. & Desimone, R. Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex. J. Neurophysiol. 77, 24–42 (1997). 14. Kastner, S., Pinsk, M.A., De Weerd, P., Desimone, R. & Ungerleider, L.G. Increased activity in human visual cortex during directed attention in the absence of visual stimulation. Neuron 22, 751–761 (1999). 15. Kastner, S. & Ungerleider, L.G. The neural basis of biased competition in the human visual cortex. Neuropsychologia 39, 1263–1276 (2001). 16. Corbetta, M. & Shulman, G.L. Control of goal-directed and stimulus-driven attention in the brain. Nat. Rev. Neurosci. 3, 201–215 (2002). 17. Driver, J. & Baylis, G.C. Movement and visual attention: the spotlight metaphor breaks down. J. Exp. Psychol. Hum. Percept. Perform. 15, 448–456 (1989). 18. Duncan, J. Selective attention and the organization of visual information. J. Exp. Psychol. Gen. 113, 501–517 (1984). 19. Bundesen, C. & Pedersen, L.F. Color segregation and visual search. Percept. Psychophys. 33, 487–493 (1983). 20. Duncan, J. & Humphreys, G.W. Visual search and stimulus similarity. Psychol. Rev. 96, 433–458 (1989). 21. Nothdurft, H.C. The role of features in preattentive vision: comparison of orientation, motion, and color cues. Vision Res. 33, 1937–1958 (1993).

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22. Knierim, J.J. & Van Essen, D.C. Neuronal responses to static texture patterns in area V1 of the alert macaque monkey. J. Neurophysiol. 67, 961–980 (1992). 23. Nothdurft, H.C., Gallant, J.L. & Van Essen, D.C. Response modulation by texture surround in primate area V1: Correlates of ‘‘popout’’ under anesthesia. Vis. Neurosci. 16, 15–34 (1999). 24. Kastner, S., Nothdurft, H.C. & Pigarev, I. Neuronal responses to motion and orientation contrast in cat striate cortex. Vis. Neurosci. 16, 587–600 (1999). 25. Yantis, S. Goal-directed and stimulus-driven determinants of attentional control. in Attention and Performance XVIII (eds. Monsell, S. & Driver, J.) 73–103 (MIT Press, Cambridge, Massachusetts, 2000). 26. de Fockert, J.W., Rees, G., Frith, C. & Lavie, N. Neural correlates of attentional capture in visual search. J. Cogn. Neurosci. 16, 751–759 (2004). 27. Corbetta, M., Kincade, J.M., Ollinger, J.M., McAvoy, M.P. & Shulman, G.L. Voluntary orienting is dissociated from target detection in human posterior parietal cortex. Nat. Neurosci. 3, 292–297 (2000). 28. Constantinidis, C. & Steinmetz, M.A. Posterior parietal cortex automatically encodes the location of salient stimuli. J. Neurosci. 25, 233–238 (2005). 29. Li, Z. Contextual influences in V1 as a basis for pop-out and asymmetry in visual search. Proc. Natl. Acad. Sci. USA 96, 10530–10535 (1999). 30. Reynolds, J.H. & Desimone, R. Interacting roles of attention and visual salience in V4. Neuron 37, 853–863 (2003). 31. Itti, L. & Koch, C. Computational modeling of visual attention. Nat. Rev. Neurosci. 2, 194–203 (2001). 32. Cave, K. & Wolfe, J. Modeling the role of parallel processing in visual search. Cognit. Psychol. 22, 225–271 (1990). 33. Koch, C. & Ullman, S. Shifts in selective visual attention: towards the underlying neural circuitry. Hum. Neurobiol. 4, 219–227 (1985). 34. Yantis, S. & Egeth, H.E. On the distinction between visual salience and stimulusdriven attentional capture. J. Exp. Psychol. Hum. Percept. Perform. 25, 661–676 (1999). 35. Neisser, U. Cognitive Psychology (Appleton-Century-Crofts, New York, 1967). 36. Gallant, J.L., Shoup, R.E. & Mazer, J.A. A human extrastriate area functionally homologous to macaque V4. Neuron 27, 227–235 (2000). 37. De Weerd, P., Peralta, M.R., III, Desimone, R. & Ungerleider, L.G. Loss of attentional stimulus selection after extrastriate cortical lesions in macaques. Nat. Neurosci. 2, 753–758 (1999). 38. Schiller, P.H. & Lee, K. The role of the primate extrastriate area V4 in vision. Science 251, 1251–1253 (1991). 39. Wolfe, J.M., Cave, K.R. & Franzel, S.L. Guided search: an alternative to the feature integration model for visual search. J. Exp. Psychol. Hum. Percept. Perform. 15, 419– 433 (1989). 40. Ogawa, T. & Komatsu, H. Target selection in area V4 during a multidimensional visual search task. J. Neurosci. 24, 6371–6382 (2004). 41. Carrasco, M., Ling, S. & Read, S. Attention alters appearance. Nat. Neurosci. 7, 308– 313 (2004). 42. Kahneman, D. & Henik, A. Perceptual organization and attention. in Perceptual Organization (eds. Kubovy, M. & Pomerantz, J.R.) 181–211 (Erlbaum, Hillsdale, New Jersey, 1981). 43. Banks, W.P. & Prinzmetal, W. Configurational effects in visual information processing. Percept. Psychophys. 19, 361–367 (1976). 44. Driver, J., Baylis, G.C. & Rafal, R.D. Preserved figure-ground segregation and symmetry perception in visual neglect. Nature 360, 73–75 (1992). 45. Brainard, D.H. The psychophysics toolbox. Spat. Vis. 10, 433–436 (1997). 46. Astafiev, S.V., Stanley, C.M., Shulman, G.L. & Corbetta, M. Extrastriate body area in human occipital cortex responds to performance of motor actions. Nat. Neurosci. 7, 542–548 (2004). 47. Woods, R.P., Mazziotta, J.C. & Cherry, S.R. MRI-PET registration with automated algorithm. J. Comput. Assist. Tomogr. 17, 536–546 (1993). 48. Friston, K.J. et al. Analysis of fMRI time-series revisted. Neuroimage 2, 45–53 (1995). 49. Sereno, M.I. et al. Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science 268, 889–893 (1995).

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Probabilistic word pre-activation during language comprehension inferred from electrical brain activity Katherine A DeLong1, Thomas P Urbach1 & Marta Kutas1,2 Despite the numerous examples of anticipatory cognitive processes at micro and macro levels in many animal species, the idea that anticipation of specific words plays an integral role in real-time language processing has been contentious. Here we exploited a phonological regularity of English indefinite articles (‘an’ precedes nouns beginning with vowel sounds, whereas ‘a’ precedes nouns beginning with consonant sounds) in combination with event-related brain potential recordings from the human scalp to show that readers’ brains can pre-activate individual words in a graded fashion to a degree that can be estimated from the probability that each word is given as a continuation for a sentence fragment offline. These findings are evidence that readers use the words in a sentence (as cues to their world knowledge) to estimate relative likelihoods for upcoming words.

Despite the variety of real-time processing domains across the phylogenetic spectrum in which anticipatory processing has been observed (at both micro and macro levels), the concept of anticipation has played a relatively minor role in language processing theories. Human languages offer unlimited possibilities not only for saying new things but also for saying old things in new ways—far too many ways, some have argued, to make prediction of words a viable and effective strategy except when contextual constraint is unusually high1. Accordingly, early language processing models often included some form of memory buffer wherein sentential elements were temporarily stored for later integration at phrasal, clausal or sentence boundaries2–6. Since the 1970s, however, the consensus view has been that sentence processing is continuous and incremental, with provisional commitments made that at least temporarily resolve linguistic ambiguities as each word is processed upon its occurrence and rapidly integrated into the sentence representation7–16. More recently, a few researchers have argued for the predictive power of context in generating expectancies during sentence processing, but it has proven difficult to distinguish prediction from integration. What some researchers take as evidence for neural pre-activation (prediction, at a psychological level), others take as a sign of the ease or difficulty in integrating words into message-level representations upon, but not before, their occurrence. A case in point is the N400 component observed in event-related brain potential (ERP) studies, in which cortical neuronal ensembles generate potentials measurable at the scalp. The N400 (B200–500 ms post–item onset) is the brain’s neural response to any potentially meaningful item. Its amplitude is sensitive to word frequency, repetition and concreteness, among other factors. The N400 is especially large to nouns that do not meaningfully fit with their preceding contexts17. However, N400s also characterize responses to all but the most highly expected nouns, even when they fit contextually, with amplitudes inversely related (r E 0.9) to their

offline cloze probabilities18. An item’s cloze probability is the percentage of individuals that continue a sentence fragment with that item in an offline sentence completion task. Despite the sensitivity of the N400 in response to offline semantic expectancy, it is impossible to determine whether variation in N400 amplitude in response to eliciting words during online, real-time sentence processing means that comprehenders are using context to generate expectancies for upcoming items (prediction view) or whether they are forced by the words themselves to devote more or fewer resources to integrating words into sentence representations (integration view). Tracking prediction in sentence processing requires a measure that has high temporal resolution (such as ERPs, magnetoencephalogram or eye movements) and does not alter the comprehension process under study. Additionally, it calls for a design that precludes interpretation in terms of integrative difficulty. A few recent ERP and eye-tracking studies have demonstrated contextually generated expectancies for semantic or syntactic features of upcoming words19–27. None, however, has demonstrated contextual generation of expectancies for specific word forms in semantically meaningful, syntactically well-formed sentences. To this end, we designed an experiment which capitalized on the phonological regularity in English whereby the singular indefinite article meaning ‘some one thing’ is phonologically realized as ‘an’ before words beginning with a vowel sound and ‘a’ before words beginning with a consonant sound (for example, ‘an airplane’ and ‘a kite’). To determine whether comprehenders pre-activate specific articles and nouns before their occurrence, we used sentences of varying constraint that led to expectations for particular consonant- or vowelinitial nouns. Across sentences, target nouns ranged from highly probable to unlikely, based on offline cloze probability norming. For instance, given ‘The day was breezy so the boy went outside to flyy,’ the most likely continuation was ‘a kite’ (cloze of ‘a’ ¼ 86%, ‘kite’ ¼

1Department of Cognitive Science and 2Department of Neurosciences, University of California San Diego, La Jolla, California 92093, USA. Correspondence should be addressed to K.A.D. ([email protected]).



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Figure 1 ERP waveforms and correlations between N400 amplitude and cloze probability showing that specific words were predicted during language comprehension. Articles and nouns were analyzed separately. (a) Illustrative ERPs at the midline central (vertex) recording site according to median splits on cloze probabilities. Negative amplitudes are plotted upwards. Both articles and nouns with o50% cloze elicited greater negativity between 200–500 ms post-stimulus onset (N400) than those with Z50% cloze. Although the ERPs include responses to both article types (‘a’, ‘an’) and both noun types (‘kite’, ‘airplane’), a single sample sentence is provided for simplicity. (b) Mean N400 amplitudes were inversely correlated with items’ cloze probabilities. Scatter diagrams show strong inverse relations between cloze and N400 amplitude at the vertex for both articles (r ¼ –0.68, P o 0.05) and nouns (r ¼ –0.79, P o 0.01). Best-fitting regression lines are also plotted. (c) The r-values for all 26 electrode sites plotted on an idealized head, looking down, nose at the top. Darker shading indicates larger negative correlations, with r-values between sites estimated by spherical spline interpolation. The dotted circle demarcates the vertex. Although ERP prediction effects were slightly larger over the right hemisphere for both articles and nouns and over posterior sites for nouns, the correlations for both articles and nouns showed maximal values over centroparietal sites, with a right hemisphere bias only for the articles (see Supplementary Note for detailed distributional analyses).

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RESULTS We obtained offline probabilities for all article and noun targets. Participants were asked to provide the best continuations for sentences truncated before the article or noun. Article cloze ranged from 0–96%; noun cloze ranged from 0–100%. These broad ranges of expectancy allowed for analysis of the correlations between the ERP effects and the offline probabilities of the relevant continuations. In the ERP experiment, different participants read sentences of varying contextual constraint that included target articles and nouns with large ranges of cloze. Across participants the same sentence context appeared with both higher- and lower-probability articles and nouns. Notably, although some continuations were more probable than others, none was nonsensical, barring participants from developing a strategy (conscious or unconscious) whereby an improbable article was taken to signal an impending semantic anomaly. ERP recording and analyses To measure brain activity associated with prediction effects, we recorded electroencephalograms at 26 scalp locations as 32 participants read sentences word-by-word from a CRT at a rate of 2 words/s (200-ms duration each). ERPs were analyzed for target articles and nouns in 160 sentences, with 16 participants viewing each item. The 160 articles and nouns were sorted into ten equal-width bins as a function of each item’s cloze probability, from highest (90–100%) to lowest (0–10%). ERPs for each 10% bin were averaged first within, then across, participants. The average numerical cloze probability of each Vertex ERPs by median split on cloze probability,

a

e.g., 'The day was breezy so the boy went outside to fly ...' Articles

Nouns

–5 µV

–5 µV

'airplane' 'an' 0

500 ms

0

500 ms

'a' 'kite' < 50% Article cloze ≥ 50% Article cloze

< 50% Noun cloze ≥ 50% Noun cloze

N400 x cloze probability correlations at vertex

b

Articles

–2.5 –2.0 –1.5 –1.0 –0.5

r = –0.68

0

–1 0 1 2

r = –0.79

3 0

0.2 0.4 0.6 0.8 1.0 Article cloze probability

c

Articles

–1.00 –0.67

–0.30 –0.62 –0.19 –0.63 –0.43 –0.60 –0.59

–0.27 –0.51

–0.68 –0.63

[

–0.33

–0.68

0.00

–0.67 –0.72

0.33

–0.69

0.67

–0.53 –0.61 –0.27 –0.52 –0.60

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0.2 0.4 0.6 0.8 1.0 Noun cloze probability

r-values at all recording sites

–0.34 –0.41 –0.53 –0.34 –0.54

–0.49

Nouns

–2 Mean amplitude 200–500 ms (µV)

89%). However, the sentence could continue with a plausible, though less likely, alternative such as ‘an airplane’. Based on previous studies we knew that the N400 in response to ‘kite’ would be smaller than that to ‘airplane’, and more generally that noun N400 amplitude would be highly inversely correlated with cloze probability. However, as previously mentioned, the pattern of noun effects may be a consequence either of the brain’s ‘surprise’ at encountering an item different than what it expects (‘prediction view’), or greater difficulty integrating the received word into the sentence representation (‘integration view’). Indeed, on the basis of our experiences, ‘kite’ may be easier to integrate into the developing sentence representation than ‘airplane’. Given the difference in their meanings, it is likely that ‘kite’ and ‘airplane’ also differ in how well they fit with event schemas that the sentence ‘brings to mind’ through semantic memory processes. However, whereas ‘kite’ and ‘airplane’ differ in meaning, ‘a’ and ‘an’ do not, being distinguished only by their phonological forms. Since their semantics are identical and they differ only in frequency of usage and length, there is no reason for the articles to be differentially difficult to integrate into a given sentence representation unless (i) ‘a’ is always easier to integrate, because it is shorter and/or more frequent than ‘an’ in everyday usage, or, as we will maintain, (ii) comprehenders have already (unconsciously) formed a higher, non-trivial expectation for ‘kite’ than for ‘airplane’. If anticipation is an integral part of language processing, then it should be reflected in the brain activity probed by the more and less expected indefinite articles. If the amount of pre-activation is driven strictly by word length or frequency, then whatever the ERP effect, it would be context independent, with all examples of ‘a’ (versus ‘an’) patterning together. Even if pre-activation is context dependent, the brain may react to the anticipated article with one response and to anything else with a different response, in a binary rather than a graded fashion. Finally, we hypothesize that the language processor exploits sentence context to probabilistically pre-activate possible continuations, consistent with constraint-based models; if so, the N400 should respond to a degree that can be estimated from the article’s offline cloze probability. In sum, no observable difference in the brain’s response to more- versus less-expected articles would be a sharp blow to predictive processing accounts, whereas a graded N400 effect correlated with the article’s offline cloze probability would support incremental, predictive processing that is sensitive to meaning-based constraints.

Mean amplitude 200–500 ms (µV)


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Nouns 0.25 0.36 –0.36 –0.32 –0.41

–0.44 –0.55 0.21 –0.05 –0.63 –0.66 –0.71

–0.83

–0.08 –0.81

–0.79 –0.65 –0.79 –0.82

–0.70 –0.76

–0.77 –0.75 –0.75 –0.75 –0.84


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bin was then calculated and correlated with mean ERP amplitude in the N400 time window (200–500 ms) for articles and nouns separately. Correlation coefficients (r-values) and percentage of variance explained by offline probability (r2) were then calculated separately for all 26 electrode sites. N400 effects and correlations As expected, N400 amplitude decreased (became less negative) as noun cloze probabilities increased (Fig. 1a). We replicated the well-known correlation between N400 amplitude and offline cloze of the target nouns (Fig. 1b), with correlation coefficients ranging from r ¼ 0.36 (not significant) to r ¼ –0.84 (P o 0.01) at various scalp sites (Fig. 1c). Noun cloze probability thus accounted for up to 71% of variance in brain activity between 200–500 ms after a noun’s appearance. Moreover, correlations peaked over posterior sites, where N400 amplitudes are typically largest, whereas anterior sites (where visual N400s are usually less prevalent) showed little if any evidence of similarly correlated brain activity (Fig. 1c). These results were an important precondition for analysis of the articles because they demonstrated that the different degrees of constraint in these materials were reflected in offline expectancies and N400 amplitude modulations in the usual way. However, as previously noted, the noun correlation pattern does not settle the question of prediction because high correlations could reflect either the degree of pre-activation or the variance in the integrability of the noun with the mental representation of the sentence up to that moment. To address the question of prediction directly we turned to the correlation pattern of the target articles. Although article ERP waveforms were significantly smaller than those elicited by nouns, the amplitude of the negativity in the N400 time window did indeed vary as a function of article expectancy (Fig. 1a). Just as for the nouns, the higher the article’s cloze probability, the smaller the ERP negativity between 200–500 ms post-onset (Fig. 1b), with correlation coefficients ranging from r ¼ 0.19 (not significant) to r ¼ 0.72 (P o 0.05) at various recording sites (Fig. 1c). Moreover, maximum correlations clustered over centroparietal sites, similar to nouns, albeit more lateralized to the right (Fig. 1c and Supplementary Note online). So at least over certain scalp areas, up to 52% of variance in article N400 amplitude was accounted for by the average probability that individuals would continue the sentence context with that particular article offline. DISCUSSION By constructing sentence contexts that led to varying offline expectations for nouns beginning with vowel or consonant sounds, we could assess the extent to which such expectations were formed online by preceding the noun with the phonologically appropriate indefinite article or the other semantically identical, sententially congruent but phonologically inappropriate one. Similar to the nouns, the more contextually unexpected an indefinite article was, the more negative the ERP mean amplitude between 200–500 ms post-word onset (N400). In other words, the brain’s response to the articles differed in a graded fashion as a function of contextual constraint. Our results thus demonstrate not only that readers can rapidly, incrementally integrate incoming words into evolving mental sentence representations, but that they do so in part by exploiting various constraining forces to form probabilistic predictions of which specific words will come next. Here, we clearly showed this for the target articles and nouns, although we have no reason to assume the same would not hold for every word in a sentence throughout the range of normal reading rates. Notably, maximum correlations for both nouns and articles were not randomly distributed across the scalp but rather clustered over centroparietal


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scalp sites (Fig. 1c) where previous reading studies have shown the largest N400 effects. This topographical pattern indicated that the values were not simply the spurious outcome of multiple testing at the 26 electrode sites. In conducting the correlational analyses, we established the functional relationship of the negativity between 200–500 ms post-article onset to the canonical N400 typically elicited by nouns and verbs. Notably, we also demonstrated that this negativity indexed expectancy for the eliciting article (and upcoming noun). Given that all articles were grammatically and semantically congruent within their contexts and that ‘a’ and ‘an’ have identical semantics, there was no reason for either article type to have been any more or less difficult to integrate into the sentence representation. Systematic variation in amplitude of the ERP negativity in relation to offline article cloze probability thus constitutes strong evidence that participants were indeed anticipating the phonological form of a particular noun and therefore had formed expectations for one article type relative to the other and seemed to experience some processing difficulty when the less-expected article appeared. Articles are relatively short; highly frequent; highly predictable as a word class; not as semantically rich as nouns, verbs, adjectives or adverbs and are often skipped over during natural reading28. In addition to providing unequivocal evidence for lexically specific prediction, the article correlations are compelling evidence that articles, too, are predicted and integrated with context in qualitatively similar ways as nouns. For reasons not yet known, the correlations with offline probability were on average lower for articles than for nouns (although at some electrode sites, the two were statistically similar). Nonetheless, the article correlations clearly demonstrated that prediction is not limited to highly constraining contexts. We believe that this sort of anticipation is an integral (perhaps inevitable) part of real-time language processing and is likely to have a functional role, although this has yet to be demonstrated. Our findings thus suggest that individuals can use linguistic input to pre-activate representations of upcoming words in advance of their appearance. Exactly what informs these predictions, as well as the neural mechanism for predictive language processing, are matters for empirical and computational investigations. An open question, for instance, is how the human sentence comprehension system handles variation in natural input rates (for example, 2 to 3.5 words/s), and in particular, whether the same (or different) mechanisms are engaged. In line with most studies of comprehension that draw general conclusions without systematically varying input rate, we assume that basic language processing mechanisms do not vary fundamentally across the range of normal input rates. This parsimonious assumption is bolstered by results of N400 studies in which variation in presentation rate showed no evidence for the engagement of qualitatively different neural mechanisms29,30. Although the current study demonstrated graded prediction only at the slower end of natural input rates, we suggest that this conclusion may generalize to faster rates, given the aforementioned arguments and ERP evidence for binary prediction (expected versus unexpected) in natural speech26,27. Subsequent experimentation will undoubtedly shed more light on these issues. We propose that single words and combinations of words in a sentence tap into and differentially activate information via semantic memory, going beyond the immediate physical input. Semantic memory is presumed to include information about individual words as well as world knowledge built up from experience of people, places, things and events. We maintain that probabilistic pre-activation of particular word forms follows the access of this experiential knowledge as a result of linguistic input. Our observation of an ERP expectancy effect at the

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ARTICLES article leads us to conclude that predictions can be for specific phonological forms—words beginning with either vowels or consonants. In this sense, we propose that prediction can be highly specific, at least under some circumstances. Our results are in line with a growing list of empirical studies demonstrating that the brain’s language parser projects probabilistic expectations about various aspects of linguistic processing during online sentence comprehension tasks. Several studies suggest that the parser uses constraints accruing as a sentence is analyzed word-by-word to (i) compute likely relationships among referents in linguistic and visual contexts (for example, upon hearing the word ‘eat’, a person is likely to scan the environment for something edible)19, (ii) pre-activate semantic features of categories (for example, expecting a particular kind of tree pre-activates features of trees, even when not all trees would be plausible in the sentence context)24 or (iii) anticipate various syntactic aspects of to-be-presented material (for example, expecting the grammatical gender of upcoming items in gender-marked languages such as Spanish or Dutch) during word-by-word reading and natural speech25–27. In particular, our study expands on findings from the aforementioned grammatical gender studies25,27 in which nouns were preceded by words whose syntactic gender marking was inconsistent with that of the ‘expected’ noun. Although both the gender studies and our study used the same general logic, the differences in experimental manipulations, design and analyses lead to substantive differences in the justifiable conclusions. Whereas the Spanish and Dutch studies utilized pre-nominal gender marking on determiners and adjectives, respectively, our study relied upon a purely phonological (sound representation) relation between probed articles and upcoming nouns. Thus, our observation of article ERP variation provides a strong test of whether the language system predicts word forms with specific phonological content (lexemes), instead of simply representations specifying words’ semantic and syntactic properties (lemmas). In addition, having tested prediction with semantically identical ‘a’/‘an’ articles (function words) instead of words richer in meaning (content words) such as adjectives, we effectively counter the argument that the observed difference between more- versus less-predictable articles reflects difficulty interpreting them. And perhaps most notably, only our study compares brain activity elicited by a range of more- or less-predictable articles, not simply most- versus least-expected. The article correlation findings thus show for the first time that the language system does not simply pre-activate a single word when its representation exceeds some threshold given a highly constraining context. Instead, a gradient of preactivation shows that the system makes graded predictions. Our electrophysiological results extend previous prediction findings in several other notable ways. First, they demonstrate that a candidate entity (or its depiction) need not be physically present in order for the brain to narrow the possibilities for likely continuations; rather, predictions can emerge on the basis of associations that form as sentential context accrues. Second, our results illustrate that at least one subclass of function words (which generally provide more grammatical structure than lexical meaning), indefinite articles, can be important in building context and facilitating linguistic processing. This finding is particularly relevant given the paucity of evidence in the comprehension literature about semantic context effects on function words31,32. And finally, our findings unambiguously show that anticipatory processing can happen not only for conceptual or semantic features but also for specific phonological word forms. In sum, although natural language comprehension must occur over a range of input rates with a nearly infinite number of possible word combinations, these factors do not seem to prevent the brain from anticipating the most probable

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continuations for sentences in advance of the actual input. In this regard, language comprehension appears to involve a special case of the anticipatory behavior observed in other biological systems. METHODS Experimental design and materials. Stimuli consisted of 80 sentence contexts with two possible target types: relatively expected and unexpected indefinite article/noun pairs. Each article/noun pair served as a more- and less-expected target in different contexts. Targets were sentence medial and congruent (that is, no agreement violations such as ‘a airplane’). The 160 stimuli were divided into two lists of 80 sentences, each participant viewing one list. Sentence contexts and article/noun targets were used only once per list. Each list contained equal numbers of relatively expected and unexpected targets as well as ‘a’ and ‘an’ targets. One-quarter of sentences were followed by yes/no comprehension questions, 94% of which were answered correctly by participants, on average (range, 88–100%). Norming for articles and nouns was done with different groups of student volunteers. Informed written consent was obtained from all norming (and ERP) participants. For articles, cloze ratings were obtained from 30 participants for 80 sentence contexts truncated before the target article. For nouns, sentences were truncated after target articles, with two versions of each context (160 sentences total): one with the more-probable article supplied, the other with the less-probable article. Individual participants saw only one version, with each normed by 30 participants. Participants. Thirty-two volunteers (23 women) participated in the ERP experiment for course credit or for cash. All were right-handed, native English speakers with normal or corrected-to-normal vision, between 18–37 years (mean, 21 years). Seven participants reported a left-handed parent or sibling. Procedure. Volunteers were tested in a single session, with visual sentences presented centrally, one word at a time (200-ms duration, 500-ms stimulus onset asynchrony). The instructions were to read sentences for comprehension and answer yes/no comprehension questions by pressing hand-held buttons. The electroencephalogram (EEG) was recorded from 26 electrodes arranged geodesically in an Electro-cap, each referenced online to the left mastoid. Blinks and eye movements were monitored from electrodes placed on the outer canthi and under each eye, referenced to the left mastoid. Electrode impedances were kept below 5 KO. The EEG was amplified with Grass amplifiers with a bandpass of 0.01 to 100 Hz, continuously digitized at a sampling rate of 250 Hz. Data analysis. Trials contaminated by eye movements, excessive muscle activity or amplifier blocking were rejected offline before averaging; on average, 10.7% of article trials and 11.4% of noun trials were rejected. Data with excessive blinks were corrected using a spatial filter algorithm. A digital band-pass filter set from 0.2 to 15 Hz was used on all data to reduce high-frequency noise. Data were re-referenced offline to the algebraic sum of left and right mastoids and averaged for each experimental condition, time-locked to the target article and noun onsets. Note: Supplementary information is available on the Nature Neuroscience website.

ACKNOWLEDGMENTS Many thanks to E. De Ochoa and J. Cagle for help with data collection and to J. Elman for helpful comments on this manuscript. This research was supported by US National Institute of Child Health and Human Development grant HD22614 and National Institute on Aging grant AG08313 to M.K. and by a Center for Research in Language Training Fellowship to K.A.D. COMPETING INTERESTS STATEMENT The authors declare that they have no competing financial interests. Received 21 April; accepted 21 June 2005 Published online at http://www.nature.com/natureneuroscience/

1. Stanovich, K.E. & West, R.F. Mechanisms of sentence context effects in reading: automatic activation and conscious attention. Mem. Cognit. 7, 77–85 (1979). 2. Kintsch, W. & van Dijk, T.A. Towards a model of text comprehension and production. Psychol. Rev. 85, 363–394 (1978).

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ARTICLES 3. Carroll, J. & Bever, T. Sentence comprehension: a case study in the relation of knowledge and perception. in Handbook of Perception, Vol. 7 (eds. Carterette, E. & Friedman, M.) 299–317 (Academic, New York, 1978). 4. Just, M.A. & Carpenter, P.A. A theory of reading: From eye fixations to comprehension. Psychol. Rev. 87, 329–354 (1980). 5. Daneman, M. & Carpenter, P.A. Individual differences in integrating information between and within sentences. J. Exp. Psychol. Learn. Mem. Cogn. 9, 561–584 (1983). 6. Mitchell, D.C. & Green, D.W. The effects of context and content on immediate processing in reading. Q. J. Exp. Psychol. 30, 609–636 (1978). 7. Marslen-Wilson, W.D. Sentence perception as an interactive parallel process. Science 189, 226–228 (1975). 8. Altmann, G.T.M. & Steedman, M.J. Interaction with context during human sentence processing. Cognition 30, 191–238 (1988). 9. Pickering, M.J. Processing local and unbounded dependencies: a unified account. J. Psycholinguist. Res. 23, 323–352 (1994). 10. Tyler, L.K. & Marslen-Wilson, W.D. The on-line effects of semantic context on syntactic processing. J. Verb. Learn. Verb. Behav. 16, 683–692 (1977). 11. Traxler, M., Bybee, M. & Pickering, M. Influence of connectives on language comprehension: eye-tracking evidence for incremental interpretation. Q. J. Exp. Psychol. A 50A, 481–497 (1997). 12. Marslen-Wilson, W.D. & Tyler, L.K. The temporal structure of spoken language understanding. Cognition 8, 1–71 (1980). 13. Steedman, M. Grammar, interpretation, and processing from the lexicon. in Lexical Representation and Process (ed. Marslen-Wilson, W.D.) 463–504 (MIT Press, Cambridge, Massachusetts, 1989). 14. Boland, J.E., Tanenhaus, M.K., Garnsey, S.M. & Carlson, G.N. Verb argument structure in parsing and interpretation: Evidence from wh-questions. J. Mem. Lang. 34, 774–806 (1995). 15. Tanenhaus, M., Spivey-Knowlton, M., Eberhard, K. & Sedivy, J. Integration of visual and linguistic information during spoken language comprehension. Science 268, 1632–1634 (1995). 16. Kutas, M. & Hillyard, S.A. Event-related brain potentials to grammatical errors and semantic anomalies. Mem. Cognit. 11, 539–550 (1983). 17. Kutas, M. & Hillyard, S.A. Reading senseless sentences: brain potentials reflect semantic incongruity. Science 207, 203–204 (1980). 18. Kutas, M. & Hillyard, S.A. Brain potentials during reading reflect word expectancy and semantic association. Nature 307, 161–163 (1984).


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19. Altmann, G.T.M. & Kamide, Y. Incremental interpretation at verbs: restricting the domain of subsequent reference. Cognition 73, 247–264 (1999). 20. Tanenhaus, M.K., Magnuson, J.S., Dahan, D. & Chambers, C. Eye movements and lexical access in spoken-language comprehension: evaluating a linking hypothesis between fixations and linguistic processing. J. Psycholinguist. Res. 29, 557–580 (2000). 21. Kamide, Y., Scheepers, C. & Altmann, G.T.M. Integration of syntactic and semantic information in predictive processing: cross-linguistic evidence from German and English. J. Psycholinguist. Res. 32, 37–55 (2003). 22. Chambers, C.G. & Smyth, R. Structural parallelism and discourse coherence: a test of centering theory. J. Mem. Lang. 39, 593–608 (1998). 23. Sedivy, J.C., Tanenhaus, M.K., Chambers, C.G. & Carlson, G.N. Achieving incremental semantic interpretation through contextual representation. Cognition 71, 109–148 (1999). 24. Federmeier, K.D. & Kutas, M. A rose by any other name: long-term memory structure and sentence processing. J. Mem. Lang. 41, 469–495 (1999). 25. Wicha, N.Y.Y., Moreno, E.M. & Kutas, M. Anticipating words and their gender: an event-related brain potential study of semantic integration, gender expectancy, and gender agreement in Spanish sentence reading. J. Cogn. Neurosci. 16, 1272–1288 (2004). 26. Wicha, N.Y.Y., Bates, E.A., Moreno, E.M. & Kutas, M. Potato not Pope: human brain potentials to gender expectation and agreement in Spanish spoken sentences. Neurosci. Lett. 346, 165–168 (2003). 27. Van Berkum, J.J.A., Brown, C.M., Zwitserlood, P., Kooijman, V. & Hagoort, P. Anticipating upcoming words in discourse: evidence from ERPs and reading times. J. Exp. Psychol. Learn. Mem. Cogn. 31, 443–467 (2005). 28. O’Regan, K. Saccade size control in reading: evidence for the linguistic control hypothesis. Percept. Psychophys. 25, 501–509 (1979). 29. Kutas, M. Event-related brain potentials (ERPs) elicited during rapid serial visual presentation of congruous and incongruous sentences. Electroencephalogr. Clin. Neurophysiol. 40 (suppl.), 406–411 (1987). 30. Gunter, T.C., Jackson, J.L. & Mulder, G. An electrophysiological study of semantic processing in young and middle-aged academics. Psychophysiology 29, 38–54 (1992). 31. King, J.W. & Kutas, M. A brain potential whose latency indexes the length and frequency of words. CRL Newsletter 10, 1–9 (1995). 32. Kluender, R. & Kutas, M. Subjacency as a processing phenomenon. Lang. Cognitive Proc. 8, 573–633 (1993).

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CHROMATOGRAPHY OF STEROIDS, Volume 8 (Journal of Chromatography Library)

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Nature Neuroscience Journal ~ August 2005, Volume 8 No 8

BusinessWeek (August 8, 2005)

October journal No.8 Spring (1979)

METHODS IN MICROBIOLOGY,VOLUME 8, Volume 8 (v. 8)

Новый Мир ( № 8 2005)

Inked Magazine, 2008 8, August

Supramolecular structure and function 8, Volume 8

Bruckner: Symphony No. 8

'Куpьеp SF' - No 8

Bruckner: Symphony No. 8

Bruckner: Symphony No. 8

Geometria Sagrada, Volume 8

Longsal Teachings: Volume 8

International Entrepreneurship (Volume 8)

Buddha, Volume 8: Jetavana

Obras Seletas volume 8

SECRETS VOLUME #8

8)

8

Emerging Infectious Diseases - Vol. 14, No.8, August 2008

sports medicine Volume 41 Issue 8 August 2011

sports medicine Volume 39 Issue 8 August 2009

sports medicine Volume 40 Issue 8 August 2010

The New Yorker Magazine August 8, 2011

Street Game (Ghostwalkers, No 8)

Cognition, Vol. 8, No. 4

Forces of Nature (Scientific American Special Online Issue No. 8)

Cinema Journal, Volume 8, Issue 2, Spring, 1969

Cognition, Vol. 8, No. 3

CHROMATOGRAPHY OF STEROIDS, Volume 8 (Journal of Chromatography Library)

Textual Practice: Journal, Volume 8, Number 2 (Textual Practice)

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