Methods of Behavior Analysis in Neuroscience, Second Edition (Frontiers in Neuroscience)

Methods of BEHAVIOR ANALYSIS in NEUROSCIENCE Second Edition © 2009 by Taylor & Francis Group, LLC Methods of BEHAVIO...

Author: Jerry J. Buccafusco

204 downloads 1550 Views 7MB Size Report

This content was uploaded by our users and we assume good faith they have the permission to share this book. If you own the copyright to this book and it is wrongfully on our website, we offer a simple DMCA procedure to remove your content from our site. Start by pressing the button below!
Report copyright / DMCA form

DOWNLOAD PDF

Methods of BEHAVIOR ANALYSIS in NEUROSCIENCE Second Edition

© 2009 by Taylor & Francis Group, LLC

Methods of BEHAVIOR ANALYSIS in NEUROSCIENCE Second Edition Edited by

Jerry J. Buccafusco Medical College of Georgia Augusta

Boca Raton London New York

CRC Press is an imprint of the Taylor & Francis Group, an informa business


CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2009 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number-13: 978-1-4200-5234-3 (Hardcover) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright. com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging-in-Publication Data Methods of behavior analysis in neuroscience / editor, Jerry J. Buccafusco. -- 2nd ed. p. ; cm. -- (Frontiers in neuroscience) Rev. ed. of: Methods of behavior analysis in neuroscience / edited by Jerry J. Buccafusco. c2001. Includes bibliographical references and index. ISBN 978-1-4200-5234-3 (hardcover : alk. paper) 1. Neurosciences. 2. Nervous system--Diseases--Animal models. 3. Animal behavior I. Buccafusco, Jerry J. II. Methods of behavior analysis in neuroscience. III. Title. IV. Series: Frontiers in neuroscience (Boca Raton, Fla.). [DNLM: 1. Behavior, Animal. 2. Neurosciences--methods. 3. Animals, Laboratory--psychology. WL 100 M5925 2008] RC343.M45 2008 616.8--dc22 Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com


2008038324

This book is dedicated to my wife Regina, to her parents Claire and James, and to my parents Rose and Dominick — with appreciation for their love and support, particularly during my early academic years; and to our children Chris and Marty, both writers in their respective fields. Acknowledgment and appreciation also goes to my office manager Vanessa Cherry for her assistance in the organization of the manuscripts and for helping (often vainly) to keep us on schedule. Finally, I would like to express my appreciation to our excellent animal behavior technical assistants, Laura Shuster-Pearson, Nancy Kille and Donna Blessing for their scientific prowess and for the kindness they impart in working with our nonhuman primate and rodent subjects.


Contents Series Preface............................................................................................................ix Preface ......................................................................................................................xi The Editor ................................................................................................................ xv Contributors ...........................................................................................................xvii Chapter 1

Transgenic Mouse Models of Alzheimer’s Disease: Behavioral Testing and Considerations .................................................................. 1 Kathryn J. Bryan, Hyoung-gon Lee, George Perry, Mark A. Smith, and Gemma Casadesus

Chapter 2

Cued and Contextual Fear Conditioning for Rodents ........................ 19 Peter Curzon, Nathan R. Rustay, and Kaitlin E. Browman

Chapter 3

Drug Discrimination .......................................................................... 39 Richard Young

Chapter 4

Conditioned Place Preference ............................................................ 59 Adam J. Prus, John R. James, and John A. Rosecrans

Chapter 5

Anxiety-Related Behaviors in Mice................................................... 77 Kathleen R. Bailey and Jacqueline N. Crawley

Chapter 6

Behavioral Assessment of Antidepressant Activity in Rodents....... 103 Vincent Castagné, Paul Moser, and Roger D. Porsolt

Chapter 7

Assessing Attention in Rodents........................................................ 119 Philip J. Bushnell and Barbara J. Strupp

Chapter 8

The Behavioral Assessment of Sensorimotor Processes in the Mouse: Acoustic Startle, Sensory Gating, Locomotor Activity, Rotarod, and Beam Walking............................................................ 145 Peter Curzon, Min Zhang, Richard J. Radek, and Gerard B. Fox vii


viii

Chapter 9

Contents

Intravenous Drug Self-Administration in Nonhuman Primates ...... 179 Leonard L. Howell and William E. Fantegrossi

Chapter 10 Contextually Induced Drug Seeking During Protracted Abstinence in Rats............................................................................ 199 Jerry J. Buccafusco and Laura Shuster Chapter 11 Operant Analysis of Fronto-striatal Function in Rodents................ 215 Máté D. Döbrössy, Simon Brooks, Rebecca Trueman, Peter J. Brasted, and Stephen B. Dunnett Chapter 12 Working Memory: Delayed Response Tasks in Monkeys ............... 247 Jesse S. Rodriguez and Merle G. Paule Chapter 13 Spatial Navigation (Water Maze) Tasks ........................................... 267 Alvin V. Terry Jr. Chapter 14 Water Maze Tasks in Mice: Special Reference to Alzheimer’s Transgenic Mice ............................................................................... 281 Dave Morgan Chapter 15 Behavioral Neuroscience of Zebrafish ............................................. 293 Edward D. Levin and Daniel T. Cerutti Chapter 16 Caenorhabditis elegans Model for Initial Screening and Mechanistic Evaluation of Potential New Drugs for Aging and Alzheimer’s Disease......................................................................... 311 Yuan Luo, Yanjue Wu, Marishka Brown, and Christopher D. Link Chapter 17 The Revival of Scopolamine Reversal for the Assessment of Cognition-Enhancing Drugs ............................................................ 329 Jerry J. Buccafusco


Series Preface Our goal in creating the Frontiers in Neuroscience Series is to present the insights of experts on emerging fields and theoretical concepts that are, or will be, in the vanguard of neuroscience. Books in the series cover genetics, ion channels, apoptosis, electrodes, neural ensemble recordings in behaving animals, and even robotics. The series also covers new and exciting multidisciplinary areas of brain research, such as computational neuroscience and neuroengineering, and describes breakthroughs in classical fields like behavioral neuroscience. We hope every neuroscientist will use these books in order to get acquainted with new ideas and frontiers in brain research. These books can be given to graduate students and postdoctoral fellows when they are looking for guidance to start a new line of research. Each book is edited by an expert and consists of chapters written by the leaders in a particular field. Books are richly illustrated and contain comprehensive bibliographies. Chapters provide substantial background material relevant to the particular subject. We hope that as the volumes become available, the effort put in by us, the publisher, the book editors, and individual authors will contribute to the further development of brain research. The extent to which we achieve this goal will be determined by the utility of these books. Sidney A. Simon, Ph.D. Miguel A.L. Nicolelis, M.D.,Ph.D. Series Editors

ix


Preface In the six years since the publication of the first edition of Methods of Behavior Analysis in Neuroscience there have been significant advances in the concepts and methodology used in the assessment of animal behavior. The purpose of this second edition is to provide the reader with updates to the technology, as well as to describe some new approaches that are becoming standard in the field. Examples of the latter are the chapters that assess behavior in zebra fish and in Caenorhabditis elegans. This edition also includes chapters describing methods for assessing the cognitive impairment associated with major psychotic disorders, as well as new approaches to assessing cognitive impairment in aged mice and in mice impaired as a consequence of high cerebral amyloid burden. Examples of the revival of the scopolamine reversal model for assessing the clinical relevance of new cognition-enhancing drugs rounds out the book. In the first edition the lead article, “Choice of Animal Subjects in Behavioral Analysis,” written by William J. Jackson, set the stage for the ensuing chapters. The discussion mainly focused on the origin of the laboratory rat, historically one of the most dominant animal species used in biomedical research, and on nonhuman primate species used in behavior research. Only a few short paragraphs were dedicated to research with mice. In recent years, with the development of transgenic and knockout mice, this species is now poised to dominate the field. In this edition the stage again is set with a timely review of the use of transgenic mice as models for Alzheimer’s disease. The chapter is balanced with a discussion of the strengths and weaknesses of the model. In fact, one of the themes of this edition is the utility of animal behavior methods in both basic and applied research. The timing of the publication of this edition is particularly relevant in view of the vast number of scientists who are returning from the past two decades of molecular and cellular biology to look toward whole animal research to translate the most important of their findings for clinical application. Since the neuroscientist trained in methodologies directed toward the molecular and cellular level does not often have experience in the intricacies of animal behavioral analyses, there is often much time devoted to analyzing complex literature, or to developing an approach de novo. Specialists who are recognized experts in several fields of cognitive and behavioral neuroscience have provided chapters that focus on a particular behavioral model. Each author has analyzed the literature to describe the most frequently used and accepted version of the model. Each chapter includes (1) a well-referenced introduction that covers the theory behind, and the utility of, the model; (2) a detailed and step-wise methodology; and (3) an approach to data interpretation. Many chapters also provide examples of actual experiments that use the method. This edition was designed as a reference manual for use by practicing scientists with various levels of experience who wish to use well-studied behavioral approaches in animal subjects to better understand the effects of disease, and to predict the effects of new therapeutic treatments on human cognition. As with the first edition, xi


xii

Preface

there has been no attempt to cover all areas of animal behavior and sensory processing, though together both volumes now provide significant coverage of the field. These texts will help take the guesswork out of designing the methodology for many of the most widely used animal behavioral approaches developed for the study of brain disorders, drug abuse, toxicology, and cognitive drug development. As a matter of convenience the topics have been arranged in chapter form, and there is a false sense of security that each method described is the last word on the subject. However, it is often not sufficient to employ only one of these methods to assess the cognitive status of an animal. For example, when studying memory or recall, it is prudent to use a test battery that can better provide a comfortable level of interpretation of the effect of the perturbation applied to the subject. Spatial and nonspatial tasks should be considered. If negative reinforcement is involved, such as electrical shock, the animal should be tested for its response to pain. Drugs or other manipulations that might alter pain sensitivity could give false impressions in a shock-motivated memory task. Drugs that affect motor activity may alter maze activity or swimming behavior, and drugs that alter taste or appetite, or that induce GI disturbances could affect food-motivated behaviors. Whenever possible, the animal should be observed (at least initially) while performing the task. It is often surprising to some investigators (this one included) to find the animal using a behavior to solve the problem that was not considered in designing the task. A good example is the mediating or non-mnemonic strategies that rats use to solve matching problems in various operant paradigms. Most animals would rather use such strategies (such as orientating to a proffered lever) to obtain food rewards than use memory. Whenever possible, the authors have provided some of these pitfalls in their chapters, although every possible contingency cannot be anticipated. Thus, it is in the best interest of the investigator to use this book to help develop several strategies to understand the complex behaviors of animals as they respond to drugs, new diets, surgical interventions, or to additional or fewer genes. While danger in anthropomorphizing the behavior of animals always exists, the investigator should feel some level of confidence that much of the behavioral literature is replete with instances of high predictive value for similar perturbations in humans. Of course, species and strain differences can limit such interpretations. Mice are clearly not little rats, and rats are not nonhuman primates. Each species has a specific level of predictive value that should be assessed. A final cautionary note is that investigators make every attempt to make their experiments as reproducible as possible when studying animal behavior. Handlers, experimenters, food, water, bedding, noise, and surrounding visual cues are just a few of the factors that should be held constant when performing behavioral studies. Inconsistency contributes mightily to response variability in a population, and may even lead to a completely opposite behavior to the one expected. I would like to express my sincere thanks to the many authors who contributed these chapters. Their difficult task in preparing this information will make easier the tasks of our readers in their own efforts to assess animal behavior. I would also like to acknowledge the support (moral and technical) of the CRC Press staff, Senior Editor Barbara Norwitz and Senior Project Coordinator Jill Jurgensen, and the Methods in Neuroscience Series Editors, Sidney Simon and Miquel Nicolelis. Finally, I would


Preface

xiii

like to thank my office administrator, Vanessa Cherry, for her many contributions in getting this book together for publication.


The Editor Jerry J. Buccafusco, Ph.D., is Director of the Alzheimer’s Research Center in the Department of Pharmacology and Toxicology of the Medical College of Georgia. He holds the ranks of Professor of Pharmacology and Toxicology and Professor of Psychiatry and Health Behavior. He holds a joint appointment as Research Pharmacologist and Director of the Neuropharmacology Laboratory at the Department of Veterans Affairs Medical Center. Dr. Buccafusco is also president and CEO (and founder, est. 03/01/2000) of Prime Behavior Testing Laboratories, Inc. (Evans, GA), a contract research company for the preclinical evaluation of cognition-enhancing therapeutic agents. Dr. Buccafusco was classically trained as a chemist, receiving the M.S. degree in inorganic chemistry from Canisius College in 1973. His pharmacological training was initiated at the University of Medicine and Dentistry of New Jersey where he received the Ph.D. degree in 1978. His doctoral thesis concerned the role of central cholinergic neurons in mediating a hypertensive state in rats. Part of this work included the measurement of several components of hypothalamically mediated escape behavior in this model. His postdoctoral experience included two years at the Roche Institute of Molecular Biology under the direction of Dr. Sydney Spector. In 1979 he joined the Department of Pharmacology and Toxicology of the Medical College of Georgia. In 1989 Dr. Buccafusco helped found and became the director of the Medical College of Georgia’s Alzheimer’s Research Center. The center hosts several core facilities, including the Animal Behavior Center, which houses more than 50 young and aged macaque monkeys who participate in cognitive research studies. Awards and honors resulting from Dr. Buccafusco’s research include the New Investigator Award, National Institute on Drug Abuse, 1980; Sandoz Distinguished Lecturer, 1983; Distinguished Faculty Award for the Basic Sciences, School of Medicine (Medical College of Georgia), 1988; Callaway Foundation of Georgia, Center Grant recipient, 1989; and the Distinguished Alumnus Award, University of Medicine and Dentistry of New Jersey, 1998. In 2008, Dr. Buccafusco was appointed Veterans Administration Career Scientist, and he was the recipient of the American Society for Pharmacology and Therapeutics’ Pharmacia-ASPET Award for Experimental Therapeutics. Dr. Buccafusco also served as member of the Pharmacology II Study Section of the National Institute on Drug Abuse from 1989–1991. He is a member of the Scientific Advisory Board of the Institute for the Study of Aging, New York, NY, and is a consultant to several pharmaceutical companies in the area of neuropharmacology and drug discovery. Dr. Buccafusco holds memberships in several scientific societies. In the professional society, the American Society for Pharmacology and Experimental Therapeutics, he recently completed a three-year term as (inaugural) Chairman of the Division of Systems and Integrated Pharmacology. He also serves as Associate Editor (Neuro-Behavioral Pharmacology section) for the Journal of Pharmacology and Experimental Therapeutics. xv


xvi

The Editor

Dr. Buccafusco has authored more than 200 research publications and book chapters. Over the years these articles have received more than 3000 citations by other authors. His research area includes the development of novel treatment modalities for Alzheimer’s disease and related disorders. In 1988, his laboratory was the first to report the cognitive enhancing action of low doses of nicotine in nonhuman primates. Since that time he has studied numerous novel memory-enhancing agents derived from several pharmacological classes in this model. His most recent work is directed at the development of single molecular entities that act on multiple CNS targets to not only enhance cognitive function, but also to provide neuroprotection or alter the disposition and metabolism of amyloid precursor protein. Dr. Buccafusco has also studied the toxic effects of organophosphorus anticholinesterases used as insecticides and chemical warfare agents. In particular, he has studied the behavioral/cognitive alterations associated with low level, chronic exposure to such agents. His work in the area of drug abuse has centered around the role of central cholinergic neurons in the development of physical dependence on opiates, and in the expression of acute and protracted withdrawal behaviors. Most recently, his laboratory is investigating the role of the immune system and in the production of autoantibodies to G-amyloid and to the receptor for advanced glycation end products (RAGE) by individuals with Alzheimer’s disease. These studies have been supported by continuous federally sponsored grants and by several private foundations and commercial interests.


Contributors Kathleen R. Bailey, Ph.D. Department of Psychology Susquehanna University Selinsgrove, Pennsylvania, USA Peter J. Brasted, Ph.D. Cardiff School of Biosciences Cardiff University Cardiff, Wales, UK Simon Brooks, Ph.D. Cardiff School of Biosciences Cardiff University Cardiff, Wales, UK Kaitlin E. Browman, Ph.D. Neuroscience Research Abbott Laboratories Abbott Park, Illinois, USA Marishka Brown, B.S. Department of Pharmaceutical Sciences School of Pharmacy University of Maryland Baltimore, Maryland, USA Kathryn J. Bryan, Ph.D. Department of Pathology Case Western Reserve University Cleveland, Ohio, USA Jerry J. Buccafusco, Ph.D. Alzheimer’s Research Center Department of Pharmacology and Toxicology Medical College of Georgia and Charlie Norwood Veterans Affairs Medical Center Augusta, Georgia, USA

xvii


xviii

Philip J. Bushnell, Ph.D. Neurotoxicology Division National Health and Environmental Effects Research Laboratory US Environmental Protection Agency Research Triangle Park, North Carolina, USA Gemma Casadesus, Ph.D. Department of Neurosciences Case Western Reserve University Cleveland, Ohio, USA Vincent Castagné, Ph.D. Porsolt & Partners Pharmacology Boulogne-Billancourt, France Daniel T. Cerutti, Ph.D. Psychology Department California State University East Bay, California, USA Jacqueline N. Crawley, Ph.D. Laboratory of Behavioral Neuroscience National Institute of Mental Health National Institutes of Health Bethesda, Maryland, USA Peter Curzon Research Investigator Neuroscience Research Abbott Laboratories Abbott Park, Illinois, USA Máté D. Döbrössy, Ph.D. Cardiff School of Biosciences Cardiff University Cardiff, Wales, UK Stephen B. Dunnett, Ph.D. Cardiff School of Biosciences Cardiff University Cardiff, Wales, UK and Stereotactic Neurosurgery Laboratory of Molecular Neurosurgery Universitätsklinikum Freiburg Freiburg, Germany


Contributors

Contributors

William E. Fantegrossi, Ph.D. Yerkes National Primate Research Center Emory University Atlanta, Georgia, USA Gerard B. Fox, Ph.D. Advanced Technology Abbott Laboratories Abbott Park, Illinois, USA Leonard L. Howell, Ph.D. Yerkes National Primate Research Center Department of Psychiatry and Behavioral Sciences and Department of Pharmacology Emory University Atlanta, Georgia, USA John R. James, Ph.D. Department of Pharmaceutics Virginia Commonwealth University Richmond, Virginia, USA Hyoung-gon Lee, Ph.D. Department of Pathology Case Western Reserve University Cleveland, Ohio, USA Edward D. Levin, Ph.D. Department of Psychiatry and Behavioral Sciences Duke University Medical Center Durham, North Carolina, USA Christopher D. Link, Ph.D. Institute for Behavioral Genetics University of Colorado Boulder, Colorado, USA Yuan Luo, Ph.D. Department of Pharmaceutical Sciences School of Pharmacy University of Maryland Baltimore, Maryland, USA


xix

xx

Dave Morgan, Ph.D. Department of Molecular Pharmacology and Physiology School of Biomedical Sciences College of Medicine University of South Florida Tampa, Florida, USA Paul Moser, Ph.D. Porsolt & Partners Pharmacology Boulogne-Billancourt, France Merle G. Paule, Ph.D. National Center for Toxicological Research Division of Neurotoxicology Jefferson, Arkansas, USA George Perry, Ph.D. College of Sciences University of Texas at San Antonio San Antonio, Texas, USA Roger D. Porsolt, Ph.D. Porsolt & Partners Pharmacology Boulogne-Billancourt, France Adam J. Prus, Ph.D. Psychology Department Northern Michigan University Marquette, Michigan, USA Richard J. Radek, M.S. Neuroscience Research Abbott Laboratories Abbott Park, Illinois, USA Jesse S. Rodriguez, Ph.D. National Center for Toxicological Research Division of Neurotoxicology Jefferson, Arkansas, USA John A. Rosecrans, Ph.D. Department of Pharmacology and Toxicology Virginia Commonwealth University Richmond, Virginia, USA


Contributors

Contributors

Nathan R. Rustay, Ph.D. Neuroscience Research Abbott Laboratories Abbott Park, Illinois, USA Laura Shuster Charlie Norwood Veterans Affairs Medical Center Augusta, Georgia, USA Mark A. Smith, Ph.D. Department of Pathology Case Western Reserve University Cleveland, Ohio, USA Barbara J. Strupp, Ph.D. Division of Nutritional Sciences and Department of Psychology Cornell University Ithaca, New York, USA Alvin V. Terry Jr., Ph.D. Department of Pharmacology and Toxicology Medical College of Georgia Augusta, Georgia, USA Rebecca Trueman, Ph.D. Cardiff School of Biosciences Cardiff University Cardiff, Wales, UK Yanjue Wu, Ph.D. Department of Pharmaceutical Sciences School of Pharmacy University of Maryland Baltimore, Maryland, USA Richard Young, Ph.D. Department of Medicinal Chemistry School of Pharmacy Virginia Commonwealth University Richmond, Virginia, USA Min Zhang, Ph.D. Neuroscience Research Abbott Laboratories Abbott Park, Illinois, USA


xxi

Mouse 1 Transgenic Models of Alzheimer’s Disease Behavioral Testing and Considerations Kathryn J. Bryan, Hyoung-gon Lee, George Perry, Mark A. Smith, and Gemma Casadesus CONTENTS 1.1 1.2

Introduction.....................................................................................................2 Behavioral Tests .............................................................................................. 2 1.2.1 Spatial Memory Tasks .........................................................................3 1.2.1.1 The Morris Water Maze .........................................................3 1.2.1.2 Radial Arm Maze...................................................................3 1.2.1.3 Radial Arm Water Maze ........................................................4 1.2.2 Contextual Memory ............................................................................. 4 1.2.2.1 Fear Conditioning................................................................... 4 1.2.2.2 Passive-Avoidance Learning .................................................. 5 1.2.3 Working Memory/Novelty/Activity ..................................................... 5 1.2.3.1 Y-Maze ................................................................................... 5 1.2.3.2 T-Maze.................................................................................... 6 1.2.3.3 Object Recognition................................................................. 6 1.2.3.4 Open Field ..............................................................................6 1.3 Transgenic Mouse Models of Alzheimer’s Disease........................................7 1.3.1 Amyloid-G Transgenic Mouse Models................................................. 7 1.3.2 Tau Transgenic Mouse Models ............................................................ 9 1.4 Concerns with Transgenic Mouse Models of Alzheimer’s Disease.............. 10 References................................................................................................................ 14

1


2

1.1

Methods of Behavior Analysis in Neuroscience, Second Edition

INTRODUCTION

One hundred years ago, the German psychiatrist and neuropathologist Alois Alzheimer gave a lecture in which he identified a disease of the cerebral cortex1 that would ultimately bear his name: Alzheimer’s disease (AD). In individuals with this condition, the cerebral cortex is thinner than normal and senile plaques, along with neurofibrillary tangles (NFTs), are found in the brain.2 In the early 1980s, the biochemical characterization of senile plaques in patients with Down’s syndrome and AD led to the identification of amyloid-G (AG) peptide as a major component. Thereafter, it was determined that AG is a product of the AG protein precursor (APP). The importance of AG/APP in the pathogenesis of AD is evidenced by the fact that genetic mutations in the APP gene invariably cause AD in cases with the early onset familial form of the disease.3–5 The relationship between APP and AG caused the research community to respond with quick enthusiasm for AG and laid the foundation for the amyloid cascade hypothesis.4,6 The amyloid cascade hypothesis states that mutations in APP (or other genes) lead to an increase in AG and that this then leads to disease. While the original hypothesis6 posited AG fibrils as the major mediator of the disease, a more recent incarnation of the hypothesis4 proposes smaller oligomeric forms of AG as key. In both cases, AG is viewed as being important in mediating the neuronal and synaptic toxicity that leads to the deterioration of cognition.7 Likewise, a steady influx of research began to elucidate the role of NFTs and their principal protein component, phosphorylated tau, in the brain and how these pathological entities related to the symptomatology of AD.8 While the pathological significance of AG and NFTs in disease, as well as their interaction is still under much discussion,9,10 the majority of investigators in the field are convinced that they play fundamental roles in the onset and progression of AD. That said, other theories of AD, unrelated to NFTs and AG deposits, are also being actively pursued (for review see11–15). Nevertheless, the development of transgenic mouse models of AD over the last decade has primarily focused on the pathological markers (NFTs and senile plaques), and such transgenic models have become promising tools to decipher the mechanistic importance of tau phosphorylation and AG deposits, as well their relationship between each other and the other pathological changes. While seemingly obvious, it is important to remember that the validity of a mouse model of disease is tightly linked to the ability of the animal to mimic the signs of the disease—in the case of AD, cognitive decline. The aim of this review is to discuss cognitive function in transgenic mouse models focused predominantly on AG and tau models and, thereafter, the validity of these models to study AD and the mechanistic questions that have arisen based on their behavioral phenotype.16,17

1.2

BEHAVIORAL TESTS

The most predominant and striking sign in an AD patient is the progressive decline in cognition, primarily due to loss of neurons and synapses in the hippocampal formation and related areas.18 As such, a “must have” feature of a valid AD-transgenic model is the ability of the model to accurately reflect the behavioral changes observed in human AD patients. To accurately interpret behavioral results from transgenic


Transgenic Mouse Models of Alzheimer’s Disease

3

mouse models of AD, it is important to intimately understand the behavioral tasks that are most often used to test cognitive changes in mice, as well as what each cognitive test is actually measuring. When examining cognition in animals, behavioral tasks are typically divided into either associative or operant learning tasks. Associative learning tasks use cues in the environment to condition a specific response in the animal. Operant learning tasks require the animal to make a particular response to a specific stimulus in order to receive an outcome. Cognitive tasks are further divided into groups by the type of memory being tested. The following are some of the most often used tasks to determine cognitive changes in mouse models, transgenic or otherwise.

1.2.1

SPATIAL MEMORY TASKS

1.2.1.1 The Morris Water Maze The Morris water maze (MWM) is a particularly sensitive task to examine agerelated/AD-like deficits because it is highly specific for hippocampal function, one of the first and most affected brain regions in AD.18 As a result, the MWM test is one of the most common behavioral tasks used to determine hippocampal spatial memory deficits.19 The test consists of placing the rodent in a circular tank filled with cloudy water, which is used to motivate the animal to escape the water by swimming to a hidden platform located right below the water’s surface. Over several days the rodent learns to find the hidden platform by using spatial cues, such as posters or taped objects strategically placed on the walls outside of the water maze, in the testing room. Distance swam, latency to reach the platform, and swim speed, most often recorded on video, are common measures of this test. The capacity of the animal to retrieve and retain learned information or the flexibility to purge and relearn new strategies can be determined using a probe trial and reversal trial. In the probe trial the platform is taken out and the animals are allowed to swim in the pool. Time spent in the region that previously contained the platform, crossings over the platform area, and time to reach the platform location are measured. The reversal trial is identical to the training trials, but in this case, the platform is switched to the opposite region of the pool, testing the cognitive flexibility of the animal that is necessary to relearn a new location. A cued version of this task, rendering the platform visible, can also be used to measure nonspatial strategies as well as visual acuity.20 Variations include the radial arm water maze (RAWM) or plus-shaped water maze.21 One desirable aspect of this task is that the motivating stimulus, i.e., escaping the water, does not require the food or water deprivation that is common in other spatial memory tasks. However, it has certain limitations as well, one of which is the fact that the various components of memory, i.e., reference and working memories, cannot be tested simultaneously. 1.2.1.2 Radial Arm Maze One task that can accommodate simultaneous measurement of memory components and has also been widely used to study spatial memory performance in rodents is the radial arm maze (RAM). This maze consists of 8–17 equally spaced arms radiating


4


from a central platform, which the rodent has to enter in order to attain a food or water reward placed in some of the arms. In this task, the animals guide themselves using spatial cues around the room, with the goal to enter each arm only once to receive the maximum amount of food or water rewards in the shortest period of time and with the least amount of effort. This maze requires the use of working memory to retain information that is important for a short time (within trial information), as well as the use of reference memory to retain the general rules of the task across days. Specifically, the animal must be able to remember which arms were baited as well as which it already entered (working memory), but it also must know to avoid non-baited arms across trials (reference memory), all of which takes place by being able to successfully encode spatial information. However, while this task permits the examination of both reference and working memory, major limitations are the use of food or water deprivation in this task, as well as the presence of odor confounds.22–24 1.2.1.3 Radial Arm Water Maze A relatively new spatial memory task, the RAWM, has been designed to eliminate the limitations of the above-mentioned tasks by combining the positive aspects of the MWM and RAM. The difference between the MWM and RAWM is that performance in the RAWM entails finding a platform that is submerged in water located in one of several arms (6–8) in the water bath, compared to the classic MWM which only has an open swim field. This makes the task a bit more difficult, but forces the animal to use spatial cues and working memory (keeping track of the arms it has already visited) to remember where the platform is located. Several variations of this task, using different numbers of platforms and platform location organization, have been used to examine spatial memory differences after pharmacological treatment25,26 and differences across species,27 gender,28 and, importantly, models of AD.24,29

1.2.2

CONTEXTUAL MEMORY

1.2.2.1 Fear Conditioning Freezing response, defined as a complete lack of movement, is the innate response of rodents to fear. In a fear conditioning paradigm, the animal is placed in a box containing a grid that delivers a mild aversive stimulus for two minutes. In the box, the animal is presented with a tone (usually 80 dB) (conditioned stimulus) that is paired with a mild shock (unconditioned stimulus) at the end of the trial with the result that the tone elicits the freezing response. Repeated exposures are sometimes necessary depending on the strain used or the interval time between the tone and the shock. Some researchers use trace fear conditioning, which increases the time gap between the tone and the shock in order to investigate prefrontal cortical activity. Here, the animal is taken out of the box and returned 24 hr later to evaluate its learned aversion for an environment associated with a mild aversive stimulus (context-dependent fear) by measuring freezing behavior in the absence of tone or aversive stimulus. Cuedependent fear can be measured by placing the animal in a new box that is different



5

in color, shape, etc., and presenting it with the tone as it explores the new environment; freezing behavior associated with the tone is measured. Fear conditioning is a widely used test to measure hippocampal-dependent associative learning. This test is thought to be sensitive to emotion-associated learning and therefore is a useful measure of amygdalar–hippocampal communication. Many of the transgenic mouse models of AD display impairments in fear and anxiety, which is primarily a function of the amygdala. The hippocampal function used in fear conditioning may be different from learning in a spatial task.30–32 1.2.2.2 Passive-Avoidance Learning In the passive-avoidance learning task, the animal must learn to avoid a mild aversive stimulus, in this case darkness, by remaining in the well-lit side of a two-chamber apparatus and not entering the dark where it receives the aversive stimulus. Note that since rodents innately gravitate to darkness, the animal has to suppress this tendency through pairing the negative stimulus with the desired compartment. Animals that do not remember the aversive stimulus will cross over earlier than animals that remember. Dependent measures include the median step-through latency (latency to cross into the unsafe side) and the percentage of animals from each experimental group that cross the threshold within an allocated time.20,33,34

1.2.3

WORKING MEMORY/NOVELTY/ACTIVITY

1.2.3.1 Y-Maze This test is based on the innate preference of mice to alternate arms when exploring a new environment. Various modifications are available with different levels of difficulty and different demands on specific types of cognition. One version that is particularly popular for the study of cognitive changes in AD transgenic models is the spontaneous alternation version of the Y-maze. In this instance, test animals are placed in a Y-shaped maze for 6–8 min and the number of arms entered, as well as the sequence of entries, is recorded and a score is calculated to determine alternation rate (degree of arm entries without repetitions). A high alternation rate is indicative of sustained cognition as the animals must remember which arm was entered last to not reenter it.35 A short-term memory version can also be carried out in which one arm of the Y-maze is blocked and the subject is allowed to explore the two arms for 15–30 min. The animal is then removed from the maze for a few minutes or up to several hours, depending on the experimental manipulation, and then placed back into the maze, this time with all arms open, to explore for 5 min. Animals with preserved cognitive function will remember the previously blocked arm and will enter that one first on the second trial. This test can also be repeated a week after the last trial with a delay time of only 2 min between the trials in order to test long-term memory and the time it takes the animal to relearn the task. Typically measured parameters include the first arm entered, amount of time spent in each arm, and total number of arm entries.35


6


1.2.3.2 T-Maze T-maze tasks are incredibly well characterized and are widely used for cognitive behavioral testing in both mice and rats. Animals are started at the base of the T and allowed to choose one of the goal arms abutting the other end of the stem. If two trials are given in quick succession, on the second trial the rodent tends to choose the arm not visited before, reflecting memory of the first choice. This is called “spontaneous alternation.” This tendency can be reinforced by making the animal hungry and rewarding it with a preferred food if it alternates. Both spontaneous and rewarded alternations are very sensitive to dysfunction of the hippocampus, and hence are sensitive to AD-like symptoms, but other brain structures are also involved. Each trial should be completed in less than 2 min, but the total number of trials required will vary according to statistical and scientific requirements.36 1.2.3.3 Object Recognition The object recognition test is based on the natural tendency of rodents to investigate a novel object instead of a familiar one, as well as their innate tendency to restart exploring when they are presented with a novel environment. The choice to explore the novel object, as well as the reactivation of exploration after object displacement, reflects the use of learning and recognition memory processes. The available objectrecognition tasks to test cognition in rodents use different numbers of available objects and environments in which the animals are tested, as well as types of configuration aimed to test spatial recognition and novelty, among other things. One particular object recognition task that is sensitive to age-related deficits is very suitable to test AD-related deficits.37–39 In this task, a rodent is placed in a circular open field filled with different objects (i.e., various plastic toys of different sizes and shapes) for 6 min. After a series of trials, during which the animal has habituated to the configuration and properties of the different objects, some of the objects are switched from one location to another to assess spatial recognition. Subsequently, some of the objects are replaced with new ones to evaluate novel object recognition. The time spent exploring the open field (movement/inactivity) as well as number of times and length of time inspecting each object over the different trials is calculated. 1.2.3.4 Open Field The open field locomotion test is used primarily to examine motor function by means of measuring spontaneous activity in an open field. The circular or square open fields vary in size depending on the experiment and are divided into distinct quadrants or sections. The animal is placed in the open field and the movements of the animal are either videotaped or monitored by automated computer programs. Rearing, line crosses, cleaning, general movement, number of lines crossed, preference for particular sections, and/or fecal movements can all be calculated to examine behavior and anxiety.40,41



1.3

TRANSGENIC MOUSE MODELS OF ALZHEIMER’S DISEASE

1.3.1

AMYLOID-G TRANSGENIC MOUSE MODELS

7

The first transgenic mouse model of AD, PDGF promoter expressing amyloid precursor protein (PDAPP), was developed in 1995 by Games et al.42 and displays increased human AG1–40 and AG1–42 that are 5–14 times higher than endogenous mouse AG. The PDGF-driven mouse human amyloid precusor displays synaptic loss; reductions in size of the hippocampus, fornix, and corpus callosum; and memory loss that is comparable to that of human AD patients.43 PDAPP mice older than 6 mo have been tested in the MWM, open field, radial arm maze, operant bar pressing, and visual object recognition tasks and have significant memory impairments on all tasks compared to age matched controls.29,44–46 For instance, when tested in the MWM, PDAPP mice have significantly higher swim latencies in finding the platform than controls. During open field trials and visual object recognition tasks, PDAPP mice tend to exhibit high levels of motor activity and revisit already explored areas or objects more often than control animals. PDAPP mice have further been tested in an associative learning task—the fear conditioning task—which relies on the ability of the animal to associate an auditory cue with a foot shock. After training, however, both PDAPP and control animals display the same amount of freezing response after the auditory cue is given, as well as when reexposed to the same training context.47 There are no studies to date that have examined how PDAPP mice perform if the context is altered (to context B). A better indicator of cognitive deficits involving the hippocampus compared to the auditory cue, which is primarily driven by the amygdala, would be to perform this test in an altered context, such as a dark room with a berry-scented odor, after initial training. No studies to date have explored different contexts. The deficits in cognition in the older PDAPP mice correlate with increased AG and reductions in the hippocampus/brain ratio. However, in many cases, the same cognitive deficits are also found in young (3–4 mo) animals in which AG deposits, or hippocampal formation reduction, are not yet apparent.43 As such, these results tend to not support the amyloid cascade hypothesis; however, the three types of mice, C57Bl/6, DBA/2J, and Swiss-Webster, that are used to produce a PDAPP mouse, are not the same for each study.43 This aspect will be further discussed, but it is important to mention that this is a recurring problem in all transgenic mouse models of AD. Another potential reason is that PDAPP mice tend to have lower body temperatures, which may result in varying degrees of hypothermia during the MWM task, which can produce amnesia in animals.4850 Although there are many theories as to why young PDAPP mice perform like older PDAPP mice, the reason for the inconsistencies in the literature is still unknown. Shortly after the PDAPP mouse was developed, another human mutant APP transgenic mouse model, which over-expresses the Swedish double mutant form of APP695, was introduced as the Tg2576 mouse.51 Tg2576 mice are similar to the PDAPP mouse in that they exhibit five times the level of endogenous murine APP in the brain and, after 11 mo, develop plaque-like deposits of AG1–40 and AG1–42/43 in the frontal, temporal, and entorhinal cortices; hippocampus; presubiculum; and cerebellum. Unlike the PDAPP mice, Tg2576 mice do not have significant synaptic


8


loss or reductions in hippocampal size. Tg2576 mice have been tested in many of the same tasks as the PDAPP mice. For example, mice at 2, 6, 9, and 12 mo of age have been tested in the MWM. In this regard, after 10 mo of age, this transgenic mouse line demonstrates poor spatial memory retention and is unable to find a visible platform after 2 and 4 days of training compared to controls.43,52 Tg2576 mice also tend to explore the familiar arm of the Y-maze more than controls. As with the PDAPP mice, Tg2576 mice are not always cognitively impaired. King and Arendash53 did not see cognitive deficits in the MWM task in young or old animals, but did find that the Tg2576 mice had sensorimotor deficits during the visual cue trials. However, many studies that did not find a difference in cognition between Tg2576 mice and controls did find a significant decline in memory if they eliminated animals that showed visual and/or motor deficits.43,54,55 Tg2576 mice have also been tested in a variety of Pavlovian tasks, such as fear conditioning. Older mice first trained in a salient context (context A) were then divided into subgroups, one of which was again tested in context A and the other in a novel context (context B). Based on the context-shift theory, normal animals perform well when trained and tested in the same context, but show a decline in memory when tested in the new context if they acquired the memory for the original training cues.56 Conversely, Tg2576 mice performed well in both contexts, unaffected by the change in cues, most likely because they were unable to remember the cues from the original training context. Although, Tg2576 mice did not distinguish between contextual cues, they were able to learn the fear response when trained with a specific cue, such as a sound or light. These results are consistent with the PDAPP mice.57 The accumulation of AG1–42 is dependent upon the cleavage of the G-secretase and the L-secretase enzymes. Individual enzymes known as presenilins are involved in L-secretase enzyme activity, and mutations in presenilins often lead to AG1–42 accumulation as found in AD patients.58 The first mouse model to examine the role of presenilin 1 (PS1) was produced by Shen et al.59 The PS1 knockout mice were deficient in PS1; however, they quickly died after birth. Massive neuronal loss and hemorrhages were found in the brain. Today there are a few types of PS1 and PS2 transgenic mouse models that survive after birth. All of the models that lack the PS1 or PS2 gene demonstrate cognitive decline on the MWM and on object recognition tasks, but compared to the Tg2576 animals, they are not severely impaired. In animals that over-express human PS1, high levels of AG1–42 were found, but without accompanying plaque-like accumulations or behavioral alterations.43,60 The first multiple gene transgenic mouse model of AD was developed to alter both the presenilins and the accumulation of human APP, today known as APP+PS1. Compared to the Tg2576 animals, the APP+PS1 has levels of AG1–40 five times higher by 6 mo of age.61 Young and old APP+PS1 mice have been tested in the Y-maze, elevated plus maze, MWM, and RAWM. Both young and old animals display deficits in the spontaneous alternation version of the Y-maze task, with fewer alternations between arms on the Y-maze. However, in the other behavioral tests, young animals tend to perform as well as controls, but by 15–17 mo of age, the APP+PS1 animals showed spatial deficits in the MWM and RAWM, and increased activity in an openfield test. This was one of the first transgenic mouse models that showed a strong positive correlation between AG1–42 development and cognitive decline.61–63



9

A second multi-gene PS1/APP mouse model, known as the PSAPP mouse, was developed from a different mutation in human PS1 (A246E) and was crossed with the Tg2576 mouse. AG1–42 and plaque loads occurred as early as 7 mo, earlier than in the Tg2576 mice. PSAPP mice perform similarly to the Tg2576 mice in a cued fear conditioning paradigm. Notably, PSAPP mice perform well at this test if they are given a cue, but are unable to distinguish altered contexts between training and testing, suggesting a hippocampal deficit. During spatial MWM testing, PSAPP mice have longer latencies to find the hidden platform, which is significantly correlated with the levels of insoluble hippocampal AG1–42.64 The CRND8 transgenic mouse is derived from an APP Swedish mutation and V717F mice. Plaque formation develops in the hippocampus and cortex around 9 wk of age. They differ from the PDAPP and Tg2576 mice in that they have dense core deposits and dystrophic neurites without hippocampal volume decreases. In an MWM test, CRND8 mice perform worse than controls when tested after plaques have developed.65 Hyde et al.66 confirmed that AG production occurs prior to the formation of plaques, and therefore animals at the pre-plaque, early/mid-plaque stage, and late-plaque stage were tested in the MWM. Pre-plaque animals perform as well as controls; however, both early/mid-plaque and late-plaque animals have deficits in swim time. Further, early/mid-plaque animals perform well on the probe trial, while the late-plaque animals do not.66 A more recent transgenic mouse model is the PDGF-APPSw,Ind mouse, which expresses the Swedish and Indiana APP mutations with increased BrdU and immature neuronal markers in the dentate gyrus and subventricular zone.67 This increased neurogenesis is also found in the brains of patients with AD. While neurogenesis in AD may be a result of increased injured neurons or the loss of neurons, the PDGFAPPSw,Ind, however, do not display neuronal loss, indicating that another mechanism is responsible for the neurogenesis.68

1.3.2

TAU TRANSGENIC MOUSE MODELS

Tau, a microtubule protein, is modified in AD, resulting in neuronal degeneration. Tau transgenic mouse models have been designed to model the NFT pathology often observed in AD. Early over-expressing tau transgenic mouse models demonstrate motor deficits and cell loss in the spinal cord; however, they did not develop “true” NFTs. Recently, a new tau transgenic mouse, P301S, was developed that demonstrates progressive NFT formation and neuronal loss,69 and NFT formation is found in the spinal cord, brainstem, cerebellum, diencephalon, and basal telencephalon when the expression of FTDP-17–associated mutation P301L is increased under the mouse prion promoter (JNPL3 line). Significantly, increased NFTs are correlated with a decline in MWM performance.70 Other mouse models using the P301S FTDP17–associated mutation, which show human tau is expressed in the spinal cord and hippocampus under the mouse Thy1.2 promoter, have phosphorylated tau, but do not have NFTs.71 The rTg(tauP301L) 4510 mouse expresses the P301L mutation in tau associated with frontotemporal dementia and develops NFTs in the neocortex and hippocampus, which is consistent with other tau transgenic mice. When tested in the MWM,


10


cognitive decline can be seen as early as 4 mo of age in the rTg(tauP301L) 4510 mice and this memory deficit is also accompanied by neuronal loss.72 The development of the P301S mouse allows researchers to examine the effect of AG on NFT formation. Injections of AG1–42 into the hippocampus of P301L mice leads to increased NFT numbers in the amygdala and hippocampus.73 The best model for AD, however, combines amyloid and tau pathology by crossing the APP, PS1, and P301L genes. The result is the 3xTg-AD mouse model, which develops amyloid plaques that quickly develop first in the neocortex and then spread to the hippocampus, and then develops NFT in the hippocampus shortly after the appearance of amyloid pathology. The 3xTg-AD mice display long-term potentiation deficits and precede plaque and tangle formation. A reduction in plaques and tangles occurs in response to immunotherapy treatment with AG antibodies.74 Cognitive testing of both male and female 3xTg-AD using the MWM and passive-avoidance tests displayed impairments by females and males by 4.5 mo of age. There were no differences between controls and 3xTg-AD on the object recognition task.75

1.4

CONCERNS WITH TRANSGENIC MOUSE MODELS OF ALZHEIMER’S DISEASE

Transgenic mouse models allow us to examine the mechanisms involved in the development of diseases such as AD. However, because of the large discrepancy in the behavioral findings observed across the now plentiful number of AD mouse models, a simple question that arises is whether we are really any closer today to determining what these mechanisms are than when the first PDAPP mouse was produced. The majority of AD research is carried out using animal models that have increased AG levels compared to controls, and while AG pathology is mimicked in these models, many other factors associated with AD pathology are not. For instance, as described above, many of the transgenic models, such as the Tg2576 and PS1+APP mice, do not have neuronal loss or larger ventricles, as would be expected in a true model of AD.51,54 We also cannot disregard the many AD mouse models that have increases in AG or APP, but do not demonstrate cognitive deficits.43,48,54,60 Inconsistencies in the literature could be due to differences in the behavioral protocols, type of tests that were conducted, age of the animals, the genetic background the transgenic animals were designed on, timing, sleep cycle of the animals, etc. Researchers often use a standard behavioral protocol, but the age of the animals, environmental cues, changes in researchers during the study, timing, techniques, handling, and time of day are difficult to keep constant from one lab to another. Any and all of these factors can affect behavioral outcomes. Likewise, the background of animals used for the transgenic mouse AD-model design influences how the animals will perform on various behavioral tasks.76 For instance, Pugh et al.76 found differences in learning of the passive avoidance task and MWM in two strains of mice (FVB/N and C57BL6/J) that are often used to engineer transgenic mouse lines. This information is an important factor when designing experiments and evaluating cognition testing. A lack of behavioral differences should not preclude the manipulated target from playing a role in the disease.



11

Another argument that further complicates the use of animal models based solely on APP and/or tau mutations is that other mechanisms may be at play.77 In this regard, the possibility that AG production and tau hyperphosphorylation are compensatory responses to other pathogenic mechanisms such as cell cycle dysregulation or oxidative stress has not been excluded.13,78 For example, oxidative stress as measured by 8-hydroxyguanosine (8OHG) and nitrotyrosine adduct formation, precedes AG deposition by decades in Down’s syndrome and AD patients.79–83 Moreover, the pathological lesions in the brains of patients with AD are associated with decreased oxidative markers compared to histologically unaffected but vulnerable neurons.16 Similarly, in Down’s syndrome, 8OHG immunoreactivity increases significantly in the teens and twenties, while AG burden only increases after age 30.79 Tau accumulation may also be an indicator of an oxidative imbalance. Oxidative stress and attendant modifications of tau byproducts of oxidative stress include Hydroxy-2,3nonenal (4-HNE) and other cytotoxic carbonyls, which may enable neurons modified by tau and neurofilament proteins to survive for decades.83 Mechanistic questions aside, the fact that studying AD via the use of mouse models carrying specific familial mutations to pathological entities of the disease (AG, tau hyperphosphorylation) may only provide a partial view rather than a complete picture of this disease.16 As such, some stereological studies have suggested that there may be little or no neuronal loss during “normal” aging, even though the number of plaques is increased.84 This observation parallels that observed in many of the transgenic mouse models. Importantly, like their human counterparts, these mice show evidence of oxidative stress that precedes the AG deposits.85,86 Also, due to the fact that AG may be an end product of an underlying cause of AD, researchers using transgenic AD models may ultimately be examining a later stage of AD, when cognitive decline is seen. Nevertheless, some reports of neuronal loss in various transgenic AD models argue that AG is a bioactive substance. Furthermore, because these models are based on mutations associated with early onset AD, careful evaluation is needed to determine whether they provide a compelling analogy to sporadic AD in humans, which comprises 95% of the cases. To address this issue, perhaps, animal models of aging rather than mutation-specific models may afford a more accurate picture of how all of these pathogenic entities interact for the development and progression of AD.87,88 In conclusion, the development of transgenic models of AD may provide tools to achieve an understanding of pathogenic mechanisms and develop new therapies. The efforts in this respect with regard to AD have been monumental, with several transgenic lines being available to researchers (Table 1.1). However, the validity of these models is overwhelmingly based on the ability of over-expression of APP and tau mutations to cause the pathological inclusions observed in the AD brain (plaques and NFTs); however, work is still needed to transfer this validity to other events-associated AD pathology. As such, AD transgenic mice differ in the timing and level of


12

TABLE 1.1 Transgenic Mouse Models of Alzheimer’s Disease Model Name

Gene

Promoter

Strain Background

Pathology

MWM

hAPP, V717f

PDGF-G

Swiss- Webster, C57B6, DBA

Plaques, ptau

Impaired, poor spatial memory, unable to find platform (6–9 mo) 44

Tg2576

Swedish

Hamster PrP

C57B6, SJL

Plaques, ptau

Impaired, poor spatial memory, unable to find platform (3 and 9 mo) 51,55

hPS1-2 Tg

Swedish

Hamster PrP

C57B6, PVBx129S6

Few plaques

Not impaired (6– 17 mo) 43,60

APP+PS1

Swedish

Hamster PrP

Swiss-Webster, B6D2F1

Plaques

Impaired, poor spatial memory, unable to find platform (15 mo) 90


Impaired, continued to visit same arms (3 mo) 45

Fear Conditioning

Passive Avoidance

Y-Maze

Good performance to auditory cue (11 mo) 47

Impaired, did not distinguish between training and testing cues (1618 mo) 57

Normal at 3 and 9 mo 89

Impaired, explored familiar arm more than controls (10, 16–18 mo) 54

Object Recognition

Open Field

Impaired, visited already explored areas/ objects (6, 9– 10 mo) 45

High levels of motor activity, visited already explored areas and objects (10 and 16 mo) 46

Normal, explored new objects more than old objects 54

Impaired at 15 mo, continued to visit same arms (12 mo) 43,60 Impaired, did not alternate between arms (5–14 wk)29,61,63

Increased activity (15– 17 mo) 29,63


PDAPP

RAM

Swedish

Hamster PrP

C3H/B6

Plaques

Impaired, poor spatial memory, took longer time to find platform (14 mo) 91

Tg CRND8

Swedish

Hamster PrP

C3H/C57B6

Plaques

Impaired during mid to late plaque development (6–17 mo) 39,65

JNPL3

Tau

PrP

C57/BL

Tau NFTs

Impaired with increasing levels of pTau (5 mo)

Impaired, did not distinguish between training and testing cues, but performed well if given an auditory cue (5 and 9 mo) 64


PSAPP

Impaired, prior to amyloid accumulation (3 mo) 61,62

70

rTg (tauP30 1L) 4510

Tau

PrP

3xTg-AD

Swedish

Thy1 (PS1 knockin)

FVB/N

Tau NFTs

Impaired, little to no retention of platform by 9.5 mo of age (4.5 mo) 69,72

Plaques Tau NFTs

Impaired (4.5 mo) 75

Impaired, shorter latencies to cross to dark side than controls (4.5 mo) 75

No impairment (4.5 mo) 75

13


14


AG, PS1/2, and tau accumulation, and not all of the animals demonstrate neuronal cell loss, or hippocampal atrophy and ventricular enlargement. More importantly, cognitive decline is not always correlated with AG deposits or NFT formation. AD pathogenesis is likely a syndrome rather than a disease of specific mutations. Therefore, full validation of an AD model will only be recognized when features of AD beyond tau and AG are incorporated in the models.

REFERENCES 1. Alzheimer, A. 1907. Uber eine eigenartige Erkrankung der Hirnrinde. Allg. Zeitschr. Psychiatr. 64:146–8. 2. Smith, M. A. 1998. Alzheimer disease. Int. Rev. Neurobiol. 42:1–54. 3. Glenner, G. G., and Wong, C. W. 1984. Alzheimer‘s disease and Down‘s syndrome: Sharing of a unique cerebrovascular amyloid fibril protein. Biochem. Biophys. Res. Commun. 122:1131–35. 4. Hardy, J., and Selkoe, D. J. 2002. The amyloid hypothesis of Alzheimer’s disease: Progress and problems on the road to therapeutics. Science 297:353–56. 5. Knowles, R. B., Gomez-Isla, T., and Hyman, B. T. 1998. AG associated neurophil changes: Correlation with neuronal loss and dementia. J. Neuropathol. Exp. Neurol. 57:1122–30. 6. Hardy, J. A., and Higgins, G. A. 1992. Alzheimer’s disease: The amyloid cascade hypothesis. Science 256:184–85. 7. Walsh, D. M., and Selkoe, D. J. 2004. Oligomers on the brain: The emerging role of soluble protein aggregates in neurodegeneration. Protein Pept. Lett. 11:213–28. 8. Tiraboschi, P., Sabbagh, M. N., Hansen, L. A., et al. 2004. Alzheimer disease without neocortical neurofibrillary tangles: ”A second look”. Neurology 62:1141–47. 9. Arriagada, P. V., Growdon, J. H., Hedley-Whyte, E. T., and Hyman, B. T. 1992. Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer’s disease. Neurology 42:631–39. 10. Roberson, E. D., Scearce-Levie, K., Palop, J. J., et al. 2007. Reducing endogenous tau ameliorates amyloid beta-induced deficits in an Alzheimer’s disease mouse model. Science 316:750–54. 11. Raina, A. K., Zhu, X., and Smith, M. A. 2004. Alzheimer’s disease and the cell cycle. Acta Neurobiol. Exp. (Wars) 64:107–12. 12. Casadesus, G., Atwood, C. S., Zhu, X., et al. 2005. Evidence for the role of gonadotropin hormones in the development of Alzheimer disease. Cell. Mol. Life Sci. 62:293–98. 13. Zhu, X., Raina, A. K., Perry, G., and Smith, M. A. 2004. Alzheimer’s disease: The twohit hypothesis. Lancet Neurol. 3:219–26. 14. Smith, M. A., Rottkamp, C. A., Nunomura, A., Raina, A. K., and Perry, G. 2000. Oxidative stress in Alzheimer’s disease. Biochim. Biophys. Acta 1502:139–44. 15. Sayre, L. M., Perry, G., Atwood, C. S., and Smith, M. A. 2000. The role of metals in neurodegenerative diseases. Cell. Mol. Biol. (Noisy-le-grand) 46:731–41. 16. Castellani, R. J., Lee, H. G., Zhu, X., et al. 2006. Neuropathology of Alzheimer disease: Pathognomonic but not pathogenic. Acta Neuropathol. (Berl). 111:503–9. 17. Berg, L., McKeel, D. W. Jr., Miller, J. P., Baty, J., and Morris, J. C. 1993. Neuropathological indexes of Alzheimer’s disease in demented and nondemented persons aged 80 years and older. Arch. Neurol. 50:349–58. 18. West, M. J. 1993. Regionally specific loss of neurons in the aging human hippocampus. Neurobiol. Aging 14:287–93. 19. Morris, R. 1984. Developments of a water-maze procedure for studying spatial learning in the rat. J. Neurosci. Methods 11:47–60.



15

20. Lawlor, P. A., Bland, R. J., Das, P., et al. 2007. Novel rat Alzheimer’s disease models based on AAV-mediated gene transfer to selectively increase hippocampal AG levels. Mol. Neurodegener. 2:11. 21. Vloeberghs, E., Van Dam, D., D’Hooge, R., Staufenbiel, M., and De Deyn, P. P. 2006. APP23 mice display working memory impairment in the plus-shaped water maze. Neurosci. Lett. 407:6–10. 22. de Toledo-Morrell, L., Morrell, F., and Fleming, S. 1984. Age-dependent deficits in spatial memory are related to impaired hippocampal kindling. Behav. Neurosci. 98:902–7. 23. Ikegami, S. 1994. Behavioral impairment in radial-arm maze learning and acetylcholine content of the hippocampus and cerebral cortex in aged mice. Behav. Brain Res. 65:103–11. 24. Morgan, D., Diamond, D. M., Gottschall, P. E., et al. 2000. A beta peptide vaccination prevents memory loss in an animal model of Alzheimer’s disease. Nature 408:982–85. 25. Shear, D. A., Dong, J., Haik-Creguer, K. L., et al. 1998. Chronic administration of quinolinic acid in the rat striatum causes spatial learning deficits in a radial arm water maze task. Exp. Neurol. 150:305–11. 26. Bimonte, H. A., and Denenberg, V. H. 1999. Estradiol facilitates performance as working memory load increases. Psychoneuroendocrinology 24:161–73. 27. Hyde, L. A., Hoplight, B. J., and Denenberg, V. H. 1998. Water version of the radial-arm maze: Learning in three inbred strains of mice. Brain Res. 785:236–44. 28. Bimonte, H. A., Hyde, L. A., Hoplight, B. J., and Denenberg, V. H. 2000. In two species, females exhibit superior working memory and inferior reference memory on the water radial-arm maze. Physiol. Behav. 70:311–17. 29. Arendash, G. W., Gordon, M. N., Diamond, D. M., et al. 2001. Behavioral assessment of Alzheimer’s transgenic mice following long-term Abeta vaccination: Task specificity and correlations between Abeta deposition and spatial memory. DNA Cell Biol. 20:737–44. 30. Fanselow, M. S. 1980. Conditioned and unconditional components of post-shock freezing. Pavlov. J. Biol. Sci. 15:177–82. 31. Fanselow, M. S., and Tighe, T. J. 1988. Contextual conditioning with massed versus distributed unconditional stimuli in the absence of explicit conditional stimuli. J. Exp. Psychol. Anim. Behav. Process. 14:187–99. 32. Hamann, S., Monarch, E. S., and Goldstein, F. C. 2002. Impaired fear conditioning in Alzheimer’s disease. Neuropsychologia 40:1187–95. 33. Senechal, Y., Kelly, P. H., and Dev, K. K. 2008. Amyloid precursor protein knockout mice show age-dependent deficits in passive avoidance learning. Behav. Brain Res. 186:126–32. 34. McGaugh, J. L. 1966. Time-dependent processes in memory storage. Science 153:1351–58. 35. Jackson, L. L. 1943. V.T.E. on an elevated maze. J. Comp. Psychol. 36:99–107. 36. Deacon, R. M., and Rawlins, J. N. 2006. T-maze alternation in the rodent. Nature protocols 1:7–12. 37. Shukitt-Hale, B., Casadesus, G., Cantuti-Castelvetri, I., and Joseph, J. A. 2001. Effect of age on object exploration, habituation, and response to spatial and nonspatial change. Behav. Neurosci. 115:1059–64. 38. Casadesus, G., Shukitt-Hale, B., Cantuti-Castelvetri, I., Rabin, B. M., and Joseph, J. A. 2004. The effects of heavy particle irradiation on exploration and response to environmental change. Adv. Space. Res. 33:1340–46.


16


39. Janus, C., Pearson, J., McLaurin, J., et al. 2000. A beta peptide immunization reduces behavioural impairment and plaques in a model of Alzheimer’s disease. Nature 408:979–82. 40. Hall, C. S. 1934. Emotional behavior in the rat: Defecation and urination as measures of individual differences in emotionality. J. Comp. Psychol. 18:385–403. 41. Hrnkova, M., Zilka, N., Minichova, Z., Koson, P., and Novak, M. 2007. Neurodegeneration caused by expression of human truncated tau leads to progressive neurobehavioural impairment in transgenic rats. Brain Res. 1130:206–13. 42. Games, D., Adams, D., Alessandrini, R., et al. 1995. Alzheimer-type neuropathology in transgenic mice overexpressing V717F beta-amyloid precursor protein. Nature 373:523–27. 43. Kobayashi, D. T., and Chen, K. S. 2005. Behavioral phenotypes of amyloid-based genetically modified mouse models of Alzheimer’s disease. Genes, Brain, and Behavior 4:173–96. 44. Chen, G., Chen, K. S., Knox, J., et al. 2000. A learning deficit related to age and betaamyloid plaques in a mouse model of Alzheimer’s disease. Nature 408:975–79. 45. Dodart, J. C., Meziane, H., Mathis, C., et al. 1999. Behavioral disturbances in transgenic mice overexpressing the V717F beta-amyloid precursor protein. Behav. Neurosci. 113:982–90. 46. Morgan, D. 2003. Learning and memory deficits in APP transgenic mouse models of amyloid deposition. Neurochem. Res. 28:1029–34. 47. Gerlai, R., Fitch, T., Bales, K. R., and Gitter, B. D. 2002. Behavioral impairment of APP(V717F) mice in fear conditioning: Is it only cognition? Behav. Brain Res. 136:503–9. 48. Justice, A., and Motter, R. 1997. Behavioral characterization of PDAPP transgenic Alzheimer mice. Soc. Neurosci. Abstr. 23:1637. 49. Rauch, T. M., Welch, D. I., and Gallego, L. 1989. Hypothermia impairs performance in the Morris water maze. Physiol. Behav. 46:315–20. 50. Richardson, R., Riccio, D. C., and Morilak, D. 1983. Anterograde memory loss induced by hypothermia in rats. Behav. Neural Biol. 37:76–88. 51. Hsiao, K., Chapman, P., Nilsen, S., et al. 1996. Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science 274:99–102. 52. Takeuchi, A., Irizarry, M. C., Duff, K., et al. 2000. Age-related amyloid beta deposition in transgenic mice overexpressing both Alzheimer mutant presenilin 1 and amyloid beta precursor protein Swedish mutant is not associated with global neuronal loss. Am. J. Pathol. 157:331–39. 53. King, D. L., and Arendash, G. W. 2002. Behavioral characterization of the Tg2576 transgenic model of Alzheimer’s disease through 19 months. Physiol. Behav. 75:627–42. 54. Arendash, G. W., and King, D. L. 2002. Intra- and intertask relationships in a behavioral test battery given to Tg2576 transgenic mice and controls. Physiol. Behav. 75:643–52. 55. Westerman, M. A., Cooper-Blacketer, D., Mariash, A., et al. 2002. The relationship between Abeta and memory in the Tg2576 mouse model of Alzheimer’s disease. J. Neurosci. 22:1858–67. 56. Riccio, D. C., Richardson, R., and Ebner, D. L. 1984. Memory retrieval deficits based upon altered contextual cues: A paradox. Psychol. Bull. 96:152–65. 57. Corcoran, K. A., Lu, Y., Turner, R. S., and Maren, S. 2002. Overexpression of hAPPswe impairs rewarded alternation and contextual fear conditioning in a transgenic mouse model of Alzheimer’s disease. Learn. Mem. 9:243–52. 58. Brunkan, A. L., and Goate, A. M. 2005. Presenilin function and gamma-secretase activity. J. Neurochem. 93:769–92. 59. Shen, J., Bronson, R. T., Chen, D. F., et al. 1997. Skeletal and CNS defects in Presenilin1-deficient mice. Cell 89:629–39.



17

60. Spires, T. L., and Hyman, B. T. 2005. Transgenic models of Alzheimer’s disease: Learning from animals. NeuroRx 2:423–37. 61. Holcomb, L., Gordon, M. N., McGowan, E., et al. 1998. Accelerated Alzheimer-type phenotype in transgenic mice carrying both mutant amyloid precursor protein and presenilin 1 transgenes. Nat. Med. 4:97–100. 62. Holcomb, L. A., Gordon, M. N., Jantzen, P., et al. 1999. Behavioral changes in transgenic mice expressing both amyloid precursor protein and presenilin-1 mutations: Lack of association with amyloid deposits. Behav. Genet. 29:177–85. 63. Arendash, G. W., King, D. L., Gordon, M. N., et al. 2001. Progressive, age-related behavioral impairments in transgenic mice carrying both mutant amyloid precursor protein and presenilin-1 transgenes. Brain Res. 891:42–53. 64. Dineley, K. T., Xia, X., Bui, D., Sweatt, J. D., and Zheng, H. 2002. Accelerated plaque accumulation, associative learning deficits, and up-regulation of alpha 7 nicotinic receptor protein in transgenic mice co-expressing mutant human presenilin 1 and amyloid precursor proteins. J. Biol. Chem. 277:22768–780. 65. Chishti, M. A., Yang, D. S., Janus, C., et al. 2001. Early-onset amyloid deposition and cognitive deficits in transgenic mice expressing a double mutant form of amyloid precursor protein 695. J. Biol. Chem. 276:21562-570. 66. Hyde, L. A., Kazdoba, T. M., Grilli, M., et al. 2005. Age-progressing cognitive impairments and neuropathology in transgenic CRND8 mice. Behav. Brain Res. 160:344–55. 67. Jin, K., Galvan, V., Xie, L., et al. 2004. Enhanced neurogenesis in Alzheimer’s disease transgenic (PDGF-APPSw,Ind) mice. Proc. Natl. Acad. Sci. U. S. A. 101:13363-367. 68. Casadesus, G., Zhu, X., Lee, H. G., et al. 2006. Neurogenesis in Alzheimer’s disease: Compensation, crisis, or chaos? In The cell cycle in the central nervous system, ed. D. Janigro, 359–70. Totowa: Humana Press. 69. Gotz, J., Chen, F., Barmettler, R., and Nitsch, R. M. 2001. Tau filament formation in transgenic mice expressing P301L tau. J. Biol. Chem. 276:529–34. 70. Ramsden, M., Kotilinek, L., Forster, C., et al. 2005. Age-dependent neurofibrillary tangle formation, neuron loss, and memory impairment in a mouse model of human tauopathy (P301L). J. Neurosci. 25:10637–647. 71. Allen, B., Ingram, E., Takao, M., et al. 2002. Abundant tau filaments and nonapoptotic neurodegeneration in transgenic mice expressing human P301S tau protein. J. Neurosci. 22:9340–51. 72. Gotz, J., Chen, F., van Dorpe, J., and Nitsch, R. M. 2001. Formation of neurofibrillary tangles in P301l tau transgenic mice induced by Abeta 42 fibrils. Science 293:1491–95. 73. Oddo, S., Caccamo, A., Kitazawa, M., Tseng, B. P., and LaFerla, F. M. 2003. Amyloid deposition precedes tangle formation in a triple transgenic model of Alzheimer’s disease. Neurobiol. Aging 24:1063–70. 74. Oddo, S., Caccamo, A., Shepherd, J. D., et al. 2003. Triple-transgenic model of Alzheimer’s disease with plaques and tangles: Intracellular Abeta and synaptic dysfunction. Neuron 39:409–21. 75. Clinton, L. K., Billings, L. M., Green, K. N., et al. 2007. Age-dependent sexual dimorphism in cognition and stress response in the 3xTg-AD mice. Neurobiol. Dis. 28:76–82. 76. Pugh, P. L., Ahmed, S. F., Smith, M. I., Upton, N., and Hunter, A. J. 2004. A behavioural characterisation of the FVB/N mouse strain. Behav. Brain Res. 155:283–89. 77. Lee, H. G., Casadesus, G., Zhu, X., et al. 2004. Challenging the amyloid cascade hypothesis: Senile plaques and amyloid-beta as protective adaptations to Alzheimer disease. Ann. N. Y. Acad. Sci. 1019:1–4.


18


78. Nunomura, A., Perry, G., Pappolla, M. A., et al. 1999. RNA oxidation is a prominent feature of vulnerable neurons in Alzheimer’s disease. J. Neurosci. 19:1959–64. 79. Nunomura, A., Perry, G., Pappolla, M. A., et al. 2000. Neuronal oxidative stress precedes amyloid-beta deposition in Down syndrome. J. Neuropathol. Exp. Neurol. 59:1011–17. 80. Nunomura, A., Perry, G., Aliev, G., et al. 2001. Oxidative damage is the earliest event in Alzheimer disease. J. Neuropathol. Exp. Neurol. 60:759–67. 81. Nunomura, A., Chiba, S., Lippa, C. F., et al. 2004. Neuronal RNA oxidation is a prominent feature of familial Alzheimer’s disease. Neurobiol. Dis. 17:108–13. 82. Odetti, P., Angelini, G., Dapino, D., et al. 1998. Early glycoxidation damage in brains from Down’s syndrome. Biochem. Biophys. Res. Commun. 243:849–51. 83. Long, J. M., Mouton, P. R., Jucker, M., and Ingram, D. K. 1999. What counts in brain aging? Design-based stereological analysis of cell number. J. Gerontol. A. Biol. Sci. Med. Sci. 54:B407–17. 84. Calhoun, M. E., Wiederhold, K. H., Abramowski, D., et al. 1998. Neuron loss in APP transgenic mice. Nature 395:755–56. 85. Morsch, R., Simon, W., and Coleman, P. D. 1999. Neurons may live for decades with neurofibrillary tangles. J. Neuropathol. Exp. Neurol. 58:188–97. 86. Smith, M. A., Hirai, K., Hsiao, K., et al. 1998. Amyloid-beta deposition in Alzheimer transgenic mice is associated with oxidative stress. J. Neurochem. 70:2212–15. 87. Wei, X., Zhang, Y., and Zhou, J. 1999. Alzheimer’s disease-related gene expression in the brain of senescence accelerated mouse. Neurosci. Lett. 268:139–42. 88. Butterfield, D. A., and Poon, H. F. 2005. The senescence-accelerated prone mouse (SAMP8): A model of age-related cognitive decline with relevance to alterations of the gene expression and protein abnormalities in Alzheimer’s disease. Exp. Gerontol. 40:774–83. 89. King, D. L., Arendash, G. W., Crawford, F., et al. 1999. Progressive and gender-dependent cognitive impairment in the APP(SW) transgenic mouse model for Alzheimer’s disease. Behav. Brain Res. 103:145–62.


and Contextual 2 Cued Fear Conditioning for Rodents Peter Curzon, Nathan R. Rustay, and Kaitlin E. Browman CONTENTS 2.1 2.2

2.3

2.4

2.5

2.6 2.7 2.8 2.9 2.10

Introduction...................................................................................................20 Contextual/Cued Fear Conditioning: Overview ........................................... 21 2.2.1 Contextual Fear Conditioning............................................................ 21 2.2.2 Cued Fear Conditioning..................................................................... 21 2.2.3 Delay and Trace Conditioning ........................................................... 21 Brain Areas Involved .................................................................................... 22 2.3.1 Amygdala ........................................................................................... 22 2.3.2 Hippocampus ..................................................................................... 22 2.3.3 Frontal/Ventromedial/Cingulate Cortex............................................ 22 Before Getting Started .................................................................................. 23 2.4.1 Types of Paradigms............................................................................ 23 2.4.1.1 Contextual/Cued Fear Conditioning .................................... 23 2.4.1.2 Contextual Conditioning ...................................................... 23 2.4.1.3 Delay/Cue Fear Conditioning...............................................24 2.4.1.4 Trace Fear Conditioning.......................................................24 2.4.1.5 Backward Trace Conditioning..............................................24 Sample Experiments .....................................................................................24 2.5.1 Delay Cued and Contextual Fear Conditioning.................................24 2.5.1.1 Day 1 ....................................................................................25 2.5.1.2 Day 2 ....................................................................................26 2.5.2 Trace Cued and Contextual Fear Conditioning .................................26 2.5.3 Contextual Fear Conditioning............................................................ 27 Data Analysis ................................................................................................ 27 Sample Data .................................................................................................. 27 Nonassociative Freezing Complications ....................................................... 29 Final Note...................................................................................................... 31 Addendum ..................................................................................................... 31 2.10.1 Available Equipment Options ............................................................ 31 2.10.2 Conditioning Chambers ..................................................................... 32 2.10.3 Considerations for the US (Shockers) ................................................ 33 19


20


2.10.4 Cued Conditioning Measurement ...................................................... 35 2.10.5 Measuring Freezing Behavior............................................................ 35 2.10.5.1 Hand Tallying Method ......................................................... 35 2.10.5.2 Activity Monitoring Method ................................................ 36 2.10.6 Animal Strain Considerations ........................................................... 36 2.10.7 Auditory Cue Considerations............................................................. 36 References................................................................................................................ 37

2.1

INTRODUCTION

Understanding what an animal learns when exposed to novelty is of great interest to behavioral neuroscientists, but it can be challenging to understand what information is acquired in a particular learning session. The behavior of an animal has to be quantified using either visual or mechanical measures of a particular response. One way of elucidating mechanisms involved in discrete learning sessions is to study associative learning processes. Simplistically, associative learning is an adaptive process that allows an organism to learn to anticipate events. One form of associative learning that has been used in multiple species, including humans, is eye-blink conditioning. The most common species used, the rabbit, has yielded interesting results, especially in identifying and elucidating the involvement of the cerebral cortex. Similar procedures have been used in cats, rats, and humans. Another form of associative learning that has gained popularity with behavioral pharmacologists is fear conditioning. While the eye-blink procedure has overlap with context/cue fear conditioning and in many cases yields similar results, there are some basic differences between fear conditioning and eye-blink conditioning. One main difference is that eye-blink conditioning takes many more training trials to establish. Fear conditioning has gained popularity, in large part as a result of the need to characterize mutant mice and the effects of genetic alterations; therefore, this chapter primarily focuses on fear conditioning. Fear conditioning to either a cue or a context represents a form of associative learning that has been well used in many species.1 The majority of the experiments reported in the literature involve the mouse; however, there is also a generous proportion of the literature devoted to the rat. There are also several reports in higher species that are not covered in this chapter. In general any of the procedures described in this chapter can be used for either the rat or the mouse. The dependent measure used in contextual and cued (delay or trace) fear conditioning is a freezing response that takes place following pairing of an unconditioned stimulus (US), such as foot shock or air puff, with a conditioned stimulus (CS), a particular context and/or such a cue. In the case of rats and mice, this US is generally a foot shock. Obviously, if in a conditioning context one administers a foot shock that is paired with a tone, there will be learning not only to the tone, but also to the context. Two types of conditioning that are typically employed are delay or trace conditioning. Delay conditioning refers to a situation in which the US is administered to co-terminate with or occur immediately after the CS. Trace conditioning differs from delay conditioning in that the US follows an empty (“trace”) interval that separates the cessation of the CS from the onset of the US. Trace conditioning adds


Cued and Contextual Fear Conditioning for Rodents

21

additional complexity to delay conditioning, as the time interval between the CS and US requires the formation of a temporal relationship between the two stimuli. In this chapter we discuss the various challenges inherent in this type of procedure in order to enable the experimenter to set the conditions to best answer the questions being posed. One of the biggest advantages of cued and contextual fear conditioning in the rodent is that they are forms of passive learning that can be used in many strains of mice and rats, even when more pronounced motor deficits are problematic in other learning assays. As a consequence of these procedural advantages, contextual fear conditioning is gaining popularity, especially in the phenotyping of transgenic mice.

2.2

CONTEXTUAL/CUED FEAR CONDITIONING: OVERVIEW

In this section we review aspects of the different conditioning assays that are crucial in conducting these tests.

2.2.1

CONTEXTUAL FEAR CONDITIONING

Contextual fear conditioning is the most basic of the conditioning procedures. It involves taking an animal and placing it in a novel environment, providing an aversive stimulus, and then removing it. When the animal is returned to the same environment, it generally will demonstrate a freezing response if it remembers and associates that environment with the aversive stimulus. Freezing is a species-specific response to fear, which has been defined as “absence of movement except for respiration.” This may last for seconds to minutes depending on the strength of the aversive stimulus, the number of presentations, and the degree of learning achieved by the subject.

2.2.2

CUED FEAR CONDITIONING

Cued fear conditioning is similar to contextual conditioning, with one notable exception: a CS is added to the context. In order to separate context from cue conditioning some investigators provide their subjects with a preexposure trial to the context without a US. This then allows the animal to take in all the information about the context without the presence of the cue. On a second exposure to the context, the CS is presented and the animal is better able to learn the CS association because the context is not as accurate a predictor of shock as the CS (since the animal has previously experienced the context in the absence of shock). However, preexposure to the context alone is not sufficient to fully separate cue- and context-specific freezing behavior.

2.2.3

DELAY AND TRACE CONDITIONING

Although delay and trace conditioning differ procedurally in the presence (trace) or absence (delay) of a time interval between the termination of the CS and US, trace conditioning uses additional brain regions in order to establish the response. Depending on the particular region of interest (or learning realm), researchers should decide on the appropriate testing paradigm. The trace interval used can range from a


22


relatively short (2–5 sec) period, when only small learning differences in associative learning between trace and delay conditioning is observed, to quite long (45–60 sec) periods, when the association to the cue is very weak. Repeated training trials are needed for trace conditioning in order for the association between the CS and US to be formed. However, contextual learning remains strong.

2.3

BRAIN AREAS INVOLVED

The major brain areas shown to be involved in contextual and cued fear conditioning include the amygdala, hippocampus, frontal cortex, and cingulate cortex.

2.3.1

AMYGDALA

Attempts to identify the contribution of individual amygdaloid nuclei demonstrate that lesions to the lateral nucleus and central nucleus attenuated freezing to both contextual and auditory conditional stimuli, while lesions of the basal nuclei produced deficits in contextual and auditory fear conditioning when the damage included anterior lesions of the amygdala.2 Evidence suggests that the basolateral amygdala complex is a critical site for fear conditioning. This observation stems, in part, from evidence demonstrating that rodents with lesions to this neuroanatomical region demonstrate a lack of freezing in the presence of cues previously paired with foot shock. An important caveat is that some studies have suggested that an intact basolateral amygdala is not essential for the formation and expression of long-term cognitive/explicit memory of contextual fear conditioning,3 but may play more of an exclusive role in cue fear conditioning.

2.3.2

HIPPOCAMPUS

While learning of the context requires input from the hippocampus, especially dorsal hippocampus and CA3, experiments have shown that this input is not necessary specifically for the learning of cue associations. It has been demonstrated, however, that for trace conditioning, the hippocampus is required for learning the tone–shock association. Manipulating the interval or “gap” between the US and CS is one way studies has isolated hippocampal involvement. As the trace interval is increased from very short intervals of 1–2 sec to 15, 30, or 45 sec, the degree of associative cue learning is reduced. Also, human subjects with damage in the hippocampus have been shown to be able to acquire delay conditioning but are not able to acquire trace conditioning.4

2.3.3

FRONTAL/VENTROMEDIAL/CINGULATE CORTEX

The frontal/cingulate cortexes are areas of attentional learning and have been shown to be involved in the acquisition of new memories.5 Consistent with this role, lesions or pharmacological inactivation produce deficits in contextual conditioning. Combined results indicate that there may be significant redundancy in the neuroanatomical regions mediating fear conditioning. The ability to dissect aspects of memory is one of the advantages of this type of learning paradigm. To understand



23

some of the literature investigating the neuroanatomical underpinnings of contextual conditioning, we suggest additional reading.5–9

2.4

BEFORE GETTING STARTED

It is important to establish the elements of the test to which the animal may respond. If, in a given environment you deliver a shock (US) to the feet of a rat or mouse at the termination of an audible sound cue (CS), the animal will learn that the testing environment (context) is unpleasant. The animal will also learn that when the auditory cue is presented there will be a shock in the near future. If this pairing is repeated, the animal’s learning generally will be stronger, and when the animal is returned to the conditioning context, will not only freeze to the context but also to the audible cue. Freezing to this auditory cue will not be specific to the conditioning environment, and can also be observed in response to the cue in a totally new environment. A challenge is dissociating how much of the learning is to the cue and how much is to the context. One way would be a subtraction process where some animals are not subjected to the audible cue, but as you will see later in this chapter, in some cases the cue may interfere with contextual learning. Therefore, separation of context and cue is ideal to establish and understand what the animal is learning.10

2.4.1

TYPES OF PARADIGMS

2.4.1.1 Contextual/Cued Fear Conditioning It is important to understand the different methodologies and their implications before selecting the method that is best for the given research needs (see Figure 2.1 for a schematic). 2.4.1.2 Contextual Conditioning This occurs when an animal is placed in a new environment (chamber, cage, etc.) and is presented with a US.

A. Context Conditioning

US Tone CS

B. Delay Conditioning

US Tone CS

C. Trace Conditioning

US Tone CS

D. Backward Trace Conditioning

US

FIGURE 2.1 Four basic conditioning paradigms illustrating the timing of US (aversive stimulus) presentation.


24


2.4.1.3 Delay/Cue Fear Conditioning This conditioning takes place when the aversive stimulus is presented at the end of a cue (CS) (light, tone, odor), and is thus paired with the aversive stimulus (US). 2.4.1.4 Trace Fear Conditioning Trace fear conditioning is similar to delay fear conditioning except the cue is presented for a period of time and terminated. Then following a short interval (100 msec to 60 sec) an aversive stimulus is presented (Figure 2.1). 2.4.1.5 Backward Trace Conditioning Backward trace conditioning is used as a control group to ascertain that the measure of freezing in a trace-conditioning paradigm reflects learning of the association and not some arbitrary freezing behavior. In this paradigm the CS is presented after the US has already been presented for the trial. If the animal freezes to the tone when it has been trained in the backward trace conditioning, it suggests that the freezing is due to nonassociative factors, because the tone does not predict shock.

2.5

SAMPLE EXPERIMENTS

In the following section we detail two different procedures with variations that readers may consider for conducting experiments in their laboratories. General Considerations. Standard housing conditions are usually acceptable for animals used in conditioning. The one caveat is that the mice should be calm and healthy before testing. In the case of some strains, fighting is quite common in male mice. This is especially prevalent in C57BL/6 and in some transgenic mice strains such as the Tg2576. Many experimenters have opted to avoid males to overcome this problem, although there are some differences in responses between male and female mice. Generally, at least 8–12 animals per treatment group are needed to generate statistical significance. Note: Always give the mice ample habituation (60–90 min) to a novel environment if you need to change the location of animals before testing.

2.5.1

DELAY CUED AND CONTEXTUAL FEAR CONDITIONING

2-Trial Delay Cued and Contextual Fear Conditioning. This is a standard procedure shown to produce good cue learning and contextual learning. Place the equipment in a quiet room. It is convenient to have an anteroom in which to house the mice; however, this anteroom should be sound insulated from the testing room so that the mice in their home cages are not exposed to any auditory cues either before or after testing. If you are running more than one chamber in the room at a time, unless the separate conditioning chambers are totally isolated, it is



25

important to have the stimuli synchronized so that any noise leakage and response to shock will not interfere across animals. 2.5.1.1 Day 1 Set up the computer control programming of the equipment for conditioning so that a house light illuminates the chamber continuously during testing. Program a 120-sec habituation period before the first of two identical trials begins. This allows the animal to explore briefly and to take in the aspects of the chamber. A tone (auditory) cue is then presented, generally at a level of 70–80 dB (we use 80 dB) for 15–30 sec. A mild foot shock is administered during the last 2 sec of the tone presentation and co-terminates with the tone. The foot shock is generally 0.6 mA, (0.17–0.8 mA) for 1–2 sec. (The level you select will depend on your shock source; an initial shock titration experiment may be advisable.) After the shock presentation, an intertrial interval (60–210 sec) precedes a second identical trial. Following the final shock presentation, the house light should remain on for an additional 60 sec, to enable removing the mouse in a 30–60 sec time period after the last trial. In setting up for the experiment it is preferable to run a set of mice from a single home cage all at once. This prevents previously tested mice from affecting the behavior of cage mates. Therefore, as we have four training boxes in the conditioning room, we house our mice four per cage when possible. If desirable, mice can be weighed and injected in the anteroom before bringing them into the room for the conditioning session. Before starting, wipe out the chamber with the same solution you are using to clean the apparatus between animals to allow the first set of mice to experience the same odors as the groups that follow. We use 70% isopropyl alcohol. 1. The first mouse is removed from the home cage and gently placed into the conditioning chamber (repeat for the other mice in the cage). Start the training session for all the boxes in the room. The animals can be observed live or recorded. If video recording is not available, the freezing can be scored for any or all periods during training. Generally the mice will freeze when the tone comes on at the start of the second trial since they have already received one tone-shock pairing. These data can be used to assess rate of acquisition and/or effect of drug treatment in the conditioning session. 2. At the end of the training, remove the mice. Keep in mind that the mice have had a stressful experience and are likely to be more difficult to handle. Use caution and handle them gently to avoid influencing the consolidation process. Place the mice back in the home cage. 3. Between animals each cage is again cleaned/wiped out with the 70% alcohol solution and is readied for the next animal. 4. Try to disrupt animals as little as possible when moving them in and out of the room.


26


2.5.1.2 Day 2 1. It is important to conduct the contextual testing as similarly to the training session as possible to maximize context conditioning. This includes odor, lighting, time of day, etc. This also maximizes differences of the novel environment where changes are made to distinguish the environments. Subjects should be well habituated to a holding area before testing if they are moved. If they are housed in an anteroom, this saves time. 2. If the context testing is performed first, it is usual to do this at the same time of day as the training, using the same habituation procedure. 3. Clean the chamber as before, then place the first mouse in the chamber with the house light illuminated. For contextual conditioning testing, simply place the mouse into the illuminated training chamber for 3–5 min; there are no tone cues presented. The mouse can be observed for the presence or absence of freezing response live or recorded for later analysis. The mice should be removed promptly at the end of contextual testing and returned to the original home cage. 4. The testing chamber should be cleaned out as on the conditioning day. 5. Allow approximately 30 min before transferring them to a new location for cue testing. 6. If cue testing is being carried out in the same “altered conditioning chamber,” it is very important to clean out the chamber thoroughly, and it is best to use a novel odor in the chamber for subsequent cue testing 7. Another alternative is to transfer the mice to a novel test room and again allow 60 min for habituation. The cue testing chambers should be distinct in size, lighting intensity, background, floor texture, and odor (we use diluted vanilla extract food flavoring wiped on the floor). 8. The mouse is placed in the chamber and allowed to habituate for 3 min. The same intensity tone cue used in the conditioning session is then activated for the next 3 min. One additional minute of recording without the cue is taken before the animal is removed. Again the mouse freezing behavior can either be captured live or recorded for later analysis. Using a Kinder Scientific Motor Monitor, activity beam breaks are recorded and measures of freezing are derived from a computer analysis. In our studies we have used a criterion of fewer than three beam breaks in 3 or 5 sec as the criterion for freezing. In addition, simply using beam breaks as an activity score can also be useful.

2.5.2

TRACE CUED AND CONTEXTUAL FEAR CONDITIONING

Trace conditioning is carried out in a similar manner to delay conditioning. Differences in the procedures are related to the setup of the programming to run the conditioning phase. Generally, trace conditioning requires more trials for the animals to associate the cue with the US. Thus, for our trace-conditioning program we settled on a five trial procedure often seen in the literature. Computer Control. The conditioning session should start with a 60–120 sec habituation period, followed by presentation of a tone cue for 30 sec. Then there is a



27

gap (trace interval) between the end of the CS and the start of the shock (US). This trace interval can range from 2–60 sec. (Note: As the trace interval increases, the association becomes more difficult to learn. A 15-sec trace interval with five repeating trials appears to differentiate between delay conditioning and allows for reasonable associative learning.) Similar shock levels (0.5–0.75 mA) and duration (1–2 sec) are used as in delay conditioning. Following each shock, a variable intertrial interval of 90–210 sec occurs when only the house light is illuminated. A variable intertrial interval is used between trials to minimize the possibility of the animals “expecting” a new trial. Again, wait 30–60 sec after the final shock to remove the animals from the chambers. Day 2 testing for freezing to the context and cue are carried out as in delay conditioning.

2.5.3

CONTEXTUAL FEAR CONDITIONING

In cases where the experimenter is only interested in observing the fear response to the training context, the two-trial cued and contextual fear parameters can be used. In this case the tone (CS) is not presented in training. It would seem appropriate that the cue testing after the exposure to the original context would be superfluous; however, if the animals are then exposed to a novel context and freezing is measured, this measure of nonassociative freezing can be factored in the contextual freezing measure by simple subtraction. Other Variations. The use of a variety of trial groups in which the CS and US are not paired within an experiment (e.g., in backward trace or backward conditioning) would show whether the learning taking place is a true measure of either delay or trace conditioning. These groups are appropriate behavioral controls.

2.6

DATA ANALYSIS

The data analysis is fairly simple for the context conditioning portion. Animals watched live or post-test can simply be timed for freezing individually and assessed a time of freezing. For a “normal” animal, this would lie in the 60%–80% range, however this will vary depending on the training paradigm and strain. As mentioned previously, if several animals are viewed simultaneously, one way to score freezing is to view each animal for time epochs and note whether freezing occurs or not.

2.7

SAMPLE DATA

Our initial experiments using delay and trace conditioning revealed some of the considerations highlighted in the previous sections. We will present some of those data and discuss some of these points. One would expect only mice that have received shock in the initial training using a tone CS to show freezing to the original context. Then, when in a novel environment for the cue test all the mice would show initial increased activity, and when presented with the CS again only mice that have made an association would demonstrate freezing. Also, the magnitude of the freezing response would demonstrate the extent of that “learned association.”


28

Methods of Behavior Analysis in Neuroscience, Second Edition Contextual Learning

Seconds Freezing in a 5 min Test

180

*sig. difference from ns

150 *

120 *

90 60 30 0 ns

t 30 0.17 mA t 30 0.35 mA Group (a) Cue Learning

150

*

Rest Time (s)

125 *

100 75

Group No shock 0.17 mA 0.35 mA *sig. increase over no tone control

50 25 0 No tone 1–3 min

Tone on 4–6 min (b)

FIGURE 2.2 (A) A measure of contextual learning, showing the magnitude of context freezing times in the original training context 24 hr post training without shock (ns), and that freezing times increase in relation to the shock level. (B) A measure of cue learning, showing the rest time (< 3 beam breaks in 5 sec) in a novel chamber before and after the presentation of the original CS (tone).

To demonstrate that mice learn this association we ran three groups of C57BL/6 mice using a five trial trace-conditioning paradigm with a 30-sec trace interval. The groups included a control group that did not receive shock during training and two groups of mice receiving shock, one at 0.17 mA and one at 0.35 mA. All mice were then tested 24 hr later in the conditioning chamber for contextual learning, followed by placement in a novel chamber to assess cue learning. As can be seen in Figure 2.2, the mice that did not receive shock during training did not freeze when assessed in the 5 min context testing session in the conditioning chamber 24 hr following training, whereas the animals that received shock froze in a significant shock related fashion. When later placed in the novel environment all mice showed some freezing to the novel environment in the first 3 min before the cue was presented, with the 0.35 mA shock group showing slightly more freezing. Following presentation of the original tone (CS) for the next 3 min there was a small increase in freezing that was


29


Seconds Freezing in a 3 min Test

180 150 120 90 60 30 0

Harlan

Delay

Jax

Harlan

Trace

Jax

Figure 2.3 Depicts the difference in freezing times (mean, +/- SEM) between C57BL/6 mice obtained from Jackson Labs (Jax) and Harlan Sprague Dawley (Harlan) when trained and tested for contextual conditioning 24 hr later.

not significant in the no-shock group (nonassociative freezing, which is discussed later), but there was a significant increase in the groups receiving shock, which indicates learning of the tone–shock association. Also studied was a direct comparison between C57BL/6 mice from two different suppliers, Jackson Labs and Harlan Sprague Dawley, Inc., keeping all environmental conditions equal. The mice were trained with five trials consisting of a 30 sec CS tone of 80 dB, and a shock (0.35 mA) administered for 2 sec, in either a delay conditioning procedure (US in the last 2 sec of the CS) or in a 30-sec trace conditioning procedure (US 30 sec following the termination of the CS). As can be seen in Figure 2.3, the Harlan mice exhibited more freezing than the Jax (Jackson Labs) mice in the original context; however, the Harlan and Jax mice were similar when trained with five trials of trace conditioning. These mice were also tested for cue conditioning in the Kinder Scientific Motor Monitors. In order to clearly show some supplier differences, Figure 2.4 shows the activity scores as beam breaks for the cue testing in a novel environment. It can be seen in the delay conditioning paradigm that mice from both Harlan and Jax demonstrate less activity when the tone is presented. However, the Jax mice recover their activity levels once the tone is turned off during the last minute of the session (see arrow), showing good associative learning; the Harlan mice do not show this. In addition, trace conditioned mice do not demonstrate this recovery of activity when the cue is turned off (minute 7). This could be interpreted as the demonstration that the mice trained in the trace conditioning paradigm learned that “tone off” is as good of a predictor of shock as is “tone on.” Also, Jax mice show more activity than the Harlan mice in the first 3 min of the session.

2.8

Nonassociative Freezing Complications

It has been shown that exposing rodents to foot shock will sometimes produce generalized, or nonassociative freezing to unconditioned stimuli, such as when placed


30


Delay

Time in Minutes

Trace

Activity Score

175 150

1 2

125

3

100

4 5

tone

6 7

no tone

75 50

no tone

25 0 Harlan

Jax

Harlan

Jax

FIGURE 2.4 Illustration of differences in freezing times (mean, +/- SEM) between C57BL/6 mice obtained from Jackson Labs (Jax) and Harlan Sprague Dawley (Harlan) when trained and tested for response to the cue when presented in a novel environment 24 hr later. The arrow points to the rapid recovery of activity in the 7th min by Jax mice only when trained in the delay paradigm.

in a novel environment.11 In our experience, we can see increased freezing to the tone stimulus in the novel environment in animals that have received contextual conditioning, i.e., those that have not been exposed to the tone during conditioning. To demonstrate these nonassociative freezing effects of the tone in our trace conditioning paradigm, we ran an experiment using groups of mice preexposed to the tone CS, thereby establishing it as a neutral stimulus. The experimental setup is seen below: the preexposure, conditioning, and context tests take place in the conditioning chamber, and the cue test takes place in a novel chamber. Group

Preexposure Day 1

Tone—Paired

Context Only

Tone—Unpaired Context and Tone

Conditioning Day 2

Context Test

Followed by Cue Test

Day 3

Tone and Shock

5 min Context

Cue Test with Tone

Shock Only

5 min Context

Cue Test with Tone

On day 1, an acclimation day, all mice were placed into the conditioning chamber. The “tone—unpaired” group was exposed to five 30-sec CS (tone 80 dB), and another “tone—paired” group of mice was exposed to the conditioning chamber without the tone. On day 2, both groups were again placed in the conditioning chamber. The unpaired tone group received five contextual conditioning (no tone) trials. The paired tone group received five trials of trace conditioning with a trace interval of 15 sec. The US was a 2-sec shock of 0.78 mA for both groups. This design resulted in both groups receiving an equal number of exposures to the tone (CS), the shock (US), and to the amount of time in the conditioning chamber. The


Cued and Contextual Fear Conditioning for Rodents Context Test

Cue Test Tone Paired Tone Unpaired

100 Percent Freezing

Percent Freezing 5 min Test

100 75 50 25 0 Tone Paired

Tone Unpaired

31

75 50 25 0

Pre-Cue

Cue Post-Cue

FIGURE 2.5 Illustration showing that nonassociative freezing to the tone cue can be reduced by preexposure to the tone in the unpaired group. Both groups had equal exposure to the tone cue, but mice in the unpaired group received tone exposure on the day prior to the foot shock conditioning. In the context test, mice trained with paired tone or unpaired tone showed similar freezing times. However, in the cue test, the paired group showed increased freezing to the tone.

only difference in the treatment of the two groups was the presence (paired) or absence (unpaired) of the tone on day 2 when the shock and tone association was presented. On day 3, both groups were tested first for contextual conditioning in the conditioning context for 5 min, then in a novel chamber with 3 min of no tone, 3 min of tone, and 1 min recovery (no tone). As can be seen in the Figure 2.5, both groups exhibited the same level of freezing in the conditioning context; however, the mice with a paired association exhibited a greater response when the CS was presented in the novel context. Statistical Analysis. Generally all that is needed is either a one- or two-way analysis of variance (ANOVA) with appropriate post hoc analysis comparing the various treatment groups using either the raw or percent freezing scores of the contextual freezing. In addition, this analysis may be performed on the data from the cued conditioning scores.

2.9

FINAL NOTE

We hope from reading this chapter the reader has gained a basic understanding of the cued and contextual fear conditioning paradigms used in rodents, and comprehension of the difference between trace and delay fear conditioning. This chapter is just a stepping-off point—there is a vast amount of literature that has been published on the involvement of the various brain regions responsible for associative learning, as well as the differences between trace and delay conditioning models. Using this information, one should easily be able to set up equipment to carry out studies that will lead to productive research. There is an extensive addendum to help you start testing.

2.10

ADDENDUM

2.10.1 AVAILABLE EQUIPMENT OPTIONS There are several options when it comes to choosing the equipment necessary to demonstrate a reliable cue and contextual fear response. The equipment does not


32


have to be terribly sophisticated and a number of labs that made their own chambers are still using the custom equipment. It is most important to be able to monitor the animals either visually (live or through the use of a video system) or by incorporating a movement monitoring system to reliably measure freezing behavior. Miniature video cameras are available, (for example, CCTVOne) and easily located inside an isolation cubicle to monitor the animal or record the session on tape or DVD. Recording of the behavior enables the researcher to review and reanalyze an experiment, which can be advantageous. Some laboratories perform live visual monitoring of animals during an experiment and when testing multiple animals simultaneously, and will time sample each chamber.

2.10.2 CONDITIONING CHAMBERS Chamber Size. The size of the chamber is not critical, but the chamber should be constructed to be easily cleaned and have a way to easily view the subject. In addition, if the same chamber is being used for both contextual and cued conditioning, it should be easily adaptable to making the context distinctly different when changing from contextual to cued conditioning. Making the chamber different should involve changes in the floor (e.g., from stainless steel bars to a solid plastic or equivalent), and changes in the inside dimensions by the addition of a diagonal divider. In addition, it is helpful to change the odor by using a diluted food essence. Equipment Examples. In this section we list some suppliers of fear conditioning equipment (Table 2.1). Kinder Scientific. Our lab uses equipment available from Kinder Scientific. The conditioning chamber we use consists of one side of the active avoidance system and is therefore used for contextual freezing testing (Figure 2.6). We run four chambers at a time that are under the control of one computer to maximize throughput. Each chamber is equipped with a video camera and the video output is fed into a splitter to record multiple animals on one DVD recorder. Coulbourn Habitest. Testing can also be achieved by using a Coulbourn Habitest chamber for conditioning and contextual fear testing. Cue testing can then be carried out in another chamber equipped with the same audible cue or by altering the conditioning chamber. Med Associates. Med Associates will sell a complete package for contextual fear conditioning and can include an infrared video analysis system that detects freezing (Figure 2.7). This analysis has been shown to be equivalent to visual scoring in a paper by Contarino and colleagues.12 There are confounds to learning when both cued and contextual conditioning are measured in the same chamber where the conditioning took place. San Diego Instruments. San Diego Instruments also provides a stand-alone Freeze Monitor that uses photocells in a higher density than a normal activity chamber arrangement. They also provide a separate Freeze Monitor context enclosure to detect nonassociative freezing. Clever Systems, Inc. Freeze Scan¥ is a software system for automatically detecting freezing states in rodents and fulfills the demand for high throughput screening. Freeze Scan¥ is a video-based tool that provides precise motion control for accu-



33

TABLE 2.1 Names and Addresses of Vendors Company Name

Company Contact Information

Clever Systems, Inc.

11425 Isaac Newton Square, Suite # 202 Reston, VA 20190. Tel: (703) 787-6946 Fax: (703) 787-6684 www.cleversysinc.com

CCTVOne

509 Mercury Lane Brea, CA 92821 Tel: (866) 582-2881 Fax: (714) 529-8599 www.cctvone.com

Coulbourn Instruments

7462 Penn Drive Allentown, PA 18106 Tel: (610) 395-3771 www.coulbourn.com

Kinder Scientific

2655 Danielson Court, Suite 308 Poway, CA 92064 Tel: (858) 679-15 Fax: (858) 679-4811

Med Associates, Inc.

PO Box 319 St. Albans, VT 05478 Tel: (802) 527-2343 Fax: (802) 527-5095 www.med-associates.com

San Diego Instruments

7758 Arjons Drive San Diego, CA 92126-4391 Tel: (858) 530-2600 Fax: (858) 530-2646 www.sandiegoinstruments.com

rate freezing detection. Freeze Scan¥ accepts video taken from different views in a confined chamber. It precisely detects the onset and completion of the freezing behavior of a rodent. Its output is a sequential list of the occurrences of the freezing behaviors. Further statistics can be analyzed from this output data. Freeze Scan¥ has the capability to set the same intervals generated by the tone, shock, or light control program. Clever Systems, Inc. can also provide the hardware for tone, shock, and light control for use in your chamber, and thus Freeze Scan¥ can synchronously work with the control program and provide accurate freezing state results based on these intervals.

2.10.3 CONSIDERATIONS FOR THE US (SHOCKERS) The level of shock produced as the US will vary to a great degree on the shock source (manufacturer). In order to present a standard shock level to each mouse or rat it is best to use a DC constant current source. Most commercially available shockers,


34


FIGURE 2.6

Kinder Scientific Learning and Memory Avoidance Systems.

FIGURE 2.7

MedAssociates Contextual Fear System including freezing detector.

such as those from Coulbourn Instruments, are square wave sources. This means that in contrast to AC or sine wave sources, there is an instantaneous rise time and off time that is more aversive at a lower current level. A scrambled shock is switched between the bars of the floor; the current is applied separately to each bar in a span of 8 bars that are sequenced over a 32-bar floor. The Kinder Scientific Active Avoidance box comes with an internal square wave constant current source. In the case of other chambers, external shock sources need to be supplied. Discrepancies in shock levels used in different laboratories usually can be attributed to the type of shocker used. The best measure is to actually observe the animal and gradually increase the



35

shock to a level where the animal first vocalizes and rapidly runs around the cage. This level is lower than that where the animals start jumping to avoid the shock, although some strains may show a hyperresponsivity to an initial shock. Note: It is advisable to use an oscilloscope to measure and view the shock output at the level of the grid in the test apparatus. This helps to reduce the possibility of not obtaining a reproducible effect.

2.10.4 CUED CONDITIONING MEASUREMENT The Kinder Scientific activity monitoring system has a board containing LED photocells that surrounds the chamber and measures beam breaks surrounding a Plexiglas chamber (7.5 in × 14 in) with a flat, white plastic tray floor that can be used for measuring conditioned association. The ceiling contains a lamp and a Mallory Sonalert® sound source identical to the ones used in training. We enclosed the chambers in a box made of pink insulation and the chambers were adapted to allow video recording of the animal behavior. You may also consider using the Kinder Scientific cued fear conditioning chamber or any of the other conditioning setups. However, it must be emphasized that the animal not only learns about the immediate context into which it was placed when it received the aversive stimulus, but it also learns all the events and places leading up to being placed in that context. To reduce any generalization from the conditioning context to the novel context, it is preferable to carry out the cue testing in a separate room with new visual, tactile, and olfactory cues.13 In our laboratory, the assessment of cued conditioning is conducted in a totally different sized room in the facility.

2.10.5 MEASURING FREEZING BEHAVIOR Two options are available for measuring freezing behavior. 2.10.5.1 Hand Tallying Method This method can be carried out in a few different ways. If the animals’ behavior is recorded, individual animals can be observed and continuously monitored for freezing. If it is desirable to monitor more than one animal simultaneously, then a sampling system can be adopted. For example, one method is to observe each cage sequentially for 5 sec and simply note whether freezing is occurring (yes or no) in each chamber for each 5-sec bin. These data can be recorded on a chart. If six cages were scored simultaneously for a 5-min session you would have 10 bins per animal. If an animal demonstrated freezing in five of the bins, this would translate to a 50% freezing score. Another similar approach is to monitor each animal once every 5–10 sec and note whether the animal is freezing at the exact moment of observation. Yes or no scores can be tabulated in an identical way as in the above approach. These sampling methods may not be as accurate as constant measuring, but if carried out uniformly they will yield reproducible results. In fact, it has been shown that scores obtained from these sampling methods correlate very highly with scores obtained from continuous sampling.12


36


2.10.5.2 Activity Monitoring Method This method takes into account distance traveled and/or the number of beams broken. In the Kinder analysis, the movement of the central part (centroid) of the animal is taken into account to calculate a “rest time.” An animal is considered at rest when there are fewer than a specific number of beam breaks in a specified period (the numbers can be specified by the experimenter). These time epochs are then counted up to give a rest time total in seconds. We consider an animal to be at rest or “freezing” if there are fewer than three beam breaks in 5 sec. The total freezing score is validated by independent observation and timing of the freezing response compared to the computer analysis of the rest time. San Diego Instruments has a similar system (Freeze Monitor) that uses a concentrated number of infrared photo beams measuring beam breaks. The analysis is similar to that described above. Infrared Video: A Fire-Wire® system is available from Med Associates, Inc. that can be used to detect freezing in the animal. This is a computer-based system that has been validated. See Anagnostaras and colleagues.14 Clever Systems also has a sophisticated online video analysis. This system uses a similar method of pixel analysis of the streamed video frames. Note: Whatever system you choose, it is always necessary to run a set of animals to demonstrate that any instrumentation analysis is producing data that correlates highly with those obtained using a visual scoring method.

2.10.6 ANIMAL STRAIN CONSIDERATIONS Many different mouse strains have been used for cued/contextual fear conditioning. Behavioral phenotype can affect the magnitude of the freezing behavior or the level of associative learning. In some strains of mice retinal degeneration is a background genetic defect that may or may not affect contextual freezing. In other cases, hearing deficits develop as the animal ages. Some mouse strains may demonstrate reduced responsiveness to foot shock. Therefore, when designing the experiment, the strain, cue type or magnitude, and aversive conditioning levels should be considered. In many studies that have reported optimal learning of the context and cue, researchers have used the C57BL/6 mouse with a white noise, tone, or clicker cue, and 0.4–0.6 mA shock level. Comparison of not only strain but also animal supplier may also yield different results and can be explored.15 In the case of rats (especially aged rats), quantification of the freezing response as well as variability in audition and response to shock could also affect the behavioral measures. Sprague Dawley rats tend to freeze more than other strains, and some of these problems have been overcome by using transmitters to measure changes in heart rate as the measure of conditioned fear.

2.10.7 AUDITORY CUE CONSIDERATIONS The superficial selection of the CS for the apparatus appears to be wide ranging. Studies have been conducted with clickers, white noise, and pure tones generally



37

between 70 and 85 dB. RadioShack makes a convenient meter that will give a good reading of dB levels. It should be set on continuous with “A” weighting to allow for mean dB levels. The noise-producing device is most effective if it can fill the chamber without noise “dead spots” to ensure that subjects will receive the CS regardless of their position in the chamber.

REFERENCES 1. Kim, J. J.. and Jung, M. W. 2006. Neural circuits and mechanisms involved in Pavlovian fear conditioning: A critical review. Neurosci. Biobehav. Rev. 30(2):188. 2. Goosens, K. A., and Maren, S. 2001. Contextual and auditory fear conditioning are mediated by the lateral, basal, and central amygdaloid nuclei in rats. Learn. Mem. 8(3):148–55. 3. Vazdarjanova, A., and McGaugh, J. L. 1998. Basolateral amygdala is not critical for cognitive memory of contextual fear conditioning. Proc. Natl. Acad. Sci. USA 95(25):15,003–7. 4. Clark, R. E., and Squire, L.R. 1998. Classical conditioning and brain systems: The role of awareness. Science 280(5360):77–81. 5. Pezze, M. A., and Feldon, J. 2004. Mesolimbic dopaminergic pathways in fear conditioning. Progress in Neurobiology 74(5):301–320. 6. Anagnostaras, S. G., Gale, G. D., and Fanselow, M. S. 2001. Hippocampus and contextual fear conditioning: Recent controversies and advances. Hippocampus 11(1):8–17. 7. Atallah, H. E., Frank, M. J., and O’Reilly, R. C. 2004. Hippocampus, cortex, and basal ganglia: Insights from computational models of complementary learning systems. Neurobiology of Learning and Memory 82(3):253–267. 8. Gewirtz, J. C., McNish, K. A., and Davis, M. 2000. Is the hippocampus necessary for contextual fear conditioning? Behavioural Brain Research 110(1–2):83–95. 9. Maren, S., and Holt, W. 2000. The hippocampus and contextual memory retrieval in Pavlovian conditioning. Behavioural Brain Research 110(1–2):97–108. 10. Rudy, J. W., Huff, N. C., and Matus-Amat, P. 2004. Understanding contextual fear conditioning: Insights from a two-process model. Neurosci. Biobehav. Rev. 28(7):675–685. 11. Balogh, S. A., and Wehner, J. M. 2003. Inbred mouse strain differences in the establishment of long-term fear memory. Behavioural Brain Research 140(1–2):97–106. 12. Contarino, A., Baca, L. Kennelly, A., and Gold, L. H. 2002. Automated assessment of conditioning parameters for context and cued fear in mice. Learn. Mem. 9(2):89–96. 13. White, N. M., and McDonald, R. J. 2002. Multiple parallel memory systems in the brain of the rat. Neurobiol. Learn. Mem. 77(2):125–84. 14. Anagnostaras, S. G., Josselyn, S. A., Frankland, P. W., and Silva, A. J. 2000. Computerassisted behavioral assessment of Pavlovian fear conditioning in mice. Learn. Mem. 7(1):58–72. 15. Schimanski, L. A., and Nguyen, P. V. 2004. Multidisciplinary approaches for investigating the mechanisms of hippocampus-dependent memory: A focus on inbred mouse strains. Neurosci. Biobehav. Rev. 28(5):463–83.


3 Drug Discrimination Richard Young CONTENTS 3.1 3.2

Introduction................................................................................................... 39 Methods......................................................................................................... 41 3.2.1 Apparatus........................................................................................... 41 3.2.2 Subjects .............................................................................................. 41 3.2.3 Operant Training................................................................................ 41 3.3 Drugs as Stimuli............................................................................................ 43 3.3.1 Discrimination Training Procedure................................................... 45 3.3.2 Discrimination Data........................................................................... 45 3.3.2.1 Percent Drug Lever Responding .......................................... 45 3.3.2.2 Response Rate ...................................................................... 47 3.4 Applications .................................................................................................. 47 3.4.1 Stimulus Generalization .................................................................... 47 3.4.2 Test Considerations ............................................................................48 3.4.2.1 Dose Response ..................................................................... 48 3.4.2.2 Comparison of Results of Test Agents ................................. 48 Data Analysis, Interpretation, Examples...................................................... 49 3.4.3.1 Statistical Analysis ............................................................... 50 3.4.3.2 Examples of Complete, Partial, and No Substitution........... 50 3.4.3.3 Time Course ......................................................................... 52 3.4.3.4 Stimulus Antagonism ........................................................... 53 3.5 Summary....................................................................................................... 54 References................................................................................................................ 56

3.1

INTRODUCTION

The psychoactive effect of a drug usually refers to a chemical agent that exerts an action upon the central nervous system (CNS), alters brain function, and, consequently, produces a temporary change in an individual’s mood, feelings, perception, and/or behavior. Such agents may be prescribed as therapeutic medications or used (or abused) as recreational drugs. In each case, the subjective effects produced by such agents are generally not accessible to independent verification by an observer. However, methods were developed about 50 years ago whereby human subjects could self-rate their experiences on questionnaires after administration of a drug.1 Generally, these self-inventories require subjects to provide information about themselves and are considered valuable because they venture “below the surface” to glean the effect of a drug on an individual. Also, they are convenient because they (usually) do 39


40


not require the services of a group of raters or interviewers. Their chief disadvantage may be that individuals might not completely understand the effect of the drug or their drug “experience” and therefore might not always give an accurate report. The drug discrimination (DD) paradigm is an assay of, and relates to, the subjective effect of drugs in nonhuman animals or humans. In a typical DD experiment, there are four basic components: (1) the subject, (2) the dose of drug that exerts an effect on the subject and precedes a response by the subject, (3) an appropriate (or correct) response, and (4) presentation of reinforcement. SUBJECT q DOSE OF DRUG q RESPONSE q REINFORCEMENT The drug effect that “leads to” a behavioral event (i.e., particular response) and signals that reinforcement is available is called the discriminative stimulus. A wide variety of psychoactive drugs can serve as discriminative stimuli (see below). In laboratory subjects, discriminative control by (usually) two treatments is established through the use of reinforcement (reward). When subjects receive a dose of a drug, it functions as a signal that prompts a correct behavioral response and results in the presentation of a reward. In other words, the effect of the drug is used as a “help” or “aid” to control appropriate behavioral responding by signaling that reinforcement is (or will be) available. Subjects are usually trained to distinguish administration of a particular dose of a particular drug (i.e., the training dose of a training drug) from administration of saline vehicle (i.e., usually a 0.9% sodium chloride solution that is often used as a solvent for many parenterally administered drugs). In a subject’s course of training sessions, the dose of drug is administered (i.e., drug sessions) and lever presses on the drug-designated lever (for that subject) produce reinforcement. In other training sessions, saline is administered (i.e., vehicle sessions) and responses on the (alternate) saline-designated lever produce reinforcement. The DD procedure can be characterized as a highly sensitive and very specific drug detection method that provides both quantitative and qualitative data on the effect of a training drug in relation to the effect of a test (i.e., challenge) agent. Historically, DD studies are linked by a common requirement that subjects must perform an appropriate (or correct) response that indicates a distinction was made between drug and nondrug conditions. As such, when employed with animals or humans, a subject’s response permits an experimenter to determine if a drug effect has been “perceived.” An excellent source of information on DD studies can be found at the Drug Discrimination Bibliography Web site (http://www.dd-database.org). The Web site, established and maintained by Drs. Ian P. Stolerman and Jonathan B. Kamien, is funded by the National Institute on Drug Abuse (NIDA) of the National Institutes of Health (NIH) and contains close to 4000 DD references published between 1951 and the present. The citations include DD abstracts, journal articles, reviews, book chapters, and books. In addition, the Web site can be navigated to selectively retrieve references on particular training drugs, drug classes, test drugs, authors, and DD methodologies.


Drug Discrimination

3.2

METHODS

3.2.1

APPARATUS

41

Behavioral experiments with animals are often conducted in testing environments that eliminate or minimize the occurrence of extraneous events or conditions (e.g., loud sounds, lights, temperature changes, etc.). The experimental setting is also designed to make more likely the occurrence of a particular behavior. For example, placing a hungry rat in a small chamber in which a lever is the most prominent object increases the likelihood that the animal will press the lever, which will result in the delivery of a reward. Studies of DD are often conducted in standard two-lever operant chambers (Coulbourn Instruments, Model E10-10, Lehigh Valley, Pennsylvania, USA, or Med Associates, Model ENV-008, St. Albans, Vermont, USA) housed within light- and sound-attenuating outer chambers. Typically, one wall of each operant chamber is fitted with two levers and a device, centered equidistant between the levers, to deliver reinforcement. The reinforcement may be, for example, a 45mg food pellet (e.g., Noyes Precision Pellets® PJAI-0045, Research Diets, Inc., New Brunswick, New Jersey, USA), sweetened condensed milk, or water (delivered in a 0.01 mL cup). An overhead 28-V house light illuminates each chamber. Solid-state and computer equipment are used to record lever presses, program the delivery of reinforcement, and record the number of reinforcements.

3.2.2

SUBJECTS

Table 3.1 shows that different species have been used as subjects in DD studies. To date, the rat has been used most often as the experimental subject in DD citations. Also of interest is the number of studies that cited humans as the experimental subjects. It is noted that DD procedures for humans are similar to those used for laboratory animals, but are adjusted to the uniqueness of humans. For example, drugs are usually administered under double-blind conditions and money typically serves as reinforcement for correct responses. In addition, many human DD studies include questionnaire data on subjective effects of the administered agent(s).12,13 In a DD study with animals or humans as subjects, however, the learning of a DD involves appropriate responses for the presentation of reinforcement under the pharmacological effect of different treatments.

3.2.3

OPERANT TRAINING

The discriminative stimulus effect of a drug is most frequently established via operant conditioning, a learning paradigm in which a subject emits a response that is followed closely by reinforcement. In general, operant behavior is “controlled” by its consequences. For example, a hungry rat may “act on” or “operate on” its environment and press a lever, which closes a switch and activates a food dispenser or liquid dipper to produce a pellet in a tray or liquid (e.g., sweetened milk) in a small cup. The operant is the behavior just prior to the reinforcement. In such a situation, the rat’s press of the lever, which is followed by reinforcement, may result in an increased probability of the animal pressing the lever in the future. In practice, however,


42


TABLE 3.1 Species Used as Subjects in Drug Discrimination Experiments Species

Citations

Reference (Example)

Cat, Dog, Guinea Pig

1 each

Kilbey and Ellinwood2 Cook et al.3 Hudzik et al.4

Gerbil

24

Jarbe et al.5

Human

262

Altman et al.6

Mice

97

Snoddy and Tessel7

Monkey

513

Schuster and Brady8

Pig

3

Carey and Fry10

Pigeon

360

Henriksson et al.10

Rat

2641

Barry11

Source: Data obtained from citations in Drug Discrimination Bibliography (http://www. dd-database.org).

operant conditioning is the study of behavior maintained by schedules of reinforcement, which are defined as the delivery of reinforcement to a subject according to some well-defined rule. In DD applications, the animals’ opportunity to press a lever under a schedule of reinforcement gives them, in effect, “communication” to the investigator of “how a drug affects their CNS.” It is also noted that schedules of reinforcement are used with humans and the pattern of responding is generally similar to those obtained with nonhuman animals. An animal’s initial training in a DD two-lever operant task begins with “magazine training,” which involves training the subject to eat from a food tray or drink from a dipper cup and, consequently, for it to learn that the noise made by the activation of the (mechanical) delivery device indicates the imminent presentation of “compensation.” At the beginning of the study, the experimenter teaches the rats to press a lever for reinforcement with the technique of successive approximation or “shaping.” The latter procedure involves the reinforcement of initial behavior that may only be vaguely similar to the final desired response (i.e., lever pressing); reinforcement continues for variations in behavior that come closer to pressing the lever. For example, an experimenter may begin with the presentation of reward (e.g., via a hand switch that bypasses a schedule of reinforcement) to a rat every time it turns toward a lever. Later, only movements that bring it closer to a lever are reinforced. After the rat has learned to approach a lever, it is not reinforced until it touches the lever. Eventually, the rat’s behavior will have been so shaped that it will readily press a lever when put in the chamber. (It is noted, however, that when a relatively large number of animals are used in an experiment, shaping can be a very timeconsuming procedure that requires much patience on the part of the experimenter.) When every press of the lever is followed by reinforcement, the organism is said to


Drug Discrimination

43

be on a continuous reinforcement schedule. As a consequence of such a schedule, the number of reinforcements could become quite high and might lead to decreased responding over time because of satiation. However, it is not necessary to reinforce every response in order to maintain responding. That is, an animal can be reinforced intermittently (i.e., part of the time). The intermittent schedule can be based on a portion of responses or on a time interval. The two most common schedules of reinforcement are ratio and interval schedules, each of which can be fixed (unvarying) or variable (random). In DD studies, the fixed ratio (FR) and variable (random) interval (VI or RI) schedules of reinforcement are used extensively and are discussed here. In an FR schedule the subject must complete a fixed number of responses in order to obtain reinforcement. In an FR 10 schedule, for example, every 10th response is reinforced. In VI schedules, the length of time elapsing before reinforcement is delivered varies around the mean value specified by the schedule. On a VI 15 sec schedule, reinforcement is available, on average, after 15 sec have elapsed since the last reinforcement but may be available, for example, as shortly as 2 sec later, or not until 60 sec have elapsed. The first response after a time interval has elapsed produces reinforcement for the organism. Once the rat learns to press on the right-side lever and the left-side lever under the schedule of reinforcement (e.g., FR or VI), DD training begins.

3.3

DRUGS AS STIMULI

Table 3.2 lists some of the drugs, from several different pharmacological and chemical classes, that have been shown to serve as stimuli. In most of these studies, either the FR or VI schedule of reinforcement was used to establish the discrimination. Although DD techniques have varied, it is typical that an organism is taught to respond on one lever (e.g., right-side lever) when a dose of training drug is administered before a training session and on another lever (e.g., left-side lever) when vehicle (e.g., saline) is given. Correct responses are intermittently reinforced by delivery of food (e.g., pellet, sweetened milk). The organism’s eventual learning of the correct response in a typical two-lever choice task involves its determination that the effect produced by the administration of the dose of the training drug on certain days is distinct from that produced by the injection of vehicle on other days. In general, there has been good agreement between species on (1) whether or not a particular drug can function as a discriminative stimulus, and (2) results obtained with test (or challenge) agents (see stimulus generalization tests below). The present survey describes some training and test results from rats trained to discriminate diazepam (3.0 mg/kg) from vehicle (one drop of Tween 80 per 10 mL distilled water) under an FR 10 schedule of reinforcement. For these studies, 12 experimentally naïve, male albino Sprague Dawley rats (Charles River Labs, Wilmington, Massachusetts, USA) weighing 325–350 g at the beginning of the experiment were used. Rats were housed individually and had free access to water, but were gradually food restricted to approximately 80% of their free-feeding weights before training began. The colony room was kept at a constant temperature (approximately 21–23°C) and humidity (~ 50%); lights were turned on from 0600 to 1800 hr.


44


TABLE 3.2 A Partial List of Drugs that Have Been Used as the Discriminative Stimulus in Drug Discrimination Experiments Drug

Drug Class or Mechanism of Action

Reference (Example)

Amphetamine

Stimulant

Schechter and Rosecrans14

Apomorphine

Dopamine receptor agonist

Colpaert et al.15

Atropine

Muscarinic antagonist

Barry and Kubena16

Buprenorphine

Partial agonist (μ-opioid receptor)

Holtzman17

Buspirone

Antianxiety

Hendry et al.18

Caffeine

Stimulant

Carney and Christensen19

Cholecystokinin

(Neuro) peptide hormone

De Witte et al.20

Chlorpromazine

Antipsychotic

Goas and Boston21

Clozapine

Antipsychotic

Browne and Koe22

Cocaine

Stimulant

Jarbe23

Desipramine

Antidepressant

Shearman et al.24

Dextromethorphan

Antitussive

Holtzman25

Diazepam

Antianxiety

Young et al.26

Diphenhydramine

Antihistamine

Winter27

DOMa

Hallucinogen

Young et al.28

Ephedrine

Agonist (adrenergic receptors)

Young and Glennon29

Ethanol

Stimulant/sedative

Schechter3

Fenfluramine

Appetite suppressant

Goudie31

Fentanyl

Opioid analgesic

Colpaert et al.32

LSD

Hallucinogen

Hirschhorn and Winter33

MDAc

Designer drug

Glennon and Young34

MDMAd

Designer drug

Glennon and Misenheimer3

Morphine

Opioid analegesic

Hirschhorn and Rosecrans36

Naloxone

Antagonist (μ-opioid receptor)

Carter and Leander37

Nicotine

Nicotinic acetylcholine receptor agent

Schechter and Rosecrans38

Agonist (NMDA receptor)

Willetts and Balster39

Pentazocine

Opioid analgesic

Kuhn et al.40

Pentobarbital

Sedative

Herling et al.4

Dissociative anesthetic

Brady and Balster42

(Neuro) steroid

Vanover3

Δ -THC

Cannabinoid1 receptor agent

Jarbe et al.44

Toluene

Solvent (Abused by Inhalation)

Rees et al.45

b

e

NMDA

f

PCP

Pregnenolone 9

g

Source: Data obtained from citations in Drug Discrimination Bibliography (http://www.dd-database. org). a1-(2,5-dimethoxy-4-methylphenyl)-2-aminopropane bLysergic acid diethylamide c1-(3,4-methylenedioxyphenyl)-2-aminopropane (3,4-MDA) dN-methyl-1-(3,4-methylenedioxyphenyl)-2-aminopropane e(N-methyl-D-aspartic acid) f1-(1-phenylcyclohexyl)piperidine (phencyclidine) gΔ9-tetrahydrocannabinol


Drug Discrimination

3.3.1

45

DISCRIMINATION TRAINING PROCEDURE

The dose-of-a-drug versus saline treatment paradigm constitutes the single most widely used DD procedure and its properties have been documented best. In the present example, the rats’ training sessions are preceded by an intraperitoneal (IP) injection of either 3 mg/kg of diazepam (dose is based on weight of base) or vehicle (one drop of Tween 80 per 10 mL of distilled water) with only the stimulus-appropriate lever present (i.e., left- or right-side lever). A pre-session injection interval (PSII) of 15 min is used; during this interval the animals are in their home cages. The route of administration and the PSII for the drug and its vehicle are typically chosen on the basis of the known pharmacokinetic properties and/or behavioral effect(s) of the drug. Training sessions are of 10 min duration, 5–7 days per week. For a particular session, just one of the two levers (i.e., the treatment-appropriate lever) is programmed to deliver reinforcement; presses on the incorrect lever have no programmed consequence. For six of the rats, responses on the right-side lever are reinforced after drug administration, while responses on the left-side lever are reinforced after vehicle administration; lever response conditions are reversed for the remaining six rats. In addition, lever assignments for a particular operant chamber are alternated (e.g., first animal in chamber 1 is assigned left-side lever as drug lever and right-side lever as saline lever; second animal in chamber 1 is assigned rightside lever as drug lever and left-side lever as saline lever, etc). The latter tactic is important because it has been observed that rodents may learn to use olfactory hints (or cues) that remain in the operant chamber from preceding animals.46 In addition, diazepam or vehicle is administered on a random schedule with the constraint that no more than two consecutive sessions with the drug or vehicle can occur; an equal number of drug and vehicle sessions occur. The experimenter will note that initial injections of the dose of training drug might hinder or disrupt the animals’ pressing of the drug-designated lever. Animals should develop behavioral tolerance to the disruptive effects of the drug (i.e., diazepam) and will, over time, perform the task. Animals do not, however, develop tolerance to the stimulus effect of the training dose of the training drug. If tolerance did develop, then the dose of the drug would not continue to serve as a discriminative stimulus and the animals’ performance would significantly decline.

3.3.2

DISCRIMINATION DATA

3.3.2.1 Percent Drug Lever Responding An animal’s degree of progress in learning the DD is determined by an evaluation of its distribution of presses on the two levers. In particular, an animal’s learning of the discrimination can be evaluated either prior to, or up to, the delivery of the first reinforcement. Thus, when an FR 10 schedule of reinforcement is used, DD learning can be assessed for each subject by dividing the number of responses that occurred on the drug-designated lever by the total number of responses that occurred on both levers up to the delivery of the first reinforcement; percent of responses on the drugappropriate lever is then obtained by multiplying the value by 100. For instance, assume that a rat has the right-side lever designated as the diazepam-appropriate lever. On a Monday, the animal is injected with 3 mg/kg of diazepam, placed in its


46


assigned operant chamber, and proceeds to press the left-side lever 9 times and the right-side lever 10 times; food reward (in this example) could be presented after the 10th right-side lever press. For this day, discriminative control would be assessed at 53% diazepam-appropriate responding (i.e., × 100). On Tuesday, this same rat is injected with vehicle, placed into its designated chamber, and presses the rightside lever 4 times and the left-side lever 10 times; food is presented after the 10th left-side press. On this day, discriminative control would be assessed at 29% diazepam-appropriate responding (i.e., × 100). Alternatively, if the VI schedule of reinforcement is programmed, then discrimination performance is evaluated during a short period (e.g., 2.5 min) of non-reinforced responding (referred to as extinction) at the beginning of a session; extinction sessions usually occur once or twice per week. Each animal’s distribution of presses on the two levers is then evaluated in the same manner as it is under the FR schedule of reinforcement. As might be expected, the administration of drug or vehicle during initial training sessions under either FR or VI schedules of reinforcement usually results in the animals dividing their responses equally (e.g., 50% diazepam-appropriate responding after injection of drug or saline) between the two levers (Figure 3.1). However, as training sessions progress with drug and vehicle, the animals gradually learn to respond on the drug-designated lever (i.e., percent of responses on the drug-designated lever is high and percent of responses on the vehicle-designated lever is low) when given drug, and on the vehicle-designated lever (i.e., percent of responses on the drug-designated lever is low and percent of responses on the vehicle-designated lever is high) when given vehicle. In other words, the learning of a DD occurs gradually over time

% Diazepam-Appropriate Responding

100 80 60

Diazepam (3.0 mg/kg) Vehicle (1.0 ml/kg)

40 20 0 0

5

10 15 20 25 30 35 40 45 50 55 60 Session

FIGURE 3.1 Learning curve results of rats trained to discriminate the stimulus effect of 3 mg/kg (IP) of diazepam (closed squares) from 1 mL/kg of vehicle (open squares). Ordinate: Mean (n = 12) percent (± SEM) of responses on the diazepam-appropriate lever after the administration of diazepam or vehicle. Abscissa: Number of sessions. Note that the animals gradually learn, as training sessions progress, to respond on the diazepam-designated lever when administered drug (i.e., percent of responses on the diazepam-assigned lever is high and percent of responses on the vehicle-designated lever is low) and on the vehicle-designated lever when administered vehicle (i.e., percent of responses on the diazepam-assigned lever is low and percent of responses on the vehicle-designated lever is high).


Drug Discrimination

47

(Figure 3.1). A generally accepted guideline is that after 6 to 9 wk of training, animals (individually and, consequently, as a group mean) consistently make ≥ 80% of their responses on the drug-appropriate lever after administration of drug (e.g., 3 mg/kg of diazepam) and ≤ 20% of their responses on the same lever after administration of vehicle (Figure 3.1). 3.3.2.2 Response Rate In addition to the animals’ distribution of responses on the two levers under FR or VI schedules of reinforcement, their response rate data (i.e., total number of responses on both levers expressed as responses per second or minute) also can be calculated. For example, animals’ (individual and/or group mean) response rate can be calculated under the FR schedule of reinforcement for a behavioral session (e.g., 15 min). Alternatively, under the VI schedule of reinforcement, the total number of responses made during the 2.5 min extinction session (or the entire session) can be recorded. The animals’ response rate can be viewed as another indicator of the effect(s) of a drug on behavior. In some cases, the animals’ response rate after the training dose of the training drug is suppressed when compared to that of the vehicle. In other instances, response rate data can assist the experimenter in the selection of (1) an appropriate training dose of the training drug, and/or (2) a range of doses to be examined for test drugs. Further, animals’ response rate can be an ancillary measure in cases where a test drug may, or may not, affect the main dependent variable (i.e., percent responding on the drug-designated lever). Finally, this parameter can be used in conjunction with an evaluation of the subjects’ general behavioral condition (e.g., sedated, incapacitated, overly excited).

3.4

APPLICATIONS

3.4.1

STIMULUS GENERALIZATION

Stimulus generalization of the training dose of the training drug is said to occur to the test drug if administration of the test substance results in the animals responding on the drug-designated lever. It is noted, however, that the phrase “stimulus generalization of the vehicle to the test agent” is not used when the animals respond on the vehicle-designated lever after administration of the test treatment; typically, the latter result would be characterized as “ the test agent induced vehicle-like responding.” In the present example, maintenance of the diazepam/vehicle discrimination was ensured by continuation of training sessions that were intermingled between stimulus generalization test sessions. Discrimination training sessions were conducted with 3 mg/kg of diazepam or vehicle on the four days prior to a stimulus generalization test session. On at least one of those days, six of the animals received 3 mg/kg of diazepam and the other six rats received vehicle; percent diazepam-appropriate responding was then determined under the FR schedule of reinforcement as described above. Animals not meeting the above criteria (i.e., ≥ 80% drug-appropriate responding after drug administration and ≤ 20% drug-appropriate responding after vehicle injection) were not used in that week’s stimulus generalization test. During generalization investigations, test sessions were interposed between


48


discrimination training sessions. In these test sessions, the rats were given a test treatment and then allowed to select one of the two levers in a 15-min session (FR procedure). The lever on which the animal first totaled 10 responses was regarded as the selected lever; percent diazepam-appropriate lever responding was calculated as described above. Subsequent reinforcement was delivered for responses on the selected lever according to the FR 10 schedule of reinforcement. Alternatively, if the VI schedule of reinforcement was programmed, then the animals would have been injected with test treatment, given a 2.5 min extinction session, and removed from the operant chambers; subsequently, percent diazepam-appropriate lever responding would have been calculated as described above.

3.4.2

TEST CONSIDERATIONS

3.4.2.1 Dose Response A very important consideration in tests of stimulus generalization is the necessity of a thorough dose-response investigation. An extensive literature review of DD tests of stimulus generalization reveals that certain agents produce saline-like effects at particular doses (usually relatively low doses), and disruption of behavior at some higher doses. While an initial conclusion to the results of such a study may be that there is a lack of stimulus generalization, it has been found in a number of instances that a careful evaluation of additional doses (i.e., doses between the highest dose that resulted in vehicle-like responding and the lowest dose that produced disruption of behavior) ultimately resulted in stimulus generalization. This has even been observed with agents where the difference in vehicle-like and disruptive doses has been quite small. Thus, several instances have been reported where doses of a challenge drug, administered in a logarithmic progression (e.g., 0.1, 0.3, 1, 3, 10 mg/kg), resulted in saline-like responding at the lower doses and disruption of behavior at the highest doses. However, an examination of doses between, for example, 3 mg/kg and 10 mg/kg resulted in stimulus generalization. As such, these types of situations appear to emphasize (1) that stimulus generalization to a test agent may occur within a “narrow window of doses,” and (2) the sensitive and specific nature of the druginduced stimulus. 3.4.2.2 Comparison of Results of Test Agents A preferred tactic is to evaluate doses of a challenge drug in drug-trained subjects until either stimulus generalization or disruption of behavior (i.e., no responding) occurs. If, for example, the highest test dose (e.g., dose X) of a challenge drug elicits 50% drug-appropriate responding, and, for some reason, the evaluation of higher doses is precluded, it is not appropriate to conclude that the challenge drug is half as potent as the training drug when, in fact, there has been no demonstration that the two agents can produce a common effect. In this situation, comparisons can only be made in a qualitative sense. That is, an appropriate conclusion that could be stated is that the challenge agent is less effective than the training drug in producing a training-drug–like effect (or, correspondingly, that it is less effective than some other challenge drug which, at a dose below dose X, produced training-drug–like


Drug Discrimination

49

effects). Likewise, if two challenge drugs produce partial generalization (e.g., 40% and 60% training-drug–appropriate responding) at dose X, it should not be stated with certainty that the second challenge drug is more potent than the first because the possibility exists that one (or both) agent(s) may not exert a stimulus effect that is common (i.e., complete generalization) to that of the training drug.

DATA ANALYSIS, INTERPRETATION, EXAMPLES In general, the phenomenon of generalization involves engaging in previously learned behaviors in response to new situations that resemble those in which the behavior was first learned. In the DD procedure, subjects respond to other drug stimuli that are more or less similar to those present during discrimination training. Stimulus generalization studies are used to determine whether a discriminative stimulus will generalize to (i.e., substitute for) other drugs. The rationale of this approach is that an animal trained to discriminate a dose of training drug will display stimulus generalization only to agents having a similar effect, though not necessarily an identical mechanism of action. Thus, in the present example, stimulus generalization is said to have occurred when the animals, after being administered a given dose of a challenge drug, make ≥ 80% of their responses on the diazepam-appropriate lever. Where stimulus generalization occurs, an effective dose 50% (ED50) value can be calculated, which reflects the dose at which the animals would be expected to make 50% of their responses on the diazepam-appropriate lever.47 In addition to complete stimulus generalization, two other results might be encountered: partial generalization and vehicle-appropriate responding. Partial generalization is said to have occurred when the animals, after being administered a thorough dose-effect test, make approximately 40%–70% of their responses on the diazepam-appropriate lever. In this case, percent diazepam-appropriate lever responding is not fully appropriate for either training condition. Data of this type are very difficult to interpret. However, it has been posited that partial generalization may occur with a test compound because there are pharmacological effects that are common to both the training drug and the challenge drug. Complete stimulus generalization does not occur, however, because the overlap of effects is incomplete. For example, one explanation for a partial generalization result may be that low doses of a test compound are similar to low doses of the training drug. However, as the dose of challenge drug is increased, another kind of pharmacological effect emerges. A third type of test result is that the administration of various doses of a challenge drug may result in ≤ 20% diazepam-appropriate responding. Such a result does not necessarily mean that a challenge drug is inert (i.e., without a pharmacological effect), but does suggest that the effect of the challenge drug is different from that produced by the training drug. Finally, an important factor in the interpretation of any DD data is that results must be considered in the context of the training drug. That is, the DD paradigm is used to generate data that are only valid with respect to a particular dose of a given training drug. The sensitivity and duration of effect of a stimulus are related to the training drug and are time dependent. As such, dose response relationships represent relative, not absolute, relationships between challenge drugs and training drugs. Finally, it should be recognized that when challenge drugs are being examined, the


50


data that are obtained relate to training-drug–like effects. For example, an investigation of the effect of a barbiturate in diazepam-trained animals does not provide data on barbiturate activity; rather, the data reflect the diazepam-like effect of the barbiturate (see example below). Thus, the result may or may not be the same as the effect of diazepam or a series of barbiturates in, for example, pentobarbital-trained animals. 3.4.3.1 Statistical Analysis The use of statistical analysis (e.g., analysis of variance, Fischer’s exact probability, t-tests, etc.) with DD data can be very problematic. One major concern is the failure of statistical procedures to account for behavioral disruption (i.e., no responding) into the analysis. In particular, an animal that fails to press a lever after being administered a dose of test agent in a stimulus generalization test cannot be assigned a percent score; 0% drug-appropriate responding cannot be assigned because it has a different meaning (i.e., the animal pressed the saline-appropriate lever). Some investigators argue that statistical analysis is robust enough to account for such missing data. However, the percent drug-appropriate lever responding data are not missing because the animals failed to appear for a test appointment. The data are lacking and unavailable because the drug interfered with the ability of the animal to respond. A more palpable description of such data is that the effect should be characterized as “disruption.” Statistically, one could (and some investigators do) ignore the disruptive effect of a dose of drug, use only the data from very few animals (sometimes n = 1 or 2 out of 6 or 8 subjects that were tested) that respond (usually those few subjects have responded to a high degree on the drug-designated lever), and statistically conclude the occurrence of stimulus generalization. However, in such cases, it would seem more appropriate and meaningful to characterize the effect as disruption rather than to promote a statistical conclusion that may be misleading. In any case, the most prudent approach to the presentation of stimulus generalization data in DD studies is to account fully, by description of the effects on subjects and/or statistically for the behavioral effect of the test agent in all subjects, individually and/or as a group. 3.4.3.2 Examples of Complete, Partial, and No Substitution In rats trained to discriminate the benzodiazepine diazepam at 3 mg/kg from vehicle at 1 mL/kg, the administration of lower doses of diazepam (i.e., construction of a dose-response function for diazepam) led to progressively less responding on the diazepam-appropriate lever (Figure 3.2); furthermore, an ED50 value (ED50 = 1.2 mg/ kg) was calculated. Moreover, several metabolites of diazepam were evaluated in tests of stimulus generalization. Figure 3.2 shows that the diazepam stimulus generalized in a dose-related manner to oxazepam (ED50 = 1.4 mg/kg), temazepam (ED50 = 1.4 mg/kg), and desmethyldiazepam (ED50 = 2.3 mg/kg). The latter results indicate that, in comparison with diazepam, the metabolites are relatively potent behaviorally, and indicate the distinct possibility that the metabolites may contribute to the stimulus effect of diazepam. Figure 3.2 also reveals that the diazepam stimulus generalized to the barbiturate anxiolytic/sedative pentobarbital (ED50 = 4.5 mg/kg), which illustrates the idea that animals trained to discriminate a dose of a training drug can display stimulus generalization to an agent that exerts a similar behavioral



Drug Discrimination

51

100

Diazepam Desmethyldiazepam Temazepam Oxazepam Pentobarbital Buspirone

80 60 40 20 0 0.1

1 Drug Dose (mg/kg IP)

10

FIGURE 3.2 Results of stimulus generalization tests with diazepam (closed squares), desmethyldiazepam (closed triangle), temazepam (closed inverted triangle), oxazepam (closed diamond), pentobarbital (closed circle), and buspirone (open square) in rats trained to discriminate 3 mg/kg of diazepam from vehicle. Ordinate: Mean (n = 12) percent (± SEM) of responses on the diazepam-appropriate lever after the administration of the test agents. Abscissa: Drug dose plotted on a logarithmic scale. Typically, a figure of response rates would appear below this figure.

effect, although not necessarily through an identical mechanism of action; diazepam and pentobarbital do not share the same mechanisms of action (see antagonism tests below). In comparison, the administration of buspirone (0.3–3.0 mg/kg), a serotonin 5-HT1A receptor (partial) agonist anxiolytic agent that is structurally unrelated to diazepam, produced only partial diazepam-appropriate lever responding (i.e., maximal 43% diazepam-appropriate lever responding), while the administration of doses between 4 mg/kg and 10 mg/kg produced disruption of behavior (Figure 3.2; disruption data not shown). Thus, the diazepam stimulus may partially generalize to buspirone because there may be some degree of pharmacological effects that is common to both diazepam and buspirone at low doses. Complete stimulus generalization does not occur, however, because the overlap of effects is incomplete. Lastly, the administration of S(+)-amphetamine (0.1–1.5 mg/kg), a CNS stimulant, to the diazepam-trained animals produced vehicle-appropriate responding (i.e., maximal 18% diazepam-appropriate lever responding; data not shown in Figure 3.2), while the administration of doses of 2–3 mg/kg produced disruption of behavior (i.e., no responding; data not depicted in Figure 3.2). Since percent diazepam-appropriate lever responding is fairly low (i.e., S(+)-amphetamine–induced responding on the vehicle-designated lever), it can be stated that the stimulus effect produced by 3.0 mg/kg of diazepam is quite different from that produced by S(+)-amphetamine. However, the fact that S(+)-amphetamine, and for that matter buspirone, can serve as training drugs indicates that these are not inert substances. Thus, animals trained in a DD task respond on the drug-designated lever only when administered a test agent that produces some degree of effect that is similar to the training dose of the training drug. If the test agent produces an effect that is “inert” or unlike that of the training drug, then responding will occur on the vehicle-designated lever until doses of the test agent are administered that disrupt lever response behavior by the animal (i.e., little or no responding). In a final comment, it is noted that results from stimulus gen-


52


eralization studies of test drugs under particular training agents have been consistent across different species trained under different schedules of reinforcement. 3.4.3.3 Time Course


Once a dose of a drug has been established as a discriminative stimulus, tests can be performed to determine its time course of actions. Such tests investigate the effects of changing the PSII of the training dose of drug and the beginning of a test session. In particular, the time course of any drug stimulus can be characterized by its latency of onset of action, peak activity, and duration of effect. The latency of onset of action refers to the time (or interval) between the administration of the training drug and the first indications of a marked effects on drug-appropriate responding. The peak activity of the drug refers to the time (or interval) that the drug exerts maximal percent drug-appropriate responding (i.e., ~80%–100% drug-appropriate responding). Lastly, the duration of action refers to the interval of time between onset of action and the point of time (or interval) that the drug no longer exerts percent drug-appropriate responding that is notable (i.e., ~20% drug-appropriate responding). In the present example, 3.0 mg/kg of diazepam was established as a discriminative stimulus with a 15 min PSII; PSII intervals of 5, 10, 30, 45, 90, 120, 180, and 240 min also were examined (Figure 3.3). The results indicated that the onset of effect of the diazepam stimulus occurred between the PSIIs of 5 min and 15 min; peak activity was exhibited from PSIIs of 10 min to approximately 90 min; and duration of action occurred between PSIIs of 10 min and ~180 min. In addition, Figure 3.3 illustrates the time course effects of the major metabolites of diazepam. These studies were conducted with the dose of each metabolite that produced stimulus generalization in the 3 mg/kg diazepam-trained animals: desmethyldiazepam (6 mg/kg), oxazepam (3 mg/kg), and temazepam (3 mg/kg). An important difference among benzodiaz-

100

Diazepam Desmethyldiazepam Temazepam Oxazepam

80 60 40 20 0 0

30 60 90 120 150 180 210 240 Pre-Session Injection Interval

FIGURE 3.3 Results of time course studies (i.e., stimulus generalization tests with various pre-session injection intervals) with diazepam (3 mg/kg; closed squares), desmethyldiazepam (6 mg/kg; open squares), temazepam (3 mg/kg; open triangle), and oxazepam (3 mg/kg; open circle) in rats trained to discriminate 3 mg/kg of diazepam from vehicle. Ordinate: Mean (n = 12) percent (± SEM) of responses on the diazepam-appropriate lever after the administration of the test agents. Abscissa: PSII. Typically, a figure of response rates would appear below this figure.


Drug Discrimination

53

epines is their pharmacokinetic properties. For example, in humans, diazepam is considered to have a relatively rapid onset of action and a relatively long half-life. In comparison, oxazepam and temazepam are considered to have slower onsets of action and much shorter half-lives, relative to diazepam. The time course studies of the stimulus effects of these agents in the diazepam-trained animals are not inconsistent with the human data. In any case, it is clear that familiarity with the time-course of action of the training drug or challenge compounds in tests of stimulus generalization and/or stimulus antagonism is of great importance; drug responses should not be measured too long, or short, after drug administration. 3.4.3.4 Stimulus Antagonism An effective strategy to determine the mechanisms of action of psychoactive agents is to study drugs that block their effects. In DD studies, the rationale of such an approach is that the training dose of the training agent will only be blocked by receptor antagonists that interfere with the mechanism of action of the drug. The results of antagonism tests, as with generalization tests, typically fall into one of three categories: (1) complete antagonism (i.e., saline-appropriate responding); (2) partial antagonism (i.e., ~ 40%–70% drug-appropriate responding); and (3) no antagonism (i.e., ≥ 80% drug-appropriate responding). Three strategies to study stimulus antagonism can be employed. One approach can determine whether the stimulus effect of the training dose of the training drug can be attenuated when various doses of an appropriate receptor antagonist are combined with the training dose of the training drug. Thus, the rats trained to 3.0 mg/kg of diazepam were administered various doses of the benzodiazepine receptor antagonist flumazenil prior to the administration of their training dose of training drug. If a drug is an effective antagonist, then a dose-related antagonism of the animals’ percent drug-appropriate responding should occur. Figure 3.4 shows that the administration of various doses of flumazenil (3–12 mg/kg) prior to the injection of the 3 mg/kg training dose of diazepam was sufficient to produce antagonism (i.e., responding ultimately occurred on the vehicle-designated lever). In contrast, the administration of various doses of flumazenil prior to the injection of the dose of pentobarbital (10 mg/kg) that produced complete stimulus generalization in these animals (see above) failed to produce antagonism (i.e., responding occurred on the diazepam-designated lever). Lastly, when the animals were administered doses of flumazenil (3–40 mg/kg) in control tests, they failed to respond on the diazepam-designated lever. Taken together, these data support the idea that diazepam and pentobarbital can induce a similar stimulus effect but the mechanism of action can be differentiated by flumazenil, a benzodiazepine receptor antagonist. In a second approach, the dose response of the training drug is determined in both the presence and absence of a constant dose of the antagonist. If the antagonism is competitive, then the dose response of the training drug (in the presence of the constant dose of the antagonist) should shift in a rightward and parallel manner. Figure 3.5 (top figure) shows the dose-response effect of diazepam in the absence (i.e., left dose-response function) and the presence (right dose-response effect) of flumazenil (5 mg/kg). As can be seen, pretreatment of the animals with flumazenil induced a rightward shift of the dose-response function of diazepam. In


Methods of Behavior Analysis in Neuroscience, Second Edition % Diazepam-Appropriate Responding

54

100 80 Flumazenil and Vehicle Flumazenil and DZP (3 mg/kg) Flumazenil and PB (10 mg/kg)

60 40 20 0 1

10 100 Flumazenil Dose (mg/kg IP)

FIGURE 3.4 The effect of flumazenil administered alone (open squares), in combination with 3 mg/kg of diazepam (DZP; open triangles), or in combination with 10 mg/kg of pentobarbital (PB; open circles). The administration of various doses of flumazenil prior to the injection of DZP produced a dose-related antagonism of the stimulus effect of DZP. In contrast, the administration of various doses of flumazenil prior to the injection of PB produced no attenuation of the diazepam-like response of PB. Lastly, flumazenil, administered alone, did not induce diazepam-appropriate responding. Ordinate: Mean (n = 12) percent (± SEM) of responses on the diazepam-appropriate lever after the administration of flumazenil (alone or) in combination with DZP or PB test. Abscissa: Flumazenil drug dose plotted on a logarithmic scale. Typically, a figure of response rates would appear below this figure.

a third approach, various doses of the training drug can be combined with various doses of the receptor antagonist. This approach will generate a series of trainingdrug/antagonist dose-response curves and probably provide the most comprehensive or detailed picture of the interaction between the agents. Figure 3.5 (bottom figure) shows the dose-response effect of diazepam in the absence (i.e., left dose-response function) and the presence (middle and far right dose-response effects) of flumazenil (5 mg/kg and 12 mg/kg, respectively). Clearly, the dose-response functions of the discriminative stimulus effect of diazepam were shifted rightward and these data strongly indicate the presence of competitive antagonism.

3.5

SUMMARY

The DD assay is a behavioral procedure whereby an organism must recognize a particular drug state, choose a correct response, and receive reinforcement. Most often, subjects are presented with the choice of two levers: one response (i.e., press of a left- or right-side lever) should be emitted in the presence of the training dose of a drug and a similar response (i.e., press of the alternate lever) should be emitted in the absence of the training drug. All other environmental conditions are held constant. Overall, DD studies have involved different species (including humans), learning paradigms (typically two-lever operant choice tasks that employ FR or VI schedules of reinforcement), and either solid or liquid reinforcement. Most often, studies have used rats that are trained to press levers on FR schedules of reinforcement for food pellets. Many agents from different psychoactive drug or chemical classes have been shown to serve as discriminative stimuli. Once trained, subjects can be



Drug Discrimination

55

100

Vehicle and DZP Flumazenil (5 mg/kg) and DZP

80 60 40 20 0 0.1

1

10


Diazepam Dose (mg/kg, IP)

100

Vehicle and DZP Flumazenil (5 mg/kg) and DZP Flumazenil (12 mg/kg) and DZP

80 60 40 20 0 0.1

1 10 100 Diazepam Dose (mg/kg, IP)

FIGURE 3.5 The effect of various doses of diazepam alone (DZP; closed squares) or in combination with 5 mg/kg of flumazenil (open squares) in rats trained to discriminate 3 mg/kg of diazepam from vehicle (top figure). The bottom figure depicts the effects of various doses of DZP alone (closed squares) or in combination with 5 mg/kg (open squares) or 12 mg/kg (open circles) of flumazenil. Ordinate: Mean (n = 12) percent (± SEM) of responses on the diazepam-appropriate lever after the administration of 5 mg/kg or 12 mg/kg of flumazenil in combination with various doses of DZP. Abscissa: Diazepam drug dose plotted on a logarithmic scale. Typically, a figure of response rates would appear below this figure.

“asked” whether they recognize a novel agent as producing a stimulus effect similar to that produced by the training dose of the training drug. Several factors can influence the results of such studies. For example, an important factor to be considered is the choice of doses to be examined for a particular challenge compound under investigation; the need for thorough dose-response investigations cannot be overemphasized because stimulus generalization can occur within a narrow window of doses. Moreover, studies have shown that drugs that generalize (substitute, transfer) to one another in tests of stimulus generalization in animals often produce similar effects in humans. Lastly, antagonism studies have evaluated the effects of purported receptor antagonists in combination with the training dose (or other doses) of the training drug. Such studies can elucidate a neurochemical mechanism involved in the discriminative stimulus properties of a drug. Taken together, the DD paradigm can be characterized as a highly sensitive and relatively specific “drug detection” assay that provides qualitative, quantitative, and mechanistic results of psychoactive agents.


56


REFERENCES 1. Beecher, H. K. 1959. Measurement of subjective responses: quantitative effects of drugs, 193–424. New York: Oxford University Press. 2. Kilbey, M. M., and Ellinwood, E. H. 1979. Discriminative stimulus properties of psychomotor stimulants in the cat. Psychopharmacology 63:151–153. 3. Cook, L., Davidson, A., Davies, D. J., and Kelleher, R. G. 1960. Epinephrine, norepinephrine, and acetylcholine as conditioned stimuli for avoidance behavior. Science 131:990–991. 4. Hudzik, T. J., Yanek, M., Porrey, T., et al. 2003. Behavioral pharmacology of ARA000002, a novel, selective 5-hydroxytryptamine1B antagonist. J. Pharmacol. Exp. Ther. 304:1072–1084. 5. Jarbe, T. U. C., Johansson, J. O., and Henriksson, B. G. 1975. Delta-9-tetrahydrocannabinol and pentobarbital as discriminative cues in the mongolian gerbil (Meriones unguiculatus). Pharmacol. Biochem. Behav. 3:403–410. 6. Altman, J. L., Albert, J., Milstein, S. L., and Greenberg, I. 1976. Drugs as discriminative events in humans. Psychopharmacol. Commun. 2:327–330. 7. Snoddy, A. M., and Tessel, R. E. 1983. Nisoxetine and amphetamine share discriminative stimulus properties in mice. Pharmacol. Biochem. Behav. 19:205–210. 8. Schuster, C. R., and Brady, J. V. 1971. The discriminative control of a food-reinforced operant by interoceptive stimulation. In Stimulus properties of drugs, ed. T. Thompson and R. Pickens, 1:133–148. New York: Appleton-Century Crofts. 9. Carey, M. P., Fry, J. P. 1991. A behavioral and pharmacological evaluation of the discriminative stimulus induced by pentylenetetrazole in the pig. Psychopharmacology 111:244–250. 10. Henriksson, B. G., Johansson, J. O., and Jarbe, T. U. C. 1975. Delta-9-tetrahydrocannabinol produced discrimination in pigeons. Pharmacol. Biochem. Behav. 3:771–774. 11. Barry, H. III, 1968. Prolonged measurements of discrimination between alcohol and nondrug states. J. Comp. Psychol. Psychol. 65:349–352. 12. Chait, L. D., Uhlenhuth, E. H., and Johanson, C. E. 1984. An experimental paradigm for studying the discriminative stimulus properties of drugs in humans. Psychopharmacology 82:272–274. 13. Kamien, J. B., Bickel, W. K., Hughes, J. R., Higgins, S. T., and Smith, B. J. 1993. Drug discrimination by humans compared to nonhumans: Current status and future directions. Psychopharmacology 111:259–270. 14. Schechter, M. D., and Rosecrans, J. A. 1973. D-amphetamine as a discriminative cue: Drugs with similar stimulus properties. Eur. J. Pharmacol. 21:212–216. 15. Colpaert, F. C., Niemegeers, C. J. E., Kuyps, J. J. M. D., and Janssen, P. A. J. 1975. Apomorphine as a discriminative stimulus, and its antagonism by haloperidol. Eur J. Pharmacol. 32:383–386. 16. Barry, H. III, and Kubena, R. K. 1972. Discriminative stimulus characteristics of alcohol, marihuana and atropine. In Drug addiction 1: Experimental pharmacology, ed. J. M. Singh, L. Miller, and H. Lal, 3–16. New York: Futura. 17. Holtzman, S. G. 1997. Discriminative stimulus effects of buprenorphine in the rat. Psychopharmacology 130:292–299. 18. Hendry, J. S., Balster, R. L., and Rosecrans, J. A. 1983. Discriminative stimulus properties of buspirone compared to central nervous system depressants in rats. Pharmacol. Biochem. Behav. 19:97–101. 19. Carney, J. M., and Christensen, H. D. 1980. Discriminative stimulus properties of caffeine: Studies using pure and natural products. Pharmacol. Biochem. Behav. 13:313.


Drug Discrimination

57

20. De Witte, P. H., Swanet, E., Gewiss, M., Goldman, S., Roques, B., and Vanderhaeghen, J. 1985. Psychopharmacological profile of cholecystokinin using the self- stimulation and drug discrimination paradigms. Ann. NY Acad. Sci. 448:470–487. 21. Goas, J. A., and Boston, J. E. 1978. Discriminative stimulus properties of clozapine and chlorpromazine. Pharmacol. Biochem. Behav. 8:235–241. 22. Browne, R. G., and Koe, B. K. 1982. Clozapine and agents with similar behavioral and biochemical properties. In Drug discrimination: Applications in CNS pharmacology, ed. F. C. Colpaert and J. L. Slangen, 241–254. Amsterdam: Elsevier. 23. Jarbe, T. U. C. 1978. Cocaine as a discriminative cue in rats: Interactions with neuroleptics and other drugs. Psychopharmacology 59:183–187. 24. Shearman, G. T., Miksic, S., and Lal, H. 1978. Discriminative stimulus properties of desipramine. Neuropharmacology 17:1045–1048. 25. Holtzman, S. G. 1994. Discriminative stimulus effects of dextromethorphan in the rat. Psychopharmacology 116:249–254. 26. Young, R., Glennon, R. A., Brasse, D. A., and Dewey, W. L. 1986. Potencies of diazepam metabolites in rats trained to discriminate diazepam. Life Sci. 39:17–20. 27. Winter, J. C. 1985. Sedation and the stimulus properties of antihistamines. Pharmacol. Biochem. Behav. 22:15–17. 28. Young, R., Glennon, R. A., and Rosecrans, J. A. 1980. Discriminative stimulus properties of the hallucinogenic agent DOM. Commun. Psychopharmacol. 4:501–506. 29. Young, R., and Glennon, R. A. 1998. Discriminative stimulus properties of (-)ephedrine. Pharmacol. Biochem. Behav. 60:771–775. 30. Schechter, M. D. 1974. Effect of propranolol, d-amphetamine and caffeine on ethanol as a discriminative cue. Eur. J. Pharmacol. 29:52–57. 31. Goudie, A. J. 1977. Discriminative stimulus properties of fenfluramine in an operant task: An analysis of its cue function. Psychopharmacology 53:97–102. 32. Colpaert, F. C., and Niemegeers, C. J. E. 1975. On the narcotic cuing action of fentanyl and other narcotic analgesic drugs. Arch. Int. Pharmacodyn. Ther. 217:170–172. 33. Hirschhorn, I. D., and Winter, J. C. 1971. Mescaline and lysergic acid diethylamide (LSD) as discriminative stimuli. Psychopharmacologia 22:64–71. 34. Glennon, R. A., and Young, R. 1984. MDA: A psychoactive agent with dual stimulus effects. Life Sci. 34:379–383. 35. Glennon, R. A., and Misenheimer, B. R. 1989. Stimulus effects of N-monoethyl-1(3,4-methylendioxyphenyl)-2-aminopropane (MDE) and N-hydroxy-1-(3,4-methylenedioxyphenyl)-2-aminopropane (N-OH MDA) in rats trained to discriminate MDMA from saline. Pharmacol. Biochem. Behav. 33:909–912. 36. Hirschhorn, I. D., and Rosecrans, J. A. 1974. A comparison of the stimulus effects of morphine and lysergic acid diethylamide (LSD). Pharmacol. Biochem. Behav. 2:361–366. 37. Carter, R. B., and Leander, J. D. 1982. Discriminative stimulus properties of naloxone. Psychopharmacology 77:305–308. 38. Schechter, M. D., and Rosecrans, J. A. 1972. Nicotine as a discriminative cue in rats: Inability of related drugs to produce a nicotine-like cueing effect. Psychopharmacologia 27:379–387. 39. Willetts, J., and Balster, R.,L. 1989. Effects of competitive and non competitive Nmethyl-D-aspartate (NMDA) antagonists in rats trained to discriminate NMDA from saline. J. Pharmacol. Exp. Ther. 251:627–633. 40. Kuhn, D. M., Greenberg, I., and Appel, J. B. 1976. Stimulus properties of the narcotic antagonist pentazocine similarity to morphine and antagonism by naloxone. J. Pharmacol. Exp. Ther. 196:121–127. 41. Herling, S., Valentino, R. J., and Winger, G. D. 1980. Discriminative stimulus effects of pentobarbital in pigeons. Psychopharmacology 71:21–28.


58


42. Brady, K. T., and Balster, R. L. 1981. Discriminative stimulus properties of phencyclidine and five analogues in the squirrel monkey. Pharmacol. Biochem. Behav. 14:213–218. 43. Vanover, K. E. 1997. Discriminative stimulus effects of the endogenous neuroactive steroid pregnanolone. Eur. J. Pharmacol. 327:97–101. 44. Jarbe, T. U. C., Henriksson, B. G., and Ohlin, G. C. 1977. Delta-9-THC as a discriminative cue in pigeons: Effects of delta-8-THC, CBD and CBN. Arch. Int. Pharmacodyn. Ther. 228:68–72. 45. Rees, D. C., Knisely, J. S., Jordan, S., and Balster, R. L. 1987. Discriminative stimulus properties of toluene in the mouse. Toxicol. Appl. Pharmacol. 88:97–104. 46. Extance, K., and Goudie, A. J. 1981. Inter-animal olfactory cues in operant drug discrimination procedures in rats. Psychopharmacology 73:363–371. 47. Finney, D. 1952. Probit analysis. 183–197. London: Cambridge University Press.


Place 4 Conditioned Preference Adam J. Prus, John R. James, and John A. Rosecrans CONTENTS 4.1 4.2 4.3 4.4 4.5

Introduction................................................................................................... 59 Research Design and Methodological Considerations..................................60 Training and Testing ..................................................................................... 63 Drug Studies Using the Conditioned Place Preference Paradigm ................64 The Mesolimbic Dopamine System Is Important for Conditioned Place Preference......................................................................................................64 4.6 Mechanisms Mediating Conditioned Place Preference for Common Drugs of Abuse ............................................................................................. 65 4.6.1 Opiates ............................................................................................... 65 4.6.2 Psychostimulants................................................................................66 4.6.3 Nicotine.............................................................................................. 67 4.6.4 Ethanol ............................................................................................... 67 4.6.5 MDMA............................................................................................... 68 4.6.6 Delta-9-THC and Endocannabinoids ................................................. 68 4.7 Conditioned Place Preference Versus Self-Administration .......................... 69 4.8 Summary....................................................................................................... 70 Acknowledgments.................................................................................................... 70 References................................................................................................................ 70

4.1

INTRODUCTION

The conditioned place preference paradigm is a standard preclinical behavioral model used to study the rewarding and aversive effects of drugs. Although a number of different designs and apparatuses are used in this model, the basic characteristics of this task involve the association of a particular environment with drug treatment, followed by the association of a different environment with the absence of the drug (i.e., the drug’s vehicle). A common variation of this design consists of a three-compartment chamber with the outer compartments being designed to have different characteristics (e.g., white vs. black walls, pine vs. corn bedding, horizontal grid vs. cross-grid flooring). The center compartment has no special characteristics and is not paired with a drug, and the gates between the compartments can be opened to allow an animal to pass freely between them. During training, an animal (typically 59


60


TABLE 4.1 Common Neuroscience Techniques Used in Conditioned Place Preference Research Technique

Example References

Lesioning

64, Spyraki et al. 1982b

Knockout mice

31

Microdialysis

53, Duvauchelle et al. 2000a, 55

Microinfusion

32, Rezayof et al. 2007b, 47

Neurotransmitter depletion

55

Strain comparisons

13

a rat or mouse) is given an injection of a drug with potentially rewarding or aversive properties, and is then placed into one of the outer compartments for several minutes. On the following day, the rat is injected with the drug’s vehicle and then placed in the opposite compartment. Generally, these daily sessions alternate between drug and vehicle for 2 or 3 days each. Afterward, a test session is conducted, which consists of placing the animal in the center compartment and then, after opening the gates to both of the outer compartments, recording the time the animal spends in each of the outer compartments during the session. A conditioned place preference (CPP) is found if the animals spend significantly more time in the drug-paired compartment versus the vehicle-paired compartment. On the other hand, if the animals spend significantly more time in the vehicle-paired compartment versus the drug-paired compartment, then this is considered a conditioned place aversion (CPA). Typically, drugs of abuse, such as cocaine, produce CPP, and drugs that elicit aversive effects, such as lithium chloride, produce CPA. As with other behavioral models used in pharmacology research, the behavioral effects of drugs used in the CPP paradigm depend on species, strain, route of administration, time interval of drug administration, dose concentration, and the CPP apparatus used. Many drugs of abuse produce both CPP and CPA, depending on the dose administered. In drug-dependent animals, withdrawal effects generally produce CPA. Because the CPP paradigm generally provides a reliable indicator for studying the rewarding effects of drugs that require relatively little training compared to self-administration paradigm, the CPP paradigm has been commonly used in conjunction with standard neuroscience techniques to elucidate the subjective effects of drugs (Table 4.1).

4.2

RESEARCH DESIGN AND METHODOLOGICAL CONSIDERATIONS

Although this chapter focuses primarily on studying the effects of drugs of abuse in the CPP model, CPP has also been established with food, copulatory activity, and other rewarding stimuli. The ability of a stimulus, whether it be a drug, food, etc., to produce a preference for the associated environment is generally considered a process governed by Pavlovian, i.e., classical or respondent, conditioning. Using the rewarding effects of a drug as an example, repeatedly pairing the rewarding


Conditioned Place Preference

61

effects of the drug (unconditioned stimulus, using Pavlov’s terminology) with certain stimuli (i.e., those contained within an environment) would be expected to result in the extension of these rewarding effects to the properties of these previously neutral stimuli. Thus, the drug-paired environment eventually serves as a conditioned stimulus (CS). Although it is not known if the compartment would actually serve as a CS in its truest sense (i.e., elicit rewarding effects similar to those produced by the drug of abuse), dopamine (DA) levels in the nucleus accumbens have been found to be elevated when rats are placed in the drug-paired environment, compared to the nondrug-paired environment.1 Although the three-compartment chamber described above is a common apparatus used in CPP research (Figure 4.1), other apparatuses vary from this design by having a different number of compartments (e.g., two or four compartments), assessing place preference within an open field, or allowing for the association of the interoceptive effects of drugs with a unique environment. Although all of these approaches have been used to study CPP, an important consideration in the choice of an apparatus is the decision to have a “forced choice” (i.e., the animal must choose the drug-paired side or the nondrug-paired side) or an “unforced choice” (i.e., the animal can remain in a compartment or other area of the apparatus that has not been associated with drug or vehicle) (Figure 4.2, top panel). Thus, a two-compartment apparatus would require a forced choice, whereas a three-compartment area could offer a central choice area between the experimental chambers. Although commonly used, the central concern of using a forced choice procedure is the potential of a bias for the compartment the animal was placed in during the test session. Another important consideration in CPP research is the use of biased versus unbiased research designs. These research designs are used to take into consideration the fact that subjects may have an initial preference for a particular compartment of the apparatus. For instance, if subjects were assessed for place preference in a twocompartment apparatus prior to conditioning, some subjects would spend more time in compartment A, whereas other subjects would spend more time in compartment B. In an unbiased CPP study, the assignment of a particular compartment for pairing with a drug is determined by the researcher, regardless of the preference of each subject for either compartment prior to conditioning (see Figure 4.2, bottom panel).

FIGURE 4.1 Standard two- (left) and three-chamber (right) shuttle boxes used to study conditioned place preference in rodents. Source: From Med-Associates, Inc., with permission.


Methods of Behavior Analysis in Neuroscience, Second Edition Unforced Choice

Forced Choice A

A

B

B

? Stay or

?

A

OR

B ? Stay or

Biased

Unbiased

A

B A

Most Preferred

B

Least Preferred Vehicle

Vehicle

Drug

Drug

?

?

FIgure . Unforced versus forced choice procedures (top panel) and biased versus unbiased designs (bottom panel) used in the conditioned place preference paradigm. In an unforced choice procedure, the subject is placed in a central choice area between the parts of the apparatus used for conditioning. In the forced choice procedure, a central choice area is not used. In the biased design, the baseline preference of the subjects for each part of the apparatus is assessed before condition sessions are begun. Each subject’s least preferred compartment is paired with the drug, and the most preferred compartment is paired with the drug’s vehicle. In the unbiased design, assignment of drug or vehicle pairing with each compartment is made regardless of each subject’s baseline preference.

In a biased design, the preference of each individual subject for a particular environment prior to conditioning is assessed first by placing the animals in the apparatus, and then by assessing the amount of time the subjects spend in each compartment. The least-preferred compartment for each subject is then assigned to be the drugpaired compartment. Depending on the design used in a CPP study, different results


Conditioned Place Preference Baseline Preference

Nicotine Paired with Most Preferred Side

80

100 Percent Preference

Percent Preference

100

63

60 40 20 0

Baseline Preference

Nicotine Paired with Least Preferred Side

80 60

*

40 20 0

Least Most

Least Most

(a)

Least Most

Least Most

(b)

FIGURE 4.3 Effects of nicotine (0.4 mg/kg) in the conditioned place preference paradigm in a biased design with (A) nicotine paired with the most preferred side and (B) nicotine paired with the least preferred side. Baseline preferences for each compartment were assessed prior to conditioning. *p < 0.05 for the baseline preference versus preference after pairing with nicotine. Source: This figure was produced from data reported in Calcagnetti, D. J., and Schechter, M. D. 1994. Nicotine place preference using the biased method of conditioning. Prog. Neuropsychopharmacol. Biol. Psychiatry 18:925.

may occur. For example, early CPP2 studies with nicotine found discrepant findings between laboratories, which included no effect, CPP, or CPA. In an attempt to clarify these discrepancies, Calcagnetti and Schechter2 tested nicotine for CPP by first assessing the most and least preferred sides of a three-chamber shuttle box. After baseline preferences were assessed, half of the rats were assigned nicotine for the least preferred side and the remaining half were assigned nicotine for the most preferred side. Nicotine produced a CPP with the least preferred side, but failed to develop a CPP or CPA for the most preferred side (Figure 4.3). Consequently, randomly assigning compartments to be paired with nicotine without assessing baseline preferences may not result in a CPP. Other important methodological procedures that should be considered in CPP research include the drug’s time course, the number of conditioning sessions, and the sensory modalities used to discriminate between environments. Generally, drugs that have a slow onset and a long duration of action (e.g., phenobarbital) are not good reinforcers, and consequently, may not readily establish CPPs. For drugs that have potent rewarding properties, fewer conditioning sessions will be needed to establish a CPP (e.g., amphetamine), whereas drugs with weaker rewarding properties may require more conditioning sessions (e.g., nicotine). Finally, sensory modalities should be appropriate for the species being used. For example, visual cues are a poor choice for albino rats, whereas olfactory cues are an excellent choice for these rats. Tactile and auditory cues are also good choices when using rodents.

4.3

TRAINING AND TESTING

Several days of free access to all environments allows the animal to habituate to the apparatus, eliminating novelty as a confounding variable. Baseline data should be determined as an average amount of time spent in each chamber over 3–5 days.


64


The length of time necessary to determine baselines depends on the environmental differences between apparatus chambers. Generally, distinct environments require fewer baseline sessions, whereas less distinct or ambiguous environments require more baseline sessions. The testing of subjects is performed in a non-manipulated state. The percentage of time spent in each chamber is tabulated during the test session. If the animal spends more time in the chamber associated with treatment, the researcher can infer that the experimental manipulation had a rewarding effect on the affective state of the animal. If the opposite were to occur, then the researcher can infer that the experimental manipulation had an aversive effect on the affective state of the animal. Designs that include a novel chamber (e.g., the center chamber of a three-chamber shuttle box) do not allow free access to the novel chamber during the habituation period.

4.4

DRUG STUDIES USING THE CONDITIONED PLACE PREFERENCE PARADIGM

The CPP paradigm has been widely used in pharmacology, behavioral science, and neuroscience research. A recent database search of Pubmed (http://www.pubmed. gov) using the keywords “conditioned place preference” yielded 1398 results. The CPP paradigm has not simply been used as a screening tool for drug abuse potential, but has been used to study neurotransmitters, brain areas, genes, signaling pathways, and other mechanisms mediating the rewarding (or aversive) effects of drugs. The drugs studied in CPP have been the subject of many reviews.3,4 Generally, psychostimulants and opiates reliably produce a CPP in this paradigm. For example, systemic administration of cocaine, amphetamine, and nicotine have been found to produce a CPP after two or three pairings in rats and mice.5–14 In addition, CPP has been established with opiates, such as morphine, heroin, and buprenorphine, as well as drugs from other classes, including the CNS depressants ethanol and diazepam, the cannabinoid receptor agonist delta-9-tetrahydrocannabinal (THC), and the adrenoceptor agonist clonidine.15–19,8,20–32 Many of these compounds also produce CPA, depending on the dose administered. For example, nicotine produces CPP in rats that are administered doses between 0.4 and 0.8 mg/kg., whereas higher doses are reported to produce CPA.5,33 Similar findings have been shown with other drugs, such as morphine and the psychostimulant apomorphine.34–39

4.5

THE MESOLIMBIC DOPAMINE SYSTEM IS IMPORTANT FOR CONDITIONED PLACE PREFERENCE

Although these drugs differ in their CNS effects, the majority of CPP-producing drugs affect the mesolimbic DA system, which consists of DA pathways that originate in the ventral tegmental area (the A10 region in rodents) and terminate in limbic system structures, including the nucleus accumbens and hippocampus. Therefore, DA D2 receptor antagonists, such as haloperidol and metoclopramide, have been found to block CPP or CPA produced by systemically administered amphetamine, cocaine, morphine, and heroin.40–45 Moreover, direct injection of psychostimulants and opiates into the ventral tegmental area or the nucleus accumbens also produces



65

CPP, whereas direct injection of amphetamine or morphine into other areas, such as the prefrontal cortex, caudate, or amygdala, fails to produce CPP or CPA.46–52 In rats that developed a CPP for cocaine after conditioning, significantly greater elevations in DA levels were found in the nucleus accumbens after vehicle injection when rats were placed in the cocaine-paired compartment, as opposed to the vehicle-paired compartment.53,54 However, DA levels in the prefrontal cortex have also been found to be elevated in rats placed in an amphetamine-paired compartment after several days of conditioning, and selective depletion of prefrontal cortical norepinephrine prevents amphetamine- and morphine-induced CPP and amphetamine- and morphine-induced DA release in the nucleus accumbens.1,55,56 Selective lesioning of DA terminals using 6-hydroxydopamine in the ventral pallidum, another target region of mesolimbic DA neurons, has been shown to attenuate the development of cocaineinduced CPP.57 CPP has also resulted from morphine infusion into the hippocampus.58 Thus, although the nucleus accumbens is an important region that mediates the effects of drugs of abuse, other limbic structures, as well as structures that mediate limbic system function, may alter the ability of drugs of abuse to elicit CPP.

4.6

MECHANISMS MEDIATING CONDITIONED PLACE PREFERENCE FOR COMMON DRUGS OF ABUSE

4.6.1

OPIATES

As presented earlier, opiates, such as morphine, are capable of producing CPP in rats and mice. The ability of opiate drugs to elicit a CPP depends, in part, on the release of dopamine from mesolimbic DA neurons, because morphine- and heroininduced CPP can be blocked by the DA D2 receptor antagonists haloperidol and metoclopramide. Furthermore, direct injection of opiates into the ventral tegmental area or nucleus accumbens also produces CPP.40,42,46–48,49,51 Opiates are known to enhance mesolimbic DA neuronal firing and ultimately release DA into the nucleus accumbens, which has been shown to be caused by a disinhibition of DA neurons in the ventral tegmental area through attenuating gamma-aminobutyric acid (GABA) release in the ventral tegmental area. The μ-opioid receptor has long been identified as the key receptor for mediating the subjective effects of opiates, and is also likely responsible for mediating opiate-induced CPP. The opioid receptor partial agonist buprenorphine has been shown to produce CPP and increase locomotor activity in wild type (WT) mice, but not in μ-receptor knockout (KO) mutant mice; whereas amphetamine has been shown to produce CPP and increase locomotor activity in both WT and μ KO mice.31 Moreover, agonists selective for μ-opioid receptors can reinstate CPP in formerly morphine-dependent rats trained in the CPP procedure.59 Other neurotransmitters may also be important for the development of CPP by opiates. CPP produced by morphine has been shown to be attenuated after pretreatment with the cannabinoid CB1 receptor antagonist SR-141716.60 In addition to potential modulation of morphine-induced CPP by cannabinoid receptors, intraventral tegmental area infusions of nicotine and the acetylcholinesterase inhibitor neostigmine have been found to facilitate CPP produced by an otherwise ineffective dose (0.5 mg/kg) of morphine. Intraventral tegmental area infusions of the musca-


66


rinic receptor antagonist atropine and the nicotinic receptor antagonist mecamylamine have been found to prevent CPP produced by an effective dose of morphine (5.0 mg/kg), suggesting that the cholinergic system may also mediate the rewarding effects of morphine and other opiates.32 Local administration of the glutamate ion channel agonist N-methyl-D-aspartate (NMDA) into the amygdala has been shown to potentiate morphine-induced CPP, whereas the glutamate ion channel blocker MK-801 has been shown to attenuate morphine-induced CPP.61

4.6.2

PSYCHOSTIMULANTS

As noted above, psychostimulants such as amphetamine and cocaine often produce a robust CPP, and these effects also depend upon limbic system functioning, particularly on the release of DA into the nucleus accumbens. Although psychostimulants as a class tend to produce rewarding effects, as demonstrated in CPP and self-administration studies, drugs in this class vary greatly as to the mechanisms mediating reward. Apomorphine, a psychostimulant and classic DA receptor agonist, has been reported to produce CPP in numerous studies, as well as CPA at relatively high doses.34,41,62,63 The rewarding effects of apomorphine are potentiated in the CPP model by pretreatment with the DA D3 receptor agonist 7-OH-DPAT, yet in the same study pretreatment with 7-OH-DPAT was found to attenuate the rewarding effects of cocaine.63 Moreover, systemic administration of the typical antipsychotic drug and D2 receptor antagonist haloperidol, as well as 6-OH-DA lesions in the nucleus accumbens, failed to attenuate cocaine-induced CPP.64 However, another study reported that haloperidol did prevent cocaine-induced CPP when cocaine was administered intravenously.44 The D1 receptor antagonist SCH23390 also has been shown to block cocaine-induced CPP in both male and female rats.65 Cocaine, unlike apomorphine and other psychostimulants, with the exception of amphetamine, which is a competitor with DA for the vesicular DA transporter, is an inhibitor of DA, norepinephrine, and serotonin transporters; although the dopamine transporter (DAT) inhibition is generally thought to be most important for the rewarding effects of cocaine. However, DAT KO mice exhibit a CPP for cocaine and are still found to self-administer cocaine.66,67 However, cocaine-induced CPP in DAT KO mice may be due to compensatory changes in DA systems in the DAT KO mice, given that cocaine-induced CPP is not found in a triple mutant DAT KO mouse line that results in a relatively cocaine-insensitive DAT that still transports DA.68 Amphetamineinduced CPP is also abolished in DAT KO mice, but can be blocked by haloperidol.4,41,43 The rewarding effects of amphetamine may be mediated, at least in part, by serotonin receptors, given that the amphetamine-induced CPP is also blocked by the 5-HT2A/2B/2C receptor antagonist ritanserin and by the 5-HT reuptake inhibitors zemilidine and fluoxetine.69–71 Despite differences between cocaine and amphetamine in the CPP paradigm, both cocaine and amphetamine have been reported to elevate cocaine- and amphetamine-regulated transcript (CART) mRNA levels after acute administration in the nucleus accumbens and ventral tegmental area, and bilateral intraventral tegmental area injections of the CART peptide fragment 55-102 have been found to produce CPP.72–74 Moreover, CART 55-102–induced CPP was blocked by systemic administration of haloperidol.



4.6.3

67

NICOTINE

Systemic administration of nicotine has been shown to produce both CPP and CPA in rodents through stimulation of nicotinic acetylcholine receptors (nAChrs).5,75,76 Both CPP and CPA is observed at low and high doses, respectively, after intra-ventral tegmental area infusions of nicotine, which can be blocked by both the B4C2 nAChr antagonist DHbeteE and the B7 nAChr antagonist methyllycaconitine (MLA).52 Moreover, MLA pretreatment shifted nicotine-induced CPP to CPA in this study. In nicotine-dependent rats, pairing withdrawal effects induced by administration of the nonselective nAChr antagonist mecamylamine produces CPA, which can be prevented upon coadministration of the 5-HT3 receptor antagonist ondansetron.77 The nAChr antagonist epibatidine produces a relatively weak CPP when administered systemically alone, but also produces a CPA at higher doses, and further nAChr studies have revealed that C2, but not B7, nAChrs are necessary to establish nicotineinduced CPP.78,79 The ability of nicotine to produce CPP differs markedly between strains of rats. For example, nicotine CPP has been established in the Lewis strain of rat, but not in the Fischer-344 strain of rat.10,13 Further individual differences in susceptibility to nicotine dependence have been shown within the same strain of mice, in which a single injection of nicotine (0.75 mg/kg) was found to either increase or decrease locomotor activity, and subsequent testing for nicotine CPP found that nicotine produced CPP in mice that had increased locomotor activity after nicotine administration, and that nicotine produced a lower degree of CPP in mice that had decreased locomotor activity after nicotine administration.80

4.6.4

ETHANOL

Ethanol, when administered alone, produces CPP and CPA in rodents, with lower doses producing CPP and higher doses producing CPA.21,24,29,81 Receptor mechanisms found to mediate ethanol’s CNS effects, GABAA, NMDA, and 5-HT3 receptors, have also been tested to determine which receptors mediate reward using the CPP paradigm. Ethanol-induced CPP was shown to be attenuated when ethanol was coadministered with the competitive NMDA receptor antagonist CGP-37849, but not when coadministered with the noncompetitive NMDA receptor antagonists MK-801 and ketamine, nor with NMDA subunit antagonists.82 Again, the mesolimbic DA pathway appears critical for the rewarding effects of ethanol, since ethanol-induced CPP can be potentiated by systemically administered heroin, and can be attenuated by intra-accumbens administration of D2 receptor antagonists, such as fluphenazine.83 Ethanol has been found to potentiate the effects of cocaine in the CPP model by shifting high cocaine doses from producing CPP to CPA and by increasing CPP induced by lower cocaine doses.84,85 In the liver, ethanol is broken down by alcohol dehydrogenase to acetaldehyde, which in turn is broken down by aldehyde dehydrogenase to acetic acid. When acetaldehyde accumulates, symptoms of acetaldehyde syndrome may occur, which include nausea, headache, and vomiting. In the CPP paradigm, acetaldehyde has been shown to produce CPP, but not CPA, including doses that approached the lethal limit.81 Intriguingly, deactivation of acetaldehyde by d-penicillamine prevents etha-


68


nol-induced CPP, whereas ethanol-induced CPA is unaffected, adding to evidence from other studies that acetaldehyde may mediate the rewarding effects (e.g., euphoria) of ethanol.86–89

4.6.5

MDMA

3,4-Methylenedioxymethamphetamine (MDMA) has been shown to readily establish a CPP in rodents.90–92 The ability of MDMA to produce a CPP may be caused by effects on the mesolimbic DA pathways, based on a microdialysis study, which found that doses of MDMA that produced CPPs also significantly elevated levels of DA and lowered levels of the DA metabolite DOPAC in the nucleus accumbens.93 Moreover, MDMA-induced CPP is attenuated upon pretreatment with the 5-HT3 receptor antagonist MDL72222 and tropisetron.94,95 MDMA-induced CPP has also been found to be diminished by pretreatment of the cannabinoid CB1 receptor antagonist SR141716A and the opioid antagonist naltrexone.95 In adolescents, the neurotoxic effects of MDMA appear to be diminished, suggesting that the MDMA receptors become more prominent in later development, perhaps during puberty. In a study by Fone et al.,96 cocaine produced CPP in adolescent rats previously treated for three consecutive days with MDMA, whereas cocaine failed to produce CPP in adolescent rats treated for seven days with the MDMA vehicle. Aberg et al.97 found a similar effect in adolescent rats, and interestingly, these effects were reversed in adult rats; MDMA-pretreated rats exhibited a diminished CPP for cocaine compared to vehicle pretreated rats. The rewarding effects of MDMA have also been shown to be potentiated when coadministered with delta-9-THC, the principle psychoactive ingredient in cannabis. Robledo et al.98 found that doses of delta-9-THC (0.3 mg/kg) and MDMA (3.0 mg/kg) that did not produce CPP when administered alone, did produce CPP when coadministered.

4.6.6

DELTA-9-THC AND ENDOCANNABINOIDS

Delta-9-THC, the psychoactive ingredient in smoked cannabis, has been shown to produce CPP under certain conditions. Initial findings of THC CPP were reported in rats using doses that ranged from 2.0–4.0 mg/kg, but a study that came out soon after reported that a THC CPP was not demonstrated by a 1.5 mg/kg dose in rats.99,100 In fact, the later study reported a CPA to THC following a 15 mg/kg dose, and that the cannabinoid CB1 receptor antagonist SR141716A produced a CPP.100 A CPA to THC has also been found in mice.25,101 Recently, the rewarding effects of THC in the CPP paradigm have been shown in mice after administering an injection of THC (as a priming dose) 24 hr prior to beginning several daily conditioning sessions with THC. This modified procedure resulted in a CPP for THC.25,102 In this methodological variation, the initial administration of THC may have resulted in tolerance to the dysphoric, or otherwise aversive, effects of THC, thus enabling the rewarding effects of THC to become more salient during the following conditioning trials with THC. However, the inability of some studies to establish a CPP for THC may have been a result of the doses used, since Braida et al.103 reported that THC, at doses ranging from 0.075–0.75 mg/kg, produced a CPP in Wistar rats. The opioid system may mediate the effects of THC in the CPP paradigm, because CPP for THC has been



69

shown to be attenuated in μ/I-opioid receptor double-KO mice, and that chronic administration of THC produces cross-tolerance to the rewarding effects of morphine in the CPP paradigm.102,104 The endogenous cannabinoid anandamide has not been well characterized in the CPP paradigm, but doses up to 16.0 mg/kg have failed to produce a CPP, despite coadministration of a protease inhibitor to lengthen the half-life of anandamide.105 However, the anandamide transport inhibitor AM404 was shown to produce a CPP in rats raised in an enriched environment, suggesting that anandamide may be capable of producing a CPP under certain conditions.106

4.7

CONDITIONED PLACE PREFERENCE VERSUS SELF-ADMINISTRATION

Another common model for assessing the rewarding properties of drugs is the selfadministration paradigm. As the name suggests, this paradigm consists of recording the number of times an animal produces a response (e.g., a lever press) that results in an infusion of drug, which is usually given intravenously. The self-administration paradigm is an important tool for screening drugs for abuse potential and to elucidate the rewarding effects of drugs. Although the conditioned place preference and self-administration paradigms both measure the rewarding properties of drugs, there are important differences between these two models (Table 4.2). First, although both CPP and self-administration studies are sensitive to the rewarding effects of many of

TABLE 4.2 Comparison of Conditioned Place Preference and Self-Administration CPP

Self-Administration

Affective drug properties

Rewarding and aversive effects

Rewarding effects

Behavioral training

Classical conditioning No surgery required Usually 1 wk of training Can conduct tests to block effects of drug

Operant conditioning Requires catheter implantation Can conduct tests to substitute for, block, or alter motivation for training drug

Drug administration

Drug injected before session

Drug administered after response by subject

Drug classes

Psychostimulants Opiates

Psychostimulants Opiates

Equipment

Generally a shuttle box (two or three chamber), open field, or maze, but many other variations used

Operant chamber, syringe pump for drug administration, liquid swivel, and animal harness

Experimental design

Between groups

Within subjects

Species

Usually rats and mice

Rats, mice, monkeys and sometimes pigeons


70


the same drugs, including psychostimulants and opiates, some drugs produce CPP but may not be self administered (e.g., LSD, buspirone, and pentylenetetrazole), while others are self administered but do not produce CPP (e.g., pentobarbital and phencyclidine).4 Second, the preponderance of CPP studies have used only rats and mice, whereas self-administration studies have been conducted in monkeys, rats, mice, and pigeons. Third, the mechanisms that mediate drug-induced CPP and selfadministration of a drug may be different. For example, D2 receptor antagonists have minimal effects on the ability of cocaine to produce CPP, whereas D2 antagonists readily attenuate self-administration for cocaine.11 Finally, an important contrast between these two paradigms is the difference in methodological procedures. Unlike the CPP paradigm, the self-administration paradigm requires surgical implantation of a catheter, usually for intravenous drug administration, and an extensive operant training history. Moreover, in CPP, the subjective effects of the drug are present prior to the task, whereas in the self-administration paradigm, a subject is learning a task where responses produce near-immediate effects from drug administration. The latter appears to be most similar of these two models to drug use in humans.

4.8

SUMMARY

The CPP paradigm is a useful tool for studying the affective properties of drugs, and is routinely used in concert with standard research techniques in neuroscience. Most drugs of abuse elicit a CPP in rats and mice, and the neural substrates of these effects can often be traced to the mesolimbic DA system. Alternative models for assessing the rewarding effects of drugs (e.g., self-administration) do not always produce similar results, and therefore, researchers should be careful when evaluating results based on the behavioral model they are using in their study.

ACKNOWLEDGMENTS The authors wish to thank Med Associates, Inc. for providing the images used in Figure 4.1 and Juan Rodriguez for producing the illustrations used in Figure 4.2.

REFERENCES 1. Lin, S. K., Pan, W. H., and Yeh, P. H. 2007. Prefrontal dopamine efflux during exposure to drug-associated contextual cues in rats with prior repeated methamphetamine. Brain Res. Bull. 71:365–371. 2. Calcagnetti, D. J., and Schechter, M. D. 1994. Nicotine place preference using the biased method of conditioning. Prog. Neuropsychopharmacol. Biol. Psychiatry 18:925–933. 3. Hoffman, D. C. 1989. The use of place conditioning in studying the neuropharmacology of drug reinforcement. Brain Res. Bull. 23:373–387. 4. Bardo, M. T., and Bevins, R. A. 2000. Conditioned place preference: What does it add to our preclinical understanding of drug reward? Psychopharmacology (Berl.) 153:31–43. 5. Fudala, P. J., Teoh, K. W., and Iwamoto, E. T. 1985. Pharmacologic characterization of nicotine-induced conditioned place preference. Pharmacol. Biochem. Behav. 22:237–241.



71

6. Tuazon, D. B., Suzuki, T., Misawa, M., and Watanabe, S. 1992. Methylxanthines (caffeine and theophylline) blocked methamphetamine-induced conditioned place preference in mice but enhanced that induced by cocaine. Ann. NY Acad. Sci. 654:531–533. 7. Masukawa, Y., Suzuki, T., and Misawa, M. 1993. Differential modification of the rewarding effects of methamphetamine and cocaine by opioids and antihistamines. Psychopharmacology (Berl.) 111:139–143. 8. Suzuki, T., and Misawa, M. 1995. Sertindole antagonizes morphine-, cocaine-, and methamphetamine-induced place preference in the rat. Life Sci. 57:1277–1284. 9. Suzuki, T., Sugano, Y., Funada, M., and Misawa, M. 1995. Adrenalectomy potentiates the morphine—but not cocaine-induced place preference in rats. Life Sci. 56: PL339–344. 10. Horan, B., Smith, M., Gardner, E. L., Lepore, M., and Ashby, C. R. Jr. 1997. (-)-Nicotine produces conditioned place preference in Lewis, but not Fischer 344 rats. Synapse 26:93–94. 11. Bardo, M. T., Valone, J. M., and Bevins, R. A. 1999. Locomotion and conditioned place preference produced by acute intravenous amphetamine: Role of dopamine receptors and individual differences in amphetamine self-administration. Psychopharmacology (Berl.) 143:39–46. 12. Busse, G. D., and Riley, A. L. 2004. Cocaine, but not alcohol, reinstates cocaineinduced place preferences. Pharmacol. Biochem. Behav. 78:827–833. 13. Philibin, S. D., Vann, R. E., Varvel, S. A., et al. 2005. Differential behavioral responses to nicotine in Lewis and Fischer-344 rats. Pharmacol. Biochem. Behav. 80:87–92. 14. Ettenberg, A., and Bernardi, R. E. 2007. Effects of buspirone on the immediate positive and delayed negative properties of intravenous cocaine as measured in the conditioned place preference test. Pharmacol. Biochem. Behav. 87:171–178. 15. Asin, K. E., and Wirtshafter, D. 1985. Clonidine produces a conditioned place preference in rats. Psychopharmacology (Berl.) 85:383–385. 16. Brown, E. E., Finlay, J. M., Wong, J. T., Damsma, G., and Fibiger, H. C. 1991. Behavioral and neurochemical interactions between cocaine and buprenorphine: Implications for the pharmacotherapy of cocaine abuse. J. Pharmacol. Exp. Ther. 256:119–126. 17. Suzuki, T., Shiozaki, Y., Masukawa, Y., Misawa, M., and Nagase, H. 1992. The role of mu- and kappa-opioid receptors in cocaine-induced conditioned place preference. Jpn. J. Pharmacol. 58:435–442. 18. Cervo, L., Rossi, C., and Samanin, R. 1993. Clonidine-induced place preference is mediated by alpha 2-adrenoceptors outside the locus coeruleus. Eur. J. Pharmacol. 238:201–207. 19. Suzuki, T., Funada, M., Narita, M., Misawa, M., and Nagase, H. 1993. Morphineinduced place preference in the CXBK mouse: Characteristics of mu opioid receptor subtypes. Brain Res. 602:45–52. 20. Gaiardi, M., Bartoletti, M., Bacchi, A., Gubellini, C., and Babbini, M. 1997. Motivational properties of buprenorphine as assessed by place and taste conditioning in rats. Psychopharmacology (Berl.) 130:104–108. 21. Matsuzawa, S., Suzuki, T., Misawa, M., and Nagase, H. 1999. Involvement of dopamine D(1) and D(2) receptors in the ethanol-associated place preference in rats exposed to conditioned fear stress. Brain Res. 835:298–305. 22. McFarland, K., and Ettenberg, A. 1999. Haloperidol does not attenuate conditioned place preferences or locomotor activation produced by food- or heroin-predictive discriminative cues. Pharmacol. Biochem. Behav. 62:631–641. 23. Cheer, J. F., Kendall, D. A., and Marsden, C. A. 2000. Cannabinoid receptors and reward in the rat: A conditioned place preference study. Psychopharmacology (Berl.) 151:25–30.


72


24. Matsuzawa, S., Suzuki, T., and Misawa, M. 2000. Ethanol, but not the anxiolytic drugs buspirone and diazepam, produces a conditioned place preference in rats exposed to conditioned fear stress. Pharmacol. Biochem. Behav. 65:281–288. 25. Valjent, E., and Maldonado, R. 2000. A behavioural model to reveal place preference to delta 9-tetrahydrocannabinol in mice. Psychopharmacology (Berl.) 147:436–438. 26. Braida, D., Pozzi, M., Cavallini, R., and Sala, M. 2001. Conditioned place preference induced by the cannabinoid agonist CP 55,940: Interaction with the opioid system. Neuroscience 104:923–926. 27. Robinson, L., Hinder, L., Pertwee, R. G., and Riedel, G. 2003. Effects of delta9-THC and WIN-55,212-2 on place preference in the water maze in rats. Psychopharmacology (Berl.) 166:40–50. 28. Walker, B. M., and Ettenberg, A. 2003. The effects of alprazolam on conditioned place preferences produced by intravenous heroin. Pharmacol. Biochem. Behav. 75:75–80. 29. Busse, G. D., Lawrence, E. T., and Riley, A. L. 2005. The effects of alcohol preexposure on cocaine, alcohol and cocaine/alcohol place conditioning. Pharmacol. Biochem. Behav. 81:459–465. 30. Simpson, G. R., and Riley, A. L. 2005. Morphine preexposure facilitates morphine place preference and attenuates morphine taste aversion. Pharmacol. Biochem. Behav. 80:471–479. 31. Marquez, P., Baliram, R., Kieffer, B. L., and Lutfy, K. 2007. The mu opioid receptor is involved in buprenorphine-induced locomotor stimulation and conditioned place preference. Neuropharmacology 52:1336–1341. 32. Rezayof, A., Nazari-Serenjeh, F., Zarrindast, M. R., Sepehri, H., and Delphi, L. 2007. Morphine-induced place preference: Involvement of cholinergic receptors of the ventral tegmental area. Eur. J. Pharmacol. 562:92–102. 33. Le Foll, B., and Goldberg, S. R. 2005. Control of the reinforcing effects of nicotine by associated environmental stimuli in animals and humans. Trends Pharmacol. Sci. 26:287–293. 34. Best, P. J., Best, M. R., and Mickley, G. A. 1973. Conditioned aversion to distinct environmental stimuli resulting from gastrointestinal distress. J. Comp. Physiol. Psychol. 85:250–257. 35. van der Kooy, D., Swerdlow, N. R., and Koob, G. F. 1983. Paradoxical reinforcing properties of apomorphine: Effects of nucleus accumbens and area postrema lesions. Brain Res. 259:111–118. 36. Bechara, A., and van der Kooy, D. 1985. Opposite motivational effects of endogenous opioids in brain and periphery. Nature 314:533–534. 37. Bechara, A., Zito, K. A., and van der Kooy, D. 1987. Peripheral receptors mediate the aversive conditioning effects of morphine in the rat. Pharmacol. Biochem. Behav. 28:219–225. 38. Papp, M. 1988. Different effects of short- and long-term treatment with imipramine on the apomorphine- and food-induced place preference conditioning in rats. Pharmacol. Biochem. Behav. 30:889–893. 39. Zito, K. A., Bechara, A., Greenwood, C., and van der Kooy, D. 1988. The dopamine innervation of the visceral cortex mediates the aversive effects of opiates. Pharmacol. Biochem. Behav. 30:693–699. 40. Schwartz, A. S., and Marchok, P. L. 1974. Depression of morphine-seeking behaviour by dopamine inhibition. Nature 248:257–258. 41. Spyraki, C., Fibiger, H. C., and Phillips, A. G. 1982. Dopaminergic substrates of amphetamine-induced place preference conditioning. Brain Res. 253:185–193. 42. Spyraki, C., Fibiger, H. C., and Phillips, A. G. 1983. Attenuation of heroin reward in rats by disruption of the mesolimbic dopamine system. Psychopharmacology (Berl.) 79:278–283.



73

43. Mithani, S., Martin-Iverson, M. T., Phillips, A. G., and Fibiger, H. C. 1986. The effects of haloperidol on amphetamine- and methylphenidate-induced conditioned place preferences and locomotor activity. Psychopharmacology (Berl.) 90:247–252. 44. Spyraki, C., Nomikos, G. G., and Varonos, D. D. 1987. Intravenous cocaine-induced place preference: Attenuation by haloperidol. Behav. Brain Res. 26:57–62. 45. Hoffman, D. C., and Beninger, R. J. 1989. The effects of selective dopamine D1 or D2 receptor antagonists on the establishment of agonist-induced place conditioning in rats. Pharmacol. Biochem. Behav. 33:273–279. 46. Phillips, A. G., and LePiane, F. G. 1980. Reinforcing effects of morphine microinjection into the ventral tegmental area. Pharmacol. Biochem. Behav. 12:965–968. 47. van der Kooy, D., Mucha, R. F., O’Shaughnessy, M., and Bucenieks, P. 1982. Reinforcing effects of brain microinjections of morphine revealed by conditioned place preference. Brain Res. 243:107–117. 48. Phillips, A. G., LePiane, F. G., and Fibiger, H. C. 1983. Dopaminergic mediation of reward produced by direct injection of enkephalin into the ventral tegmental area of the rat. Life Sci. 33:2505–2511. 49. Glimcher, P. W., Giovino, A. A., Margolin, D. H., and Hoebel, B. G. 1984. Endogenous opiate reward induced by an enkephalinase inhibitor, thiorphan, injected into the ventral midbrain. Behav. Neurosci. 98:262–268. 50. Carr, G. D., and White, N. M. 1986. Anatomical disassociation of amphetamine’s rewarding and aversive effects: An intracranial microinjection study. Psychopharmacology (Berl.) 89:340–346. 51. Bozarth, M. A. 1987. Neuroanatomical boundaries of the reward-relevant opiate-receptor field in the ventral tegmental area as mapped by the conditioned place preference method in rats. Brain Res. 414:77–84. 52. Laviolette, S. R., and van der Kooy, D. 2003. The motivational valence of nicotine in the rat ventral tegmental area is switched from rewarding to aversive following blockade of the alpha7-subunit-containing nicotinic acetylcholine receptor. Psychopharmacology (Berl.) 166:306–313. 53. Duvauchelle, C. L., Ikegami, A., Asami, S., Robens, J., Kressin, K., and Castaneda, E. 2000. Effects of cocaine context on NAcc dopamine and behavioral activity after repeated intravenous cocaine administration. Brain Res. 862:49–58. 54. Duvauchelle, C. L., Ikegami, A., and Castaneda, E. 2000. Conditioned increases in behavioral activity and accumbens dopamine levels produced by intravenous cocaine. Behav. Neurosci. 114:1156–1166. 55. Ventura, R., Cabib, S., Alcaro, A., Orsini, C., and Puglisi-Allegra, S. 2003. Norepinephrine in the prefrontal cortex is critical for amphetamine-induced reward and mesoaccumbens dopamine release. J. Neurosci. 23:1879–1885. 56. Ventura, R., Alcaro, A., and Puglisi-Allegra, S. 2005. Prefrontal cortical norepinephrine release is critical for morphine-induced reward, reinstatement and dopamine release in the nucleus accumbens. Cereb. Cortex 15:1877–1886. 57. Gong, W., Neill, D., and Justice, J. B. Jr. 1997. 6-Hydroxydopamine lesion of ventral pallidum blocks acquisition of place preference conditioning to cocaine. Brain Res. 754:103–112. 58. Corrigall, W. A., and Linseman, M. A. 1988. Conditioned place preference produced by intra-hippocampal morphine. Pharmacol. Biochem. Behav. 30:787–789. 59. Lenard, N. R., Daniels, D. J., Portoghese, P. S., and Roerig, S. C. 2007. Absence of conditioned place preference or reinstatement with bivalent ligands containing muopioid receptor agonist and delta-opioid receptor antagonist pharmacophores. Eur. J. Pharmacol. 566:75–82.


74


60. Singh, M. E., Verty, A. N., McGregor, I. S., and Mallet, P. E. 2004. A cannabinoid receptor antagonist attenuates conditioned place preference but not behavioural sensitization to morphine. Brain Res. 1026:244–253. 61. Rezayof, A., Golhasani-Keshtan, F., Haeri-Rohani, A., and Zarrindast, M. R. 2007. Morphine-induced place preference: Involvement of the central amygdala NMDA receptors. Brain Res. 1133:34–41. 62. Swerdlow, N. R., Swanson, L. W., and Koob, G. F. 1984. Electrolytic lesions of the substantia innominata and lateral preoptic area attenuate the “supersensitive” locomotor response to apomorphine resulting from denervation of the nucleus accumbens. Brain Res. 306:141–148. 63. Khroyan, T. V., Fuchs, R. A., Beck, A. M., Groff, R. S., and Neisewander, J. L. 1999. Behavioral interactions produced by co-administration of 7-OH-DPAT with cocaine or apomorphine in the rat. Psychopharmacology (Berl.) 142:383–392. 64. Spyraki, C., Fibiger, H. C., and Phillips, A. G. 1982. Cocaine-induced place preference conditioning: Lack of effects of neuroleptics and 6-hydroxydopamine lesions. Brain Res. 253:195–203. 65. Nazarian, A., Russo, S. J., Festa, E. D., Kraish, M., and Quinones-Jenab, V. 2004. The role of D1 and D2 receptors in the cocaine conditioned place preference of male and female rats. Brain Res. Bull. 63:295–299. 66. Sora, I., Wichems, C., Takahashi, N., et al. 1998. Cocaine reward models: Conditioned place preference can be established in dopamine- and in serotonin-transporter knockout mice. Proc. Natl. Acad. Sci. USA 95:7699.–7704. 67. Medvedev, I. O., Gainetdinov, R. R., Sotnikova, T. D., Bohn, L. M., Caron, M. G., and Dykstra, L. A. 2005. Characterization of conditioned place preference to cocaine in congenic dopamine transporter knockout female mice. Psychopharmacology (Berl.) 180:408–413. 68. Chen, R., Tilley, M. R., Wei, H., et al. 2006. Abolished cocaine reward in mice with a cocaine-insensitive dopamine transporter. Proc. Natl. Acad. Sci. USA 103:9333–9338. 69. Kruszewska, A., Romandini, S., and Samanin, R. 1986. Different effects of zimelidine on the reinforcing properties of d-amphetamine and morphine on conditioned place preference in rats. Eur. J. Pharmacol. 125:283–286. 70. Nomikos, G. G., and Spyraki, C. 1988. Effects of ritanserin on the rewarding properties of d-amphetamine, morphine and diazepam revealed by conditioned place preference in rats. Pharmacol. Biochem. Behav. 30:853–858. 71. Takamatsu, Y., Yamamoto, H., Ogai, Y., Hagino, Y., Markou, A., and Ikeda, K. 2006. Fluoxetine as a potential pharmacotherapy for methamphetamine dependence: Studies in mice. Ann. NY Acad. Sci. 1074:295–302. 72. Douglass, J., McKinzie, A. A., and Couceyro, P. 1995. PCR differential display identifies a rat brain mRNA that is transcriptionally regulated by cocaine and amphetamine. J. Neurosci. 15:2471–2481. 73. Koylu, E. O., Couceyro, P. R., Lambert, P. D., and Kuhar, M. J. 1998. Cocaine- and amphetamine-regulated transcript peptide immunohistochemical localization in the rat brain. J. Comp. Neurol. 391:115–132. 74. Kimmel, H. L., Gong, W., Vechia, S. D., Hunter, R. G., and Kuhar, M. J. 2000. Intraventral tegmental area injection of rat cocaine and amphetamine-regulated transcript peptide 55-102 induces locomotor activity and promotes conditioned place preference. J. Pharmacol. Exp. Ther. 294:784–792. 75. Fudala, P. J., and Iwamoto, E. T. 1986. Further studies on nicotine-induced conditioned place preference in the rat. Pharmacol. Biochem. Behav. 25:1041–1049. 76. Le Foll, B., and Goldberg, S. R. 2005. Nicotine induces conditioned place preferences over a large range of doses in rats. Psychopharmacology (Berl.) 178:481–492.



75

77. Suzuki, T., Ise, Y., Mori, T., and Misawa, M. 1997. Attenuation of mecamylamine-precipitated nicotine-withdrawal aversion by the 5-HT3 receptor antagonist ondansetron. Life Sci. 61:PL249–254. 78. Janhunen, S., Linnervuo, A., Svensk, M., and Ahtee, L. 2005. Effects of nicotine and epibatidine on locomotor activity and conditioned place preference in rats. Pharmacol. Biochem. Behav. 82:758–765. 79. Walters, C. L., Brown, S., Changeux, J. P., Martin, B., and Damaj, M. I. 2006. The beta2 but not alpha7 subunit of the nicotinic acetylcholine receptor is required for nicotine-conditioned place preference in mice. Psychopharmacology (Berl.) 184:339–344. 80. Schechter, M. D., Meehan, S. M., and Schechter, J. B. 1995. Genetic selection for nicotine activity in mice correlates with conditioned place preference. Eur. J. Pharmacol. 279:59–64. 81. Quertemont, E., and De Witte, P. 2001. Conditioned stimulus preference after acetaldehyde but not ethanol injections. Pharmacol. Biochem. Behav. 68:449–454. 82. Boyce-Rustay, J. M., and Cunningham, C. L. 2004. The role of NMDA receptor binding sites in ethanol place conditioning. Behav. Neurosci. 118:822–834. 83. Walker, B. M., and Ettenberg, A. 2007. Intracerebroventricular ethanol-induced conditioned place preferences are prevented by fluphenazine infusions into the nucleus accumbens of rats. Behav. Neurosci. 121:401–410. 84. Busse, G. D., and Riley, A. L. 2002. Modulation of cocaine-induced place preferences by alcohol. Prog. Neuropsychopharmacol. Biol. Psychiatry 26:1373–1381. 85. Busse, G. D., Lawrence, E. T., and Riley, A. L. 2004. The modulation of cocaineinduced conditioned place preferences by alcohol: effects of cocaine dose. Prog. Neuropsychopharmacol. Biol. Psychiatry 28:149–155. 86. Brown, Z. W., Amit, Z., and Rockman, G. E. 1979. Intraventricular self-administration of acetaldehyde, but not ethanol, in naive laboratory rats. Psychopharmacology (Berl.) 64:271–276. 87. Smith, B. R., Amit, Z., and Splawinsky, J. 1984. Conditioned place preference induced by intraventricular infusions of acetaldehyde. Alcohol 1:193–195. 88. Rodd, Z. A., Bell, R. L., Zhang, Y., et al. 2005. Regional heterogeneity for the intracranial self-administration of ethanol and acetaldehyde within the ventral tegmental area of alcohol-preferring (P) rats: Involvement of dopamine and serotonin. Neuropsychopharmacology 30:330–338. 89. Font, L., Aragon, C. M., and Miquel, M. 2006. Ethanol-induced conditioned place preference, but not aversion, is blocked by treatment with D-penicillamine, an inactivation agent for acetaldehyde. Psychopharmacology (Berl.) 184:56–64 90. Bilsky, E. J., Hui, Y. Z., Hubbell, C. L., and Reid, L. D. 1990. Methylenedioxymethamphetamine’s capacity to establish place preferences and modify intake of an alcoholic beverage. Pharmacol. Biochem. Behav. 37:633–638. 91. Bilsky, E. J., Hubbell, C. L., Delconte, J. D., and Reid, L. D. 1991. MDMA produces a conditioned place preference and elicits ejaculation in male rats: A modulatory role for the endogenous opioids. Pharmacol. Biochem. Behav. 40:443–447. 92. Daza-Losada, M., Ribeiro Do Couto, B., Manzanedo, C., Aguilar, M. A., RodriguezArias, M., and Minarro, J. 2007. Rewarding effects and reinstatement of MDMAinduced CPP in adolescent mice. Neuropsychopharmacology 32:1750–1759. 93. Marona-Lewicka, D., Rhee, G. S., Sprague, J. E., and Nichols, D. E. 1996. Reinforcing effects of certain serotonin-releasing amphetamine derivatives. Pharmacol. Biochem. Behav. 53:99–105. 94. Bilsky, E. J., and Reid, L. D. 1991. MDL72222, a serotonin 5-HT3 receptor antagonist, blocks MDMA’s ability to establish a conditioned place preference. Pharmacol. Biochem. Behav. 39:509–512.


76


95. Braida, D., Iosue, S., Pegorini, S., and Sala, M. 2005. 3,4 Methylenedioxymethamphetamine-induced conditioned place preference (CPP) is mediated by endocannabinoid system. Pharmacol. Res. 51:177–182. 96. Fone, K. C., Beckett, S. R., Topham, I. A., Swettenham, J., Ball, M., and Maddocks, L. 2002. Long-term changes in social interaction and reward following repeated MDMA administration to adolescent rats without accompanying serotonergic neurotoxicity. Psychopharmacology (Berl.) 159:437–444. 97. Aberg, M., Wade, D., Wall, E., and Izenwasser, S. 2007. Effect of MDMA (ecstasy) on activity and cocaine conditioned place preference in adult and adolescent rats. Neurotoxicol. Teratol. 29:37–46. 98. Robledo, P., Trigo, J. M., Panayi, F., de la Torre, R., and Maldonado, R. 2007. Behavioural and neurochemical effects of combined MDMA and THC administration in mice. Psychopharmacology (Berl.). 195:255–264. 99. Lepore, M., Vorel, S. R., Lowinson, J., and Gardner, E. L. 1995. Conditioned place preference induced by delta 9-tetrahydrocannabinol: Comparison with cocaine, morphine, and food reward. Life Sci. 56:2073–2080. 100. Sanudo-Pena, M. C., Tsou, K., Delay, E. R., Hohman, A. G., Force, M., and Walker, J. M. 1997. Endogenous cannabinoids as an aversive or counter-rewarding system in the rat. Neurosci. Lett. 223:125–128. 101. Hutcheson, D. M., Tzavara, E. T., Smadja, C., et al. 1998. Behavioural and biochemical evidence for signs of abstinence in mice chronically treated with delta-9-tetrahydrocannabinol. Br. J. Pharmacol. 125:1567–1577. 102. Castane, A., Robledo, P., Matifas, A., Kieffer, B. L., and Maldonado, R. 2003. Cannabinoid withdrawal syndrome is reduced in double mu and delta opioid receptor knockout mice. Eur. J. Neurosci. 17:155–159. 103. Braida, D., Iosue, S., Pegorini, S., and Sala, M. 2004. Delta9-tetrahydrocannabinolinduced conditioned place preference and intracerebroventricular self-administration in rats. Eur. J. Pharmacol. 506:63–69. 104. Jardinaud, F., Roques, B. P., and Noble, F. 2006. Tolerance to the reinforcing effects of morphine in delta9-tetrahydrocannabinol treated mice. Behav. Brain Res. 173:255. 105. Mallet, P. E., and Beninger, R.J. 1998. Delta9-tetrahydrocannabinol, but not the endogenous cannabinoid receptor ligand anandamide, produces conditioned place avoidance. Life Sci. 62:2431–2439. 106. Bortolato, M., Campolongo, P., Mangieri, R. A., Scattoni, M. L., Frau, R., Trezza, V., La Rana, G., Russo, R., Calignano, A., Gessa, G. L., Cuomo, V., Piomelli, D. 2006. Anxiolytic-like properties of the anandamide transport inhibitor AM404. Neuropsychopharmacology 31:2652–2659. 107. Bardo et al. 1999.


5 Anxiety-Related Behaviors in Mice Kathleen R. Bailey and Jacqueline N. Crawley CONTENTS 5.1 5.2 5.3

Introduction................................................................................................... 78 General Methodological Considerations....................................................... 79 Paradigms...................................................................................................... 79 5.3.1 Open Field Exploration Test .............................................................. 79 5.3.1.1 Equipment ............................................................................80 5.3.1.2 Procedure .............................................................................80 5.3.1.3 Analysis and Interpretation .................................................. 81 5.3.1.4 Sample Results ..................................................................... 81 5.3.2 Elevated Plus-Maze/Elevated Zero-Maze ......................................... 81 5.3.2.1 Subjects ................................................................................ 83 5.3.2.2 Equipment ............................................................................ 83 5.3.2.3 Procedure .............................................................................84 5.3.2.4 Analysis and Interpretation ..................................................84 5.3.2.5 Sample Results ..................................................................... 85 5.3.3 Light n Dark Exploration Test ......................................................... 85 5.3.3.1 Subjects ................................................................................ 87 5.3.3.2 Equipment ............................................................................ 87 5.3.3.3 Procedure ............................................................................. 87 5.3.3.4 Analysis and Interpretation .................................................. 87 5.3.3.5 Sample Results ..................................................................... 88 5.3.4 The Social Interaction Test ................................................................ 88 5.3.4.1 Subjects ................................................................................90 5.3.4.2 Equipment ............................................................................90 5.3.4.3 Procedure .............................................................................90 5.3.4.4 Analysis and Interpretation .................................................. 91 5.3.4.5 Sample Results ..................................................................... 91 5.3.5 Novelty-Induced Hypophagia ............................................................ 91 5.3.5.1 Subjects ................................................................................92 5.3.5.2 Equipment ............................................................................ 93 5.3.5.3 Procedure ............................................................................. 93 5.3.5.4 Analysis and Interpretation .................................................. 93 5.3.5.5 Sample Results ..................................................................... 93 5.4 Conclusion..................................................................................................... 95 References................................................................................................................ 95 77


78

5.1


INTRODUCTION

Human anxiety disorders are broadly grouped according to symptomology and responsiveness to pharmacological and psychological treatment.1,2 Generalized anxiety disorder and panic disorder are the two primary classifications of pathological anxiety in humans. The distinguishing feature of generalized anxiety disorder is a pervading sense of unrealistic worry about everyday life situations. In contrast, panic attacks constitute the primary symptom of panic disorder. These events are characterized as sudden, extreme fear accompanied by autonomic nervous system arousal.3 Similar changes in physiological indicators and behavioral responses to fear and painful stimuli in humans and other animals suggest the possibility of homologous or analogous, ethologically motivated defensive responses4–10 In the description of human anxiety disorders, the concepts of “state” and “trait” anxiety have a long history. However, it is only recently that these concepts have been suggested as a means of differentiating situational anxiety-like behavior in rodents from anxiety that transcends the situation and is an enduring condition in the animal.11 The former is the focus of the rodent behavioral tests reviewed in this chapter. Procedures are designed to trigger ethologically relevant conflict or conditioned behaviors. The latter is most often associated with selective breeding, e.g., the high versus low anxietyrelated traits in the high anxiety-related behavior (HAB) versus low anxiety-related behavior (LAB) rats,12 inbred mouse strains such as BALB/c, and mice with relevant targeted gene mutations.13,14 In an attempt to model human pathological anxiety in rodents, a wide range of behavioral testing paradigms have been developed.8,15–19 Many of these tests induce a fearful response through an aversive event or anticipated aversive event. Others integrate an approach–avoidance conflict designed to inhibit an ongoing behavior that is characteristic for the animal, such as contrasting the tendency of mice to engage in exploratory activity or social investigation against the aversive properties of an open, brightly lit, or elevated space. The premise that basic physiological mechanisms underlying fear in rodents can be equated to similar mechanisms operating in humans provides a degree of face validity for these paradigms.7,9,10 In rodents, these responses are deemed appropriate and adaptive for the current conditions, whereas in humans, anxiety disorders constitute maladaptive or pathological responses to the existing situation. Further exploration of rodent neuroanatomy and neurochemistry involved in fear extinction and inhibition of conditioned fear could offer important insights into effective targets for novel pharmacological treatment of pathological human anxiety.20 Although rats have been the rodent of choice for much of the preclinical research on anxiety-like behavior, recent technical advances in molecular genetics have placed the mouse in the forefront of neuropsychiatric research.7,13,21–26 This has resulted in the adaptation of many well-validated behavioral tests of anxiety from rats to mice, with varying degrees of success. This chapter offers a sampling of well-established tests of anxiety-like behavior in mice that use an ethological conflict. The interested researcher is directed to the classic source literature for more information on other


Anxiety-Related Behaviors in Mice

79

types of anxiety-based tests, including conditioning paradigms,27–29 punishmentinduced conflict tests,18,19,30,31 developmental models,32,33 and aversive tests.5,34

5.2

GENERAL METHODOLOGICAL CONSIDERATIONS

Several excellent papers have identified important factors that careful researchers will want to consider when designing experiments to assess anxiety-like behaviors in mice.35–37 The behavioral paradigms described in this chapter are suitable for most inbred mouse strains. In addition, mice with targeted genetic mutations that do not alter exploratory drive, motor ability, or recognition memory are also suitable test subjects for these paradigms. Other factors to consider when designing experiments assessing anxiety-like behavior include, but are not limited to, the experimental history of test subjects, prior test exposure, differences in exploratory motivation, and whether the test is to be conducted as part of a test battery or administered as a single behavioral assessment.9,38–42 Mice are social animals and are typically group-housed (four to five per cage) in same-sex home cages. Special circumstances (e.g., aggressive strains or mice with head mounts or other surgical interventions) may require single-housing prior to testing. Environmental conditions in the animal housing rooms should be as quiet as possible and consistent across experiments to control for extraneous variables that can significantly alter physiological and behavioral indicators of stress.37,43 Food and water are typically ad libitum unless the experimental design requires restriction. Avoid behavioral testing on days when, as a part of normal animal husbandry, home cages are scheduled for changing. Cage change typically causes an increase in general activity and stress levels.44–46 Researchers should fully describe any special circumstances pertaining to housing and care of test subjects in their experimental methods. To ensure consistency of experience prior to the test session, subjects are brought to the testing room or a common staging area, in their home cages, at least 1 hr prior to the start of behavioral testing. Individual mice can then be transported singly, in clean cages, into the testing apparatus. Test room lighting, temperature, and noise levels should be consistent for all subjects. Behavioral testing equipment described in this chapter is usually cleaned thoroughly with a solution of mild soapy water at the end of a test session. Prior to running the first subject on a day of testing, the experimenter wipes the behavioral equipment with 70% ethanol. After each subject completes its test session, fecal boli and urine are removed, surfaces are wiped with 70% ethanol, and the test chamber is allowed to dry completely before starting another subject. Most studies use a minimum of 12–15 animals per experimental group to insure sufficient power for statistical analysis.22

5.3

PARADIGMS

5.3.1

OPEN FIELD EXPLORATION TEST

Originally introduced as a measure of emotional behavior in rats,8 open field exploration has proven to be equally successful with mice.47 The test provides a unique opportunity to systematically assess novel environment exploration, general locomotor activity, and provide an initial screen for anxiety-related behavior in rodents.48


80


In addition, repeated exposure or extended session length provides a method for assessing habituation to the increasingly familiar chamber environment. It has been suggested that two factors influence anxiety-like behavior in the open field. The first is social isolation resulting from the physical separation from cage mates when performing the test. The second is the stress created by the brightly lit, unprotected, novel test environment.17,48 5.3.1.1 Equipment Although several different shapes have been used as rodent open field arenas,49,50 the most common design for mice is a large square chamber ranging in size from 28 × 28 cm to 56 × 56 cm. Chamber walls and floor can be plastic or wood but many automated systems use transparent Plexiglas. The open field arena is divided into a grid of equally sized areas by infrared photocell beams or lines drawn on the chamber floor for visual scoring of activity by the experimenter. Automated systems such as the VersaMax Animal Activity Monitoring System with Analyzer software (AccuScan Instruments, Inc., Columbus, Ohio, USA), SmartFrame open field system with Motor Monitor control and software (Lafayette Instruments, Lafayette, Indiana, USA), Open Field Activity System MED–OFA-MS (Med Associates, Inc., St. Albans, Vermont, USA), and Photobeam activity system–open field (San Diego Instruments, San Diego, California, USA), record each beam break as one unit of exploratory activity, similar to manual scoring of each line crossed. 5.3.1.2 Procedure Transport acclimated mice to the test room singly, if only one test chamber is available, or as a group in the home cage, if several automated chambers are available for testing. Place each mouse in the center of a chamber. If the experimenter intends to remain in the testing room, care should be taken to be as distant and unmoving as possible once the test session has started. Sudden motion or noise can greatly affect exploratory activity. Mice are allowed to freely explore the chamber for the duration of the test session. Each line crossed or photocell beam break is scored as one unit of activity. For assessing novel environment exploration, a 5-min test length is typical. If the researcher is interested in examining habituation to an increasingly familiar environment, a 30-min test session is recommended. Mice are allowed to freely explore the test arena for the entire session duration. Upon completion of the test, return the mouse to the home cage. In addition to horizontal units of activity, rearing behavior, defecation, and grooming activity can also be scored. These parameters provide measures of general physical motor abilities and level of interest in the novelty of the environment. Rodents will typically spend a significantly greater amount of time exploring the periphery of the arena, usually in contact with the walls (thigmotaxis), than the unprotected center area. Mice that spend significantly more time exploring the unprotected center area demonstrate anxiolytic-like baseline behavior. The center area of the chamber can be defined by the experimenter as a proportion of the overall test arena size. Many software systems allow the researcher to designate this center area, as well as multiple other regions of the test chamber, to track exploratory



81

activity. When the open field arena size is 40 × 40 cm2, the center region size is often designated as 20 × 20 cm2.51,52 5.3.1.3 Analysis and Interpretation Open field exploration results are generally analyzed using repeated-measures analysis of variance (ANOVA) for longer sessions when the researcher is interested in comparing levels of exploratory activity over the duration of the session. The session can be divided into time bins (e.g., 5 min) and changes in exploratory behavior can be compared across the length of the session. By contrast, if the experimenter’s only interest is novel environment exploration, then a one-way ANOVA can be run using the total scores across the test session for each behavioral measure (e.g., vertical activity, horizontal activity, total distance, and center time). A 5-min test session is often sufficient to capture the critical components of general exploratory locomotion. The most commonly used measure of overall exploratory/locomotor activity is currently the total distance traveled. Although horizontal activity appears to be recording a similar measure, in fact, the equipment records every beam break including those not associated with ambulatory activity (e.g., repetitive head movements). In contrast, the calculation of total distance includes constraints that exclude units of activity that are generated by these repetitive beam breaks. Time spent investigating the central region of the chamber can be reported as a percent of total session length for both the short and longer habituation versions of this test. Alternatively, center time can be examined in 5-min bins over the duration of the 30-min session to examine changing patterns of anxiety-related behavior. 5.3.1.4 Sample Results Figure 5.1A–C illustrates open field activity for galanin receptor subtype 2 (GalR2) null mutant mice.53 Behavioral measures reported include total distance traveled, horizontal beam breaks, and time spent exploring the center area of the chamber. There were no effects of genotype on horizontal activity or total distance traveled (all p comparisons > 0.05). Males were significantly more active than females on horizontal activity and total distance traveled in the arena (p = 0.0009 and p = 0.0042, respectively). Galanin null mutant mice spent less time exploring the central area of the chamber compared to wild type (WT) littermates, but this did not reach significance (p = 0.0714).

5.3.2

ELEVATED PLUS-MAZE/ELEVATED ZERO-MAZE

This well-established paradigm has a long and successful history in assessing anxiety-like behavior in mice.22,42,54–56 The test takes advantage of the natural tendency of mice to explore novel environments. The mouse is given the choice of spending time in open, unprotected maze arms or enclosed, protected arms, all elevated approximately 1 m from the floor. Mice tend to avoid the open areas, especially when they are brightly lit, favoring darker, more enclosed spaces. This approach–avoidance conflict results in behaviors that have been correlated with increases in physiological stress indicators.52 In contrast, administration of benzodiazepines and other



M +/+ M +/– M –/– F +/+ F +/– F –/–

Total Distance-Cumulative Beam Breaks

800 700 600 500 400 300 200 100 1-5

Horizontal Activity-Cumulative Beam Breaks

82

6-10 11-15 16-20 21-25 26-30 Minutes

450 400 350 300 250 200 150 100 50 1-5

(a)

6-10 11-15 16-20 21-25 26-30 Minutes

(b)

12

10

% Center Time

8

6

4

2

0 +/+

+/–

–/–

(c)

FIGURE 5.1 Effect of GalR2 mutation on open field exploration. There were no significant genotype differences on horizontal activity or total distance traveled (p > 0.05). Males were significantly more active than females on horizontal activity and distance traveled (all p comparisons < 0.01). Examination of open field center time as a preliminary screen for anxietylike behavior revealed no sex differences, thus data from males and females were combined. GalR2 -/- spent less time exploring the center of the open field than their wild type littermates (p = 0.0714), although this trend did not reach significance. N = 22 +/+, 23 +/-, 17 -/-. Data are shown as mean + standard error of the mean. Source: Reprinted from Bailey, Pavlova, Rohde, Hohmann, and Crawley. 2007. Galanin receptor subtype 2 (GalR2) null mutant mice display an anxiogenic-like phenotype specific to the elevated plus-maze. Pharmacol. Biochem. and Behav. 86:13, with permission from Elsevier.



83

anxiolytic treatments results in increased exploration of the open arms, without affecting general motivation or locomotion.42,55,57,58 5.3.2.1 Subjects The primary requirements for subjects performing this test are normal ambulatory ability and average levels of exploratory drive. Mice that spend prolonged time in the center start area, enter only partially into one arm of the maze without transitioning through, or do not explore the entire maze, may confound the interpretation of behavioral data for a group. In these cases, data may primarily reflect physical motor abilities that are minimally relevant to anxiogenic or anxiolytic traits. It is important to note this type of behavior during the test session, as it may be necessary for later identification of outliers. Strains that consistently demonstrate very low levels of exploratory behavior (e.g., AJ, some 129 substrains) should be avoided. 5.3.2.2 Equipment Conceptually the equipment design has remained virtually unchanged for mice since its introduction.59–61 However, there have been substantial alterations and modifications in the materials and specific details of the maze construction. The apparatus consists of two sets of opposing arms approximately 30 × 5 cm extending from a central (5 × 5 cm) region. Two arms are enclosed with 15-cm high walls. The remaining two arms are open. Differences in maze construction include wood construction versus Perspex or other similarly smooth material. Some researchers have provided a slightly raised lip (0.25 cm) on three sides of the open arms to minimize falls. Walls of the enclosed arms may be transparent, opaque, or dark. While a consensus has not been reached about the advantages or limitations of wall transparency, researchers may want to consider the impact of these different materials on light levels within the arm.62 Ideally, minimizing variability in external factors (e.g., light level differences) will increase replication across labs and simplify interpretation of behavioral findings. The elevated zero-maze offers a conceptually identical behavioral test that eliminates the ambiguous center start area of the elevated plus-maze (EPM).63 In the plusmaze, test subjects will often remain in the central start area, or return to it regularly, thereby spending considerable amounts of time in a region of the maze that is considered ambiguous in the evaluation of anxiety-related behavior. The elevated circular runway alternates equally sized, open, brightly lit areas and enclosed, dark arc areas. The uninterrupted nature of the open versus closed segments of the circular runway mitigates the concerns surrounding the central start area of the plus-maze. Similar behavioral measures are scored for this version of the test during the 5-min session. Scoring from a videotaped session minimizes environmental variables introduced by the presence of the investigator that may impact anxiety-related behaviors. Technological advances have been introduced as a means of standardizing the EPM paradigm, including automated tracking and scoring software (e.g., Noldus Ethovision video tracking, Hamilton-Kinder infrared photobeam tracking). Concerns have been raised10,42 about the sensitivity of automated systems for detecting measures of ethologically relevant risk assessment behaviors and the utility of


84


scoring many additional behavioral indices as factors to explain anxiety-related behavior of animals.64,65 Inconsistent results with anxiolytic compounds and a desire for more targeted therapeutic treatments suggests that scoring additional, ethologically relevant behavioral indicators (e.g., head dipping, stretch-attend postures) may provide more sensitive measures of the effects of new anxiolytic compounds.10,65 It remains to be determined whether current tracking and scoring software can accurately and consistently detect these additional behavioral indices in the wide variety of inbred strains and transgenic and knockout (KO) lines currently being studied. 5.3.2.3 Procedure Subjects are generally group-housed (four to five per cage) in same-sex home cages. Home cages are brought to the testing room or a common staging area 1 hr prior to testing. Transport mice singly in clean cages to the apparatus or testing room. Room level lighting should be consistent for all subjects. Mice generally avoid brightly lit areas, therefore high illumination levels would be expected to increase anxiety-like behaviors. Care is taken to avoid light levels that are high enough to restrict the natural exploratory tendency of mice. Pilot studies will assist in determining the most appropriate illumination level from those reported in the literature.67–70 Each subject is placed in the central area of the maze with open access to any arm. Mice are allowed to freely explore the maze for 5 min. The number of arm entries and the amount of time spent in the open and closed arms are recorded. These can be recorded manually by a highly trained observer, or by an automated photo beam sensor recording system. The session can also be recorded using any one of the currently available video tracking systems for subsequent scoring. There are advantages and limitations to each of these methods. The obvious advantage to scoring from a recorded test session is the ability to minimize errors and recheck the reliability of the scoring at a later time. Similarly, photo beam recording systems remove the subjective interpretations by the experimenter. For researchers with limited resources, however, these systems may be cost prohibitive. Two advantages of manual scoring by highly trained observers are lower equipment costs and identifying unusual or ethologically relevant behaviors that might go undetected by automated systems. 5.3.2.4 Analysis and Interpretation EPM results are generally analyzed using between-subjects ANOVAs followed by Newman-Keuls post-hoc comparisons when a significant ANOVA value is obtained. There are several factors that should be considered when interpreting EPM results. Strains or treatment groups that show unusually high or low time spent in the open arms may do so for reasons other than anxiety-related behavior. For instance, extensive time spent in the open arms may reflect a group that displays very low levels of exploratory activity. The arm they first transition into, closed or open, is where they remain. In addition, specific pharmacological treatments, background strain differences, genetic mutations, or environmental factors can impact locomotor activity, exploratory behavior, or behavioral motivation for novelty.25,38,39,44,71,72 Finally,



85

behavior in the EPM is influenced by prior handling, exposure to previous behavioral testing paradigms, or repeated experience in the plus-maze.10,54,56,73–77 Repeated testing was thought to have no significant impact on measures of anxiety behavior.59,61 However, recent studies suggest that prior test experience increases open arm avoidance behavior and alters the effectiveness of anxiolytic drugs in reducing open arm avoidance.57,75,77–84 The change in pharmacological efficacy has been termed “one-trial tolerance”78 and has been alternately explained as reflecting a change in the state of the benzodiazepine receptor or the gamma-aminobutyric acid (GABA)A receptor complex,58,83 a change in the anxiety state manifested in trial 1 compared to trial 2,84 or a change in the underlying mechanism triggering the behavior from one of unconditioned fear avoidance to learned avoidance based on prior exposure to the situation.85 These concerns can best be addressed by ensuring that test subjects are experimentally naïve and receive minimal handling. For situations in which retest in the EPM is necessary, Adamec and Shallow86 have developed a test–retest protocol that appears to prevent the increase in open arm avoidance generally exhibited in trial 2. They suggest a 3-wk interval between test sessions and moving the maze to a novel test room for the second session. 5.3.2.5 Sample Results Figure 5.2A–D provides an example of the behavioral measures most commonly reported in the literature.60,61,87 In this experiment mice with a null mutation in the galanin receptor subtype GalR2 were tested in several complementary approach– avoidance paradigms designed to assess anxiety-like traits. Previous research has implicated the neuropeptide galanin in rodent emotionality.52,88–91 The results from two independent cohorts of mice missing the galanin subtype-2 receptor indicate an anxiogenic phenotype in the EPM. Both cohorts spent significantly less time exploring the open arms (Figure 5.2A) and made fewer open arm entries (Figure 5.2B). Importantly, the number of overall arm transitions (Figure 5.2D) did not significantly differ compared with WT littermates.53 Although not shown in the figure, some labs are now reporting additional ethologically relevant behaviors in their experimental results, including head dips and stretch-attend postures. These behaviors have been described as a means for the animal to actively assess dangers within the specific testing environment and are characterized as risk assessment behaviors.6,42

5.3.3

LIGHT n DARK EXPLORATION TEST

The light n dark exploration test, developed by Crawley and Goodwin,16 was a precursor to the EPM and provides another means of examining anxiety-like behavior in rodents. As with the EPM, the subject is exposed to a novel environment with protected (dark compartment) and unprotected (light compartment) areas. The inherent conflict between exploratory drive and risk avoidance is thought to inhibit exploration.16,92,93 Most mice naturally demonstrate a preference for the dark, protected compartment. The key measure for assessing anxiety-related behavior in this design is a change in willingness to explore the illuminated, unprotected area, reflected in increases or decreases in the number of transitions between the compartments, and in time spent in each compartment, during a 10-min test session. Treatment


Methods of Behavior Analysis in Neuroscience, Second Edition 60

70

50

60 50

40

% Open Entries

% Time Spent in Open Arms

86

30 * 20

30 20

* 10 0

* 40

10 +/+ +/– –/–

+/+ +/– –/–

Cohort 1

Cohort 2

0

+/+ +/– –/– Cohort 1

Cohort 2

(a)

(b)

12

20

*

16

8

# Total Entries

# Closed Entries

10

6 4

12

8

4

2 0

+/+ +/– –/–

+/+ +/– –/–

+/+ +/– –/–

Cohort 1

Cohort 2

(c)

0

+/+ +/– –/– Cohort 1

+/+ +/––/– Cohort 2

(d)

FIGURE 5.2 Anxiogenic-like phenotype of GalR2 knockout mice on the elevated plusmaze. Two independent cohorts of GalR2 -/- displayed an anxiogenic-like phenotype compared to their +/+ littermates in the elevated plus-maze. GalR2 -/- mice spent significantly (*p < .05) less time in the open arms (A) and made fewer entries into the open arms (B) than +/+ mice. The -/- mice in experiment 1 made significantly (*) more entries into the closed arms (C), while total arm entries were similar across genotypes (D), suggesting that less exploration of the open arms did not reflect lower overall exploratory behavior. Cohort 1 N = 22 +/+, 23 +/-, 19 -/-; Cohort 2 N = 14 +/+, 12 +/-, 17 -/-. Data are shown as mean + standard error of the mean. Source: Reprinted from Bailey, Pavlova, Rohde, Hohmann, and Crawley. 2007. Galanin receptor subtype 2 (GalR2) null mutant mice display an anxiogenic-like phenotype specific to the elevated plus-maze. Pharmacol. Biochem. and Behav. 86:13, with permission from Elsevier.

with anxiolytic drugs increased the number of transitions between the two compartments, without altering the preference of the mice to spend more time in the dark compartment.16,93 This increase in exploratory activity is interpreted as a release of exploratory inhibition.16



87

5.3.3.1 Subjects Similar to the EPM, careful consideration should be given to testing specific inbred strains of mice and mice with genetic manipulations that inhibit locomotor activity or interfere with novelty-seeking behavior. 5.3.3.2 Equipment The chamber is constructed from a standard polypropylene rat cage (44 × 21 × 21 cm) divided into two unequal compartments by a dark partition with a small aperture (13 × 5 cm) located in the bottom center. The smaller compartment (14 cm) is painted black and covered by a hinged lid. The larger compartment (28 cm) is uncovered with transparent sides and is brightly lit from above by fluorescent room lighting. Transitions between the compartments are electronically recorded by four sets of photocells mounted in the partition opening. Entry into the dark compartment triggers a timer that records the duration of time spent in the dark compartment. 5.3.3.3 Procedure Transport acclimated mice to the test room or test apparatus singly, in clean cages. The mouse is placed centrally into the larger, brightly illuminated compartment facing away from the partition. Mice are allowed to freely explore the chamber for 10 min while transitions and time spent in the dark compartment are recorded. After completion of the test, return mice to the home cage. Unlike the EPM, some previous testing experience with this, or other behavioral tests, does not appear to alter behavioral performance.40,92,94 5.3.3.4 Analysis and Interpretation The number of transitions and the time spent in the dark compartment are analyzed using one-way ANOVAs and Newman-Keuls post-hoc comparisons when indicated. Mice exhibiting higher levels of anxiogenic-like behavior will make fewer transitions between the brightly illuminated, open area and the dark, enclosed compartment. Many laboratories also use time in the dark or, reciprocally, time in the light as a measure of anxiogenic-like behavior.51,95–97 Recently some laboratories have included time spent in risk assessment as another measure of anxiety-related behavior.97 Risk assessment includes a stretch-attend posture in which the head and forepaws extend into the lighted area but the remainder of the body stays in the dark compartment. This test has been shown to be very sensitive to the anti-anxiety–like effects of benzodiazepines. Benzodiazepines increase transitions between the compartments without affecting general locomotor activity. Investigators should use caution when interpreting results of new compounds on anxiety-like behavior until they have been screened for nonspecific locomotor effects in a separate apparatus such as an automated open field.


88


5.3.3.5 Sample Results Figure 5.3A and B illustrate the two most commonly reported behavioral measures from the light n dark exploration test. Figure 5.3C illustrates risk assessment, a measure appearing more often in recent literature as another indicator of anxietyrelated behavior in rodents.5,6,42 The study97 illustrated in Figure 5.3 examined the effects of two centrally administered neuropeptides, NPY and galanin, on anxietyrelated behavior in C57BL/6J mice. Mice receiving two different doses of NPY made more transitions between the two chambers and spent more time in the light compartment than controls or galanin-treated mice. In addition, Figure 5.3C illustrates that NPY-treated mice spent significantly less time engaged in risk assessment than controls or galanin-treated mice.97 Thus, neuropeptide Y, but not galanin, produced an anxiolytic-like action when centrally administered to mice.

5.3.4

THE SOCIAL INTERACTION TEST

The social interaction test, developed by File and Hyde,98 provided the first test of anxiety-like behavior that focused on ethologically relevant concepts. The test eliminated the need to introduce aversive or appetitive conditions. In addition, the design of the social interaction test is suitable for use with naïve animals. Pairs of male rats are allowed to freely interact in an arena while time spent interacting is recorded as the dependent measure. Interaction time for each of the rats in the pair is directly impacted by the behavior of the partner animal. Therefore, the pair counts as one unit for data collection purposes. If the design of the experiment involves one rat receiving treatment while the other serves as a control, then interaction time initiated by the treated rat is the appropriate dependent measure. Anxiolytic-like behavior is inferred if social interaction time increases and general motor activity remains unaffected. Conversely, decreased time spent engaging in social behavior would indicate anxiogenic-like behavior. Manipulating environmental conditions allows the researcher to induce varying levels of anxiety in the test subject. The arena is either familiar or novel and illumination levels can range from bright to dim. These conditions can be characterized as low anxiety inducing when the environment is familiar (F) and illumination levels are low (L), versus high anxiety inducing when lighting conditions are bright and the test arena is unfamiliar (U). The remaining two conditions, low illumination, novel arena and high (H) illumination, familiar arena, result in moderate baseline anxiety levels.99 The ability to systematically increase or decrease baseline anxiety levels has proven especially useful for screening novel pharmaceutical compounds developed for treating anxiety. Higher baseline anxiety levels, induced by the HU condition, are well suited for detecting the effects of anxiolytic compounds. Conversely, robust anxiogenic effects can be detected in the LF condition, when it is expected that the greatest amount of time would be spent in social interaction.99 It should be noted that adult female rats failed to increase time spent in social interaction as a function of increasing familiarity of the test environment,100 suggesting that some environmental manipulations have different salience for the social behaviors of each sex.101 Although originally designed for rats, modified versions of this test have been used relatively successfully to evaluate anxiety-like behavior in mice.102,103 It



89

Time Spent in the Light Compartment (sec)

500 ***

***

0.5 NPY

1 NPY

400 300 200 100 0

Veh

0.5 GAL 1 GAL (a)

*

Light-dark Transitions

75

*

50

25

0 Veh

0.5 GAL 1 GAL 0.5 NPY 1 NPY (b)

Time of Risk Assessment (sec)

100

75

50 **

25

**

0 Veh

0.5 GAL 1 GAL

0.5 NPY

1 NPY

(c)

FIGURE 5.3 Light n dark exploration. Mice treated with NPY at an icv dose of 0.5 and 1.0 nmol spent significantly more time in the brightly lit open area (A) and made significantly more transitions (B) between the two compartments than the vehicle-treated (deionized water) control group. Attempts to enter the light compartment, termed risk assessment, were significantly lower in NPY-treated mice than vehicle-treated mice (C). The neuropeptide galanin did not produce any significant effects at similar doses in this test. N = 8–13 per treatment group. *p < 0.05, **p < 0.01, ***p < 0.001. Data are shown as mean + standard error of the mean. Source: Reprinted from Karlsson, Holmes, Heilig, and Crawley. 2005. Anxiolytic-like actions of centrally administered neuropeptide Y, but not galanin, in C57BL/6J mice. Pharmacol. Biochem. and Behav. 80:431, with permission from Elsevier.


90


should be noted that effects demonstrated in mice are less consistent than those exhibited by rats. Of the manipulated variables, light level appears to have the greatest impact on anxiety in mice,104,105 while familiarity of the test arena, similar to the response of female rats, does not provide consistent changes in anxiety level in mice. In singly housed mice, similar to the effect seen in rats, anxiolytics reverse the inhibition of social interaction induced by brighter lighting.102,106 5.3.4.1 Subjects Inconsistent findings with female mice would indicate that this test is more suitable for testing male social behavior. Young male mice of approximately the same weight (< 4 g difference) are the preferred subjects. Noticeably aggressive, dominant, grouphoused mice should not be used, as this could significantly impact the sociability of the isolate mouse. 5.3.4.2 Equipment The novel cage environment can be a standard polypropylene rat cage or clear Plexiglas chamber that is unfamiliar to the subjects before acclimation. Recording equipment is mounted above the cage at a distance that provides complete coverage of the arena but does not interfere with the test environment. 5.3.4.3 Procedure Social interaction is tested between pairs of mice that are either singly housed for 3–6 wk or group housed. Test pairs can involve one group-housed and one isolate mouse, or two unfamiliar, group-housed mice. Singly housing mice has been demonstrated to increase social investigation.105,106 Isolate mice are acclimated to the testing cage (size ranges 30 × 25 × 17 cm, 20 × 30 × 20 cm) for 30 min prior to testing. At the end of the acclimation period a group-housed mouse is introduced for a 4-min test period. In the case of pairs of unfamiliar, group-housed mice, each mouse is given a 10-min acclimation session in the test cage on the two days prior to the experiment. On day 3 the pair of mice is placed into the test cage for the 10-min test session.103 Test sessions are recorded and scored at a later time. As the test was originally developed, the mean total time engaged in social behaviors is scored, analyzed, and reported.17 An alternative to this method is to score categories of behavior for each treatment group including aggressive (attack, aggressive unrest), fearful (vigilant posture, escape and defense activity), social (following, social sniffing, overunder climbing), and locomotion (rearing, walking during cage investigation) and report the mean number of events in each category.102 Scorers should be blind to any experimental treatment. Inter-rater reliability values are determined for a sampling of the tested mice by multiple scorers. If the experimental design includes evaluating the effects of anxiolytic ligands, illumination levels can be increased to inhibit baseline social investigation. Conversely, low illumination levels (< 20 lux) may enhance social investigation, providing a method for exploring anxiogenic effects on baseline social interactions.



91

5.3.4.4 Analysis and Interpretation Mean time spent in social interaction is the most reported parameter of social behavior. Active social behavior of the subject mouse is scored, including following, sniffing, and climbing on or under the other mouse. The means for two groups are analyzed using an unpaired Student’s t-test. If lighting levels have been manipulated, or more than two groups are included, then analyze the means using an ANOVA followed by Neuman-Keuls post-hoc test when indicated. 5.3.4.5 Sample Results Time spent interacting with an unfamiliar partner is the primary measure reported as a measure of sociability in mice. Figure 5.4 illustrates a study that examined social investigation in vasopressin 1a receptor (V1aR) KO and WT control mice.103 Previous findings had implicated this receptor in modulating social recognition memory. The mean amount of time spent engaged in social behavior is shown in Figure 5.4 for pairs of mice with a null mutation in the V1aR KO compared to WT pairs. V1aR KO pairs spent significantly less time in social interaction than WT pairs.

5.3.5

NOVELTY-INDUCED HYPOPHAGIA

Rodents encountering a desirable food in a novel environment will consume very limited quantities after considerable investigation. Mice tend to avoid exploration of novel open environments, yet are motivated to approach and consume palatable food.

Social Interaction Time (sec)

150

120

* * *

90

60

30 (8) 0

WT

(8) V1aR KO

FIGURE 5.4 Time spent in social investigation in the social interaction test of V1aR knockout (KO) mice and wild type mice. V1aR KO mice spent significantly less time in social interactions (***p < 0.0001) compared to wild type mice. N = 8 pairs of each genotype. Data are shown as mean + standard error of the mean. Source: Reprinted from Egashira, Tanove, and Matsuda et al. 2007. Impaired social interaction and reduced anxiety-related behavior in vasopressin V1a receptor knockout mice. Behavioral Brain Research 178:125, with permission from Elsevier.


92


This inhibition of feeding behavior has been termed hyponeophagia and is robust in both rats and mice. The response is unconditioned, requires no training, and can be elicited in food-deprived or satiated animals by substituting a highly palatable food source for regular chow. Treatment with a variety of drugs used to manage anxiety in humans reliably reverses this decrement in feeding, reducing the latency to the first taste and increasing the total amount of food consumed (for review see107,108). Several factors have been found to influence baseline levels of hyponeophagia in mice, including the genetic background of inbred strains, long durations of isolate housing, and specific genetic mutations that affect anxiety-related behaviors.109–112 Several methodological concerns have been raised with hyponeophagia-based testing. One is the failure of many designs to include a comparison of food consumption in the home cage environment.107 Investigators should report equivalent assessment measures of feeding behavior (latency and total consumed) in both the novel and home cage environments to determine the contribution of the independent variable to any observed differences.107 Another possible confound is the potential impact of drug treatments or genetic manipulations on factors unrelated to anxiety. Drugs targeting serotonergic function selectively decrease feeding behavior and alter macronutrient intake.113,114 Experimental protocols that incorporate food deprivation may compound these appetite-related effects, potentially masking or exacerbating anxiety-like measures. Substituting a familiar, highly palatable food in the home cage and unfamiliar environment minimizes some of these methodological problems.107 In the home cage mice quickly approach and ingest the food. In the novel environment they show a marked increase in latency to first taste the familiar food.108 In addition, Dulawa and Hen107 suggest using higher illumination levels for the novel environment to optimize hyponeophagia levels. In their modified model, Dulawa, Holick, Gundersen, and Hen (2004)115 propose reporting measures of both latency and total food consumed in the novel and home cage environments. When latency alone is reported, home cage scores may be very low, making it extremely difficult to detect manipulations expected to enhance appetite. This modified model provides some advantages over older versions, including improved sensitivity and reliability of the test results by assessing two behavioral measures, and increasing the likelihood that the test will discriminate treatments that enhance, as well as decrease, feeding behavior. However, as with most designs, there are a few limitations to note, including training the mice to consume the highly palatable novel food and single housing animals immediately prior to testing. 5.3.5.1 Subjects Mice ranging in age from juvenile to older adult can be tested in this paradigm. As mentioned above, attention should be given to the background strain, housing arrangements, and genetic mutations designed to influence emotionality, as these may alter baseline levels of feeding behavior. Depending on the independent variables of interest in the experimental design, group-housed mice should be singly housed for at least 5 days prior to testing.



93

5.3.5.2 Equipment Standard mouse cages of identical size can be used for the home cage and novel cage environments. In the novel environment condition, cages can be either free of bedding or have new bedding. One option for a highly palatable food source is diluted (3–1) sweetened condensed milk (Carnation), although other food may be substituted. Lighting in the home cage condition is dim (~50 lux). The illumination level for novel cage testing is very bright (~1200 lux) and the table area under the test cage is lined with white paper. 5.3.5.3 Procedure Singly housed mice are trained to consume the palatable food source by introducing it to them in their home cage for 30 min daily over three consecutive days. Diluted condensed milk in plastic serological pipettes (10 mL) with attached sippers and rubber stoppers are mounted to the wire cage lid. Mice are allowed access for 30 min daily. On the fourth day mice are tested in the home cage condition. Remove mice from the cage while the pipette is installed on the cage lid. This maintains a consistency in the handling procedure for the two (home versus novel cage) experimental conditions. Commence testing as soon as mice are returned to the cage. Record the latency to the first lick and the total volume consumed in 5-min intervals across the 30-min session. Note any mice that do not consume any condensed milk. They should be excluded from further testing as they failed the training protocol. On day 5, position the pipette in the wire lid of the novel cage and place the mouse into the novel cage environment. Record latency and total volume consumed as previously described. 5.3.5.4 Analysis and Interpretation Comparison of the total volume of food consumed across the 30 min can be analyzed using a between-subjects repeated measures ANOVA. Although the initial 5-min period may provide sufficient information for assessing anxiolytic effects of treatment, the sensitivity of this initial period for distinguishing anxiogenic effects is less certain.115 One-way ANOVA may be used for comparing means for total food consumed. Latency data generally violate several assumptions of the ANOVA test; therefore, violations of these tenets should be examined. It may be necessary to transform or truncate the data, according to statistical convention, prior to analysis.116 5.3.5.5 Sample Results The graphs presented in Figure 5.5A and B illustrate the behavioral measures generally reported in novelty-induced hypophagia testing, latency to the first lick, and total volume of food consumed in the initial 5-min period.115 This study examined the effect of chronic fluoxetine treatment (29 days) on the latency and volume of food consumed in a familiar home cage environment versus a novel environment for BALB/cJ mice, a highly anxious strain. Fifteen mice per group received tap water laced with one of three fluoxetine doses or tap water only. Fluoxetine decreased the latency to the first lick at all doses in the novel cage, but had no effect on latency to drink in the home cage (Figure 5.5A). In addition, in the novel environment fluoxetine


94


")(+

!

"&#)*%'%$

FIGURE 5.5 Novelty-induced hypophagia. The effects of a novel cage on latency to consume, and the amount consumed, of a familiar and palatable snack are shown for BALB/c mice. The difference in latency to consume (A) in the home cage, (B) in a novel cage, and (C) amount consumed in the first 5 min in the home cage and a novel cage, for BALB/c mice receiving 0 (n = 13), 10 (n = 13), 18 (n = 12), or 25 (n = 14) mg/kg/day chronic fluoxetine treatment, *p < 0.05 vs. control group with ANOVA, is shown. Data are shown as mean + standard error of the mean. Source: Reprinted from Dulawa, Holick, Gundersen and Hen. 2004. Effects of chronic fluoxetine in animal models of anxiety and depression. Neuropsychopharmacology. 29:1327, with permission from Elsevier.



95

decreased overall food consumption compared to the home environment. However, in both the home and novel cages, the 18 mg/kg dose increased food consumption over that of the 0 and 10 mg/kg doses. Although 25 mg/kg did increase food consumption in both conditions, serum levels of mice in the home cage were more than twice that observed in humans. In this study the 10 and 18 mg/kg doses produced anxiolytic effects in the novelty-induced hypophagia test.115

5.4

CONCLUSION

Several ethologically relevant tests of anxiety-like behavior have been presented as a representative sampling of the broader collection of assays designed to assess anxiety-related behavior in mice in the field of behavioral neuroscience. Space limitations and methodological specificity necessitated limiting the scope of the present work to this smaller subset of anxiety-related behavioral tests. The interested researcher seeking additional tests that directly assess anxiety-like behavior may wish to explore the following excellent paradigms: stress-induced hyperthermia, a measure of the effect of stress (handling, temperature measurement) on body temperature;117 the mouse marble-burying test, a modification of the shock-probe burying test for rats;118,119 the open field emergence test;52 fear conditioned startle and light enhanced startle;27,120,121 and the Vogel conflict test.19 Investigators seeking an in-depth characterization of anxiety-related behaviors in a mutant line of mice are encouraged to conduct two or more of these well-validated assays to strengthen the interpretation of their findings.

REFERENCES 1. Nutt, D. J. 1990. The pharmacology of human anxiety. Pharmacology & Therapeutics 47 (2):233–66. 2. Weiss, S. J. 2007. Neurobiological alterations associated with traumatic stress. Perspectives in Psychiatric Care 43 (3):114–22. 3. American Psychiatric Association. 2000. Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Washington, DC: American Psychiatric Association. 4. Blanchard, R. J., and Blanchard D. C. 1989 Attack and defense in rodents as ethoexperimental models for the study of emotion. Progress in Neuro-Psychopharmacology & Biological Psychiatry 13:S3–S14. 5. Blanchard, R. J., Griebel, G., Henrie, J. A., and Blanchard, D. C. 1997. Differentiation of anxiolytic and panicolytic drugs by effects on rat and mouse defense test batteries. Neurosci. Biobehav. Rev. 21 (6):783–89. 6. Blanchard, D. C., Griebel, G., and Blanchard, R. J. 2003. The mouse defensive test battery: Pharmacological and behavioral assays for anxiety and panic. European Journal of Neuroscience 463:97–116. 7. Cryan, J. F., and Holmes, A. 2005. The ascent of mouse: Advances in modelling human depression and anxiety. Nature Reviews: Drug Discovery 4 (9):775–90. 8. Hall, C. S. 1934. Emotional behavior in the rat. I. Defecation and urination as measures of individual differences in emotionality. Journal of Comparative Psychology 18 (3):385–403. 9. Ohl, F. 2005. Animal models of anxiety. Handbook of Experimental Pharmacology (169):35–69.


96


10. Rodgers, R. J., Cao, B. J., Dalvi, A., and Holmes, A. 1997. Animal models of anxiety: An ethological perspective. Brazilian Journal of Medical and Biological Research 30 (3):289–304. 11. Belzung, C., and Griebel, G. 2001. Measuring normal and pathological anxiety-like behaviour in mice: A review. Behavioural Brain Research 125:141–49. 12. Landgraf, R., and Wigger, A. 2002. High vs. low anxiety-related behavior rats: An animal model of extremes in trait anxiety. Behavior Genetics 32 (5):301–14. 13. Finn, D. A., Rutledge-Gorman, M. T., and Crabbe, J. C. 2003. Genetic animal models of anxiety. Neurogenetics 4 (3):109–35. 14. Gross, C., Zhuang, X., Stark, K., et al. 2002. Serotonin1A receptor acts during development to establish normal anxiety-like behaviour in the adult. Nature 416:396–400. 15. Borsini, F., Lecci, A., Volterra, G., and Meli, A. 1989. A model to measure anticipatory anxiety in mice? Psychopharmacology 98 (2):207–11. 16. Crawley, J., and Goodwin, F. K. 1980. Preliminary report of a simple animal behavior model for the anxiolytic effects of benzodiazepines. Pharmacology, Biochemistry, and Behavior 13 (2):167–70. 17. File, S. E. 1980. The use of social interaction as a method for detecting anxiolytic activity of chlordiazepoxide-like drugs. Journal of Neuroscience Methods 2 (3):219–38. 18. Slotnick, B. M., and Jarvik, M. E. 1966. Deficits in passive avoidance and fear conditioning in mice with septal lesions. Science 154 (3753):1207–8. 19. Vogel, J. R., Beer, B., and Clody, D. E. 1971. A simple and reliable conflict procedure for testing anti-anxiety agents. Psychopharmacologia 21 (1):1–7. 20. Fendt, M., and Fanselow, M. S. 1999. The neuroanatomical and neurochemical basis of conditioned fear. Neurosci. Biobehav. Rev. 23 (5):743–60. 21. Crawley, J. N. 1999. Behavioral phenotyping of transgenic and knockout mice: Experimental design and evaluation of general health, sensory functions, motor abilities, and specific behavioral tests. Brain Research 835 (1):18–26. 22. Crawley, J. N. 2007. What’s wrong with my mouse?: Behavioral phenotyping of transgenic and knockout mice. 2nd ed. Hoboken, NJ: Wiley-Liss. 23. Crawley, J. N., Belknap, J. K., Collins, A., et al. 1997. Behavioral phenotypes of inbred mouse strains: Implications and recommendations for molecular studies. Psychopharmacology 132:107–24. 24. Crawley, J. N., and Paylor, R. 1997. A proposed test battery and constellations of specific behavioral paradigms to investigate the behavioral phenotypes of transgenic and knockout mice. Hormones and Behavior 31:197–211. 25. Holmes, A. 2001. Targeted gene mutation approaches to the study of anxiety-like behavior in mice. Neurosci. Biobehav. Rev. 25 (3):261–73. 26. Weiss, S.M., Lightowler, S., Stanhope, K. J., Kennett, G. A., and Dourish, C. T. 2000. Measurement of anxiety in transgenic mice. Reviews in the Neurosciences 11 (1):59–74. 27. Davis, M. 1979. Morphine and naloxone: Effects on conditioned fear as measured with the potentiated startle paradigm. European Journal of Pharmacology 54 (4):341–47. 28. Davis, M. 1990. Animal models of anxiety based on classical conditioning: The conditioned emotional response (CER) and the fear-potentiated startle effect. Pharmacology & Therapeutics 47 (2):147–65. 29. Davis, M. 1992. The role of the amygdala in fear-potentiated startle: Implications for animal models of anxiety. Trends in Pharmacological Sciences 13 (1):35–41. 30. Aron, C., Simon, P., Larousse, C., and Boissier, J. R. 1971. Evaluation of a rapid technique for detecting minor tranquilizers. Neuropharmacology 10 (4):459–69. 31. Pinel, J. P., and Treit, D. 1978. Burying as a defensive response in rats. Journal of Comparative and Physiological Psychology 92 (4):708–12.



97

32. Hofer, M. A. 1973. Maternal separation affects infant rats’ behavior. Behavioral Biology 9 (5):629–33. 33. Plotsky, P.M., and Meaney, M. J. 1993. Early, postnatal experience alters hypothalamic corticotropin-releasing factor (CRF) mRNA, median eminence CRF content and stress-induced release in adult rats. Brain Research: Molecular Brain Research 18 (3):195–200. 34. Archer, T., Sjödén, P. O., and Nilsson, L. G. 1984. The importance of contextual elements in taste-aversion learning. Scandinavian Journal of Psychology 25 (3):251–57. 35. Wahlsten, D. 2001. Standardizing tests of mouse behavior: Reasons, recommendations, and reality. Physiology & Behavior 73:695–704. 36. Wahlsten, D., Rustay, N. R., Metten, P., and Crabbe, J. C. 2003. In search of a better mouse test. Trends in Neurosciences 26:132–36. 37. Würbel, H. 2001. Ideal homes? Housing effects on rodent brain and behaviour. Trends in Neurosciences 24:207–11. 38. Crabbe, J. C. 1986. Genetic differences in locomotor activation in mice. Pharmacology, Biochemistry, and Behavior 25:289–92. 39. DeFries, J. C., Gervais, M. C., and Thomas, E. A. 1978. Response to 30 generations of selection for open-field activity in laboratory mice. Behavior Genetics 8 (1):3–13. 40. McIlwain, K. L., Merriweather, M. Y., Yuva-Paylor, L. A., and Paylor, R. 2001. The use of behavioral test batteries: Effects of training history. Physiology & Behavior 73 (5):705–17. 41. Paylor, R., Spencer, C. M., Yuva-Paylor, L. A., and Pieke-Dahl, S. 2006. The use of behavioral test batteries, II: Effect of test interval. Physiology & Behavior 87 (1):95–102. 42. Rodgers, R. J., and Dalvi, A. 1997. Anxiety, defence and the elevated plus-maze. Neurosci. Biobehav. Rev. 21 (6):801–10. 43. Elliott, B. M., and Grunberg, N. E. 2005. Effects of social and physical enrichment on open field activity differ in male and female Sprague-Dawley rats. Behavioural Brain Research 165 (2):187–96. 44. Bailey, K. R., Rustay, N. R., and Crawley, J. N. 2006. Behavioral phenotyping of transgenic and knockout mice: Practical concerns and potential pitfalls. ILAR Journal/ National Research Council, Institute of Laboratory Animal Resources 47 (2):124–31. 45. Meijer, M. K., Sommer, R., Spruijt, B. M., van Zutphen, L. F., and Baumans, V. 2007. Influence of environmental enrichment and handling on the acute stress response in individually housed mice. Laboratory Animals 41 (2):161–73. 46. Van Loo, P. L., Van der Meer, E., Kruitwagen, C. L., Koolhaas, J. M, Van Zutphen, L. F., and Baumans, V. 2004. Long-term effects of husbandry procedures on stress-related parameters in male mice of two strains. Laboratory Animals 38 (2):169–77. 47. Christmas, A. J., and Maxwell, D. R. 1970. A comparison of the effects of some benzodiazepines and other drugs on aggressive and exploratory behaviour in mice and rats. Neuropharmacology 9 (1):17–29. 48. Prut, L., and Belzung, C. 2003. The open field as a paradigm to measure the effects of drugs on anxiety-like behaviors: A review. European Journal of Pharmacology 463 (1–3):3–33. 49. Ernsberger, P., Azar, S., and Iwai, J. 1983. Open-field behavior in two models of genetic hypertension and the behavioral effects of salt excess. Behavioral and Neural Biology 37 (1):46–60. 50. Kafkafi, N., Lipkind, D., Benjamini, Y., Mayo, C. L., Elmer, G. I., and Golani, I. 2003. SEE locomotor behavior test discriminates C57BL/6J and DBA/2J mouse inbred strains across laboratories and protocol conditions. Behavioral Neuroscience 117 (3):464–77.


98


51. Hefner, K., Cameron, H. A., Karlsson, R. M., and Holmes, A. 2007. Short-term and long-term effects of postnatal exposure to an adult male in C57BL/6J mice. Behavioural Brain Research 182 (2):344–8. 52. Holmes, A., Kinney, J. A., Wrenn, C. C. et al. 2003. Galanin GAL-R1 receptor null mutant mice display increased anxiety-like behavior specific to the elevated plus-maze. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology 28 (6):1031–44. 53. Bailey, K.R., Pavlova, M. N., Rohde, A. D., Hohmann, J. G., and Crawley, J. N. 2007. Galanin receptor subtype 2 (GalR2) null mutant mice display an anxiogenic-like phenotype specific to the elevated plus-maze. Pharmacology, Biochemistry, and Behavior 86 (1):8–20. 54. Pellow, S., and File, S. E. 1986. Anxiolytic and anxiogenic drug effects on exploratory activity in an elevated plus-maze: A novel test of anxiety in the rat. Pharmacology, Biochemistry, and Behavior 24 (3):525–29. 55. Rodgers, R. J., Johnson, N. J., Carr, J., and Hodgson, T. P. 1997. Resistance of experientially induced changes in murine plus-maze behaviour to altered retest conditions. Behavioural Brain Research 86 (1):71–77. 56. Bertoglio, L. J., and Carobrez, A. P. 2002. Prior maze experience required to alter midazolam effects in rats submitted to the elevated plus-maze. Pharmacology, Biochemistry, and Behavior 72 (1–2):449–55. 57. Gonzalez, L.E., and File, S. E. 1997. A five minute experience in the elevated plus-maze alters the state of the benzodiazepine receptor in the dorsal raphe nucleus. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 17 (4):1505–11. 58. Handley, S. L., and Mithani, S. 1984. Effects of alpha-adrenoceptor agonists and antagonists in a maze-exploration model of “fear”-motivated behaviour. Naunyn-Schmiedeberg’s Archives of Pharmacology 327 (1):1–5. 59. Pellow, S., Chopin, P., File, S. E., and Briley, M. 1985. Validation of open:closed arm entries in an elevated plus-maze as a measure of anxiety in the rat. Journal of Neuroscience Methods 14 (3):149–67. 60. Lister, R. G. 1987. The use of the plus-maze to measure anxiety in the mouse. Psychopharmacology 92:180–85. 61. Hagenbuch, N., Feldon, J., and Yee, B. K. 2006. Use of the elevated plus-maze test with opaque or transparent walls in the detection of mouse strain differences and the anxiolytic effects of diazepam. Behavioural Pharmacology 17:31–41. 62. Shepherd, J. K., Grewal, S. S., Fletcher, A., Bill, D. J., and Dourish, C. T. 1994. Behavioural and pharmacological characterisation of the elevated “zero-maze” as an animal model of anxiety. Psychopharmacology 116 (1):56–64. 63. Wall, P. M., and Messier, C. 2000. Ethological confirmatory factor analysis of anxiety-like behaviour in the murine elevated plus-maze. Behavioural Brain Research 114 (1–2):199–212. 64. Wall, P. M., and Messier, C. 2001. Methodological and conceptual issues in the use of the elevated plus-maze as a psychological measurement instrument of animal anxietylike behavior. Neurosci. Biobehav. Rev. 25 (3):275–86. 65. Borsini, F., Podhorna, J., and Marazziti, D. 2002. Do animal models of anxiety predict anxiolytic-like effects of antidepressants? Psychopharmacology 163 (2):121–41. 66. Griebel, G., Belzung, C., Perrault, G., and Sanger, D. J. 2000. Differences in anxietyrelated behaviours and in sensitivity to diazepam in inbred and outbred strains of mice. Psychopharmacology 148 (2):164–70. 67. Haller, J., Varga, B., Ledent, C., Barna, I., and Freund, T. F. 2004. Context-dependent effects of CB1 cannabinoid gene disruption on anxiety-like and social behaviour in mice. The European Journal of Neuroscience 19 (7):1906–12.



99

68. Patti, C.L., Kameda, S. R., Carvalho, R. C., et al. 2006. Effects of morphine on the plus-maze discriminative avoidance task: Role of state-dependent learning. Psychopharmacology 184 (1):112. 69. Rodgers, R.J., Boullier, E., Chatzimichalaki, P., Cooper, G. D., and Shorten, A. 2002. Contrasting phenotypes of C57BL/6JOlaHsd, 129S2/SvHsd and 129/SvEv mice in two exploration-based tests of anxiety-related behaviour. Physiology & Behavior 77 (2–3):301–10. 70. Galani, R., Duconseille, E., Bildstein, O., and Cassel, J. C. 2001. Effects of room and cage familiarity on locomotor activity measures in rats. Physiology & Behavior 74 (1–2):1–4. 71. Holmes, A., and Rodgers, R. J. 1998. Responses of Swiss-Webster mice to repeated plus-maze experience: Further evidence for a qualitative shift in emotional state? Pharmacology, Biochemistry, and Behavior 60 (2):473–88. 72. Mitchell, H. A., Ahern, T. H., Liles, L. C., Javors, M. A., and Weinshenker, D. 2006. The effects of norepinephrine transporter inactivation on locomotor activity in mice. Biological Psychiatry 60 (10):1046–52. 73. Rodgers, R. J. 1997. Animal models of “anxiety”: Where next? Behavioural Pharmacology 8:477–96. Discussion 497–501. 74. Rodgers, R.J., Lee, C., and Shepherd, J. K. 1992. Effects of diazepam on behavioural and antinociceptive responses to the elevated plus-maze in male mice depend upon treatment regimen and prior maze experience. Psychopharmacology 106 (1):102–10. 75. Rodgers, R.J., Johnson, N. J., Cole, J. C., Dewar, C. V., Kidd, G. R., and Kimpson, P. H. 1996. Plus-maze retest profile in mice: Importance of initial stages of trail 1 and response to post-trail cholinergic receptor blockade. Pharmacology, Biochemistry, and Behavior 54 (1):41–50. 76. Rodgers, R.J., and Shepherd, J. K. 1993. Influence of prior maze experience on behaviour and response to diazepam in the elevated plus-maze and light/dark tests of anxiety in mice. Psychopharmacology 113 (2):237–42. 77. Treit, D., Menard, J., and Royan, C. 1993. Anxiogenic stimuli in the elevated plus-maze. Pharmacology, Biochemistry, and Behavior 44 (2):463–69. 78. File, S.E. 1990. One-trial tolerance to the anxiolytic effects of chlordiazepoxide in the plus-maze. Psychopharmacology 100 (2):281–82. 79. Lee, C., and Rodgers, R. J. 1990. Antinociceptive effects of elevated plus-maze exposure: Influence of opiate receptor manipulations. Psychopharmacology 102 (4):507–13. 80. Griebel, G., Moreau, J. L., Jenck, F., Misslin, R., and Martin, J. R. 1994. Acute and chronic treatment with 5-HT reuptake inhibitors differentially modulate emotional responses in anxiety models in rodents. Psychopharmacology 113 (3–4):463–70. 81. Bertoglio, L.J., and Carobrez, A. P. 2000. Previous maze experience required to increase open arms avoidance in rats submitted to the elevated plus-maze model of anxiety. Behavioural Brain Research 108 (2):197–203. 82. Bertoglio, L.J., and Carobrez, A. P. 2002. Behavioral profile of rats submitted to session 1-session 2 in the elevated plus-maze during diurnal/nocturnal phases and under different illumination conditions. Behavioural Brain Research 132 (2):135–43. 83. Bertoglio, L.J., and Carobrez, A. P. 2002. Anxiolytic effects of ethanol and phenobarbital are abolished in test-experienced rats submitted to the elevated plus maze. Pharmacology, Biochemistry, and Behavior 73 (4):963–69. 84. Carobrez, A. P., and Bertoglio, L. J. 2005. Ethological and temporal analyses of anxiety-like behavior: The elevated plus-maze model 20 years on. Neurosci. Biobehav. Rev. 29 (8):1193–1205. 85. File, SE. 1993. The interplay of learning and anxiety in the elevated plus-maze. Behavioural Brain Research 58 (1–2):199–202.


100


86. Adamec, R., and Shallow, T. 2000. Effects of baseline anxiety on response to kindling of the right medial amygdala. Physiology & Behavior 70 (1–2):67–80. 87. Hogg, S. 1996. A review of the validity and variability of the elevated plus-maze as an animal model of anxiety. Pharmacology, Biochemistry, and Behavior 54 (1):21–30. 88. Karlsson, R. M., and Holmes, A. 2006. Galanin as a modulator of anxiety and depression and a therapeutic target for affective disease. Amino Acids 31 (3):231–39. 89. Ogren, S. O., Kuteeva, E., Hökfelt, T., and Kehr, J. 2006. Galanin receptor antagonists: A potential novel pharmacological treatment for mood disorders. CNS Drugs 20 (8):633–54. 90. Swanson, C.J., Blackburn, T. J., Zhang, X. et al. 2005. Anxiolytic- and antidepressant-like profiles of the galanin-3 receptor (Gal3) antagonists SNAP 37889 and SNAP 398299. Proceedings of the National Academy of Sciences of the United States of America. 102 (48):17,489–94. 91. Wrenn, C.C., and Holmes, A. 2006. The role of galanin in modulating stress-related neural pathways. Drug News & Perspectives 19 (8):461–67. 92. Blumstein, L. K., and Crawley, J. N. 1983. Further characterization of a simple, automated exploratory model for the anxiolytic effects of benzodiazepines. Pharmacology, Biochemistry, and Behavior 18 (1):37–40. 93. Crawley, J. N. 1981. Neuropharmacologic specificity of a simple animal model for the behavioral actions of benzodiazepines. Pharmacology, Biochemistry, and Behavior 15 (5):695–99. 94. Crawley, J. N. 1985. Exploratory behavior models of anxiety in mice. Neuroscience & Biobehavioral Reviews 9:37–44. 95. Jacobson, L. H., Bettler, B., Kaupmann, K., and Cryan, J. F. 2007. Behavioral evaluation of mice deficient in GABA-sub(B(1)) receptor isoforms in tests of unconditioned anxiety. Psychopharmacology 190 (4):541–53. 96. Karl, T., Burne, T. H. J., and Herzog, H. 2006. Effect of Y-sub-1 receptor deficiency on motor activity, exploration, and anxiety. Behavioural Brain Research 167 (1):87–93. 97. Karlsson, R. M., Holmes, A., Heilig, M., and Crawley, J. N. 2005. Anxiolytic-like actions of centrally-administered neuropeptide Y, but not galanin, in C57BL/6J mice. Pharmacology, Biochemistry, and Behavior 80 (3):427–36. 98. File, S.E., and Hyde, J. R. 1978. Can social interaction be used to measure anxiety? British Journal of Pharmacology 62 (1):19–24. 99. File, S.E., and Seth, P. 2003. A review of 25 years of the social interaction test. European Journal of Pharmacology 463 (1–3):35–53. 100. Johnston, A. L., and File, S. E. 1991. Sex differences in animal tests of anxiety. Physiology & Behavior 49 (2):245–50. 101. File, S. E. 2001. Factors controlling measures of anxiety and responses to novelty in the mouse. Behavioural Brain Research 125:151–57. 102. Krsiak, M., and Sulcova, A. 1990. Differential effects of six structurally related benzodiazepines on some ethological measures of timidity, aggression and locomotion in mice. Psychopharmacology 101 (3):396–402. 103. Egashira, N., Tanoue, A., Matsuda, T., et al. 2007. Impaired social interaction and reduced anxiety-related behavior in vasopressin V1a receptor knockout mice. Behavioural Brain Research 178 (1):123–27. 104. de Angelis, L., and File, S. E. 1979. Acute and chronic effects of three benzodiazepines in the social interaction anxiety test in mice. Psychopharmacology 64 (2):127–29. 105. Lister, R. G., and Hilakivi, L. A. 1988. The effects of novelty, isolation, light and ethanol on the social behavior of mice. Psychopharmacology 96 (2):181–87. 106. Krsiak, M., Sulcova, A., Donat, P., Tomasikova, Z., Dlohozkova, N., Kosar, E., et al. 1984. Can social and agonistic interactions be used to detect anxiolytic activity of drugs? Progress in Clinical and Biological Research 167:93–114.



101

107. Dulawa, S. C., and Hen, R. 2005. Recent advances in animal models of chronic antidepressant effects: The novelty-induced hypophagia test. Neurosci. Biobehav. Rev. 29 (4–5):771–83. 108. Merali, Z., Levac, C., and Anisman, H. 2003. Validation of a simple, ethologically relevant paradigm for assessing anxiety in mice. Biological Psychiatry 54 (5):552–65. 109. Jennings, K. A., Loder, M. K., Sheward, W. J., et al. 2006. Increased expression of the 5-HT transporter confers a low-anxiety phenotype linked to decreased 5-HT transmission. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience 26 (35):8955–64. 110. Santarelli, L., Gobbi, G., Blier, P., and Hen, R. 2002. Behavioral and physiologic effects of genetic or pharmacologic inactivation of the substance P receptor (NK1). The Journal of Clinical Psychiatry 63:11–7. 111. Trullas, R., and Skolnick, P. 1993. Differences in fear motivated behaviors among inbred mouse strains. Psychopharmacology 111 (3):323–31. 112. Võikar, V., Polus, A., Vasar, E., and Rauvala, H. 2005. Long-term individual housing in C57BL/6J and DBA/2 mice: Assessment of behavioral consequences. Genes, Brain, and Behavior 4 (4):240–52. 113. Heisler, L. K., Kanarek, R. B, and Gerstein, A. 1997. Fluoxetine decreases fat and protein intakes but not carbohydrate intake in male rats. Pharmacology, Biochemistry, and Behavior 58 (3):767–73. 114. Leibowitz, S. F., Alexander, J. T., Cheung, W. K., and Weiss, G. F. 1993. Effects of serotonin and the serotonin blocker metergoline on meal patterns and macronutrient selection. Pharmacology, Biochemistry, and Behavior 45 (1):185–94. 115. Dulawa, S. C., Holick, K. A., Gundersen, B., and Hen, R. 2004. Effects of chronic fluoxetine in animal models of anxiety and depression. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology 29 (7):1321–30. 116. Kirk, R. E. 1995. Experimental design: Procedures for the behavioral sciences. Pacific Grove: Brooks/Cole Publishing Company. 117. Bouwknecht, A. J., Olivier, B., and Paylor, R. E. 2007. The stress-induced hyperthermia paradigm as a physiological animal model for anxiety: A review of pharmacological and genetic studies in the mouse. Neurosci. Biobehav. Rev. 31 (1):41–59. 118. Njung’e, K., and Handley, S. L. 1991. Evaluation of marble-burying behavior as a model of anxiety. Pharmacology, Biochemistry, and Behavior 38 (1):63–67. 119. Treit, D., Pinel. J. P., and Fibiger, H. C. 1981. Conditioned defensive burying: A new paradigm for the study of anxiolytic agents. Pharmacology, Biochemistry, and Behavior 15:619–26. 120. Kehne, J. H., Cassella, J. V., and Davis, M. 1988. Anxiolytic effects of buspirone and gepirone in the fear-potentiated startle paradigm. Psychopharmacology 94 (1):8–13. 121. Walker, D. L., and Davis, M. 2002. Light-enhanced startle: Further pharmacological and behavioral characterization. Psychopharmacology 159 (3):304–10.


Assessment 6 Behavioral of Antidepressant Activity in Rodents Vincent Castagné, Paul Moser, and Roger D. Porsolt CONTENTS 6.1 6.2

Introduction................................................................................................. 103 Methods....................................................................................................... 106 6.2.1 Animal Subjects............................................................................... 107 6.2.2 Equipment ........................................................................................ 107 6.2.3 Procedure: Forced Swimming Test in the Rat (Protocol 1)............. 108 6.2.4 Procedure: Forced Swimming Test in the Mouse (Protocol 2) ....... 109 6.2.5 Procedure: Tail Suspension Test in the Mouse (Protocol 3)............ 109 6.3 Typical Applications ................................................................................... 110 6.4 Analysis and Interpretation......................................................................... 110 6.5 Representative Data .................................................................................... 111 6.6 Comparison with Related Procedures......................................................... 114 References.............................................................................................................. 114

6.1

INTRODUCTION

Depression is one of several disorders affecting mood, along with mania, hypomania, and bipolar disorders. The present chapter focuses on behavioral assessment of antidepressant action in animals with a focus on simple tests performed in rodents. Many of the primary symptoms of depression (depressed mood, low self-esteem, guilt, difficulty in concentration, suicidal ideation, thoughts of death) are by their nature difficult to model in animals. This problem is further confounded by their unknown etiology. Several theories have been proposed1 but most theories of depression concur in suggesting that stressful life events play an important role. There is also a small genetic component, as demonstrated by substantially increased risk in families with heritability being estimated at between 40% and 70%, leading to a much greater incidence than observed in the general population, which is nevertheless very high at around 10%.2 If little is known about the etiology of depression, even less is known about mania and bipolar disorders. The genetic component appears to be greater than for unipolar depression.3 Modeling the cycling, recurrent nature of bipolar disorder in animals 103


104


has not even been attempted. There are, however, some models for mania that present an interesting pharmacology, in particular the combined amphetamine-chlordiazepoxide hyperactivity model, although the few publications on these models and their lack of reproducibility from one laboratory to another4–7 make an overview of their utility difficult. They will not be further discussed in this chapter. The clinical diagnosis of depression requires the presence of several “core” symptoms (depressed mood, decreased pleasure) often accompanied by more variable symptoms such as irritability, changes in weight, sleep disturbance, feelings of guilt, poor concentration, thoughts of death, suicidal ideation, etc. It is clearly not possible to reproduce in animals all symptoms observed clinically. Table 6.1 shows the principal symptoms observed in depressed patients and suggests analogous signs that can be observed in animals. These signs can be used as dependent variables (end point measures) allowing behavioral assessment in different animal models of depressive states.

TABLE 6.1 Human Symptoms of Depressive States, Animal Behavioral Signs, Preclinical Tests Human Symptom

Behavioral Sign

Preclinical Test

Depressed mood

Resignation

Forced swimming Tail suspension Learned helplessness

Decreased pleasure

Anhedonia

Sucrose consumption ICSS Sexual behavior Novelty seeking Chronic mild stress

Irritability

Aggressiveness

Muricidal behavior Social behavior Olfactory bulbectomy

Changes in weight

Body weight

Body weight Food and water intake

Sleep disturbance

Sleep architecture

EEG Circadian rhythms

Psychomotor disturbance

Locomotor activity Impulsivity

Activity meter DRL

Feelings of guilt

No sign identified

Not applicable

Poor concentration

No sign identified

Not applicable

Suicidal ideation

No sign identified

Not applicable

Thoughts of death

No sign identified

Not applicable

Note: DRL, differential reinforcement of low rate; EEG, electroencephalograph; ICSS, intracranial self-stimulation.


Behavioral Assessment of Antidepressant Activity in Rodents

105

Several of the behavioral signs presented in Table 6.1 are, however, amenable to preclinical testing. Measures thought to be related to resignation (often termed “behavioral despair” or “learned helplessness”) are used as the main behavioral parameter in screening tests for antidepressant activity (forced swim and tail suspension tests), as well as in the learned helplessness model. In the first two tests, immobility induced by exposure to an inescapable aversive situation (forced swimming or suspension by the tail) serves as an indicator of resignation. In the learned helplessness model, animals (generally rats) are exposed to inescapable foot shocks and show “helplessness” by subsequently failing to learn to escape when the environment is modified to allow escape.8 The forced swim and tail suspension procedures are best viewed as simple tests for antidepressants rather than as models of depression, because the dependent variable (immobility) is a direct reaction to the test itself and does not persist outside the test situation. There is no obvious induction of a “depressive state,” although there are elements of construct validity (stressful inducing conditions, decreased behavioral output). The learned helplessness procedure, where prior exposure to the aversive stress induces a more long lasting change in that animals are subsequently less able to learn appropriate escape responses, can be considered closer to a model of depression.8,9 The above procedures have nonetheless been used not only to assess potential antidepressant activity of test substances, but also to study possible neurobiological substrates of depression.9–11 The most obvious difference between these tests is the duration and frequency of the initiating factors. Prolonged and repeated stress is probably necessary for inducing a lasting change that could be construed as a “depressive state.” The decreased sensitivity and lack of interest in pleasure observed in depressed patients has some analogy to anhedonia as measured in animals.12 Anhedonia can be assessed by a variety of tests including the consumption of palatable food (such as sucrose), intracranial self-stimulation (ICSS), preference for novel objects or situations, or frequency of sexual interactions.13 Several of these tests have been used to assess the effects of chronic mild stress and olfactory bulbectomy.13,14 Preference for sucrose is the most widely used measure of anhedonia.15 Other tests for anhedonia are technically challenging (ICSS) and are thus less widely used. Of all the available models, the chronic mild stress procedure possesses the greatest number of attributes of clinical depression, including putative inducing conditions and a wide variety of long-lasting behavioral changes. Rats (or mice) submitted to a series of mild stressors, such as food and water deprivation, soiled cages, and light cycle shifts, show clear and enduring signs of anhedonia (absence of preference for palatable foods or for novel objects, higher thresholds for ICSS, lowered sexual activity) and other signs (decreased food and water intake, weight loss, decreased locomotion, sleep disturbance). On the other hand, chronic mild stress procedures are very time consuming—a single study could last 2–3 months16 —are frequently subject to methodological bias, and are reportedly difficult to reproduce from one laboratory to another.17–18 The olfactory bulbectomy model in rats also induces several long-lasting behavioral changes (increased locomotor activity, passive avoidance deficit, mouse killing, and intra-specific aggressiveness as observed in dyadic social interaction tests), together with a variety of neurochemical changes.14–20 Although most of these bear


106


little direct relation to the clinical symptoms of depression, it is of more concern for this model that there is no clear analogy between the inducing conditions (olfactory bulbectomy) and the kind of life events thought to induce or favor depressive states in humans.21 The usefulness of the olfactory bulbectomy model therefore resides largely on its predictive validity, in that most clinically effective antidepressants show activity in the test.14,22 Another approach to assessing the potential antidepressant action of novel substances is to look at their effects on different behavioral signs that are observed in clinical depression, but are not necessarily linked to an induced “depressive” state in the animal. Although problems of body weight loss or gain feature prominently in depression, and tests for assessing changes in food/water intake or body weight gain present no major technical difficulty, no specific effects of antidepressants on these parameters have been described.13,23 Sleep architecture, which is comparable between humans and animals,24 can be studied by electroencephalographic (EEG) analysis,25 or more simply by measurement of circadian changes in locomotor activity.26,27 On the other hand, although it is known that antidepressants affect sleep architecture in rats,28 there are no data demonstrating the specificity of such changes to antidepressant action. Few data are available on sleep disturbance in animal models of depressive states.14,25,29 Another behavior, the capacity of animals to repress a response over a predefined duration, which is assessed by the differential reinforcement of low rate (DRL) operant schedule, is thought to represent a measure of impulsivity.30 An abundant amount of literature31 has shown that numerous antidepressants show a characteristic profile in this test (moderate decreases in the number of responses accompanied by clear increases in the number of reinforcements), which can been interpreted as suggesting anti-impulsive activity. It is less clear whether anti-impulsivity characterizes clinical antidepressant activity. The brief review presented above indicates the complexity of modeling depression in animals,18,32,33 in particular the low construct validity of available models.11,34 The problem is less severe for antidepressant testing, where the lack of construct validity is tempered by an increase in predictive validity.35 The procedures selected for the following sections (forced swim and tail suspension) represent a compromise in that they possess high predictive validity but also elements of construct validity. Furthermore, they do not present any major technical difficulty, are rapid to execute, and generate data that are highly reproducible.

6.2

METHODS

Rodents forced to swim in small enclosures (cylinders) from which there is no escape rapidly become immobile after an initial period of vigorous activity.36 Initially, immobility was interpreted as evidence they had learned that escape was impossible and had given up hope. Immobility was therefore given the name “behavioral despair.” It has subsequently been shown in numerous laboratories that immobility is reduced by a wide range of clinically active antidepressant drugs.37 As a consequence, this simple test is now widely used to screen novel substances for potential antidepressant activity. The following paragraphs describe the basic protocol (forced



107

swimming test, protocol 138) for examining drug effects in the rat, an equivalent procedure in the mouse (protocol 239), and the conceptually related tail suspension test, where immobility is induced by suspending mice by the tail (protocol 340).

6.2.1

ANIMAL SUBJECTS

A large number of rodent strains have been used in the following procedures. Different strains of rats display different durations of immobility and variable sensitivity to antidepressants in the forced swimming test.41,42 Likewise, marked strain differences have been described in the forced swimming and the tail suspension tests in the mouse.43–45 To control the variability between different experiments, we recommend using the same rodent strains within a specific laboratory. House animals in standard plastic cages (usually 41 × 25 × 15 cm, four to six rats per cage, or 25 × 19 × 13 cm, 10 mice per cage) containing wood shavings, and provide free access to a standard rodent diet and tap water, except during the test. Maintain the animals under strictly controlled environmental conditions (usually 21°C ± 3°C on a standard light-dark cycle with illumination from 0700 to 1900 hr). Note 1: We recommend that the animals are delivered to the laboratory at least 5 days before the experiment, and are placed in the experimental room at least 60 min before the test. Experiments should be performed during the light phase of the cycle, although it is also possible to perform the test under dim red light during the dark phase of the cycle. In this latter case the light-dark cycle should also be reversed. Note 2: All protocols using live animals must first be reviewed and approved by an Institutional Animal Care and Use Committee (IACUC) or must conform to governmental regulations regarding the care and use of laboratory animals.

6.2.2

EQUIPMENT

1. Forced Swimming Test in the Rat (Protocol 1). Transparent Plexiglas cylinders (20 cm in diameter × 40 cm high) containing water (25°C) to a depth of 13 cm (made in house or obtained from local commercial suppliers). Opaque screens for visually separating cylinders. 2. Forced Swimming Test in the Mouse (Protocol 2). Transparent Plexiglas cylinders (13 cm in diameter × 24 cm high) containing water (22°C) to a depth of 10 cm. Opaque screens for visually separating cylinders. 3. Tail Suspension Test in the Mouse (Protocol 3). Automated tail suspension apparatus (e.g., Tail Suspension Test System, Bioseb, France) consisting of plastic enclosures (20 × 25 × 30 cm) fitted with a ceiling hook connected to a strain gauge and computer assembly.46,47 Without an automated apparatus it is possible to perform the test using standard laboratory chronometers. Note: All tests should be performed blind with coded solutions to avoid bias in evaluating the animal’s behavior. Decoding of treatment group codes should be performed after all evaluations have been completed.


108

6.2.3


PROCEDURE: FORCED SWIMMING TEST IN THE RAT (PROTOCOL 1)

In two sessions separated by 24 hr, rats are forced to swim in a cylinder from which they cannot escape. The first 15-min session is conducted prior to drug administration and without behavioral recording. This prior habituation session ensures a stable and high duration of immobility during the 5-min test session, usually performed 24 hr later. In the standard procedure, rats are administered the test substance three times: 24 hr (i.e., immediately after the first session), 4 hr, and 60 or 30 min before the test (the last pretreatment time depending on the route of administration). Two or three test substance administrations before the test provide more stable pharmacological results than a single administration. Control animals receive the same number of administrations of vehicle. A variation of the protocol is to insert repeated treatments between the two sessions. In these cases, the interval between the two sessions usually has to be increased. We have used intersession intervals of up to 15 days without observing any change in the behavior during the second session. Repeated administration in animals is more comparable to the clinical situation where the therapeutic effect of the majority of antidepressants appears only after several weeks of treatment.48 Equip the experimental room with white neon ceiling lights (standard lighting). Set up two transparent cylinders separated visually from each other by opaque screens. On day 1, at least 60 min before the beginning of the habituation session, mark the animals and randomly assign them to a drug treatment. All animals within a cage receive the same treatment. Weigh two animals individually, then place one rat in each of the two cylinders for 15 min (habituation session). No scoring of immobility is performed during the habituation session. Remove the rats from the cylinders, dry them with a cloth towel, and place them into a cage adjacent to their home cage. Immediately after the habituation session, treat the first group of two rats with the appropriate treatment (the first pretest administration), and place them back in their home cages. Change the water in the cylinders after every three rats. When the day 1 session is completed, return the animals to the colony room and provide food and water ad libitum. On the test day, administer the test substance 4 hr prior to the session and 30 min (for intraperitoneal or subcutaneous injection) or 60 min (for oral administration) prior to the session. Test two animals simultaneously in adjacent cylinders separated by an opaque screen. Observe their behavior for 5 min. Score the duration of immobility by summing the total time spent immobile (i.e., the time not spent actively exploring the cylinder or trying to escape from it). Included within the time spent immobile are the short periods of slight activity where the animals just make those movements necessary to maintain their heads above water. Note: A standard forced swimming test using 30 rats (five treatment groups of N = 6) requires two consecutive afternoons to perform the two sessions, with the morning of day 2 reserved for the 4-hr pretest drug administration. If necessary, one extra group can be tested within the same time frame (i.e., the maximum number of rats tested per experiment is 36). Experiments requiring more animals should be performed in separate sub-experiments, with the same number of animals from each treatment group being tested in each sub-experiment.



6.2.4

109

PROCEDURE: FORCED SWIMMING TEST IN THE MOUSE (PROTOCOL 2)

In a single session, mice are forced to swim in a narrow cylinder from which they cannot escape. Equip the experimental room with white neon ceiling lights (standard lighting). Set up two transparent cylinders separated visually from each other by opaque screens. At least 60 min before testing, mark the animals and randomly assign them to a drug treatment. All animals within a cage receive the same treatment. Weigh two mice individually, administer the test substance 30 min (for intraperitoneal or subcutaneous injection) or 60 min (for oral administration) prior to the test and place them back in their home cages. Test two animals simultaneously in adjacent cylinders separated by an opaque screen. Score immobility during the last 4 min of the 6-min test session by summing the total time spent immobile (i.e., the time not spent actively exploring the cylinder or trying to escape from it). Included within the time spent immobile are the short periods of slight activity where the animals just make those movements necessary to maintain their heads above water. Whereas mice show a high frequency of exploratory and escape-directed behaviors during the first 2 min of the test session, the last 4 min is the time during which the animals show the most immobility. The first 2 min of the session can be used for preparing other animals. Note: A standard forced swimming test using 50 mice (five treatment groups of N = 10) requires a morning or an afternoon. If necessary, two extra groups can be tested within the same time frame (i.e., the maximum number of mice tested per experiment is 70). Experiments requiring more animals should be performed in separate sub-experiments, with the same number of animals from each treatment group being tested in each sub-experiment.

6.2.5

PROCEDURE: TAIL SUSPENSION TEST IN THE MOUSE (PROTOCOL 3)

This protocol describes a procedure in mice that is conceptually related to the forced swimming test, except that immobility is induced by suspending the mice by the tail. After initially trying to escape by engaging in vigorous movements, mice rapidly become immobile. The duration of immobility is reduced by a wide variety of antidepressants. This procedure has several advantages over the forced swim procedure (protocol 2). No hypothermia is induced and the animals resume normal spontaneous activity immediately after the test. No special post-experimental treatment (rubbing down, maintenance in a warmed environment) is required. The procedure readily lends itself to automation, permitting testing of a greater number of mice simultaneously. Equip the experimental room with white neon ceiling lights (standard lighting). With the automated tail suspension apparatus (we use the TST System, Bioseb, France), six mice are tested simultaneously. Weigh the mice and administer the test substance 30 min (for intraperitoneal or subcutaneous injection) or 60 min (for oral administration) prior to the test and place the mice back in their home cages. The different treatments should be administered to individual animals in a fixed rotation to ensure a regular distribution of the different treatments over time. Our automated apparatus provides randomization sequences, permitting balanced distribution over


110


time and over the different positions in the apparatus. Wrap adhesive tape around the animal’s tail in a constant position three quarters of the distance from the base of the tail. Suspend the animals by passing the suspension hook through the adhesive tape so that the animal hangs with its tail in a straight line. Measure the duration of immobility continuously for 6 min. If an automated testing apparatus is not available, the duration of immobility can be measured using separate chronometers for each animal. Note: Our automated procedure (TST System, Bioseb, France) permits testing of six animals simultaneously, with all animals being placed in the apparatus before starting the measurement. For nonautomatic observation, the same observer can comfortably observe two animals simultaneously. Whatever the configuration, the animals should be visually shielded from one another during the test. Note: A standard tail suspension test in the mouse using our automated device (five treatment groups of N = 12) requires an afternoon. If necessary, three extra groups can be tested within the same time frame (i.e., the maximum number of mice tested per experiment is 96). If an automated device cannot be used, the throughput becomes similar to the forced swimming test in the mouse (i.e., 70 animals can be tested during the same session).

6.3

TYPICAL APPLICATIONS

The forced swimming test in the rat and the mouse, and the tail suspension test in the mouse are widely used for early behavioral screening of antidepressants.49,50 Some false positives (mainly excitatory substances) and some false negatives (mainly serotonin reuptake inhibitors) have been described (see Section 6.5). As a consequence, we recommend using all three procedures to evaluate new test substances, instead of relying on a single procedure.34 This reduces the number of false positives and false negatives and thereby enhances the efficiency of drug discovery programs. The forced swimming and the tail suspension tests can also be used to characterize the phenotype of different strains of animals, including transgenic mice. 51 In this respect, the forced swimming and the tail suspension tests can also be used as research tools for investigating the neurobiological bases of depressive states.

6.4

ANALYSIS AND INTERPRETATION

Compare data from treated groups with data from the control group using unpaired Student’s t-tests (two tailed), although other statistical evaluations (e.g., analysis of variance followed by post-hoc tests) can also be used. For initial screening, we strongly recommend two-by-two t-test comparisons of treated groups with control. Although increasing the risk of a type I error (false positive), there is a decreased risk of a type II error, i.e., missing a potential drug effect at a particular dose (false negative), as can happen with more global analyses including all treatments. Antidepressants decrease the duration of immobility in the forced swimming test in the rat and the mouse (protocols 1 and 2), and in the tail suspension test in the



111

mouse (protocol 3). Sedative/myorelaxant substances are generally inactive or even increase the duration of immobility in the different tests.

6.5

REPRESENTATIVE DATA

Pharmacotherapy of depressed patients uses various classes of antidepressants that generally target central monoaminergic systems.52,53 Besides monoamine oxidase inhibitors (MAOIs), the majority of antidepressants belong to different classes of monoamine reuptake inhibitors, including selective serotonin reuptake inhibitors (SSRIs), selective norepinephrine reuptake inhibitors (NRIs), and mixed reuptake inhibitors (SNRIs).54 The etiology of depression is, however, insufficiently understood to limit discovery efforts to substances with clearly identified targets.1 Although the involvement of central monoaminergic systems in antidepressant action is widely accepted, the long delay between the initiation of monoamine-based treatments and the first clinical effects suggests that more complex mechanisms are involved.53 In addition, studies showing that multiple central neurotransmitter systems are implicated in depression suggest that non-monoamine-based treatments may represent potentially interesting new therapeutic approaches.55 The major problem with current pharmacological treatments is that they either fail to produce complete recovery or induce unwanted side effects. Thus there is urgency for the development of new pharmacological treatments. The data presented in Table 6.2 show the effects of diverse substances after i.p. administration in the forced swimming test in the rat. All substances were adminis-

TABLE 6.2 Effects of Diverse Substances in the Forced Swimming Test in the Rat Substance

Change in immobility (versus vehicle control group) (%) Dose (mg/kg) 0.5

1

2

4

8

16

32

64

Imipramine

NT

NT

NT

NT

-17

-23

-48***

-69***

Fluoxetine

NT

NT

NT

NT

-19

+9

-38*

-56*

Desipramine

NT

NT

NT

NT

-23***

-44***

-45***

-29 84***

Venlafaxine

NT

NT

NT

NT

-6

-10*

-30

8-OH-DPAT

-41*

-73**

NT

-100***

NT

NT

NT

NT

Flesinoxan

NT

+7

NT

-64**

NT

-82**

NT

NT

Idazoxan

NT

+7

NT

-24*

NT

NT

NT

NT

Note: Animals were individually placed in a cylinder (height = 40 cm, diameter = 20 cm) containing 13 cm water (25°C) for 15 min on the first day of the experiment (session 1) and were then put back in the water 24 hr later for a 5-min test (session 2). The duration of immobility during the 5-min test was measured. The test substances were administered i.p. 24 hr, 4 hr, and 30 min before the test (session 2). The duration of immobility was comprised between 150 and 250 sec in the vehicle control group. Data shown as mean ± SEM. (N = 6 per group). NT, not tested. *p < 0.05; **p < 0.01 and ***p < 0.001. Student’s t-tests, as compared with vehicle controls.


112


TABLE 6.3 Effects of Diverse Substances in the Forced Swimming Test in the Mouse Substance

Change in immobility (versus vehicle control group) (%) Dose (mg/kg) 0.5

1

2

4

8

16

32

64

Imipramine

NT

NT

NT

-4

-22***

-45***

-60***

-100***

Fluoxetine

NT

NT

NT

NT

-2

-12*

-25***

-49***

Desipramine

NT

NT

NT

NT

-22***

-45***

-60***

-100***

Venlafaxine

NT

NT

NT

NT

-18***

-32***

-86***

-100***

Clobazam

NT

NT

NT

NT

+10

+8

+12*

+13*

Clozapine

NT

+2

0

-1

0

NT

NT

NT

Nicotine

NT

-12*

NT

NT

NT

NT

NT

NT

8-OH-DPAT

-1

NT

-54***

NT

-27**

NT

NT

NT

Flesinoxan

NT

+2

NT

+13

NT

+44**

NT

NT

Idazoxan

NT

-6

NT

-26***

-30***

NT

NT

NT

Buspirone

NT

+24

NT

+12

NT

+10

NT

NT

Alnespirone

NT

-18

NT

-50***

NT

-77***

NT

NT

Note: Animals were individually placed in a cylinder (height = 24 cm, diameter = 13 cm) containing 10 cm water (approximately 22°C) from which they cannot escape. The mice were placed in the water for 6 min and the duration of immobility during the last 4 min was measured. The test substances were administered i.p. 30 min before the test. The duration of immobility was comprised between 160 and 220 sec in the vehicle control group. Data shown as mean ± SEM. (N = 10 per group). NT, not tested. *p < 0.05; **p < 0.01 and ***p < 0.001. Student’s t-tests, as compared with vehicle controls.

tered 24 hr, 4 hr, and 30 min before the test. Dose-dependent decreases in the duration of immobility are observed with imipramine (8–64 mg/kg), fluoxetine (32 and 64 mg/kg), desipramine (8–32 mg/kg, but not 64 mg/kg), and venlafaxine (16–64 mg/kg). Some serotonergic substances targeting the 5-HT1A receptor also decrease immobility. This was observed for 8-OH-DPAT (0.5–4 mg/kg), flesinoxan (4 and 16 mg/kg), and idazoxan (4 mg/kg). The data presented in Table 6.3 show the effects of diverse substances after i.p. administration in the forced swimming test in the mouse. All substances were administered 30 min before the test. Dose-dependent activity is observed for imipramine (8–64 mg/kg). Monoamine reuptake inhibitors show clear activity, generally more marked than in the rat, as observed with fluoxetine (16–64 mg/kg), and desipramine and venlafaxine (8–64 mg/kg). Clobazam (32 and 64 mg/kg) increases immobility consistently with its sedative/myorelaxant effects. Clozapine (1–8 mg/kg) is devoid of activity. Nicotine decreases immobility at 1 mg/kg. Serotonergic substances targeting the 5-HT1A receptor have variable effects in the mouse. 8-OH-DPAT (2 and 8 mg/kg), idazoxan (4 and 8 mg/kg), and alnespirone (4 and 16 mg/kg) decrease immobility, whereas buspirone (1–16 mg/kg) is devoid of activity, and flesinoxan increases immobility at 16 mg/kg.



113

TABLE 6.4 Effects of Diverse Substances in the Tail Suspension Test in the Mouse Substance

Change in immobility (versus vehicle control group) (%) Dose (mg/kg)

Imipramine

0.5

1

2

4

8

16

32

64

NT

NT

NT

NT

-44

-73*

-78**

NT

Fluoxetine

NT

NT

NT

NT

-58**

-39*

-20

-46*

Desipramine

NT

NT

NT

NT

-75**

-64**

-53*

-62**

Venlafaxine

NT

NT

NT

NT

-64**

-70**

-87***

-95***

Clobazam

NT

NT

NT

NT

+167***

+127***

+100**

NT

Clozapine

NT

+62

+73

+168***

+294***

NT

NT

NT

Nicotine

-17

+5

-12

NT

NT

NT

NT

NT

8-OH-DPAT

+28

NT

+38

NT

+154***

NT

NT

NT

Flesinoxan

NT

+26

NT

+135***

NT

+176***

NT

NT

Buspirone

NT

+17

NT

+58

NT

+103**

NT

NT

Alnespirone

NT

+66

NT

+109**

NT

+110**

NT

NT

Note: Animals were suspended by the tail and the duration of immobility was recorded automatically for 6 min using a computerized device (Bioseb TST). Six mice were studied simultaneously. The test substances were administered i.p. 30 min before the test. The duration of immobility was comprised between 60 and 120 sec in the vehicle control group. Data shown as mean ± SEM. (N = 10 or 12 per group). NT, not tested. *p < 0.05; **p < 0.01 and ***p < 0.001. Student’s t-tests, as compared with vehicle controls.

The data presented in Table 6.4 show the effects of diverse substances after i.p. administration in the tail suspension test in the mouse. All substances were administered 30 min before the test. Decreases in immobility are observed for imipramine (8–32 mg/kg), and fluoxetine, desipramine, and venlafaxine (all over the dose range 8–64 mg/kg). Clobazam (8–32 mg/kg) and clozapine (4 and 8 mg/kg) increase immobility. Nicotine (0.5–2 mg/kg) does not affect immobility. 5-HT1A agonists increase immobility in the tail suspension test. This is observed for 8-OH-DPAT (8 mg/kg), and buspirone, flesinoxan, and alnespirone (all at 4 and 16 mg/kg). Taken together, these results confirm the specificity of the forced swimming test toward antidepressant substances.36 In our hands, the mouse version appears somewhat more sensitive to serotonin reuptake inhibitors. The weak but significant activity of nicotine at 1 mg/kg is consistent with the fact that excitatory substances may constitute false positives in the forced swimming test.41,56 Nevertheless, antidepressant-like activity for nicotine has also been described in the mouse57 and in the rat.58 The tail suspension test is sensitive toward a wide variety of antidepressant substances that are clearly distinguished from other psychotropic substances such as anxiolytics, neuroleptics, and other diverse agents.47,59 It is interesting to note that the tail suspension test in the mouse appears to be more sensitive to the sedative activity (increase in immobility) of 5-HT1A agonists, in contrast to the forced swimming


114


test in the rat, which detects mainly their antidepressant-like activity (decrease in immobility).

6.6

COMPARISON WITH RELATED PROCEDURES

The methods of testing clearly influence the results of the tests. Some studies suggest absence of activity of serotonin reuptake inhibitors using the standard forced swimming test.60,61 Modifications of the original procedure, including measurement of active behaviors such as swimming and climbing and increasing the water depth, have been claimed to facilitate detection of SSRIs.62 Although this scoring method is now used by several laboratories,63 other data cast doubt on a clear behavioral distinction of the effects of SSRIs and NRIs.64 Since the standard forced swimming test allows detection of multiple classes of antidepressants, we prefer to limit the behavioral analysis to the measure of immobility, which is simpler to estimate than the measure of active behaviors. Extensive training of the observers to score immobility is needed even in the standard version of the forced swimming test.10

REFERENCES 1. Berton, O., and Nestler, E. J. 2006. New approaches to antidepressant drug discovery: Beyond monoamines. Nat. Rev. Neurosci. 7:137–51. 2. Sullivan, P. F., Neale, M. C., and Kendler, K. S. 2000. Genetic epidemiology of major depression: Review and meta-analysis. Am. J. Psychiatry 157:1552–62. 3. Machado-Vieira, R., Kapczinski, F., and Soares, J. C. 2004. Perspectives for the development of animal models of bipolar disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 28:209–24. 4. Okada, K., Oishi, R., and Saeki, K. 1990. Inhibition by antimanic drugs of hyperactivity induced by methamphetamine-chlordiazepoxide mixture in mice. Pharmacol. Biochem. Behav. 35:897–901. 5. Cao, B. J., and Peng, N. A. 1993. Magnesium valproate attenuates hyperactivity induced by dexamphetamine-chlordiazepoxide mixture in rodents. Eur. J. Pharmacol. 237:177–81. 6. Lamberty, Y., Margineanu, D. G., and Klitgaard, H. 2001. Effect of the new antiepileptic drug levetiracetam in an animal model of mania. Epilepsy Behav. 2:454–59. 7. Arban, R., Maraia, G., Brackenborough, K., et al. 2005. Evaluation of the effects of lamotrigine, valproate and carbamazepine in a rodent model of mania. Behav. Brain Res. 158:123–32. 8. Telner, J. I., and Singhal, R. L. 1984. Psychiatric progress: The learned helplessness model of depression. J. Psychiatr. Res. 18:207–15. 9. Vollmayr, B., and Henn, F. A. 2001. Learned helplessness in the rat: Improvements in validity and reliability. Brain Res. Protoc. 8:1–7. 10. Petit-Demouliere, B., Chenu, F., and Bourin, M. 2005. Forced swimming test in mice: A review of antidepressant activity. Psychopharmacology (Berl.) 177:245–55. 11. Cryan, J. F., and Slattery, D. A. 2007. Animal models of mood disorders: Recent developments. Curr. Opin. Psychiatry 20:1–7. 12. Anisman, H., and Matheson, K. 2005. Stress, depression, and anhedonia: Caveats concerning animal models. Neurosci. Biobehav. Rev. 29:525–46. 13. Willner, P. 2005. Chronic mild stress (CMS) revisited: Consistency and behaviouralneurobiological concordance in the effects of CMS. Neuropsychobiology 52:90–110.



115

14. Song, C., and Leonard, B. E. 2005. The olfactory bulbectomised rat as a model of depression. Neurosci. Biobehav. Rev. 29:627–47. 15. Papp, M., Willner, P., and Muscat, R. 1991. An animal model of anhedonia: Attenuation of sucrose consumption and place preference conditioning by chronic unpredictable mild stress. Psychopharmacology (Berl.) 104:255–59. 16. Papp, M. 2000. Models of affective illness: Chronic mild stress. In Current Protocols in Pharmacology, eds. S. J. Enna and M. Williams. Chap. 5.9, 1-8. Hoboken, NJ: John Wiley & Sons, Inc. 17. Porsolt, R. D. 1997. Historical perspective on CMS model. Psychopharmacology (Berl.) 134:363–64. 18. Nestler, E. J., Gould, E., Manji, H., et al. 2002. Preclinical models: Status of basic research in depression. Biol. Psychiatry 52:503–28. 19. Slattery, D. A., Markou, A., and Cryan, J. F. 2007. Evaluation of reward processes in an animal model of depression. Psychopharmacology (Berl.) 190:555–68. 20. Wang, D., Noda, Y., Tsunekawa, H., et al. 2007. Behavioural and neurochemical features of olfactory bulbectomized rats resembling depression with comorbid anxiety. Behav. Brain Res. 178:262–73. 21. Holmes, P. V. 2003. Rodent models of depression: Reexamining validity without anthropomorphic inference. Crit. Rev. Neurobiol. 15:143–74. 22. Kelly, J. P., Wrynn, A. S., and Leonard, B. E. 1997. The olfactory bulbectomized rat as a model of depression: An update. Pharmacol. Ther. 74:299–316. 23. Willner, P. 1997. Validity, reliability and utility of the chronic mild stress model of depression: A 10-year review and evaluation. Psychopharmacology (Berl.) 134:319–29. 24. Dürmüller, N., Scherschlicht, R., and Porsolt, R. D. 2000. Vigilance-controlled quantified EEG in safety pharmacology. In Current Protocols in Pharmacology, eds. S. J. Enna and M. Williams. Chap. 10.6, 1-27. Hoboken, NJ: John Wiley & Sons, Inc. 25. Cheeta, S., Ruigt, G., van, Proosdijt, J., and Willner, P. 1997. Changes in sleep architecture following chronic mild stress. Biol. Psychiatry 41:419–27. 26. Vanderwolf, C. H. 1992. The electrocorticogram in relation to physiology and behavior: A new analysis. Electroencephalogr. Clin. Neurophysiol. 82:165–75. 27. Benstaali, C., Mailloux, A., Bogdan, A., Auzeby, A., and Touitou, Y. 2001. Circadian rhythms of body temperature and motor activity in rodents their relationships with the light-dark cycle. Life Sci. 68:2645–56. 28. Sanchez, C., Brennum, L. T., Storustovu, S. I., Kreilgard, M., and Mork, A. 2007. Depression and poor sleep: The effect of monoaminergic antidepressants in a pre-clinical model in rats. Pharmacol. Biochem. Behav. 86:468–76. 29. Overstreet, D. H., Friedman, E., Mathe, A. A., and Yadid, G. 2005. The Flinders sensitive line rat: A selectively bred putative animal model of depression. Neurosci. Biobehav. Rev. 29:739–59. 30. Seiden, L. S., Dahms, J. L., and Shaughnessy, R. A. 1985. Behavioral screen for antidepressants: The effects of drugs and electroconvulsive shock on performance under a differential-reinforcement-of-low-rate schedule. Psychopharmacology (Berl.) 86:55–60. 31. O’Donnell, J. M., Marek, G. J., and Seiden, L. S. 2005. Antidepressant effects assessed using behavior maintained under a differential-reinforcement-of-low-rate (DRL) operant schedule. Neurosci. Biobehav. Rev. 29:785–98. 32. Willner, P. 1991. Animal models as simulations of depression. Trends Pharmacol. Sci. 12:131–36. 33. Porsolt, R. D., and Lenegre, A. 1992. Behavioural models of depression. In Experimental Approaches to Anxiety and Depression, ed. J. M. Elliott, D. J. Heal, C. A. Marsden, 73–85. Chichester: Wiley. 34. Castagné, V., Porsolt, R. D., and Moser, P. 2006. Early behavioral screening for antidepressants and anxiolytics. Drug Dev. Res. 67:729–42.


116


35. Willner, P. 1991. Methods for assessing the validity of animal models of human psychopathology. In Animal models in psychiatry, Ed. A. Boulton, G. Baker, M. MartinIverson, Chap. 1, 1-23. Clifton, NJ: The Humana Press. 36. Porsolt, R. D., Le Pichon, M., and Jalfre, M. 1977. Depression: A new animal model sensitive to antidepressant treatments. Nature 266:730–32. 37. Borsini, F., and Meli, A. 1988. Is the forced swimming test a suitable model for revealing antidepressant activity? Psychopharmacology (Berl.) 94:147–60. 38. Porsolt, R. D., Anton, G., Blavet, N., and Jalfre, M. 1978. Behavioural despair in rats: A new model sensitive to antidepressant treatments. Eur. J. Pharmacol. 47:379–91. 39. Porsolt, R. D., Bertin, A., and Jalfre, M. 1977. Behavioral despair in mice: A primary screening test for antidepressants. Arch. Int. Pharmacodyn. Ther. 229:327–36. 40. Steru, L., Chermat, R., Thierry, B., and Simon, P. 1985. The tail suspension test: A new method for screening antidepressants in mice. Psychopharmacology (Berl.) 85:367–70. 41. Porsolt, R. D., Bertin, A., and Jalfre, M. 1978. “Behavioural despair” in rats and mice: Strain differences and the effects of imipramine. Eur. J. Pharmacol. 51:291–94. 42. Lopez-Rubalcava, C., and Lucki, I. 2000. Strain differences in the behavioral effects of antidepressant drugs in the rat forced swimming test. Neuropsychopharmacology 22:191–99. 43. Porsolt, R. D., Chermat, R., Lenegre, A., Avril, I., Janvier, S., and Steru, L. 1987. Use of the automated tail suspension test for the primary screening of psychotropic agents. Arch. Int. Pharmacodyn. Ther. 288:11–30. 44. Ripoll, N., David, D. J., Dailly, E., Hascoet, M., and Bourin, M. 2003. Antidepressant-like effects in various mice strains in the tail suspension test. Behav. Brain Res. 143:193–200. 45. David, D. J., Renard, C. E., Jolliet, P., Hascoet, M., and Bourin, M. 2003. Antidepressant-like effects in various mice strains in the forced swimming test. Psychopharmacology (Berl.) 166:373–82. 46. Steru, L., Chermat, R., Thierry, B., et al. 1987. The automated Tail Suspension Test: A computerized device which differentiates psychotropic drugs. Prog. Neuropsychopharmacol. Biol. Psychiatry 11:659–71. 47. Cryan, J. F., Mombereau, C., and Vassout, A. 2005. The tail suspension test as a model for assessing antidepressant activity: Review of pharmacological and genetic studies in mice. Neurosci. Biobehav. Rev. 29:571–625. 48. Katz, M. M., Tekell, J. L., Bowden, C. L., et al. 2004. Onset and early behavioral effects of pharmacologically different antidepressants and placebo in depression. Neuropsychopharmacology 29:566–79. 49. Porsolt, R. D., Brossard, G., Hautbois, C., and Roux, S. 2000. Models of affective illness: Forced swimming and tail suspension tests in rodents. In Current Protocols in Pharmacology, eds. S. J. Enna and M. Williams. Chap. 5.8, 1-9. Hoboken, NJ: John Wiley & Sons, Inc. 50. Porsolt, R. D., Brossard, G., Hautbois, C., and Roux, S. 2001. Rodent models of depression: Forced swimming and tail suspension behavioral despair tests in rats and mice. In Current Protocols in Neuroscience, eds. S. J. Enna and M. Williams. Chap. 8.10, 1-10. Hoboken, NJ: John Wiley & Sons, Inc. 51. Porsolt, R. D. 2000. Animal models of depression: Utility for transgenic research. Rev. Neurosci. 11:53–58. 52. Stafford, R. S., MacDonald, E. A., and Finkelstein, S. N. 2001. National patterns of medication treatment for depression, 1987 to 2001. Prim. Care Companion, J. Clin. Psychiatry 3:232–35. 53. Slattery, D. A., Hudson, A. L., and Nutt, D. J. 2004. Invited review: The evolution of antidepressant mechanisms. Fundam. Clin. Pharmacol. 18:1–21.



117

54. Walter, M. W. 2005. Monoamine reuptake inhibitors: Highlights of recent research developments. Drug Dev. Res. 65:97–118. 55. Slattery, D. A., and Cryan, J. F. 2006. The role of GABAb receptors in depression and antidepressant-related behavioural responses. Drug Dev. Res. 67:477–94. 56. Panconi, E., Roux, J., Altenbaumer, M., Hampe, S., and Porsolt, R. D. 1993. MK-801 and enantiomers: Potential antidepressants or false positives in classical screening models? Pharmacol. Biochem. Behav. 46:15–20. 57. Suemaru, K., Yasuda, K., Cui, R., et al. 2006. Antidepressant-like action of nicotine in forced swimming test and brain serotonin in mice. Physiol. Behav. 88:545–49. 58. Vazquez-Palacios, G., Bonilla-Jaime, H., and Velazquez-Moctezuma, J. 2004. Antidepressant-like effects of the acute and chronic administration of nicotine in the rat forced swimming test and its interaction with fluoxetine. Pharmacol. Biochem. Behav. 78:165–69. 59. Porsolt, R. D., Chermat, R., Lenegre, A., Avril, I., Janvier, S., and Steru, L. 1987. Use of the automated tail suspension test for the primary screening of psychotropic agents. Arch. Int. Pharmacodyn. Ther. 288:11–30. 60. Detke, M. J., Rickels, M., and Lucki, I. 1995. Active behaviors in the rat forced swimming test differentially produced by serotonergic and noradrenergic antidepressants. Psychopharmacology (Berl.) 121:66–72. 61. Porsolt, R. D., Bertin, A., Blavet, N., Deniel, M., and Jalfre, M. 1979. Immobility induced by forced swimming in rats: Effects of agents which modify central catecholamine and serotonin activity. Eur. J. Pharmacol. 57:201–10. 62. Detke, M. J., and Lucki, I. 1996. Detection of serotonergic and noradrenergic antidepressants in the rat forced swimming test: The effects of water depth. Behav. Brain Res. 73:43–46. 63. Cryan, J. F., Valentino, R. J., and Lucki, I. 2005. Assessing substrates underlying the behavioral effects of antidepressants using the modified rat forced swimming test. Neurosci. Biobehav. Rev. 29:547–69. 64. Kelliher, P., Kelly, J. P., Leonard, B. E., and Sanchez, C. 2003. Effects of acute and chronic administration of selective monoamine re-uptake inhibitors in the rat forced swim test. Psychoneuroendocrinology 28:332–47.


Attention 7 Assessing in Rodents Philip J. Bushnell and Barbara J. Strupp CONTENTS 7.1 7.2

Introduction................................................................................................. 119 Multiple-Choice Serial Reaction Time Tasks ............................................. 120 7.2.1 Introduction...................................................................................... 120 7.2.2 Materials and Methods .................................................................... 122 7.2.3 Preparation of the Subjects .............................................................. 123 7.2.4 Training Steps .................................................................................. 123 7.2.5 Alternative Methods ........................................................................ 124 7.2.6 Testing Mice in the 5-CSRTT.......................................................... 124 7.2.7 Apparatus and Methodology for the 3-Choice Variant ................... 125 7.2.8 Data Analysis and Notes.................................................................. 125 7.3 Signal Detection Tasks with Blank Trials................................................... 128 7.3.1 Introduction...................................................................................... 128 7.3.2 Materials .......................................................................................... 129 7.3.3 Preparation of the Subjects .............................................................. 129 7.3.4 Training Steps .................................................................................. 130 7.3.5 Data Analysis and Notes.................................................................. 131 7.4 Attentional Set-Shifting .............................................................................. 131 7.4.1 Introduction...................................................................................... 131 7.4.2 Sand-Digging Task: Materials and Methods ................................... 134 7.4.3 Preparation of the Subjects .............................................................. 134 7.4.4 Training Steps .................................................................................. 135 7.4.5 Data Analysis and Notes.................................................................. 135 7.5 Selecting a Test Method .............................................................................. 136 Disclaimer.............................................................................................................. 137 References ............................................................................................................. 137 Appendix: Names and Addresses of Vendors Discussed in the Text .................... 143

7.1

INTRODUCTION

“Attention” refers to a variety of hypothetical constructs by which the nervous system apprehends and organizes sensory input and generates coordinated behavior. Although it has been a subject of psychological investigation since William James introduced it to the field in the late 19th century, systematic assessment of attention in animals has a shorter history. As with any unobservable cognitive process, 119


120


assessment of attention requires quantification of an observable phenomenon, such as the behavior of the animal or the electrical activity of its nervous system. To the extent that these events can be measured objectively, attention can be inferred equally readily in any animal species, including humans or other primates, rats, mice, or birds.1 As James2 pointed out, attention is not a unitary phenomenon, but rather a term that subsumes several different varieties of attentional processes. In the present discussion, we focus on three such processes: the ability to sustain attention over time, the ability to attend selectively to a subset of environmental information while filtering out extraneous stimuli, and the ability to shift attentional set. Accordingly, this chapter discusses three behavioral approaches to assessing attention in rodents. These approaches include multiple-choice serial reaction time tests that can be arranged to assess both sustained and selective attention, signal detection tests with blank trials that focus on sustained attention, and attentional set-shifting procedures. For each of these approaches, we present a commonly used method and then discuss design and analytic procedures that can help determine whether observed changes in performance can be attributed to the target attentional construct (see Sections 7.2–7.4). Section 7.5 discusses some guidelines for task selection. The appendix lists suppliers for necessary equipment.

7.2

MULTIPLE-CHOICE SERIAL REACTION TIME TASKS

7.2.1

INTRODUCTION

In 1983, Robbins and colleagues3 developed a test for assessing attention in rats based on a test for human subjects that was originally ascribed to Leonard,4 and is still in use.5 The rat method was called the “5-choice serial reaction time test” (5-CSRTT) and has since been widely applied for exploring the neurobiology of normal attentional processes and dysfunctions associated with disease states. In the prototypical application, a rat or mouse faces five openings (or ports) in a horizontal array along one curved wall of a test chamber, and a food cup with a clear plastic door is located on the wall behind it. The animal initiates a trial by opening the food cup door. After a short delay, a visual signal is presented, consisting of a brief illumination of one of the five ports. If the animal then breaks a photobeam at the opening of the port, a food pellet (or fixed volume of liquid reinforcer) is delivered into the food cup. A 3-choice variant of this type of task has been developed by Strupp and colleagues.6–11 This task is similar in concept to the 5-CSRTT and taps similar functions but uses a slightly different apparatus. The most important difference is that the rat is not required to turn around and obtain the reinforcer at the back wall; the pellet dispenser delivers the reinforcer under the center response port. In these tasks, the animal must maintain attention to the array of ports in order to detect the signal and respond correctly. Accurate responding thus requires attention in both the temporal and spatial domains. In addition, because responses prior to cue presentation (premature responses) are tallied as errors and terminate the trial,


Assessing Attention in Rodents

121

the task also places demands on inhibitory control, which permits inferences about effects on impulsivity. The location, duration, and timing (pre-cue delay) of the visual cue can be varied across trials, enabling independent assessments of sustained attention as well as impulsivity. Varying the duration of cue illumination allows one to parametrically manipulate the demands on sustained attention. Selective attention may also be tapped by presenting distracting stimuli on some trials during the interval between trial onset and cue presentation. An impressive accumulation of studies over the past 25 years using the 5CSRTT has substantially increased understanding of the neural substrates underlying sustained and selective attention, as well as inhibitory control.12,13 These studies have generally used selective lesions or pharmacological manipulations of ascending monoaminergic systems. In general, accuracy of responding on the basic task appears to depend upon cortical acetylcholine, and speed of responding is mediated by mesolimbic dopamine. Auditory distractors are particularly disruptive to rats with loss of ceruleocortical norepinephrine, and adequate forebrain serotonin appears to be necessary to suppress premature responding. Further work with both methods has illuminated conditions known—or suspected—to cause deficits in attention and inhibitory control, such as attention deficit hyperactivity disorder,14 prenatal cocaine exposure,7,11,15 and early childhood lead exposure.8,10 Research into the genetic underpinnings of attention has been facilitated by new techniques to manipulate the mouse genome, which has stimulated the development of behavioral methods for assessing attention in mice. Humby et al.16 first showed that mice could be trained to perform the 5-CSRTT, and demonstrated the sensitivity of two mouse strains to parametric manipulations and the muscarinic cholinergic antagonist scopolamine. Since that time, a number of studies have employed genetic manipulations to examine the influence of affective states17,18 and neurochemical pathways19–21 on sustained attention. This task has also proven to be a valuable tool for studying murine models of genetic disorders in which attentional dysfunction is prominent; examples include attention deficit hyperactivity disorder,20,22 fragile X syndrome,23 and Down syndrome.24 In addition to its use in its original form for assessing visuo-spatial sustained attention, variations on the method have been used for a number of interesting purposes. For example, true “serial reaction time”—that is, the accuracy and speed of responding to sequentially-presented stimuli—has also been modeled in rats using illuminated nosepoke ports. This method focuses on the analysis of sequential behaviors per se, rather than of control of behavior via attention to temporally unpredictable stimuli.25–27 To probe attention in terms of the Pearce–Hall model of attention,28 Holland’s group29,30 modified the 5-CSRTT method to dissociate effects of the information value of the cue, using continuous reinforcement for responses to two ports and partial reinforcement for responding to two other ports in the five-choice apparatus. Responses to the fifth port were never reinforced. Trials were paced by the experimenter, not the rat, to maintain an appropriate balance of trial types. Asymptotic performance was more accurate to continuously reinforced ports, but new learning (involving discriminative auditory cues) was more rapid to partially reinforced ports. Lesion studies using this behavioral method showed that cholinergic projections


122


from the nucleus basalis magnocellularis to the amygdala central nucleus, medial prefrontal cortex, and posterior parietal cortex support performance of the task.

7.2.2

MATERIALS AND METHODS

The following section describes the apparatus and methods commonly used for the 5-CSRTT for rats. Some modifications that pertain to the 3-choice variant for rats (discussed above), as well as those for the mouse version of the 5-CSRTT are noted briefly at the end of this section. Subjects. Rats and mice, male and female, of several strains and varieties, can learn to perform these multiple-choice serial reaction time tasks. The animal must be mildly hungry at the time of testing, which can be arranged by a number of standard methods. 31 Methods are available to maintain adult rodents at a constant body weight.32 See section 7.2.3, “Preparation of the Subjects,” below. Apparatus. The 5-CSRTT requires equipment that was originally built in the Laboratory of Experimental Psychology, Cambridge, UK.3 It has since become commercially available from a number of manufacturers, including Campden Instruments, Ltd.; Lafayette Instrument Co.; Med Associates, Inc.; PanLab, S.L.; and TSE Systems. The test chambers for rats are roughly the size of a standard operant conditioning chamber, with dimensions approximately 25 × 25 cm horizontally, and roughly 30 cm in height. In place of response levers, a series of five or nine openings, each about 2.5 × 2.5 cm in size, are arranged along a curved rear wall of the chamber, about 2 cm from the floor. Each opening is bisected by a photobeam, which is used to detect entry of the animal’s nose into the opening. A light mounted inside each opening is illuminated briefly on each trial to serve as a signal, and the animal is trained to poke its nose into the illuminated opening to receive food, which is delivered into a cup mounted in the wall opposite to the openings. The food cup must either be accessed via a hinged door with a microswitch, or bisected by a photobeam, so that nosepokes to retrieve the food can be detected. A dispenser is needed to deliver food pellets or liquid food to the animal. A house light is also needed for general illumination of the chamber. Mouse chambers are designed the same way, but scaled down in size, with smaller openings for nosepokes and food delivery. Both solid (dustless pellets) and liquid (diluted condensed milk) reinforcers have been used. A computer and interface for programming the stimulus events and recording the animals’ responses are also necessary. Systems are available commercially for PCs. Programming the procedures can be accomplished in a number of ways, including state notation software for Windows-based systems, and several graphical-displaybased programming systems. Sources of these systems (detailed in the appendix) include Campden Instruments, Ltd.; Lafayette Instrument Co.; Med Associates, Inc.; PanLab, S.L.; and TSE Systems. A repository of open-code programs for MedState notation software is available at http://www.mednr.com/. Calibration devices should include a photometer for measuring the intensity of the light under various stimulus conditions and a sound level meter for measuring the intensity of the white noise and any auditory distractors that might be employed.



7.2.3

123

PREPARATION OF THE SUBJECTS

1. Ensure that the animals are motivated (hungry). One method is to determine their free-feeding body weight, and then reduce that weight by about 15%. Do not deprive the animals completely of food, but reduce their daily allotment such that target body weights are achieved within 5–10 days. If the animal is fully grown, this target weight can be maintained for the remainder of the experiment. On the other hand, if the animal is still growing, allow it to grow in parallel with free-fed animals to a maximum level (e.g., 350 g for an adult male Long-Evans rat and 250 g for an adult female L-E rat). 2. Adapt the animals to the handling procedures31 and to the food pellets or liquid reinforcers that will be used to reinforce responding in the chambers. Commercially available precision 45-mg pellets are appropriate for adult male rats; use 25- or 12-mg pellets for small rats or mice. This latter step can be accomplished by offering the animals the new food each day in their home cages or in a holding cage for several days prior to beginning training. This adaptation will obviate possible bait-shyness that may accompany introduction of a novel food. The following procedure describes methods for using food pellets.

7.2.4

TRAINING STEPS

1. Cover the response openings. Place the hungry animal in the chamber and turn on the house light. Provide food pellets in the food cup. On the first day, begin with 10–20 pellets in the cup, and allow the animal 30 min to explore the chamber and collect the food. On the three following days, deliver the pellets singly at 30-sec intervals and ensure that the animal retrieves the pellets and consumes them. 2. Remove the covers from the openings. Turn on the house light and deliver a single food pellet to start the session and begin the first trial when the animal retrieves the pellet. A trial involves illuminating the signal light in one opening (selected at random) after an inter-trial interval (ITI) of 2 sec and recording the nosepokes made by the animal into the five openings. When the animal pokes its nose into the illuminated opening, turn off the signal light and deliver a single reinforcer. (An auditory cue may be helpful in informing the rat that food has been delivered, if the action of the dispenser is quiet.) If the animal pokes its nose into a dark opening, turn off the house light for a 2-sec timeout period and do not deliver food. Reset the timeout each time the animal pokes its nose into a dark opening. Begin a new trial when the animal pokes its nose into the food cup after either timeout or food delivery. Present signals in each opening an equal number of times in each session, and select at random the opening to illuminate on each trial. Criterion: 100 reinforced nosepoke responses in a 30-min test session.


124


3. Repeat step 2, but place a time limit on the signal light and the response period (called a “limited hold”). Allow the animal to initiate each trial as above, and use a 2-sec delay (pre-cue delay) before illuminating a signal. Illuminate each opening for 60 sec and set a 60-sec limited hold after the signal period. If the animal pokes its nose into the illuminated opening during this 2-min period, deliver a food pellet and count a correct response. If the animal pokes its nose into an unlit opening during this period, turn off the signal light and house light and count an error of commission. If the animal fails to make a nosepoke response in this period, turn off the signal light and the house light and count an error of omission. If the animal makes a nosepoke into any opening during the pre-cue delay, turn off the house light, count a premature response, and restart the same trial. Sessions for rats commonly terminate after either 100 correct responses in a 30-min test session, or a 100-trial session with 80% correct responding (see below). 4. Repeat step 3, progressively shortening the signal duration and limited hold, ending with a signal duration of 0.5 sec and a limited hold of 5 sec. Lengthen the pre-cue delay to 5 sec and the timeout period to 3 sec during these steps. A stable baseline of about 80% correct responding with about 15% omissions should be achieved in about 30 training sessions. 5. After the basic rules have been learned, it is useful to vary the duration of the pre-cue delay across trials within each session (e.g., 0, 3, 5, and 9 sec for rats; 0, 2, and 4 sec for mice). Similarly it is useful to vary the duration of the visual cue across trials within the session (as discussed below).

7.2.5

ALTERNATIVE METHODS

1. The apparatus may be modified so that the food is dispensed on the same side of the apparatus as the response ports.17 This arrangement requires more hardware but facilitates training. Another advantage of this setup, as noted above for the 3-choice variant, is that the animal does not have to turn around and traverse the chamber to obtain the reinforcer. The animal can thereby maintain attentional focus on the response ports throughout the testing session, rendering it more similar to human tests of attention. 2. Trials may be paced by the experimenter rather than the animal29,30,33,34 by starting a new trial at some fixed or variable time after the animal’s choice response on the previous trial, rather than at the time that the animal retrieves the reinforcer (as is done in the standard procedure). This procedure gives the experimenter control over the timing of events in the test, and removes any potential influence that the animal might exert on the trial pacing by its speed of retrieving reinforcers.

7.2.6

TESTING MICE IN THE 5-CSRTT

DeBruin et al.35 provide a systematic, step-by-step approach to training mice in this task, based on their previous work with rats.23



7.2.7

125

APPARATUS AND METHODOLOGY FOR THE 3-CHOICE VARIANT

The 3-choice serial reaction time task used by Strupp and colleagues is identical in concept to the 5-CSRTT, but uses a 3-choice chamber originally developed by Eichenbaum for olfactory discrimination tasks.37 Briefly, the apparatus is comprised of a small testing alcove containing three response ports, separated from a larger waiting area by a metal guillotine-type door that closes at the end of each trial, and then opens to initiate the next trial following an inter-trial interval. Light emitting diodes (LEDs), one positioned above each of the three response ports, provide the target cue. A correct response (a nosepoke into the port under the illuminated LED) is rewarded with a 45-mg Noyes pellet, delivered onto the floor of the chamber via an opening beneath the center port. As noted above, this feature obviates the need for the animal to turn around to retrieve the reward as required in the 5-CSRTT. This feature of the 3-choice variant makes the task more similar to vigilance tasks used for humans and nonhuman primates and, consequently, facilitates extrapolations from the animal findings to the target human population.38 This task has provided important information on the lasting cognitive and affective changes produced by prenatal cocaine exposure,7,9,11,39–42 early postnatal lead exposure,8,10,43–47 prenatal or postnatal hyperphenylalaninemia (models of maternal and classic phenylketonuria),48,49 as well as the attentional role of the ceruleocortical noradrenergic system.6

7.2.8

DATA ANALYSIS AND NOTES

Parametric Manipulation of Cue Characteristics: As noted above, schedule parameters may be manipulated to place greater or lesser challenges on various aspects of attention as well as inhibitory control. Temporal challenges to attending include lengthening and/or shortening the pre-cue delay, or making it variable across trials rather than constant. In addition, shortening the duration of the signal is commonly claimed to increase the “attentional load” of the task.50 In contrast, dimmer signals have been used to challenge visual detection of the signals, a manipulation that has been claimed to differ in nature from reducing its duration.51 By presenting olfactory or auditory distractors on some trials within a session, one can assess selective attention. Systematically varying these parameters (e.g., duration of the pre-cue delay, cue duration, presence or absence of olfactory distractors) within a given testing session is often an effective means of gaining insight into the integrity of specific functions, because information is then provided concerning the particular conditions under which the subjects succeed and fail. This approach can often effectively exclude alternative explanations for poor performance, and thereby specify the nature of the impairment. Evaluating Performance as a Function of the Outcome of the Prior Trial: These multiple-choice reaction time tasks not only provide indices of various attentional functions and inhibitory control, but they can also provide measures of arousal and/or emotion. One available index of arousal and/or emotion within the context of performance in these multiple-choice tasks is the animals’ reaction to committing an error. Several dependent measures in these tasks have been found to vary significantly as a function of the outcome of the previous trial. Specifically, on trials following an error, the animals take longer to enter the testing alcove at trial onset, take longer


126


to make a response, and are more likely to commit all types of errors: premature responses, inaccurate responses (responding after cue onset but to an incorrect port), and omission errors (missing the cue). This pattern—increased response latency and increased error rate on post-error trials—likely reflects an emotional response to the error (for discussion, see23,24). Thus, the degree of disruption produced by committing an error provides a useful index of emotion or arousal. This type of analysis has revealed functionally important deficits in rat models of early developmental exposure to toxicants such as lead8 or cocaine,7,15 and in murine models of Down syndrome24 or fragile X syndrome.23 In some cases, such as the Down syndrome model, the greater reactivity of the mutant mice to committing an error became apparent only as a result of coding videotapes of the mice performing the task (see24). Different Types of Errors: Several types of errors are possible in these tasks, the delineation of which can shed light on the nature of group differences. Nosepokes into the ports prior to cue presentation (premature responses) terminate the trial and are tallied as errors. The percentage of such responses can provide an index of impulsivity or inhibitory control. Trials on which the animal initiates the trial but then does not make a nosepoke into one of the response ports within a specified time after trial onset, scored as omission errors, suggest that the animal missed the cue due to impairment of sustained attention. Inaccurate responses (responses made after cue onset but to a port that had not been illuminated) are also indicative of lapses in attention. The most basic measure of accuracy is the ratio of the number of correct responses divided by the total number of trials. Another useful measure is to calculate the accuracy of the animal given a response at the correct time; this measure is calculated as the number of correct responses divided by the number of “timely” responses (trials on which the animal responded within the limited hold, i.e., excluding premature responses and omission errors). Clues regarding the nature of the dysfunction are also often provided by categorizing the types of errors committed, and then evaluating each error type as a function of these various parameters (delay before cue onset, cue duration, trial block [portion of session]), as well as the outcome of the previous trial, as discussed above. For example, in this visual attention task, we found that adult male rats exposed to cocaine in utero committed more omission errors than controls only on trials in the final third of the testing session that occurred after an error.9,15 These animals were not impaired in this final portion of the session on trials that followed a correct response, or earlier in the session, regardless of prior trial outcome. This pattern implicates the additive effects of impairments in two areas: sustained attention and emotion regulation. Use of Distractors to Assess Selective Attention: The task may be modified to assess selective attention by presenting irrelevant auditory3 or olfactory stimuli7,8,23 during the interval between trial onset and cue presentation while the animal is waiting for the cue. These distracting stimuli lead to an increase in premature and inaccurate responses. It is best to present the distractors on a minority of the trials in a session, so that they are surprising, and therefore maximally disruptive. This procedure also minimizes habituation to the distracting stimuli. Interestingly, in studies with olfactory distractors, the distractors seem to produce the greatest disruption in



127

performance when presented 1 sec following trial onset, regardless of whether the cue is presented after a 2 or 3 sec delay.7 Two different indices are useful for assessing the effect of the distractors. First, the effect of the manipulation of interest (e.g., lesion, drug treatment, genetic manipulation) on selective attention can be assessed by comparing performance on trials with distractors (distraction trials) to performance on trials without distractors (non-distraction trials). However, the distractors may disrupt performance on the non-distraction trials as well as the distraction trials, due to heightened arousal or emotion. To ascertain whether the manipulation of interest alters this putative effect (which may be thought of in terms of emotion or arousal regulation), performance on the non-distraction trials of the distraction task can be compared to performance on a baseline task that is identical in terms of light cue presentation parameters but does not include distractors. Interestingly, which of these two measures will be more sensitive in any given case depends on the nature of the dysfunction seen in the experimental group. For example, in a mouse model of fragile X syndrome, which in humans is characterized by impairments in attention and arousal regulation, the mutant mice differed from controls in terms of the generalized disruption produced by the distractors; performance on the distraction trials did not differ between groups.23 Latency Measures: Several latency measures are also informative. Response latency (the time between onset of the signal and a correct response) on correct trials provides a measure of information processing speed. Food retrieval latency (the time between delivery of a food pellet and the animal’s entry into the food cup) provides a measure of motivation. Similarly, in task variants in which trial onset is indicated by the opening of a door at the dipper alcove (e.g., see23,24), the latency to respond to the dipper alcove after the door is raised provides another index of motivation, and also an index of the emotional reaction to the outcome (correct or incorrect) of the prior trial. All of these latency measures may, however, be influenced by changes in motoric function. Therefore, it is important to determine whether all of these latency measures are altered or only certain ones. For example, if correct response latency is slowed but alcove latency and dipper latency are not altered, the most parsimonious interpretation is that information processing speed is slowed; the fact that alcove latency and dipper latency are normal allows one to exclude an impairment of motor function. Varying the Probability of Reinforcement: The probability of reinforcement for correct responses has been manipulated as a way to control the predictive validity of selected cue-port stimulus complexes to test the associability of these cues with new learning.29 Strupp and colleagues have also used periodic reward omission as a means of assessing reaction to non-reward (e.g., emotion or affect regulation) in both rats and mice using a similar task.47


128


7.3

SIGNAL DETECTION TASKS WITH BLANK TRIALS

7.3.1

INTRODUCTION

The ability of human subjects to report the occurrence of rare and unpredictable signal events over prolonged periods of time has been extensively characterized.52,53 Accurate detection of such signals is assumed to depend upon maintaining attention to the task over time, and many of the factors that affect performance of humans on these tasks have been systematized. Sustained attention tasks comprise an important and sensitive component of neurobehavioral test batteries used for assessing the effects of drugs in humans, e.g., benzodiazepines,54 stimulants,55 and ethanol.56 A major problem for tests of sustained attention involves quantifying and minimizing the false alarm rate. That is, a subject can successfully report many signals simply by responding frequently—though doing so will generate a large number of erroneous reports that a signal had occurred (false alarms). Human subjects can be instructed not to respond in this manner and will normally withhold most false alarms; animals can be trained to do so as well. However, manipulations that increase or decrease overall “responsivity” or response rate are difficult to interpret if no independent measure of the false alarm rate is obtained. Better estimates of the false alarm rate can be obtained by counting responses to specified non-signal events (blank trials). This approach has been used with both fixed and retractable response levers. The task described below employs a discretetrial, two-lever approach that requires rats to report the occurrence or nonoccurrence of a single, brief, centrally located signal. Thus, two retractable levers are inserted into the test chamber after a variable period of time to “ask” the rat to report whether a brief signal was presented during that period. If a signal was presented (“signal trial”), a press on one lever produces food and a press on the other lever produces a short timeout period without food. If no signal has occurred (“blank trial”), the converse contingencies apply. Because the levers are retracted between trials, no presses can occur during the inter-trial interval (ITI). Because an explicit response is required on each trial, the proportions of hits and false alarms (P[hit] and P[fa]) can be calculated in relation to the total number of completed signal and blank trials, respectively. Validation of this method includes both studies of the effects of parameters known to affect human sustained attention, and pharmacological and neurobiological manipulations. Parametric studies include observations that signal intensity, signal rate, and the type of task all affect response accuracy,57–59 as predicted from studies of vigilance in humans.52 Thus the parameters that affect the behavior of rats in this task closely parallel those that affect sustained attention in humans. In addition, three of the variables that control the behavior of rats in this task (signal intensity, trial presentation rate, and whether detection of a single stimulus or discrimination between two stimulus classes is required) have been shown experimentally to control the behavior of humans in this task. Pharmacological studies have shown dose-related impairment of signal detection in this task after a variety of nicotinic drugs,59,61–68 d-amphetamine,59 the muscarinic



129

drugs pilocarpine and scopolamine, and the F2-adrenergic compounds clonidine and idazoxan.65 Further, the influence of cholinergic projections from the basal forebrain to the cortical mantle in sustained attention has been described in a series of elegant studies.69–74 This work has led to advances in understanding the neurobiology of sustained attention75,76 and hypotheses regarding the role of attention in addictive behavior.63 The method has also been used to characterize the acute effects of organic solvents58,78–80 and other neurotoxic chemicals.81–83 This method has also been enhanced by systematic manipulation of the postsignal interval to engage working memory as well as attention.84 Using this hybrid task, the effects of scopolamine and mecamylamine, drugs often presumed to impair working memory, were shown to affect attention. Martin et al.85 trained wild type and lurcher mice to perform this task, and determined that the effects on performance in the lurchers were due to motoric rather than attentional deficits.

7.3.2

MATERIALS

Subjects. Rats and mice can perform the task. See section 7.2.3, “Preparation of the Subjects” above. Apparatus. Assemble one or more standard operant conditioning chambers equipped at minimum with a signal light, a food cup and food pellet dispenser, and two retractable response levers. A loudspeaker for presentation of masking noise may also be used. The two retractable levers should be mounted on either side of the food cup. Mount the signal light immediately above one of the levers at the start of training, and later move it to the top center of the wall above the food cup when the rat has learned the response rule required for the task. This equipment can be purchased from one of the vendors of behavioral test systems listed in the appendix. Assign the lever below the signal lamp as the “signal” lever and the other lever as the “blank” lever. Set up half of the chambers with the signal lever on the left and the other half with it on the right. Counterbalance all treatments for signal lever position. A computer and interface for programming the stimulus events and recording the animals’ responses are also necessary. Commercially available hardware and software systems are available, as described above for the 5-CSRTT. Calibration devices should include a photometer for measuring the intensity of the light under various stimulus conditions and a sound level meter for measuring the intensity of the white noise.

7.3.3


Same as above for the 5-CSRTT.


130

7.3.4


TRAINING STEPS

1. Shape the rats to press the signal lever for food by autoshaping,86,87 by long (e.g., overnight) sessions with a continuous reinforcement schedule in effect, or by hand shaping. If an autoshaping procedure is used, turn on the signal lamp whenever the lever is extended into the chamber, and turn it off when the lever retracts (either when the rat presses it, or after 15 sec without a press). If overnight sessions are used, be sure to provide adequate water. Criterion: one session of 50 reinforced responses on this lever. 2. Shape the rats to press the other (“blank”) lever by the same means. However, do not turn on the signal lamp when shaping responses on this lever. Criterion: one session of 50 reinforced responses on this lever. 3. Begin training using trials in which both levers are extended into the chamber simultaneously on each trial. Light the signal lamp in half the trials (“signal” trials) and not in the other half (“blank” trials). Retract both levers as soon as one is pressed. Deliver a food pellet after a press on the signal lever in a signal trial and after a press on the blank lever in a blank trial. Turn off all lights for 3 sec after a press on the signal lever in a blank trial and after a press on the blank lever in a signal trial. In signal trials, turn on the signal light 2 sec before extending the levers, and leave it on until the rat presses a lever. Use correction trials to reduce the likelihood of position habits: repeat the conditions presented in each trial that terminates in an incorrect response, up to a maximum of three such correction trials. If the rat makes three consecutive errors, extend only the other (correct) lever in the fourth trial to force a correct response. Criterion: two 100-trial sessions with overall accuracy of 80% or better. 4. Remove the correction trials and increase the total number of trials to 120. Criterion: one 120-trial session with overall accuracy of 80% or better. 5. Turn off the signal when the levers extend (rather than when the rat makes a response) and increase the total number of trials to 150. Criterion: one 150-trial session with overall accuracy of 80% or better. 6. Reduce the duration of the signal from 2 sec to 0.3 sec in gradual steps (e.g., 1.5 sec, 1.0 sec, 0.7 sec, 0.5 sec, and 0.3 sec). The onset of the signal should occur 2 sec before insertion of the levers in all cases, leaving an empty period between offset of the signal and insertion of the levers. Increase the total number of trials in stages to 240. Criterion: one session with overall accuracy of 80% or better at each signal duration. 7. Move the signal lamp from its position above the signal lever to a position at the top of the panel, centered between the levers (above the food cup). Retrain to criterion accuracy. 8. Make the interval after the signal offset variable (select values of 2, 3, or 4 sec randomly on each trial). Maintain accuracy at the 80% criterion. 9. Make the interval before the signal onset variable. (Begin with a list of relatively short and homogeneous values, and work up to a list of values ranging from less than 1 sec to about 25 sec, selected randomly on each trial. A con-



131

stant-probability list, such as that provided by Fleschler and Hoffman88 is recommended for the final stage.) Maintain accuracy at the 80% criterion. 10. Vary the strength of the signal. Either the intensity or duration may be varied. Varying the intensity is preferred, but requires digital control of the voltage provided to the signal lamp (through a digital-to-analog converter). At least three signal strengths should be used, preferably more (up to seven). Administer at least 20 trials at each signal strength (10 signal and 10 blank). Maintain accuracy at the 80% criterion.

7.3.5


The proportion of correct detections of the signal (P[hit]) should increase with increasing signal strength. The signal strength should be adjusted so that the weakest signal produces a P(hit) about equal to the guessing rate, and the strongest signal produces a P(hit) of about 1.0. The guessing rate is given by the proportion of errors on blank trials, or false alarms (P[fa]). P(fa) should be independent of signal strength and range from about 0.10–0.20. A wide range of signal strength values improves the consistency of the baseline from day to day, and allows one to differentiate between changes in attention and visual function.65 That is, poor attending to the signals should cause an increase in P(fa) and a decrease in P(hit) at all signal strengths where P(hit) exceeds P(fa). In other words, the P(hit) by signal strength gradient should shift downward. In contrast, a change in the ability of the rat to see the signal should produce a horizontal shift in the P(hit) by signal strength gradient, so that P(hit) is altered only for signals of intermediate intensity; in addition, P(fa) should not change. P(hit) and P(fa) can be used to calculate signal detection indices of sensitivity and bias by any of a number of methods.88–91 However, interpretation of these derived measures depends upon the particular assumptions upon which their calculation is based, and explanation of their meaning invariably requires reference to the values of P(hit) and P(fa) from which they were derived. Thus the advantages of deriving signal detection indices—which involves trading one pair of measures (P[hit] and P[fa]) for another pair of more derived measures (sensitivity and bias)—are generally outweighed by the effort required to calculate and explain these derived measures. Response time may also be measured as the latency between insertion of the lever and the rat’s response. This variable provides an index of motor function similar to a simple reaction time, because rats typically choose which lever to press during the time interval after the signal by positioning themselves in front of one of the levers and pressing it during its insertion into the chamber. Response time typically does not vary with signal intensity, but does tend to be shorter for hits and false alarms than for misses and correct rejections.58

7.4

ATTENTIONAL SET-SHIFTING

7.4.1

INTRODUCTION

Another aspect of attentional function frequently assessed in human neuropsychological testing batteries is attentional set-shifting, commonly indexed by the Wisconsin


132


Card Sorting Task (WCST), the primary clinical index for frontal lobe dysfunction. This function can also be tested by the extradimensional shift (EDS) task which is part of the Cambridge Neuropsychological Test Automated Battery (CANTAB), a testing battery originally developed for the assessment of cognitive function in elderly and dementing patients,93 but now also widely used to test patients with Alzheimer’s disease and other forms of dementia, basal ganglia disorders including Parkinson’s disease, Korsakoff syndrome, depression, and schizophrenia, as well as children with learning difficulties or autism (see94). Notably, versions of the EDS paradigm have been developed for nonhuman primates and rodents (described below). In this paradigm, which includes a series of tasks, the subject is first trained to respond to one stimulus dimension (e.g., odor) of a multidimensional compound stimulus and is then required to respond instead to a previously irrelevant dimension (e.g., texture). This shift from one stimulus dimension to another defines an EDS. Insight into the nature of the dysfunction is provided by comparing the rate of mastering the EDS to the rate of mastering an intradimensional shift (IDS), in which two novel stimuli are presented, but the predictive dimension is the same as in the original discrimination. If the subject has formed an attentional set, the mastery of the IDS is more rapid than for the original discrimination, and mastery of the EDS is slower than for the IDS. The EDS phase requires cognitive flexibility (to shift attention from the previously predictive dimension to the newly predictive dimension), and associative ability (to figure out the new contingencies), as well as selective attention (to attend selectively to the new predictive dimension while ignoring the previously predictive dimension). In a typical study, reversals of the correct and incorrect cues within a dimension are also commonly introduced following both the IDS and the EDS, to determine the extent to which behavior is controlled by the dimension as opposed to the specific exemplars of the dimension. (Further discussion of methodological issues can be found in95,96.) As discussed by Chudasama and Robbins,94 the ED/ID set-shifting test can serve several functions. First, it provides a sensitive index of frontal lobe dysfunction, based not only on recent empirical evidence from lesion studies,96,97 but also on the fact that it taps the primary function required for successful performance on the WCST, the primary clinical index for frontal lobe dysfunction.92 Second, it allows one to distinguish between two levels of cognitive flexibility: perseveration to a specific exemplar (tapped by the reversal learning task in this series) versus inflexibility with respect to shifting attention from one perceptual domain to another (i.e., attentional set-shifting). An attractive feature of this task series is that parallel versions have been devised for testing monkeys,98 rats (e.g., see41,45,96), and mice,99 thereby providing an opportunity to integrate clinical findings with human subjects (e.g., from the CANTAB) with information concerning the neural and neurochemical systems that underlie specific aspects of task performance. Both operant and sand-digging versions of the set-shifting paradigm have been described for rodents. In the following sections, we discuss these two versions and outline the key advantages and disadvantages of each, to aid the reader in deciding which task would be preferable for achieving specific goals while considering temporal and fiscal constraints. We describe the sand-digging version of the paradigm



133

in preference to the operant method because of its relative efficiency in time and equipment. The sand-digging EDS method developed by Brown and colleagues96 consists of a series of seven tasks, including a simple discrimination,50 a compound discrimination, a reversal of the CD (R1), an IDS, and an EDS, and a reversal of the EDS (R3). Two sessions are required: an initial training session, in which the animals are trained to dig for bits of food hidden in bowls of digging medium, followed by a second test session in which seven discrimination, reversal, and shift tasks are given in sequence. The task is detailed below. There are several attractive features of this task. First, it does not require expensive operant equipment and can be set up quickly. Second, the entire series of seven tasks can be completed in a single session, representing a considerable savings in time relative to the operant EDS task version. Third, this task series includes novel stimuli at each stage, i.e., a “total change design.” This feature, which aids in interpretation of results (discussed in96,97) is more difficult to implement in operant setups. Finally, the task has been validated as an index of frontal lobe dysfunction for rats based on the fact that, in both rats and primates, medial prefrontal lesions impair EDS but not reversal learning, and orbitofrontal cortex lesions impair reversal learning but not EDS learning.96,97,100 Despite these assets, there are two drawbacks to the sand-digging EDS task relative to the operant version. First, it cannot be automated because it requires hands-on, trial-by-trial administration by an experimenter. Second, as presently configured, it does not enable one to determine the basis of an observed alteration in EDS learning rate. That is, if the EDS task is the only task in the series that is impaired by the experimental manipulation (i.e., no group differences are observed in original learning, IDS, or reversals), it is possible to conclude that the manipulation being tested (e.g., a lesion or a drug) specifically impaired the rate at which the rat mastered an EDS, but the nature of the cognitive change remains ambiguous. This is because there are at least two possible reasons for a selective EDS impairment: (1) an impaired ability to shift attention from the previously predictive cues (inflexibility with regard to attentional set); and (2) impaired selective attention (an inability to filter out the previously predictive cues. In contrast, because acquisition of the operant EDS task is more prolonged, it is possible to demarcate different phases of learning based on the subject’s patterns of responding. These phases include a perseverative phase, characterized by repetitive responding to the previously correct stimulus; a subsequent chance phase, reflecting trial-and-error responding, with inconsistent patterns of correct responding; and a post-chance phase, in which accuracy exceeds chance and increases steadily toward criterion. Changes in the durations of the specific phases can shed light on the nature of the impairment. For example, an experimental group that exhibits a significant lengthening of the initial perseverative phase, with later learning phases of normal length, is likely to suffer from cognitive inflexibility. In contrast, a group that exhibits an elongated post-chance phase, combined with normal IDS performance, is likely to be impaired in selective attention, unable to focus selectively on the new predictive dimension as a result of being distracted by the previously predictive cues.


134


Previous research involving a rodent model of prenatal cocaine exposure illustrates how phase analysis of this type of task series can shed light on the integrity of these specific cognitive functions. In this study, the animals were administered a series of olfactory discrimination and reversal tasks followed by two EDS tasks.41 The first and third EDS tasks required a shift from the olfactory to the spatial dimension; the second EDS task required a shift from spatial to olfactory cues. Analyses of learning rate (errors to criterion) demonstrated that the cocaine-exposed (COC) animals were significantly impaired in the two spatial EDS tasks, but not in the olfactory EDS task. The fact that the COC animals exhibited slower learning than controls only late in the task (after the subjects had made eight consecutive correct responses) suggests that the deficiency was not related to being inflexible in shifting attentional set, as they did not show perseverative responding to the dimension that was previously predictive. Rather, the increased error rate (relative to controls) seen later in the task suggests impairment of selective attention (i.e., difficulty ignoring the irrelevant cues).

7.4.2

SAND-DIGGING TASK: MATERIALS AND METHODS

Below we describe the sand-digging EDS task series developed for96 and also adapted for mice.99 This method entails easily mastered tasks that do not require expensive equipment, and therefore may be accessible to investigators on a tight budget in terms of time or money. However, the interpretive limitations associated with the rapid learning, in terms of being able to identify the specific nature of the dysfunction, should also be kept in mind. Subjects. Rats and mice can perform the task. The animals must be hungry; methods for maintaining appetitive motivation are discussed above. The method described here is designed for rats and can be scaled down for mice. Apparatus. A large plastic rodent cage (e.g., 40 × 70 × 18 cm) with clear plastic dividers and a set of digging bowls (e.g., ceramic pots, 7 cm diameter) are needed. The cage is divided along its long axis for one-third of its length with a permanent vertical plastic panel, and a single digging bowl is placed on either side of this panel. This panel serves to prevent rapid movement of the animal from one bowl to the other. A second, removable panel is placed across the short axis of the cage blocking entrance to the divided area, and serves to prevent the animal from starting the trial prematurely. Digging bowls are covered on the sides and rim with various materials that differ in texture (e.g., sandpaper, cloth, or wax paper) and are filled with digging medium of various textures (e.g., sawdust, sand, or tea leaves). The media are also scented (e.g., with cumin, cinnamon, or cloves). Six exemplars of each stimulus dimension (texture, medium, and odor) are necessary for the complete design.

7.4.3


Rats require habituation to the apparatus and to digging in bowls for food (e.g., a small piece of sweetened cereal as bait). During a single 60-min session, the rat first learns to dig for bait, which is replaced in the bowl every 5 min as the animal retrieves it. Next, the rat is given three simple discrimination tasks, in which bait is



135

placed in one of two bowls, which differ along one of the three stimulus dimensions (texture, odor, or medium). The exemplars used in this session are not used further. Each rat is trained to a criterion of six consecutive correct choices, where a choice is defined as the first bowl that the rat digs in.

7.4.4

TRAINING STEPS

In the second session, the rats are given a series of seven discriminations using three different pairs of stimulus exemplars of each dimension: a simple discrimination (SD), a compound discrimination (CD), a reversal of the CD (R1), an IDS, a second reversal (R2), an EDS, and a reversal of the EDS (R3). Each rat receives the tests in the same order, and is tested with one relevant stimulus dimension and one irrelevant dimension. In the first five tests, the relevant dimension is always the same; it changes at test 6, the EDS. In each test, the bowls are baited and placed on either side of the permanent barrier at the end of the cage. The removable barrier is set in place, and the rat is placed in the test box on the side of the removable barrier opposite the bowls. A trial begins with removal of the barrier and ends when the rat obtains the bait or makes an error. The first four trials of each test are “discovery trials” in which the rat is permitted to dig in each bowl to find the bait. Beginning on the fifth trial, the rat is permitted to eat the bait if it chooses the baited bowl first. If it chooses the unbaited bowl first, an error is scored and the trial is terminated. The rat is trained to a criterion of six consecutive correct choices.

7.4.5


The stimulus dimensions used and the correct and incorrect exemplars must be distributed systematically across individual subjects so that, when averaged across animals, learning scores are not biased by the relative difficulty of the specific discriminations used in each test. In contrast, treatment groups should be matched for stimulus conditions at each stage of testing, to prevent confounding of differences in stimulus discriminability or dimensional salience with the treatment. See Birrell and Brown96 for further details of the design. For control animals, the rate of learning (errors or trials to criterion) should be faster for the ID than for the ED. Note that the rat is presented with two multidimensional stimuli in both of these tasks; if the animal had not formed an attentional set (predisposing it to focus on one perceptual dimension over others), then these two tasks would be solved at exactly the same rate and, indeed in this method, a particular set of cues must be used for the ED for some animals and the ID for others, ruling out the possibility that a particular set of cues is easier to master than others. The inclusion of the five task types in the series (simple and compound discrimination, IDS, EDS, and reversals) aids in interpreting the nature of observed group differences. For example, if the simple and compound discrimination tasks do not reveal group differences, but the experimental group is impaired on the IDS, the reversals, and/or the EDS tasks, then one can exclude the possibility that the observed impairment on one or more of these latter tasks is a result of decreased motivation,


136


impaired ability to perform the motoric demands of the task, or impaired sensory acuity. If the experimental group is unimpaired on all tasks except for the reversals (as seen following lesions of the orbitofrontal cortex100), then one can conclude that the experimental group has a specific deficit in the ability to inhibit responses to a previously rewarded object within a given perceptual domain. Finally, if the deficit is limited to the EDS phase, one can conclude that the manipulation specifically altered the ability to shift attentional set; the intact IDS phase allows one to rule out formation of the attentional set as the locus of the impairment. However, as noted above, an impaired ability to shift attentional set could be due to either inflexibility in shifting attentional set or impaired selective attention.

7.5

SELECTING A TEST METHOD

The several methods described here represent commonly used approaches to assessing attention in rodents. Others are also available; a more comprehensive treatment of them was compiled by Bushnell,1 and surely more have been devised in the interim. The choice of method should ultimately depend on the question being addressed, although issues of practicality (e.g., availability of equipment and time for training) will inevitably affect the choice. Guidance regarding the variety of attention to be assessed should be taken from literature on the disease state or phenomenon of interest. A first cut might be to decide whether the aspect of attention most likely to be affected is selective attention, sustained attention, or attentional set-shifting. Sustained attention is better assessed by the serial reaction time tasks and discretetrial signal detection methods described in sections 7.2 and 7.3. Selective attention is best tapped by serial reaction time tasks with periodic presentation of distracters. EDS methods provide an index of attentional set-shifting and, indirectly, also a measure of selective attention; that is, impaired selective attention would be expected to impair EDSs but slower EDS mastery does not necessarily indicate impaired selective attention, as discussed above. The serial reaction time tasks also provide an index of impulsivity or inhibitory control, an area of dysfunction that is prominent in attention deficit hyperactivity disorder, and therefore is also of interest in many assessments of attentional function. Sustained attention can involve both temporal and spatial components. The 5CSRTT combines the two, and can be arranged to focus on one or the other of these dimensions. For example, the spatial distribution of the stimuli can be widened by using only the peripheral ports, or narrowed by using only the central ones. The temporal uncertainty and the duration of the cue are routinely varied to manipulate the “attentional load” placed on the animal. One attractive feature of this task is that sustained and selective attention as well as inhibitory control can all be independently assessed in the same task. A drawback of the standard method is that trials are initiated by the animal, so that control over the pacing of the session is under the animal’s control. However, this aspect is easily modified, and has been placed under the control of the experimenter in both the 5-CSRTT23,24 and the 3-choice variant (e.g., see6,39,45,48). The discrete-trial signal detection method removes the spatial component and focuses only on the temporal dimension. Trial pacing is determined by the program-



137

ming, so that the experimenter retains control over the entire test session. In addition, if the intensity of the signal can be manipulated independently of its duration and timing, then the method can be used in a psychophysical manner to determine changes in threshold for detecting increments in stimulus intensity as a check for visual dysfunction (in contrast to attentional problems). EDS tasks (both operant and sand-digging) provide an index of attentional setshifting, an aspect of attention frequently assessed in human neuropsychological testing batteries, and a classic index of frontal lobe functioning. An attractive feature of this task series is that virtually identical tasks have been developed for humans, nonhuman primates, and rodents, facilitating cross-species extrapolation of findings. An additional advantage of the sand-digging version of this task is that it does not require expensive equipment and can be administered in a few days. As noted above, this task series provides an assessment of two types of flexibility, as well as an indirect index of selective attention. The database of literature should also be considered when selecting a test. The 5CSRTT has been more widely used in the study of attention in rodents than any other task; early work with it focused on the neurobiological pathways mediating behavior in the test,12 whereas more recent work has included the psychopharmacology of systemic treatments as well.13 The discrete-trial signal detection task has also been used to evaluate CNS pathways involved in attention,76 with a focus on questions of drug addiction and mental disorders.77 It has also been used extensively to study the acute effects of psychoactive drugs65,101 and volatile organic solvents.78

DISCLAIMER This manuscript has been reviewed by the National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency and approved for publication. Approval does not signify that the contents necessarily reflect the policies of the Agency nor does mention of trade names or commercial products constitute endorsement or recommendation for use.

REFERENCES 1. Bushnell, P.J., Behavioral approaches to the assessment of attention in animals. Psychopharmacology (Berl), 1998. 138(3-4): p. 231-59. 2. James, W., The Principles of Psychology. 1950, New York: Dover Publications Inc. 3. Carli, M., et al., Effects of lesions to ascending noradrenergic neurones on performance of a 5-choice serial reaction task in rats; implications for theories of dorsal noradrenergic bundle function based on selective attention and arousal. Behav Brain Res, 1983. 9(3): p. 361-80. 4. Wilkinson, R., Interaction of noise with knowledge of results and sleep deprivation. Journal of Experimental Psychology, 1963. 66: p. 332-337. 5. Sahakian, B., et al., Further analysis of the cognitive effects of tetrahydroaminoacridine (THA) in Alzheimer’s disease: Assessment of attentional and mnemonic function using CANTAB. Psychopharmacology (Berl), 1993. 110: p. 395-401.


138


6. Bunsey, M.D. and B.J. Strupp, Specific effects of idazoxan in a distraction task: evidence that endogenous norepinephrine plays a role in selective attention in rats. Behav Neurosci, 1995. 109(5): p. 903-11. 7. Gendle, M.H., et al., Enduring effects of prenatal cocaine exposure on selective attention and reactivity to errors: evidence from an animal model. Behav Neurosci, 2004. 118(2): p. 290-7. 8. Stangle, D.E., et al., Succimer chelation improves learning, attention, and arousal regulation in lead-exposed rats but produces lasting cognitive impairment in the absence of lead exposure. Environ Health Perspect, 2007. 115(2): p. 201-209. 9. Gendle, M.H., et al., Alterations in reactivity to errors and sustained attention in an animal model of prenatal cocaine exposure (Special Edition on Drugs of Abuse, invited contribution). Developmental Brain Research 2003. 147: p. 85-96. 10. Morgan, R.E., et al., Early lead exposure produces lasting changes in sustained attention, response initiation, and reactivity to errors. Neurotoxicol Teratol, 2001. 23(6): p. 519-31. 11. Morgan, R.E., et al., Enduring effects of prenatal cocaine exposure on attention and reaction to errors. Behav Neurosci, 2002. 116(4): p. 624-33. 12. Robbins, T.W. and B.J. Everitt, Arousal systems and attention, in The Cognitive Neurosciences, M.S. Gazzaniga, Editor. 1995, MIT Press: Cambridge, MA. p. 703-720. 13. Robbins, T.W., The 5-choice serial reaction time task: behavioural pharmacology and functional neurochemistry. Psychopharmacology (Berl), 2002. 163(3-4): p. 362-80. 14. Puumala, T., et al., Behavioral and pharmacological studies on the validation of a new animal model for attention deficit hyperactivity disorder. Neurobiol Learn Mem, 1996. 66(2): p. 198-211. 15. Gendle, M.H., et al., Impaired sustained attention and altered reactivity to errors in an animal model of prenatal cocaine exposure. Brain Res Dev Brain Res, 2003. 147(1-2): p. 85-96. 16. Humby, T., et al., Visuospatial attentional functioning in mice: interactions between cholinergic manipulations and genotype. Eur J Neurosci, 1999. 11(8): p. 2813-23. 17. van Gaalen, M.M., et al., Reduced attention in mice overproducing corticotropinreleasing hormone. Behav Brain Res, 2003. 142(1-2): p. 69-79. 18. Greco, B. and M. Carli, Reduced attention and increased impulsivity in mice lacking NPY Y2 receptors: relation to anxiolytic-like phenotype. Behav Brain Res, 2006. 169(2): p. 325-34. 19. Pattij, T., et al., Strain specificity and cholinergic modulation of visuospatial attention in three inbred mouse strains. Genes Brain Behav, 2007. 6(6): p. 579-87. 20. Greco, B., R.W. Invernizzi, and M. Carli, Phencyclidine-induced impairment in attention and response control depends on the background genotype of mice: reversal by the mGLU(2/3) receptor agonist LY379268. Psychopharmacology (Berl), 2005. 179(1): p. 68-76. 21. Hoyle, E., et al., Impaired performance of alpha7 nicotinic receptor knockout mice in the five-choice serial reaction time task. Psychopharmacology (Berl), 2006. 189(2): p. 211-23. 22. Davies, W., et al., X-monosomy effects on visuospatial attention in mice: a candidate gene and implications for Turner syndrome and attention deficit hyperactivity disorder. Biol Psychiatry, 2007. 61(12): p. 1351-60. 23. Moon, J., et al., Attentional dysfunction, impulsivity, and resistance to change in a mouse model of fragile X syndrome. Behav Neurosci, 2006. 120(6): p. 1367-79. 24. Driscoll, L.L., et al., Impaired sustained attention and error-induced stereotypy in the aged Ts65Dn mouse: a mouse model of Down syndrome and Alzheimer’s disease. Behav Neurosci, 2004. 118(6): p. 1196-205.



139

25. Domenger, D. and R.K. Schwarting, Sequential behavior in the rat: role of skill and attention. Exp Brain Res, 2007. 182(2): p. 223-31. 26. Domenger, D. and R.K. Schwarting, The serial reaction time task in the rat: effects of D1 and D2 dopamine-receptor antagonists. Behav Brain Res, 2006. 175(2): p. 212-22. 27. Domenger, D. and R.K. Schwarting, Sequential behavior in the rat: a new model using food-reinforced instrumental behavior. Behav Brain Res, 2005. 160(2): p. 197-207. 28. Pearce, J.M. and G. Hall, A model for Pavlovian learning: variations in the effectiveness of conditioned but not of unconditioned stimuli. Psychol Rev, 1980. 87(6): p. 532-52. 29. Maddux, J.M., et al., Dissociation of attention in learning and action: effects of lesions of the amygdala central nucleus, medial prefrontal cortex, and posterior parietal cortex. Behav Neurosci, 2007. 121(1): p. 63-79. 30. Holland, P.C., Disconnection of the amygdala central nucleus and the substantia innominata/nucleus basalis magnocellularis disrupts performance in a sustained attention task. Behav Neurosci, 2007. 121(1): p. 80-9. 31. Ator, N.A., Subjects and instrumentation., in Experimental Analysis of Behavior, Part 1, I.H. Iversen and K.A. Lattal, Editors. 1991, Elsevier Science Publishers: Amsterdam. p. 1-62. 32. Ali, J.S., et al., A LOTUS 1-2-3 - based animal weighing system with a weight maintenance algorithm. Behavior Research Methods, Instrumentation, and Computers, 1992. 24: p. 82-87. 33. Patel, S., et al., Attentional performance of C57BL/6 and DBA/2 mice in the 5-choice serial reaction time task. Behav Brain Res, 2006. 170(2): p. 197-203. 34. Wrenn, C.C., et al., Performance of galanin transgenic mice in the 5-choice serial reaction time attentional task. Pharmacol Biochem Behav, 2006. 83: p. 428-440. 35. De Bruin, N.M., et al., Attentional performance of (C57BL/6Jx129Sv)F2 mice in the five-choice serial reaction time task. Physiol Behav, 2006. 89(5): p. 692-703. 36. De Bruin, N.M., et al., Combined uridine and choline administration improves cognitive deficits in spontaneously hypertensive rats. Neurobiol Learn Mem, 2003. 80(1): p. 63-79. 37. Eichenbaum, H., A. Fagan, and N.J. Cohen, Normal olfactory discrimination learning set and facilitation of reversal learning after medial-temporal damage in rats: implications for an account of preserved learning abilities in amnesia. J Neurosci, 1986. 6(7): p. 1876-84. 38. Strupp, B.J. and A. Diamond, Assessing cognitive function in animal models of mental retardation. Mental Retard Develop Dis Res Rev, 1996. 2(4): p. 216-226. 39. ayer, L.E., et al., Prenatal cocaine exposure increases sensitivity to the attentional effects of the dopamine D1 agonist SKF81297. J Neurosci, 2000. 20(23): p. 8902-8. 40. Bayer, L.E., et al., Increased sensitivity to idazoxan in rats exposed to cocaine in utero: Evidence for enduring effects on catecholaminergic systems underlying attention. Behav Brain Res, 2002. 133(2): p. 185-196. 41. Garavan, H., et al., Prenatal cocaine exposure impairs selective attention: evidence from serial reversal and extradimensional shift tasks. Behav Neurosci, 2000. 114(4): p. 725-38. 42. Gendle, M.H., et al., Prenatal cocaine exposure does not alter working memory in adult rats. Neurotoxicol Teratol, 2004. 26(2): p. 319-29. 43. Alber, S.A. and B.J. Strupp, An in-depth analysis of lead effects in a delayed spatial alternation task: assessment of mnemonic effects, side bias, and proactive interference. Neurotoxicol Teratol, 1996. 18(1): p. 3-15. 44. Garavan, H., et al., Enduring effects of early lead exposure: evidence for a specific deficit in associative ability. Neurotoxicol Teratol, 2000. 22(2): p. 151-64.


140


45. Hilson, J.A. and B.J. Strupp, Analyses of response patterns clarify lead effects in olfactory reversal and extradimensional shift tasks: assessment of inhibitory control, associative ability, and memory. Behav Neurosci, 1997. 111(3): p. 532-42. 46. Morgan, R.E., D.A. Levitsky, and B.J. Strupp, Effects of chronic lead exposure on learning and reaction time in a visual discrimination task. Neurotoxicol Teratol, 2000. 22(3): p. 337-45. 47. Beaudin, S.A., et al., Succimer chelation normalizes reactivity to reward omission and errors in lead-exposed rats. Neurotoxicol Teratol, 2007. 29(2): p. 188-202. 48. Strupp, B.J., et al., Deficient cumulative learning: an animal model of retarded cognitive development. Neurotoxicol Teratol, 1994. 16(1): p. 71-9. 49. Strupp, B.J., et al., Cognitive profile of rats exposed to lactational hyperphenylalaninemia: correspondence with human mental retardation. Dev Psychobiol, 1990. 23(3): p. 195-214. 50. Muir, J.L., B.J. Everitt, and T.W. Robbins, AMPA-induced excitotoxic lesions of the basal forebrain: a significant role for the cortical cholinergic system in attentional function. J Neurosci, 1994. 14(4): p. 2313-26. 51. Muir, J.L., Attention and stimulus processing in the rat. Brain Res Cogn Brain Res, 1996. 3(3-4): p. 215-25. 52. Beaudin, S.A., et al., Succimer chelation normalizes reactivity to reward omission and errors in lead-exposed rats. Neurotoxicol Teratol, 2006. 53. Parasuraman, R., The psychobiology of sustained attention., in Sustained attention in human performance, W. JS, Editor. 1984, Wiley: Nw York. p. 61-101. 54. Craig, A. and D. Davies, Vigilance: Sustained visual monitoring and attention., in Vision and Visual Dysfunction, J. Roufs, Editor. 1991, MacMillan: Basingstoke, UK. p. 83-98. 55. Koelega, H.S., Benzodiazepines and vigilance performance: a review. Psychopharmacology (Berl), 1989. 98(2): p. 145-56. 56. Koelega, H.S., Stimulant drugs and vigilance performance: a review. Psychopharmacology (Berl), 1993. 111(1): p. 1-16. 57. Koelega, H.S., Alcohol and vigilance performance: a review. Psychopharmacology (Berl), 1995. 118(3): p. 233-49. 58. Bushnell, P.J., Detection of visual signals by rats:Effects of signal intensity, event rate and task type. Behavioural Processes 1999. 46: p. 141-150. 59. Bushnell, P.J., K.L. Kelly, and K.M. Crofton, Effects of toluene inhalation on detection of auditory signals in rats. Neurotoxicol Teratol, 1994. 16(2): p. 149-60. 60. McGaughy, J. and M. Sarter, Behavioral vigilance in rats: task validation and effects of age, amphetamine, and benzodiazepine receptor ligands. Psychopharmacology (Berl), 1995. 117(3): p. 340-57. 61. Bushnell, P.J., V.A. Benignus, and M.W. Case, Signal detection behavior in humans and rats: a comparison with matched tasks. Behav Processes, 2003. 64(1): p. 121-129. 62. Rezvani, A.H., D.P. Caldwell, and E.D. Levin, Chronic nicotine interactions with clozapine and risperidone and attentional function in rats. Prog Neuropsychopharmacol Biol Psychiatry, 2006. 30(2): p. 190-7. 63. Rezvani, A.H., D.P. Caldwell, and E.D. Levin, Nicotinic-serotonergic drug interactions and attentional performance in rats. Psychopharmacology (Berl), 2005. 179(3): p. 521-8. 64. Rezvani, A.H. and E.D. Levin, Nicotine-alcohol interactions and attentional performance on an operant visual signal detection task in female rats. Pharmacol Biochem Behav, 2003. 76(1): p. 75-83. 65. Rezvani, A.H. and E.D. Levin, Nicotinic-glutamatergic interactions and attentional performance on an operant visual signal detection task in female rats. Eur J Pharmacol, 2003. 465(1-2): p. 83-90.



141

66. Bushnell, P.J., W.M. Oshiro, and B.K. Padnos, Detection of visual signals by rats: effects of chlordiazepoxide and cholinergic and adrenergic drugs on sustained attention. Psychopharmacology (Berl), 1997. 134(3): p. 230-41. 67. McGaughy, J. and M. Sarter, Effects of ovariectomy, 192 IgG-saporin-induced cortical cholinergic deafferentation, and administration of estradiol on sustained attention performance in rats. Behav Neurosci, 1999. 113(6): p. 1216-32. 68. urchi, J., L.A. Holley, and M. Sarter, Effects of nicotinic acetylcholine receptor ligands on behavioral vigilance in rats. Psychopharmacology (Berl), 1995. 118(2): p. 195-205. 69. Rezvani, A.H., P.J. Bushnell, and E.D. Levin, Effects of nicotine and mecamylamine on choice accuracy in an operant visual signal detection task in female rats. Psychopharmacology (Berl), 2002. 164(4): p. 369-75. 70. McGaughy, J., T. Kaiser, and M. Sarter, Behavioral vigilance following infusions of 192 IgG-saporin into the basal forebrain: selectivity of the behavioral impairment and relation to cortical AChE-positive fiber density. Behav Neurosci, 1996. 110(2): p. 247-65. 71. McGaughy, J. and M. Sarter, Sustained attention performance in rats with intracortical infusions of 192 IgG-saporin-induced cortical cholinergic deafferentation: effects of physostigmine and FG 7142. Behav Neurosci, 1998. 112(6): p. 1519-25. 72. Turchi, J. and M. Sarter, Cortical cholinergic inputs mediate processing capacity: effects of 192 IgG-saporin-induced lesions on olfactory span performance. Eur J Neurosci, 2000. 12(12): p. 4505-14. 73. Burk, J.A. and M. Sarter, Dissociation between the attentional functions mediated via basal forebrain cholinergic and GABAergic neurons. Neuroscience, 2001. 105(4): p. 899-909. 74. Turchi, J. and M. Sarter, Antisense oligodeoxynucleotide-induced suppression of basal forebrain NMDA-NR1 subunits selectively impairs visual attentional performance in rats. Eur J Neurosci, 2001. 14(1): p. 103-17. 75. Turchi, J. and M. Sarter, Bidirectional modulation of basal forebrain N-methyl-Daspartate receptor function differentially affects visual attention but not visual discrimination performance. Neuroscience, 2001. 104(2): p. 407-17. 76. Sarter, M., J.P. Bruno, and B. Givens, Attentional functions of cortical cholinergic inputs: what does it mean for learning and memory? Neurobiol Learn Mem, 2003. 80(3): p. 245-56. 77. Sarter, M., et al., Unraveling the attentional functions of cortical cholinergic inputs: interactions between signal-driven and cognitive modulation of signal detection. Brain Res Brain Res Rev, 2005. 48(1): p. 98-111. 78. Sarter, M., et al., Forebrain dopaminergic-cholinergic interactions, attentional effort, psychostimulant addiction and schizophrenia. Exs, 2006. 98: p. 65-86. 79. Bushnell, P.J., et al., A dosimetric analysis of the acute behavioral effects of inhaled toluene in rats. Toxicol Sci, 2007. 99(1): p. 181-9. 80. Oshiro, W.M., Q.T. Krantz, and P.J. Bushnell, Characterizing tolerance to trichloroethylene (TCE): effects of repeated inhalation of TCE on performance of a signal detection task in rats. Neurotoxicol Teratol, 2001. 23(6): p. 617-28. 81. Bushnell, P.J., Concentration-time relationships for the effects of inhaled trichloroethylene on signal detection behavior in rats. Fundam Appl Toxicol, 1997. 36(1): p. 30-8. 82. Samsam, T.E., D.L. Hunter, and P.J. Bushnell, Effects of chronic dietary and repeated acute exposure to chlorpyrifos on learning and sustained attention in rats. Toxicol Sci, 2005. 87(2): p. 460-8. 83. Bushnell, P.J., et al., Neurobehavioral assessments of rats perinatally exposed to a commercial mixture of polychlorinated biphenyls. Toxicol Sci, 2002. 68(1): p. 109-20.


142


84. Geller, A.M., et al., Gender-dependent behavioral and sensory effects of a commercial mixture of polychlorinated biphenyls (Aroclor 1254) in rats. Toxicol Sci, 2001. 59(2): p. 268-77. 85. Burk, J.A., Introduction of a retention interval in a sustained attention task in rats: effects of a visual distracter and increasing the inter-trial interval. Behav Processes, 2004. 67(3): p. 521-31. 86. Martin, L.A., D. Goldowitz, and G. Mittleman, Sustained attention in the mouse: a study of the relationship with the cerebellum. Behav Neurosci, 2006. 120(2): p. 477-81. 87. Davenport, J., Combined autoshaping-operant (AO) training: CS-UCS interval effects in the rat. Bulletin of Psychonomic Sciences 1974. 3: p. 383-385. 88. Bushnell, P.J., Behavioral effects of acute p-xylene inhalation in rats: autoshaping, motor activity, and reversal learning. Neurotoxicol Teratol, 1988. 10(6): p. 569-77. 89. Fleschler, M. and H. Hoffman, A progression for generating variable-interval schedules. Journal of the Experimental Analysis of Behavior, 1963. 5: p. 529-530. 90. Grier, J.B., Nonparametric indexes for sensitivity and bias: computing formulas. Psychol Bull, 1971. 75(6): p. 424-9. 91. Green, D. and J. Swets, Signal Detection Theory and Psychophysics. 1974, Huntington, NY: R.E. Krieger Publishing. 92. Frey, P. and J. Colliver, Sensitivity and responsivity measures for discrimination learning. Learning and Motivation, 1973. 4: p. 327-342. 93. Milner, B., Effects of different brain lesions on card sorting. Archives of Neurology, 1963. 9: p. 90-99. 94. Robbins, T.W., et al., Cambridge Neuropsychological Test Automated Battery (CANTAB): a factor analytic study of a large sample of normal elderly volunteers. Dementia, 1994. 5(5): p. 266-81. 95. Chudasama, Y. and T.W. Robbins, Functions of frontostriatal systems in cognition: comparative neuropsychopharmacological studies in rats, monkeys and humans. Biol Psychol, 2006. 73(1): p. 19-38. 96. Roberts, A.C., et al., 6-Hydroxydopamine lesions of the prefrontal cortex in monkeys enhance performance on an analog of the Wisconsin Card Sort Test: possible interactions with subcortical dopamine. J Neurosci, 1994. 14(5 Pt 1): p. 2531-44. 97. Birrell, J.M. and V.J. Brown, Medial frontal cortex mediates perceptual attentional set shifting in the rat. J Neurosci, 2000. 20(11): p. 4320-4. 98. Dias, R., T.W. Robbins, and A.C. Roberts, Primate analogue of the Wisconsin Card Sorting Test: effects of excitotoxic lesions of the prefrontal cortex in the marmoset. Behav Neurosci, 1996. 110(5): p. 872-86. 99. Roberts, A.C., T.W. Robbins, and B.J. Everitt, The effects of intradimensional and extradimensional shifts on visual discrimination learning in humans and non-human primates. Q J Exp Psychol B, 1988. 40(4): p. 321-41. 100. Colacicco, G., et al., Attentional set-shifting in mice: modification of a rat paradigm, and evidence for strain-dependent variation. Behav Brain Res, 2002. 132(1): p. 95-102. 101. McAlonan, K. and V.J. Brown, Orbital prefrontal cortex mediates reversal learning and not attentional set shifting in the rat. Behav Brain Res, 2003. 146(1-2): p. 97-103. 102. Rezvani, A.H. and E.D. Levin, Nicotine-antipsychotic drug interactions and attentional performance in female rats. Eur J Pharmacol, 2004. 486(2): p. 175-82.



143

APPENDIX: NAMES AND ADDRESSES OF VENDORS DISCUSSED IN THE TEXT Behavioral Test Systems Campden Instruments Ltd. http://www.campdeninstruments. com/home.htm (Europe) Loughborough LE127XT, England Tel: 0150-981-14790 [email protected] (Worldwide) Lafayette, IN USA Tel: 765-423-1505 [email protected] Coulbourn Instruments, LLC 7462 Penn Drive Allentown, PA 18106 USA Tel: 610-395-3771 www.coulbourninst.com Med Associates Inc. PO Box 319 St. Albans, VT 05478 USA Tel: 802-527-2343 www.med-associates.com Panlab, SL C/ Energia,112 08940 Cornellà (Barcelona), Spain Tel: +34-934-750-697 (Int’l Sales) http://www.panlab.com/ TSE Systems http://www.tse-systems.com/


(USA/Canada/Mexico) TSE Systems, Inc. 784 S. Poseyville Road Midland, MI 48640 USA Tel: 989-698-3067 (Worldwide) TSE Systems GmbH Siemensstr. 21 61352 Bad Homburg, Germany Tel: +49-(0)6172-789-0

Calibration: Audiometric Brüel & Kjær Instruments, Inc. 185 Forest St. Marlborough, MA 10752 USA

Calibration: Photometric EG&G Gamma Scientific 8581 Aero Drive San Diego, CA 92123 USA

Food Pellets Bio-Serv One 8th Street, Suite 1 Frenchtown, NJ 08825 USA www.bio-serv.com P.J. Noyes Company, Inc. PO Box 381 Bridge St. Lancaster, NH 03584 USA

Behavioral 8 The Assessment of Sensorimotor Processes in the Mouse Acoustic Startle, Sensory Gating, Locomotor Activity, Rotarod, and Beam Walking Peter Curzon, Min Zhang, Richard J. Radek, and Gerard B. Fox CONTENTS 8.1 8.2

8.3

Introduction................................................................................................. 146 Acoustic Startle.......................................................................................... 148 8.2.1 Equipment ........................................................................................ 148 8.2.2 Setup and Decibel Confirmation ..................................................... 149 8.2.3 Stimulus Parameters ........................................................................ 149 8.2.4 Testing Location .............................................................................. 149 8.2.5 Subjects ............................................................................................ 149 8.2.6 Acoustic Startle Protocol ................................................................. 150 8.2.7 Startle Habituation........................................................................... 151 Sensory Gating............................................................................................ 152 8.3.1 Prepulse Inhibition........................................................................... 152 8.3.1.1 Statistical Analysis ............................................................. 152 8.3.1.2 Association of PPI and Startle Responses.......................... 153 8.3.1.3 Sample Prepulse Inhibition Experiment ............................ 153 8.3.2 N-40 Sensory Gating ....................................................................... 155 8.3.2.1 Introduction ........................................................................ 155 8.3.2.2 Method ............................................................................... 158 8.3.2.3 Subjects and Surgery.......................................................... 158 8.3.2.4 Recording of Paired Stimulus Sensory Gating Evoked Potentials ............................................................................ 159 145


146


8.3.2.5 Auditory Stimuli................................................................. 160 8.3.2.6 Evoked Potential Analysis.................................................. 161 8.3.2.7 Example Drug Studies with DBA/2 Mice.......................... 161 8.4 Motor Function and Spontaneous Exploration ........................................... 163 8.4.1 Spontaneous Activity....................................................................... 165 8.4.1.1 Open Field (Non-automated).............................................. 165 8.4.1.2 Typical Protocol ................................................................. 165 8.4.1.3 Open Field (Automated)..................................................... 166 8.4.1.4 Typical Protocol ................................................................. 166 8.4.1.5 Variations ........................................................................... 167 8.4.1.6 Sample Experiment ............................................................ 168 8.4.1.7 Motor Function................................................................... 168 8.4.2 Rotarod............................................................................................. 168 8.4.2.1 Typical Protocol ................................................................. 169 8.4.2.2 Variation ............................................................................. 170 8.4.2.3 Sample Experiment ............................................................ 170 8.4.3 Beam Balance/Walking ................................................................... 171 8.4.3.1 Typical Protocol ................................................................. 172 8.4.3.2 Variation ............................................................................. 172 8.4.3.3 Example Experiment.......................................................... 172 References.............................................................................................................. 174 Appendix: Equipment Suppliers ............................................................................ 177

8.1

INTRODUCTION

Assessment of sensorimotor competence is an important part of the evaluation of animal behavior. Measurement of sensorimotor performance is of obvious importance in investigations of sensory or motor processes; however, the effects of experimental manipulations on sensorimotor performance have broader implications for behavioral neuroscience because behavioral experiments typically measure motor responses to sensory information. Thus, the results of behavioral experiments designed to assess other neurobiological processes often cannot be properly interpreted without considering concomitant effects on sensorimotor function. For example, if a lesion or genetic manipulation impairs performance on a spatial memory test, such as the radial arm maze, this impairment cannot be interpreted as evidence of cognitive dysfunction unless it is first established that it is not the result of sensorimotor deficits. Moreover, sensorimotor effects of manipulations can often be used in animal models as surrogates for effects that are more difficult to measure, and relatively simple variations of sensorimotor measures can be used as indices of performance in other behavioral domains, including cognition and emotion. A number of behavioral tasks have been designed to assess sensorimotor performance in rodents, and this chapter focuses on five general procedures—acoustic startle, sensory gating, open field exploration, rotarod, and beam walking. The startle reflex is a stereotyped motor response to a sudden, intense stimulus that has been assessed experimentally in a variety of species, including rats, mice, cats, monkeys, and humans.1,2 In rodents, the startle response is typically evoked


The Behavioral Assessment of Sensorimotor Processes in the Mouse

147

using either acoustic or tactile stimuli and is characterized by contractions of the major muscles of the body, generally leading to extension of the forepaws and hind paws followed by muscle flexion into a hunched position. Mapping studies have demonstrated that the acoustic startle reflex is mediated by a specific neural pathway with acoustic information entering the CNS through auditory nerve input to the cochlear nucleus, which projects to the reticular pontine nucleus via the lateral lemnisus. Motor outputs are generated in the reticular pontine nucleus, which projects to the ventral spinal horn through the reticulospinal tract. Although the basic reflex pathway appears to be relatively simple, the reflex is subject to modulatory influences from higher brain structures.3 Measurement of acoustic startle responses can provide general information regarding sensorimotor processing, but measurement of the reflex under conditions that engage the influence of higher brain centers provides an even richer source of data. For example, presentation of lower intensity acoustic stimuli immediately prior to the acoustic startle stimulus attenuates the response to the startle stimulus. This phenomenon, called prepulse inhibition (PPI) of startle reflex, is regulated by forebrain neural circuits and is considered an operational measure of sensorimotor gating, a filtering mechanism to prevent information flooding in the brain so that attentional recourses can be selectively allocated to salient stimuli.4,5 The normally functioning brain has endogenous mechanisms that filter out the multitude of irrelevant sensory stimuli from those of importance. Sensory gating is a term given to this filtering mechanism and can be measured. A sensory gating deficit, or the lack of an ability to inhibit responding to the test stimulus, is used as a clinical measure of schizophrenia.6–9 The two methods of sensory gating described in this chapter, PPI and N-40 gating, both measure the transmission of auditory sensory information to the nervous system. For PPI the observable and measured response is based on the motor output (startle) following a loud acoustic stimulus. Inhibition of the response to this stimulus is observed if the stimulus is preceded very shortly (10–500 msec) by a prepulse stimulus to which the organism normally does not respond. PPI is defined as reduction of a response to a stimulus. In contrast, the N-40 response is a measure of electrical brain activity to repeated auditory stimuli. Although more involved, there are several advantages to measuring sensory gating using electrophysiological recordings. First, afferent neuronal activity largely contributes to sensory gating evoked potential (EP) response, while afferent, efferent, and neuromuscular activity contribute to the PPI response. Therefore, recording EPs allows for the study of sensory information processing without the influence of descending motor responding as in PPI. Secondly, although the hippocampus and cortex are most frequently recorded, electrophysiological techniques allow the study of the inhibitory processes in different brain regions.10 Pharmacological manipulations and strains of mice yield sensory deficits reminiscent of those seen in schizophrenic patients. For example, the pro-psychotic amphetamine produces N-40 sensory gating deficits in rodents and P-50 deficits in humans.11,12 As another example, the F7 nicotinic receptor subtype, is thought to be deficient in schizophrenia, and decreased hippocampal F7 receptor levels in DBA/2 mice are thought to account for the N-40 sensory gating deficits expressed in this strain.13 Also, as in schizophrenic patients and PPI procedures in rodents, atypi-


148


cal antipsychotics reverse sensory gating deficits in both PPI and N-40 in DBA/2 mice.14,15 Thus, sensory gating measures show considerable parallels across species and have good rodent–human translation. Other sensory gating deficit models have been reported, but the use of the DBA/2 mouse is described herein as representative of an approach to study the nicotinic-acetylcholine system and sensory gating.

8.2

ACOUSTIC STARTLE

8.2.1

EQUIPMENT

The equipment used to measure the startle response has varied from simple labmade devices16,17 to more sophisticated units available from various commercial suppliers. We have used the SR-LAB Startle Response System (San Diego Instruments, San Diego, California, USA) and Kinder Scientific Startle Monitor (SM 100 version 4.1, Poway, California, USA). In addition, acoustic startle equipment can also be obtained from Coulbourn Instruments. The ability to deliver stimuli for 5–1000 msec with consistent intensity is important. Each device is typically enclosed in a larger soundproof cubicle that isolates the animal in the presence of background noise. This also serves to protect the animals in the immediate vicinity from being exposed to the acoustic startle stimulus. A simpler, cheaper SR-LAB screening system is also available from San Diego Instruments, but it has no enclosure and the animals must obviously be isolated by location from other test animals. The magnitude of the response of an animal depends on the size of the animal, which means that the assessment of the acoustic startle reflex in the mouse requires more sensitive equipment than the assessment of the reflex in the rat. The SR-LAB system and Kinder Scientific Startle Monitor include a separate isolation chamber for each individual startle unit. The outer sound-attenuating chamber is illuminated and ventilated with a small fan that also provides some level of background noise. An acoustic sound source is located in the upper part of this chamber and consists of a loudspeaker that delivers a full spectrum white noise that is computer controlled for duration and decibel level. The startle unit is available in assorted sizes to accommodate mice or rats. With the SR-LAB system, the cylindrical animal enclosure and the enclosure base are installed within the SR-LAB chamber. Each animal enclosure has an attached piezoelectric motion sensor that detects the movement of the animal. The signal from the motion sensor is sent to a computer for digital transformation. The motion sensor supplied by San Diego Instruments has an adjustable potentiometer on the underside. Compared to the SRLAB system, the Kinder Scientific Startle Monitor has some unique features that we liked. The Kinder Scientific equipment animal enclosure is separable from the sensing plate that serves as a motion sensor, allowing for easy cleaning of the animal enclosure without damaging the motion sensor. Also, the SR-LAB system requires calibration to standardize test chambers before each test, whereas calibration is not necessary for each test with the Kinder Scientific Startle Monitor. Furthermore, Kinder Scientific uses direct readings for the magnitude of acoustic stimuli rather than analog levels used by the SR-LAB system that require the use of a sound meter to calculate decibel levels.



8.2.2

149

SETUP AND DECIBEL CONFIRMATION

The initial setup of the equipment is fairly simple and the experimental programming is easily accomplished by following the manual provided. Measuring the decibel levels in each enclosure prior to commencing experiments is recommended. A RadioShack (Allied Electronics) Sound Level Meter #33-2050 set on slow response (“A” weighting) is a simple and inexpensive device for measuring the intensity of the acoustic stimuli. Kinder Scientific sells a device with a sensor connected via a cord to the decibel meter, making it convenient to read the sound level outside the closed chamber. The startle unit sound duration must be set long enough (e.g., 6000 msec) to accurately measure sound level, and the sound meter should be placed in the position normally occupied by the animal holder. If isolation chambers are used, calibration should be done with all of the chamber doors closed to reduce the likelihood that sound from the other chambers will influence the reading made in the chamber being calibrated.

8.2.3

STIMULUS PARAMETERS

Startle responses can be measured over a period of time up to 1 sec after the presentation of the startle stimulus. However, since the startle response is typically over within 100 msec of stimulus presentation, the window should be set to include only movements generated within the first 200 msec following the startle stimulus. When analyzing data, use the maximal voltage generated during this 200-msec period; however, it is also possible to use average voltage across the entire response window if desired. For mice, stimuli with intensities of 90 dB or higher will typically produce startle responses, although there is some strain-dependent variability.18 The magnitude of the startle response varies as a function of the intensity of the startle stimulus, so more reliable responses are often obtained at higher intensities. Acoustic stimuli intensities should not be set higher than 120 dB to avoid producing damage to the ear and the loudspeakers.

8.2.4

TESTING LOCATION

Animals are brought to a convenient holding area near the room containing the startle chambers for acclimation. Thus, the startle equipment is best located within an inner room with a heavy door. This provides additional sound attenuation and keeps animals held in the vicinity of the testing room from being exposed to the startle stimulus.

8.2.5

SUBJECTS

Among the mouse strains used, the DBA/2J (Jackson Laboratories, USA) mice, 11–17 g, exhibit a naturally occurring low PPI and thus provide a window to detect a PPI enhancing effect (See Figure 8.1).19,20 One caveat concerning the DBA/2J mice is mice older than 8 wk have hearing loss and thus only young DBA/2J mice are used. Also used are CD1 and C57BL/6 mice, 28–40 g, for PPI or startle habituation studies. The animals are housed eight per cage (reflecting the number of test chambers


150

Methods of Behavior Analysis in Neuroscience, Second Edition 70 CD1 mice 60

C57BL/6

% PPI

50

DBA/2J

40 30 20 10 0 70 dB

75 dB Prepulses

80 dB

FIGURE 8.1 The effect of 70, 75, and 80 dB prepulse on prepulse inhibition (PPI) displayed by CD1, C57BL/6, and DBA/2J mice. Shown are mean ± SEM. Note that increasing the intensity of the prepulse levels increases PPI. Kinder Scientific Startle Monitor was used. N = 8–12 per group. Source: Author’s unpublished data.

employed) with water and food available ad libitum. Aggressive dominant males should be removed from holding cages before commencement of any experiment. Best results are often obtained from animals that have been protected from stressors and have been habituated to the laboratory/animal quarters for at least 7 days.

8.2.6

ACOUSTIC STARTLE PROTOCOL

After placing the animal in the test chambers allow a 5-min adaptation period before the start of the session. Background white noise (65 dB) is present during this adaptation period and throughout the session. The session starts with four 120 dB, 40 msec sound bursts. These are not included in the analysis because the responses to the first few startle bursts generally differ in magnitude from the rest of the trials. Thus, exposure to these initial bursts allows for the establishment of a stable baseline. Following this, acoustic startle trials are initiated. For simple assessment of acoustic startle responses, use two or three stimulus intensities (90 and 105 dB or 90, 105, and 120 dB). The stimuli are 40 msec in duration and are presented in a quasi random order so that an equal number of presentations of each stimulus intensity is included in each half of the session, and no single intensity is presented more than two times in succession. The time between stimuli averages 15 sec but this interval should be varied within a range of 5–30 sec so that the animals do not anticipate the stimulus. At least 10 trials at each stimulus intensity should be used to obtain reliable results. An alternative to evaluating the magnitude of the startle response is to measure the startle threshold. Here, a wider range of stimulus intensities, e.g., from 70 to 120 dB, is used. Stimuli are presented in quasi-random order, and the lowest intensity producing a reliable response is determined. Since some habituation of the



151

response can occur both within a session and between sessions (see below), trials at each intensity should always be evenly distributed within a session (but they should not, of course, be presented in a predictable sequence).

8.2.7

STARTLE HABITUATION

This measure is of interest in the area of schizophrenia research, since schizophrenics show impaired startle habituation, an impairment that may be related to the hypervigilance characteristic of this condition.21,22 For startle habituation, a single stimulus intensity is repeatedly presented using either a fixed or variable interval. Responses normally decline (habituate) over trials. An example of the data generated in such an experiment is shown in Figure 8.2. In this case, each session is initiated with a 10-min acclimation period followed by 121 successive 120 dB, 40 msec trials separated by a fixed inter-trial interval (ITI) of 10 sec. The first trial is excluded from analysis due to variability. Each block has 20 trials. Two groups of CD1 mice received ip injection of water and MK-801 at 0.3 mg/kg, respectively, 15 min before the test. As shown in the figure, startle habituation is displayed by the water-treated group but not by the MK-801-treated group. Longterm habituation of the startle response can also be used as a memory index by conducting a second session at a later time (e.g., 24 hr later) and assessing longterm retention of habituation.

Startle Response to s120 1.6 1.5

VEH

1.4

MK-801 0.3

Newtons (± SE M)

1.3 1.2 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0

1

2

3 Blocks

4

5

6

FIGURE 8.2 An example of startle habituation in two groups of CD1 mice treated with water and MK-801 at 0.3 mg/kg, respectively. The study was carried out in Kinder Scientific Startle Monitor equipment. Shown are mean ± SEM. The study showed that MK-801 treatment impaired startle habituation. N = 9–12 per group. Source: Author’s unpublished data.


152


8.3

SENSORY GATING

8.3.1

PREPULSE INHIBITION

In this version of the test, the attenuation produced by a low intensity stimulus presented just before the startle stimulus is assessed. We sometimes assess PPI on the day following standard startle testing. This serves to habituate the animals to the basic handling procedures and, in the case of pharmacological studies of PPI, allows groups to be matched for baseline startle, as well as elimination of animals that either startle excessively or do not respond. The animals are given a 5-min acclimation period in the startle chambers during which a 65-dB background noise is presented. This background noise remains throughout the entire test. Following the 5-min acclimation period, four successive trials of 40-msec noise bursts at 120 dB are presented. These trials are not included in data analysis. Subjects are then exposed to five different types of acoustic stimuli in a randomized order: pulse alone (120-dB noise for 40 msec), no stimulus (no stimulus is presented), and three separate prepulse + pulse combinations, with prepulse set at three sound levels of 70, 75, and 80 dB for 20 msec followed by a 40-msec pulse at 120 dB. There are 100 msec between the prepulse and the pulse. A total number of 12 trials under each acoustic stimulus condition are presented with average 20-sec variable intervals ranging from 5 sec to 25 sec. The inclusion of four pulse-alone trials in the beginning of the experiments is to help normalize the response of the mice, as there is rapid habituation to the startle responses seen within the first few trials. More than one level of prepulse intensity is used, whereas a “no stimulus” trial is used to assess the influence of background movement on startle measures. To reduce variability, at least 12 trials of each type should be conducted within a single session. As with standard startle testing, trial types and ITIs should be presented in a quasirandom, balanced manner with equal representations of trial types and intervals in each half of the session. This allows the session to be analyzed in two blocks to assess any changes over time. 8.3.1.1 Statistical Analysis The results can either be printed out or, more practically, assembled in a computer text file. Microsoft Excel or similar spreadsheet software easily assemble the data into the various trial types. Percent PPI is calculated as follows: [1 − (startle response to prepulse + pulse) ÷ (startle response to pulse alone)] × 100. If there is a drug treatment involved using naïve rodents, data are typically analyzed with two-way analysis of variance (ANOVA), with the drug treatment as a between-subjects variable and prepulse level as a repeated measure. If a significant treatment effect and interaction of treatment and prepulse are identified, percent PPI is then analyzed by post-hoc comparisons to compare group means at each prepulse level. If a significant treatment effect is identified without the presence of significant interaction of treatment and prepulse, percent PPI can be collapsed across prepulse levels and analyzed by post-hoc comparisons for treatment difference. Use of a post-



153

hoc test such as Fisher’s post-hoc PLSD and Dunnett’s test in order to compare the groups treated with vehicle and the groups treated with drug should be decided a priori. To evaluate drug effects on the response to the startle (s120) alone, a separate one-way ANOVA, followed by post-hoc comparisons if there is a significant treatment effect, is calculated. Programs such as JMP statistics software package (SAS Institute, Cary, North Carolina, USA) or Graph Pad Prism (Graph Pad Software, San Diego, California, USA) are useful for statistical analysis. 8.3.1.2 Association of PPI and Startle Responses Substantial effects of an experimental treatment, resulting in an increase or decrease of the startle response (s120), may confound the effects on PPI. However, there is no agreement upon how PPI and startle responses are correlated. A reduced startle response could be accompanied by a PPI reduction, PPI enhancement, or no change of PPI dependent upon the drug treatment. Our previous studies show that antipsychotics enhance PPI responding while substantially decreasing startle responses (Figure 8.3).20 To address the question whether the PPI-enhancing effects observed with antipsychotics is secondary to their effects on startle response,20 we pooled data of vehicle and 1 mg/kg risperidone-treated mice from studies using risperidone as positive control. We then sorted the data by startle responses in ascending values. In order to obtain equal startle magnitude in the vehicle and risperidone groups, the pairs of individuals with risperidone and vehicle treatment listed next to each other were kept for further analysis. In cases where there were two possible pairs (e.g., if there was a sequence of vehicle-risperidone-vehicle, risperidone could be paired with the first vehicle and the second vehicle), the pair that had the smaller startle difference between vehicle- and risperidone-treated mice was chosen. This selection resulted in n = 19 in water- and risperidone-treated groups, respectively. The remaining mice were excluded. One-way ANOVA revealed (Figure 8.4) that there was a significant difference (p < 0.01) in percent PPI between risperidone- and water-treated mice when their mean values of startle magnitude were equal, suggesting that the effects on PPI responding can be independent of the effects on startle magnitude. A study investigating basal acoustic startle responses and PPI among several inbred mouse strains showed there was no correlation between the magnitude of basal acoustic startle responses and PPI,23, suggesting that different physiological processes are involved in basal acoustic startle and PPI of startle reflex. These observations support the notion that different neurobiological processes may underlie gating processes and the startle reflex. 8.3.1.3 Sample Prepulse Inhibition Experiment An experiment was conducted to evaluate the effects of BP 897, a preferential dopamine D3 receptor antagonist, on PPI.20 In pharmacological experiments, it is often important to conduct the maximum number of trials in the shortest possible time because of pharmacokinetic considerations with many test compounds. Session duration will obviously increase as more trial types/numbers are added, and this was taken into account when we set up our standard rodent testing paradigm. Please see section 8.3.1, “Prepulse Inhibition,” for details of the paradigm. The sequence of


Methods of Behavior Analysis in Neuroscience, Second Edition Haloperidol 0.6

55 50 45 40 35 30 25 20 15 10 5 0

**

*

**

0.5

Startle to s120

% PPI

154

0.4 0.3 0.2 0.1 0.0

0

0.3 1 3 (Treatment mg/kg IP)

0

0.3 1 3 (Treatment mg/kg IP)

0

0.1 0.3 1 (Treatment mg/kg IP)

55 50 45 40 35 30 25 20 15 10 5 0

**

Risperidone 0.6 ** 0.5

Startle to s120

% PPI

(a)

0.4 0.3 0.2 0.1 0.0

0

0.1 0.3 1 (Treatment mg/kg IP) (b)

FIGURE 8.3 Effects of the antipsychotics, haloperidol and risperidone on prepulse inhibition (PPI) in DBA/2J mice. The effects on PPI and startle responses are presented on the left and the right side of the panels, respectively. Haloperidol (a) and respiridone (b), N = 9–10 per group, significantly increased PPI at all of the doses tested while eliciting a nonsignificant reduction of startle response to pulse alone. Shown are mean ± SEM. *p < 0.05 and **p < 0.01, compared to vehicle-treated alone group. Source: Data reproduced with permission from Zhang, M., et al. 2006. Effect of dopamine D3 antagonists on PPI in DBA/2J mice or PPI deficit induced by neonatal hippocampal lesions in rats. Neuropsychopharmacology 31(7):1382–92. 2006.

trials is illustrated in Table 8.1. The 68-trial session used ran for approximately 25 min. In this experiment, DBA/2J mice (11–13 per group) were used. Included in the study was a positive control group in order to be certain that the experiment ran as expected. In this study, risperidone at 1 mg/kg was used as a positive control. Both BP 897 and risperidone were dissolved in 1 N HCL and then titrated to a final pH of 5 with 1 N NaOH. Both of the compounds were given ip in a volume of 10 mL/kg 30 min before the test. The results, which were analyzed using a two-way ANOVA with treatment as a between-subjects variable and prepulse as a repeated measure, revealed a significant main effect of treatment on percent PPI [F(5, 66) = 2.936, p < 0.05] in the absence of significant interaction of treatment and prepulse; the data was collapsed across the three prepulses and the average percent PPI values of the three


55 50 45 40 35 30 25 20 15 10 5 0

155

Risperidone (re-analysis of the pooled data) 0.6 ** 0.5

Startle to s120

% PPI


0 1 (Treatment mg/kg IP)

0.4 0.3 0.2 0.1 0.0

0 1 (Treatment mg/kg IP)

FIGURE 8.4 All of the data of vehicle- and 1-mg/kg-risperidone-treated DBA mice from several mouse studies were pooled and then the startle magnitude of vehicle- and risperidone-treated individuals were matched (for details, see section 8.3.1, “Prepulse Inhibition”) to compare the effect of vehicle and risperidone on percent prepulse inhibition (PPI) when the startle magnitude was equal. This selection resulted in N = 19 in water- and risperidonetreated groups, respectively. One-way ANOVA revealed a significant difference (p < 0.01) between risperidone- and water-treated mice when their mean values of startle magnitude were equal, suggesting that the effects on PPI responding can be independent of the effects on startle magnitude. Shown are mean ± SEM. Hamilton Kinder Startle Monitor was used. Source: Data reproduced with permission from Zhang, M., et al. 2006. Effect of dopamine D3 antagonists on PPI in DBA/2J mice or PPI deficit induced by neonatal hippocampal lesions in rats. Neuropsychopharmacology 31(7):1382–92. 2006.

prepulses were analyzed with Fisher’s PLSD to compare the vehicle-treated group to each of the drug-treated groups. As shown in Figure 8.5, the positive control, risperidone, significantly increased PPI (p < 0.05), suggesting the study was valid. The test compound, BP 897, also significantly enhanced PPI at 8 mg/kg (p < 0.05). Startle response to s120 was analyzed with a one-way ANOVA with treatment as a betweensubject variable. A significant main effect of treatment on startle was identified [F(5, 66) = 5.575, p < 0.01]. The follow-up Fisher’s PLSD showed that risperidone, but not BP 897, significantly reduced startle response to s120. As previously mentioned, DBA/2J mice have a lower PPI response compared to other mouse strains and thus would provide enough of a window for seeing a PPI-enhancing effect following a drug treatment. We also use other mouse strains such as CD1 mice in studies to investigate PPI deficits. Pharmacological disruption of PPI in mice can also be obtained with compounds that influence dopaminergic (e.g., apomorphine, amphetamine), glutaminergic (e.g., phencyclidine, MK-801), muscarinic cholinergic (e.g., scopolamine), and serotoninergic (e.g., 2,5. dimethoxy4-iodoamphetamine) neurotransmission.15

8.3.2

N-40 SENSORY GATING

8.3.2.1 Introduction Evoked potentials are synchronous discharges of neuronal circuits or populations that are time locked to a sensory stimulus. Sensorimotor gating can be measured by


156


TABLE 8.1 Session Protocol for Prepulse Inhibition Experiment Trial #

Trial Type (dB)

ITI (msec)

Trial #

Trial Type

ITI (msec)

1

Pulse alone 120

10

35

Prepulse 70

20

2

Pulse alone 120

15

36

Prepulse 75

5

3

Pulse alone 120

20

37

No-stimulus

15

4

Pulse alone 120

15

38

Pulse alone 120

25

5

Prepulse 70

5

39

Prepulse 80

15

6

Prepulse 75

20

40

Prepulse 75

20

7

No-stimulus

15

41

Prepulse 70

20

8

Pulse alone 120

5

42

Pulse alone 120

10

9

Prepulse 80

5

43

Prepulse 80

20

10

Prepulse 75

10

44

Prepulse 75

15

11

Prepulse 70

10

45

No-stimulus

20

12

Pulse alone 120

15

46

Pulse alone 120

15

13

Prepulse 80

5

47

Prepulse 80

20

14

Prepulse 75

5

48

Prepulse 70

20

15

No-stimulus

20

49

No-stimulus

10

16

Pulse alone 120

10

50

Prepulse 75

10

17

Prepulse 80

25

51

Prepulse 80

25

18

Prepulse 70

20

52

Prepulse 70

10

19

No-stimulus

20

53

Pulse alone 120

10

20

Prepulse 75

25

54

No-stimulus

25

21

Prepulse 80

10

55

Prepulse 70

10

22

Prepulse 70

20

56

Prepulse 75

10

23

Pulse alone 120

10

57

Prepulse 80

15

24

Prepulse 75

10

58

No-stimulus

10

25

Prepulse 70

20

59

Pulse alone 120

25

26

Prepulse 80

15

60

Prepulse 70

5

27

Prepulse 70

20

61

Prepulse 80

10

28

No-stimulus

15

62

No-stimulus

15

29

Pulse alone 120

25

63

Pulse alone 120

5

30

No-stimulus

15

64

Prepulse 75

5

31

Prepulse 80

15

65

Pulse alone 120

25

32

No-stimulus

5

66

Pulse alone 120

10

33

Pulse alone 120

10

67

Pulse alone 120

5

34

Prepulse 75

15

68

Pulse alone 120

20

a

ITI, inter-trial interval, the delay (in sec) prior to the initiation of the trial bEach prepulse trial consists of a 20 msec prepulse stimulus and a 40 msec, 120 dB startle stimulus (separated by 100 msec); each pulse alone trial consists of a 40 msec presentation of the 120 dB startle stimulus by itself.



50 *

% PPI

40 30 20 10 0

1

2

4

8

*

Startle Response to Pulse Alone

BP 897

60

0

157

0.8 0.7 0.6 0.5 0.4 0.3 **

0.2 0.1

0 RISP 1 0 Treatment (mg/kg IP)

1

2

4

8

RISP 1

FIGURE 8.5 Prepulse inhibition (PPI)-enhancing effects of BP 897 in DBA/2J mice. BP 897 at 8 mg/kg significantly increased percent PPI without affecting startle response to pulse alone, while the positive control, risperidone, significantly increased PPI and decreased startle response to pulse alone. *p < 0.05 and **p < 0.01, compared to the vehicle group. Shown are mean ± SEM. Hamilton Kinder Startle Monitor was used. N = 11–13 per group. Source: Data reproduced with permission from Zhang, M., et al. 2006. Effect of dopamine D3 antagonists on PPI in DBA/2J mice or PPI deficit induced by neonatal hippocampal lesions in rats. Neuropsychopharmacology 31(7):1382–92. 2006.

recording electroencephalographic (EEG) EP responses to pairs of identical auditory stimuli.9 Each stimulus of a pair in a sensory gating paradigm is given a specific name; the first stimulus of a pair is typically called the conditioning stimulus, or S1, while the second is referred to as the test stimulus, or S2. The terminology used for stimuli in this section will be “condition” and “test.” Ordinarily, the EP elicited by the test stimulus, typically an auditory click or tone, is smaller in amplitude than that evoked by the conditioning stimulus (Figure 8.6). A lowered test response amplitude is widely considered to be indicative of sensory gating or the filtering function of the brain.6,7 A gated EP response to visual stimuli, such as to paired strobe flashes, is not observed in humans; however, cross-modal visual to auditory sensory gating phenomenon have been reported.24–26 The majority of animal sensory gating studies are reported to use auditory stimuli. The component of the human auditory EP that shows this gating response is the P-50 wave, a major positive deflection in the ongoing EEG with a latency of about 50 msec after the stimulus. It is thought that some form of active inhibition of neuronal activity is initiated by the first stimulus, and suppresses neuronal activity thereafter.27,28 Although somewhat controversial, in rodents the major EP component analogous to the human P-50 is thought by some to be the N-40 (negative polarity, 40 msec latency), and is typically suppressed in many strains after presentation of the test stimulus.29,30


158


Condition

Test

N-40

N-40 200 ms

FIGURE 8.6 Example of an auditory evoked potential sensory (inhibitory) gating response from a C3H strain mouse. These electrographic potentials were recorded from the CA3 region of the hippocampus. The condition and test stimuli are separated by a delay of 500 msec. The major negative deflection of the potential is approximately 40 msec after the stimulus, and thus is termed the N-40 wave. The N-40 amplitude in response to the conditioning stimulus is much larger than the test stimulus amplitude, and is thought to reflect the inhibitory processes of sensory filtering.

8.3.2.2 Method The techniques for recording sensory EPs in anesthetized and unanesthetized rodents are well established. Recording freely moving unanesthetized versus anesthetized rats and mice is somewhat more difficult because of movement artifact; however, this approach avoids any possible confounds of the anesthetic in pharmacological studies. The recording techniques described herein are of auditory EPs recorded in the hippocampus from unanesthetized DBA/2 mice, but many of these methods are applicable to recordings in rats and recordings in other areas of the brain. 8.3.2.3 Subjects and Surgery For implantation of EEG recording electrodes, DBA/2 mice (16–20 g, 6–7 wk, Harlan) are anesthetized with a solution of 2.8% ketamine, 0.28% xylazine, 0.05% acepromazine (Sigma Chem. Co.) at 140 mg/kg of ketamine. Other anesthetics produce less satisfactory results in mice in terms of survival. After achieving a stable plane of anesthesia, scalp hair is removed and the skin is cleaned with a standard veterinary disinfectant solution (e.g., povidone iodine). The mouse is placed in a Kopf student stereotaxic frame and a sagittal incision approximately 6 mm long is made along the centerline to expose the bone between lambda and bregma. The bone is dried with a 30% hydrogen peroxide solution, which makes suture landmarks easier to see. Three drill holes (#68 drill bit) are made at medial lateral (ML) 1.0, 1.8, and 2.6 mm from the central suture. All three are located at anterior posterior (AP) −1.8



159

mm from bregma, thus, they are in a plane perpendicular to the central suture. The hole at ML 2.6 and AP −1.8 mm is for the electrode directed at the CA3 region of the hippocampus. The holes at ML 1.0, AP −1.8 mm, and ML 1.8, AP −1.8 mm, are for two electrodes that lie on the surface of the cortex. The depth of the hippocampal electrode tip is dorsal ventral (DV) 1.65–1.70 mm below the surface of the cortex. The depth of the cortical electrodes are dorsal ventral (DV) 0.5 mm from the surface of the skull; a distance that results in the electrode tip being in contact with, but not penetrating, the cortical tissue. The electrodes we use for recording mouse EPs are from Plastics One, Inc., Roanoke, Virginia, USA. They are tripolar stainless steel wires that have an integral mounting pedestal for connecting a tether when recording the EEG. These electrodes are cut to a length that is appropriate for the cortical or subcortical target. After experiments are completed, the accuracy of the electrode placement should be verified histologically (e.g., crystal violet staining) and, if inaccurate, coordinates and electrode length should be adjusted accordingly. Two additional holes are drilled in the contralateral skull for placement of anchoring screws (#00-90, 1/16 in). After the screws are driven into the skull, the tripolar electrode is lowered into the brain with a stereotaxic electrode holder. Before completely inserting the electrodes, a drop of cyanoacrylic glue is placed on the skull underneath the electrode pedestal. The electrodes and pedestal are then completely lowered and the glue is allowed to dry for several minutes. The pedestal is permanently affixed to the skull with dental acrylic. The mice should be allowed to recover for at least four days before conducting experiments. 8.3.2.4 Recording of Paired Stimulus Sensory Gating Evoked Potentials Routine use of this technique requires a dedicated lab space. To minimize the influence of ambient noise, the animals are recorded in plastic shoebox cages within acoustically isolated chambers (Med Associates) that are internally lined with sound-absorbent foam. A mouse previously implanted with indwelling electrodes is connected to a flexible electrical tether and swivel device, also called a commutator, which is mounted to the ceiling of the isolation chamber. The commutator allows the animal to rotate freely without twisting the tether. Commercially available tether and commutator systems from Plastics One, Inc. have at least two channels, and some models have up to 16 channels or more to record multiple brain areas simultaneously. For recording EEGs from one location, two channels will be required; one is the active channel, in our example the hippocampal electrode, and the other is a reference channel, in our example one of the cortical electrodes. We do not use the third electrode of the tripolar configuration. The small microvolt EEG biosignals must be amplified and filtered, thus the commutator is electrically cabled to differential AC amplifiers (Grass Instrument Division, Astro-Med, Inc., West Warwick, Rhode Island, USA). Cortical and subcortical EEGs are typically amplified by a factor of 1000, and band pass filters are set at 1 and 300 Hz. A standard PC with large storage capacity is used in conjunction with acquisition software (e.g., Datawave, Inc., Berthoud, Colorado, USA) that digitizes the EEG signals at 1000 Hz, a sample rate that captures the rapid rise and fall of auditory EP waveforms. Currently, our lab has eight recording chambers that can record two channels of EEG per mouse, thus


160


EEGs from eight mice can be recorded simultaneously. This shortens the amount of time required to record animals in a given day without reducing N size. 8.3.2.5 Auditory Stimuli Sensory gating auditory EPs are generated by presentation of paired white noise bursts (5 msec duration) from a wide-dynamic-range speaker mounted within the recording chamber at a distance of approximately 15–20 cm from the mouse. Tone bursts of 2–3 KHz have also been successfully used. The auditory stimulus can be generated by a computer, or by an external audio generator (e.g., from Med Associates). The first conditioning auditory stimulus is followed 0.5 sec later by an identical auditory test stimulus. The latency between the two stimuli of the pair, or inter-stimulus interval (ISI), is critical. Generally, ISIs of less than 1 sec result in lowered test stimulus EP amplitudes. While an ISI of 0.5 sec produces a consistent suppression of the test EP response in humans and animals, ISIs of greater than 2–3 sec yield similar condition and test stimulus EP amplitudes (Figure 8.7). Thus, gating function, initiated by sensory input, seems to gradually extinguish over time to a point where the brain is reset to a ready-state level of maximal sensitivity to sensory input. The length of time between stimulus pairs, or trials, is 15 sec. ITIs are generally reported to be 10–15 sec, a range that minimizes a potential influence from the previous stimulus pair. Clear and measurable auditory EP responses cannot be obtained from a single stimulus because of variability of the background EEG. We present 120 paired auditory stimuli to subjects and the data acquisition computer averages each EEG trace starting 100 msec before and 900 msec after every conditioning stimulus. This averaging produces prototypical-evoked waveforms (potentials) with peaks at relatively stable latencies after the auditory stimulus. Thirty minutes are required to obtain an average EP using an ITI of 15 sec. Other labs using anesthetized mice report using fewer stimulus repetitions to obtain auditory EPs, probably because of a more stable background EEG under anesthesia. The volume of auditory stimuli is 65 dB, which is about 5 dB above the constant 60 dB background noise of the recording

A. 500 msec ISI, 15 sec ITI

Stim

Stim

B. 2000 msec ISI, 15 sec ITI

50 µV Condition Test

Condition Test 0

100

200

300

msec

400

500

0

100

200

300

400

500

msec

FIGURE 8.7 Condition and test stimulus evoked potential (EP) responses are superimposed. The recording is from the hippocampus of a CD-1 mouse. In A, the 500 msec inter-stimulus interval (ISI) results in an attenuated test stimulus EP amplitude. In B, no attenuation of the test stimulus EP amplitude is seen when the ISI is increased to 2000 msec.



161

chambers. The use of louder intensities has been reported, but this relatively low level yields clear averaged EPs for us without producing a startle response. The acquisition software is set to acquire 1 sec of data starting 100 msec before and ending 900 msec after the initial conditioning stimulus. In addition to recording the EEG EPs, the software triggers the audio generator to synchronize the EP recording with the stimulus. 8.3.2.6 Evoked Potential Analysis The hippocampal auditory EP response is identified as a peak in the ongoing EEG at a latency of 15–25 msec after the stimulus, followed by the peak of opposite polarity at 30–50 msec after the stimulus. The difference in amplitude between these peaks is defined as the N-40 amplitude in microvolts (μV). N-40 amplitude is determined for both the averaged conditioning (CAMP) and test (TAMP) EPs. A sensory gating ratio is calculated by dividing the test amplitude by the conditioning amplitude. This calculation, termed the T:C ratio, is the index by which sensory gating is assessed (Figure 8.8). T:C ratios in schizophrenic patients are often well above 0.4; in other words, TAMP is greater than 40% of CAMP. In anesthetized and unanesthetized DBA/2 mice, T:C ratios usually exceed 0.5, while in other strains such as C3H, T: C ratios often are below 0.4 (Figure 8.8). These findings have led to a considerable use of the DBA/2 mouse strain as a model of sensory gating deficits. On average, we have found that about 10% of DBA/2 mice have control T:C ratios below 0.4. Mice with low T:C ratios are considered to be clinically normal and show little or no response to drugs that improve gating. Thus, animals with control T:C ratios below 0.4 are retrospectively dropped from studies and data analysis. 8.3.2.7 Example Drug Studies with DBA/2 Mice In a typical study, drugs are administered immediately before mice are placed into the isolation chambers and initiation of auditory EP recording. The duration of the recordings can vary, but they last for 30 min in many of our studies. Multiple treatments (e.g., doses), including vehicle control, are administered to each mouse on separate days with at least 48 hr between treatments. So, for example, a three-point dose response with vehicle would require 4 recording days. With a 48-hr washout between days, this study would take 7 days. This within-subjects design allows each mouse to serve as its own control. For drugs with robust effects on sensory gating, such as nicotine, an N size of eight is sufficient to demonstrate a statistically significant effect. However, we routinely use an N size of 12 or more to detect low dose effects, or the effects of weaker drugs. Paired t-tests for two–group or repeated measures ANOVA for multiple-group statistical evaluation are used. For a drug study where only the dose is varied, a one-way ANOVA is used, while for time course or multiple drug studies, a two-way ANOVA is employed. Post-hoc analyses for between-group comparisons are Newman-Keuls for the one-way ANOVA and Boferroni for the twoway ANOVA. As mentioned before, the atypical antipsychotics clozapine and olanzapine improve sensory gating in DBA/2 mice, that is, they lower T:C ratios (Figure 8.9).15 Sensory gating deficits in schizophrenia are hypothesized to be, in part, mediated


162

Methods of Behavior Analysis in Neuroscience, Second Edition DBA mice

C3H mice

Condition

Test

Condition

Test

N40 N40 Condition = 77 µV Amplitude

N40

N40

Test = 72 µV Amplitude

72/77 = T:C ratio 0.93

Condition = 67 µV Amplitude

Test = 31 µV Amplitude

29/69 = T:C ratio 0.42

(a)

0.8 0.7

T:C Ratio

0.6 0.5

**

0.4 0.3 0.2 0.1 0.0

DBA/2

Strain

C3H

(b)

Figure 8.8 Examples of sensory evoked potentials from either DBA/2 or C3H mice. The N-40 amplitude is measured from the positive peak about 20 msec after the stimulus (P20) to the trough of the N-40 wave. In (a), the DBA/2 mouse has a calculated test amplitude:conditioning amplitude (T:C) ratio of 0.93, while the C3H mouse has a T:C ratio of 0.42. The high T:C ratio of the DBA/2 mouse is indicative of a sensory gating deficit. (b) shows average T: C ratios for groups of DBA/2 and C3H mice. The DBA/2 group had significantly higher T:C ratios. **p = 0.0022, t51 = 3.232, unpaired, two-tailed t-test.

by α-7 receptor hypofunction.31 The selective α-7 agonist GTS-21 and the nonselective nicotinic agonist nicotine improve sensory gating in both DBA/2 mice and schizophrenic patients.32–34 Thus, one of the uses of the DBA/2 mouse is to study compounds that may have potential therapeutic effects in schizophrenia. Figure 8.10 shows the effects of the selective α-7 agonist A-582941 on sensory gating T:C ratios



163

0.8

T:C Ratio

0.6

**

0.4 0.2 0.0

0.0

Clozapine mg/kg IP

0.3

FIGURE 8.9 Clozapine significantly lowers T:C ratios in DBA/2 mice. **p = 0.0056, t 9 = 3.622, paired, two-tailed t-test. Source: Author’s unpublished data.

in DBA/2 mice.35 As with GTS-21, A-582941 lowers T:C ratios, an effect consistent with improved sensory gating. Substantial literature exists on the pharmacology of sensory gating using in vivo electrophysiological recordings of auditory EPs. It has been particularly useful in advancing the understanding of the role of brain cholinergic systems in information processing, and the role of cholinergic deficiencies in disease states such as schizophrenia.

8.4

MOTOR FUNCTION AND SPONTANEOUS EXPLORATION

Although many experimenters view locomotor activity as an overly simplistic measure that provides only limited information, alterations in this behavior can reveal important information on potential mechanisms of drug action. Moreover, locomotor activity may influence functional outcome in animal models of CNS injury or disease. For example, many different psychoactive drugs can act at neuronal receptor sites and directly affect motor function. Similarly, brain injury models employed by many researchers can produce subtle or sometimes pronounced alterations in motor behavior. Furthermore, genetically altered animals have become popular in an attempt at unmasking the molecular and cellular correlates of such behaviors as learning and memory in addition to numerous disease states. These animal models, however, are not without their drawbacks, including profound changes in motor function that can confound the interpretation of behavioral results. Therefore, it is important for the neuroscientist to be aware of, and to characterize, these changes carefully. The following examines several methods for assessing motor and exploratory activity in the adult mouse. Locomotor and exploratory behavior may also be influenced by several other factors such as time of day (rodents are nocturnal animals and are therefore significantly more active during periods of darkness); anxiety (animals may be more or less active depending on the situation to which they are exposed); state of wakefulness or arousal (stimulants will tend to increase activity, whereas sedatives will tend to


164

Methods of Behavior Analysis in Neuroscience, Second Edition T:C Ratio

1.0 0.8 0.6

*

0.4 0.2 0.0

0.0

1.0

3.0

A-582941 µmol/kg IP (a) CAMP

100

µV

80 60 40 20 0

0.0

1.0 A-582941 µmol/kg

3.0

(b) TAMP

µV

60 *

40 20 0

0. 0

1. 0 A-582941 µmol/kg (c)

3. 0

FIGURE 8.10 Example of the effects of a selective B7 agonist. In panel (a), A-582941 (3.0 μmol/kg ip) significantly lowers test amplitude:conditioning amplitude (T:C) ratios in DBA/2 mice, one-way repeated measures ANOVA p = 0.0158 F(2,38) = 4.955, *p < 0.05 NewmanKeuls post-hoc test vs. vehicle. Panel (c) shows that the T:C ratio in this instance was lowered by significantly decreasing the amplitude of the test stimulus evoked potential (TAMP), oneway repeated measures ANOVA p = 0.0427 F(2,38) = 3.608, *p < 0.05, Newman-Keuls posthoc test vs. vehicle. The condition stimulus amplitude in panel (b) (CAMP) was unchanged, one-way repeated measures ANOVA p = 0.7516 F(2,38) = 0.289. Source: Data reproduced with permission from Bitner, R. S., Bunnelle, W. H., Anderson, D. J., et al. 2007. Broad-spectrum efficacy across cognitive domains by alpha-7 nicotinic acetylcholine receptor agonism correlates with activation of ERK1/2 and CREB phosphorylation pathways. Journal of Neuroscience, 27:10578–87, 2007.



165

decrease activity, although the magnitude of these effects can often depend upon the strain of animal used); environmental novelty (mice tend to exhibit increased exploratory behavior when exposed to a novel environment and decreased activity upon reexposure to the same environment, i.e., “habituation”); motivation (food-deprived mice may show increased activity); age (younger rodents are more active than aged animals); general health; and genetic strain (C57BL/6 mice are more active than 129-derived animals). All of these factors necessitate careful experimental design and it is therefore prudent to control for these and maintain consistency from the outset. However, natural variations in activity and stress levels often exist between mice of the same strain despite controlling for all of the factors described above, hence the need for adequate group sizes that will accommodate appropriate statistical analyses.

8.4.1

SPONTANEOUS ACTIVITY

8.4.1.1 Open Field (Non-automated) Perhaps the simplest and most economical method for assessing both exploratory and locomotor activity is the open-field apparatus. As the name suggests, this generally consists of a square (or circular, depending on personal preference) arena of adequate size (e.g., 50 × 50 cm or 50 cm diameter for mice) surrounded by walls to prevent the animal from escaping. The box itself may be composed of either wood or plastic, although the latter is preferred to reduce olfactory issues and for ease in cleaning. In its simplest form, the floor is divided into equally spaced regions by marker pen which has been allowed sufficient time to dry so as not to produce unwanted olfactory effects. Alternatively, the box can be video monitored and lines can be drawn on the screen to divide the arena. 8.4.1.2 Typical Protocol 1. The open field should be located in a quiet room with controlled temperature and ventilation. A low-level illumination is preferred to reduce anxiety and thus lessen freezing behaviors, unless this is a component of the task that you wish to study. The observer should be seated comfortably at a distance from the apparatus, or ideally watching a monitor fed by a video camera positioned above the open field. If visible to the behaving rodent, the investigator should be consistent with seating position, clothing, and potential olfactory cues. 2. If stimulant activity of a drug is to be examined, the rodent should first be habituated to the apparatus for three or more 5-min sessions to reduce baseline activity. Habituation should be omitted if anxiety or response to novelty is being studied. For brain lesion or injury studies, you may wish to examine performance at discreet times before and after surgery. Bear in mind, however, that in general, activity and/or exploration following repeated exposure to the open field will decrease with habituation and cognition. 3. On the test day, administer the test drug, if required, at an appropriate time prior to placing the rodent into the center of the open field. The investiga-


166


tor records the following specific behaviors using prepared data sheets and appropriate counters over a specified period of time, usually 5–10 min. Parameters to record: locomotion (number of square crossings within the specified time); rearing; grooming; and stereotypical behaviors such as licking, biting, and head weaving. These activities may be recorded separately for peripheral regions or in the center of the arena, the latter being thought to reflect the degree of anxiety experienced by the rodent (i.e., animals with higher levels of activity in the center of the arena are less anxious). Defecation frequency may also be recorded as a measure of fear, but this tends to be more variable due to the relatively small numbers involved. 8.4.1.3 Open Field (Automated) For large studies it is impractical to directly observe each animal individually. This can be resolved by making use of a set of automated activity boxes consisting of arenas similar to those described above, but with regions demarcated by infrared beams instead of marker pen. Each box is connected individually to a computer that collates all data from up to 30 or more boxes at a time. Equipment available from AccuScan Instruments (formerly Omnitech, Columbus, Ohio, USA; www.accuscanusa.com) offers flexibility in experimental design and data analysis. Although the cost can be somewhat prohibitive for smaller laboratories (upwards of $80,000 for a set of 16 boxes), the major advantage of such systems is that they allow the collection of both vertical (rearing) and horizontal activity from the periphery and center of the apparatus over time periods that could not be accurately completed by a manual observer. For example, the computer can be programmed to accept data every 15 sec and to calculate a mean for each 1 min time bin for up 2 hr or more. Clearly the amount of data collected rises considerably with increased time. In our laboratories, a system of 16 boxes is employed (AccuScan Instruments) in a dedicated quiet room with dimmed lighting. Each arena is 40 × 40 cm in size with removable clear Plexiglas chambers for ease of cleaning. Two sets of infrared photocells (one for detecting rearing, the other for locomotion), are fixed to a rack that surrounds the Plexiglas and that can be adjusted in the vertical plane to allow measurements from rats or mice. 8.4.1.4 Typical Protocol 1. If a stimulant drug-induced increase in activity is expected, habituate the mice to the apparatus for several 1-hr sessions. Do not habituate for drugs expected to decrease activity. 2. Program the computer to record activity as desired. An example would be to bin data every 5 min for up to 1 hr and to distinguish horizontal activity from vertical in both the peripheral and central regions of each arena. 3. Administer test drug at the appropriate time. If decreased activity is expected, inject before placing mice into the center of the arena. Conversely, if increased activity is expected, place mice into the center of the arenas and allow for habituation to the novel environment for at least 30 min before drug administration. If animals are subjected to brain injury or



167

other surgery, allow sufficient time for recovery (at least 24 hr, if not more, depending on severity) before placement into the arenas. 4. Record data for a predetermined period of time, usually 30–120 min. Print out all raw data as a hard copy backup and convert the data file produced into a form suitable for analysis using software programs such as Microsoft Excel (Microsoft Corporation, Seattle, Washington, USA; www.microsoft.com) and JUMP (SAS Institute, Cary, North Carolina, USA; www.sas.com). Arenas employed by more advanced systems (AccuScan Instruments; www.accuscan-usa.com) can be subdivided into zones both physically by using a Plexiglas insert and virtually by specifying different software parameters. This allows many additional animals to be assessed simultaneously. In addition, this system can allow measurements of distance traveled, movement time, rearing duration, etc. If the additional cost of such systems is prohibitive, but something more sophisticated than the manual version of the open field apparatus is desired, other equipment options are available. Software for video tracking systems that identify images in contrast to the background and track a center point for movement, and which have been used for tracking in water mazes, are available for multiple chambers for analysis. These can produce measures of distance and orientation over time, although rearing activity may have to be recorded separately. In addition, there are more sophisticated video systems that track the directionality of the animal and other behaviors such as weaving and stereotypy. Therefore, if cost is an important factor, the investigator should determine whether existing equipment could be easily modified to measure motor activity. In addition, some photocell systems have been designed to measure activity in the home cage, where response to a novel environment is undesirable, or for monitoring over the light-dark cycle. Such systems tend to come in specially designed cages, and racks and can be expensive. However, there is now a very competitive market for analyzing locomotor activity, and this has led to a reduction in the price of systems, allowing a small lab to tailor equipment according to need. A list of vendors is included at the end of the chapter. 8.4.1.5 Variations Locomotor activity can also provide indices of learning and memory and anxiety. Habituation of locomotor activity in a novel environment can be used to assess memory in mice.36 For this procedure, the mouse is briefly exposed (e.g., 5 min) to a novel open field and locomotor activity is assessed. Memory for the novel experience is then tested at a later time by reexposing the mouse to the same open field. Activity during the second exposure is used as an index for assessing memory, with lower activity being indicative of better memory for the open field. Of course, it is important that the treatments evaluated with this method do not have direct effects on locomotor behavior. One way to minimize the effects of the drug is to treat immediately following the first activity session. The pattern of exploration can also be an important index of anxiety. Informal assessment of anxiety can be derived by comparing time spent in the periphery of the arena relative to time spent in the center. Anxious animals tend to spend more


168


time in the periphery. In addition, initial freezing in an open field is an index of anxiety, so the latency to move a given distance (or to move through a given number of squares) can also be used to assess fear and anxiety. A more formal assessment of anxiety can be made using a modified open-field apparatus. The open field is separated into a well-lit area and a dark area and the relative time and activity in these two zones is compared. Anxiolytics increase the time spent in the well-lit zone in this light–dark test.37 8.4.1.6 Sample Experiment Data from a typical automated experiment are presented in Figure 8.11. In this study, vertical (or rearing) (Figure 8.11A) and horizontal (Figure 8.11B) activity was assessed for three mouse strains, with data collected in 5-min bins for 30 min.38 Note that BALB/c mice appear significantly less active than animals from the other strains. Note also the habituation response indicated by decreased activity over time for most groups. It is important that appropriate statistical methods be used for analysis of behavioral data. Locomotor data are generally normally distributed so parametric ANOVAs are used routinely. A repeated measures ANOVA should be considered in most cases when a time course is employed. Post-hoc tests that examine the mean square error relative to the overall analysis (e.g., Tukey’s) can then be used for multiple comparisons between groups. Individual t-tests should not be used unless they are corrected for multiple comparisons. For the data presented in Figure 8.11B, a repeated measures ANOVA yielded a significant group effect [F(2,26) = 4.382, p < 0.0229], indicating overall differences between the strains in the study; time effect [F(5,130) = 126.103, p < 0.0001], reflecting the decreased activity with time (habituation) overall; and group × time interaction [F(10,130) = 3.049, p < 0.0017], indicating significant differences between groups over time. Post-hoc analysis with Tukey’s pairwise comparisons detected significant differences for the 5-, 10-, 15-, and 30min time points between C57BL/6 and BALB/c mice (p < 0.01). 8.4.1.7 Motor Function Motor function can be differentially affected depending on experimental parameters. For example, unilateral brain injury models often produce hemiparesis-like effects, which may be reflected by deficits in grip strength, balance, and turning behavior, or may induce forepaw flexion. Many drugs can have either sedative or stimulant properties. Consequently, several models have been developed to examine specific motor deficits such as these. Two commonly used procedures are thus described.

8.4.2

ROTAROD

The ability of a rodent to maintain balance and keep pace with a rotating rod has been used with varying degrees of success over the years to assess motor function. Several versions of this test (commonly referred to as the rotarod test) have been described over the years. Most require the mouse to walk on a rotating rod of fixed diameter (3.5 cm for the apparatus we use) that increases in speed over a predetermined period of time until the animal can no longer maintain its position. The



169

Mean no. Beam Breaks

110 100

C57BL/6 CD-1 BALB/c

90 80 70 60 50 40 30

5

10

15 20 Time (min) (a)

25

30

Mean no. Beam Breaks

800 700

C57BL/6 CD-1 BALB/c

600 500 400 300 200 100

5

10

15 20 Time (min) (b)

25

30

FIGURE 8.11 Automated measure of vertical (a) and horizontal (b) activity in the same animals from three different mouse strains. Data were collected over 5-min intervals for a total of 30 min. Most mice habituated to the test environment, as evidenced by the decline in activity over the duration of the experiment. Note that BALB/c mice were less active than mice from the other two strains. (Statistical significance described in detail in main text.) Source: Author’s unpublished data.

rotarod apparatus employed in our laboratories consists of a central drive rod connected to a stepper motor (AccuScan Instruments) that is divided into four separate testing stations. The speed at which the rod rotates can be accelerated up from 0 rpm to over 100 rpm over a set time period. Other rotarod models are available and can be found in the vendor list at the end of the chapter. 8.4.2.1 Typical Protocol 1. Administer drug, as appropriate. For lesioned or injured animals, wait at least 24 hr following the surgical procedure. 2. Set the apparatus to accelerate from 0–40 rpm over 60 sec. This is a good standard for young adult mice, although it should be noted that juvenile and older animals perform poorly at this task.


170


3. Place four mice on the rotarod, one per testing station, and then start the stepper motor and timer. Many models come equipped with a timer that begins automatically when the motor is switched on and stops when the animal falls down to the floor of the apparatus, as detected by interruption of an infrared beam. 4. As the speed increases, the mouse is required to walk faster to remain in a stationary position. The latency to fall from the rotating rod is determined and taken as a measure of motor function. It is generally a good idea to take the mean of at least two to three measures from each animal. 8.4.2.2 Variation Some investigators39,40 modify the rod itself by enclosing the core of the rod with a series of stainless steel bars of a specific diameter (Figure 8.12A). In this instance the time either to fall (Figure 8.12B) or to cling and make two full rotations is recorded as the outcome measure. This design may offer some advantages over the more traditional, relatively smooth rod in that data, particularly in brain injury studies, may be more consistent within groups. With rodent strains that exhibit a poor baseline performance in this task, it is usually beneficial to pre-train these animals at least two to three times before commencing the study proper. 8.4.2.3 Sample Experiment Data from a typical experiment are presented in Figure 8.12C, where the effect of sham surgery and controlled cortical impact (CCI) brain injury on time spent on the rotating rod is shown for three mouse strains. Sham operated controls exhibited a stable performance over the 4 wk of testing, whereas a decrease in time spent on the rotarod device was observed in injured mice from all strains for up to 7 days following injury. Because of these pronounced deficits, it would be unwise to conduct cognitive experiments with a significant motor component (e.g., Morris water maze) during this time period. Once again a repeated measures ANOVA is appropriate for comparing groups over time as rotarod data tends to be normally distributed and this test was conducted repeatedly over a 4-wk period in this study. A significant group effect [F(5,57) = 16.601, p < 0.0001], indicating overall differences between the strains in the study; time effect [F(7,399) = 47.183, p < 0.0001], reflecting the attenuation of the deficits with time in the injured groups; and group × time interaction [F(35,399) = 6.480, p < 0.0001], indicating significant differences between groups over time, were observed. Using a post-hoc test (Tukey’s pairwise comparison), a significant impairment was detected among CCI injured mice from all three strains when compared with their respective surgery controls on days 1, 2, and 3 (p < 0.05) following surgery. A one-way ANOVA would be suitable for comparing these groups if no time component was involved. A t-test may also be appropriate in such instances. No significant difference was observed between strains for either treatment group.



171

(b)

(a) 42

Time on Rotarod (sec)

40 38 36

*

34

*

32

*

30

CCI 129/SvEMS CCI C57 CCI FVB/N

28 26

0

1

Sham 129/SvEMS Sham C57 Sham FVB/N

2

3 7 Days Post-Surgery (c)

14

21

28

FIGURE 8.12. The effect of moderate controlled cortical impact (CCI) brain injury on rotarod performance. As the device gradually ramped up to speed (35 rpm), the mouse was required to walk faster to maintain a stationary position on the rod, which has been modified here to include a series of stainless steel bars (a). When the mouse can no longer keep up with the speed of rotation, it either falls from the bars (b) or clings tight and begins to rotate with the rod (not shown). Uninjured or sham-operated mice are generally adept at this task. However, a significant deficit can be seen for approximately 7 days following CCI brain injury, shown for three different mouse strains in (c). Photos depict an adult male C57BL/6 mouse.

8.4.3

BEAM BALANCE/WALKING

While the rotarod is useful for determining gross motor deficits in the rodent, the detection of more subtle motor effects requires a different approach. Fine motor


172


coordination, for example, can be assessed using a beam walking or balance task. This test essentially examines the ability of the animal to remain upright and to walk on an elevated and relatively narrow beam (Figure 8.13A) without falling to the cushioned pads below or slipping to one side of the beam. Again, unilateral brain injury models tend to induce a hemiparesis-like effect, which can cause the rodent to slip to one side, usually contralateral to the injury site (Figure 8.13B). 8.4.3.1 Typical Protocol 1. For mice, set up a beam approximately 0.6 cm wide and 120 cm in length, suspended about 60 cm above some foam pads. (A larger beam, approximately 1.8 cm wide and 240 cm in length, in addition to a flat platform at one end to rest between trials is required for rats.) 2. Place the animal on one end of the beam (for the rat this would be farthest from the platform). Animals from active strains such as the C57BL/6 mouse or the Long-Evans rat will instinctively walk along the beam to reach the opposite end. Once at this point they will generally turn 180° and continue to walk on to the opposite end. Establish a basal level of performance before surgery or treatment, and allow sufficient time for recovery (at least 24 hr) before retesting. 3. Count the number of foot faults, defined as the number of times the forepaws and/or hindpaws slip from the horizontal surface of the beam over a predetermined number of steps (50 is usually adequate). Allow the performing animal sufficient time (approximately 5 min) to complete this task. (It is useful to use a mirror on the side of the beam opposite the observer and to videotape the performance for scoring.) 4. Remove to home cage and retest as appropriate. It should be noted that rodents, especially rats, tire and are reluctant to move if exposed to this test repeatedly over a short period on the same day. 8.4.3.2 Variation This task works well for active rodent strains and may not be suitable for less active animals. Another variation partly designed to address this issue in the rat involves training animals to walk across the beam to a “safe” dark box; the cognitive requirements for this version, however, may influence motor outcome to some degree so care should be taken here. A simpler approach measures the time taken to fall down onto the foam pads. In this instance, the investigator should vary the beam width until an acceptable latency is found for the particular strain to be used. Attention should also be paid to the body weight of the animal, as the suitable width of the beam may change according to the mouse’s ability to grip the edge of the beam, for example, mice heavier than 35 g generally require a beam approximately 0.9-cm thick. 8.4.3.3 Example Experiment Data from a typical experiment are reproduced in Figure 8.13C. In this experiment, adult C57BL/6 mice were subjected to mild (4.5 m/s) or moderate (6.0 m/s) unilateral



173

(a)

Mean Number Footfaults

(b) 50

CCI 6.0 m/s

40 30

CCI 4.5 m/s

20 10 0

Sham 0

1

2 3 7 14 Days Post-surgery (c)

21

28

FIGURE 8.13 The effect of moderate controlled cortical impact (CCI) brain injury on beam walking performance for the C57BL/6 mouse. Surgery-naive or sham-operated mice perform well on this task, traversing the beam several times, gripping its horizontal edge with the innermost digits (arrow in (a) illustrates this point). Foot faults, defined as forelimb and/or hind limb slipping from the horizontal surface of the beam, (arrow in (b) shows contralateral hind limb slipping down the side of the beam) are generally counted over a total of 50 steps; a foot fault frequency of 15% or less is normal for control mice from this strain (c). However, mice subjected to mild (low velocity, 4.5 m/s) or moderate (higher velocity, 6.0 m/s) unilateral CCI brain injury exhibit a highly significant deficit (statistical significance described in detail in main text) in this task, which is dependent on injury severity and persists for an extended period (c). Source: Data reproduced with permission from Fox, G. B., et al. 1998. Sustained sensory/motor and cognitive deficits with neuronal apoptosis following controlled cortical impact brain injury in the mouse. J. Neurotrauma 15(8):599–614.


174


CCI brain injury, and the number of contralateral hind limb foot faults were recorded over a 4-wk period. An obvious deficit, dependent on injury severity, was observed when compared with sham-operated controls. For statistical analysis, beam-walking data are generally normally distributed so parametric ANOVAs are advised. A repeated measures ANOVA should be considered in most cases when a time course such as that presented above is employed. Post-hoc tests that examine the mean square error relative to the overall analysis (e.g., Tukey’s) can then be used for multiple comparisons between groups. Individual t-tests should not be used. For the data presented in Figure 8.13C, a repeated measures ANOVA yielded a significant group effect [F(2,33) = 94.265, p < 0.0001], indicating overall differences between the different treatment groups in the study; time effect [F(7,231) = 89.383, p < 0.0001], indicating significant overall changes in performance over the duration of the study; and group × day interaction [F(14,231) = 20.995, p < 0.0001], indicating significant performance differences between groups over time. Post-hoc analysis with Tukey’s pairwise comparisons detected significant differences for days 1–28 between sham controls and CCI-injured mice from both groups (p < 0.001). There were no significant differences between groups before injury (day 0; p > 0.05).

REFERENCES 1. Davis, M. 1980. Neurochemical modulation of sensory-motor reactivity: Acoustic and tactile startle reflexes. Neurosci. Biobehav. Rev. 4(2):241–63. 2. Davis, M. 1984. The mamalian startle response. In Neural mechanisms of startle behavior, ed. R.C. Eaton, 287–351. New York: Plenum Press. 3. Koch, M., and Schnitzler, H. U. 1997. The acoustic startle response in rats—circuits mediating evocation, inhibition and potentiation. Behav. Brain Res. 89(1–2):35–49. 4. Braff, D. L., et al., 2001. Impact of prepulse characteristics on the detection of sensorimotor gating deficits in schizophrenia. Schizophr. Res. 49(1–2):71–8. 5. Swerdlow, N. R. 1996. Cortico-striatal substrates of cognitive, motor and sensory gating: Speculations and implications for psychological function and dysfunction. In Advances in biological psychiatry, Vol. 2, ed. Panksepp, J. Greenwich, CT: JAI Press. 6. Alder, L. E., et al. 1982. Neurophysiological evidence for a defect in neuronal mechanisms involved in sensory gating in schizophrenia. Biological Psychiatry 17(6):639–54. 7. Boutros, N. N., Zouridakis, G., and Overall, J. 1991. Replication and extension of P50 findings in schizophrenia. Clinical EEG (electroencephalography) 22(1):40–45. 8. Freedman, R., Alder, L. E., Myles-Worsley, M., et al., 1996. Inhibitory gating of an evoked response to repeated auditory stimuli in schizophrenic and normal subjects: Human recordings, computer simulation, and an animal model. Archives of General Psychiatry 53(12):1114–1121. 9. Freedman, R., Alder, L. E., Waldo, M. C., Pachtman, E., and Franks, R. D., 1983. Neurophysiological evidence for a defect in inhibitory pathways in schizophrenia: Comparison of medicated and drug-free patients. Biological Psychiatry 18(5):537–551. 10. Bickford, P. C., Luntz, L. V., and Freedman, R. 1993. Auditory sensory gating in the rat hippocampus: Modulation by brainstem activity. Brain Research 607(1-2):33–38. 11. Adler, L. E., Rose, G., and Freedman, R. 1986. Neurophysiological studies of sensory gating in rats: Effects of amphetamine, phencyclidine, and haloperidol. Biological Psychiatry 21(8–9):787–798. 12. Light, G. A., Malaspina, D., Geyer, M. A., et al., 1999. Amphetamine disrupts P50 suppression in normal subjects. Biological Psychiatry 46(7):990–996.



175

13. Stevens, K. E., Freedman, R., Collins, A. C., et al. 1996. Genetic correlation of inhibitory gating of hippocampal auditory evoked response and alpha-bungarotoxin-binding nicotinic cholinergic receptors in inbred mouse strains. Neuropsychopharmacology: 15(2):152–162. 14. Light, G. A., Geyer, M. A., Clementz, B. A., Cadenhead, K. S., and Bratt, D. L. 2000. Normal P50 suppression in schizophrenia patients treated with atypical antipsychotic medications. The American Journal of Psychiatry 157(5):767–771. 15. Simosky, J. K., Stevens, K.E., and Freedman, R. 2002. Nicotinic agonists and psychosis: Current drug targets. CNS and Neurological Disorders 1(2):149–162. 16. Hunter, K. P., and Willott, J. F. 1993. Effects of bilateral lesions of auditory cortex in mice on the acoustic startle response. Physiology & Behavior 54(6):1133–39. 17. Weiss, G. T., and Davis, M. 1976. Automated system for acquisition and reduction of startle response data. Pharmacol. Biochem. Behav. 4(6):713–20. 18. Crawley, J. N., et al., 1997. Behavioral phenotypes of inbred mouse strains: Implications and recommendations for molecular studies. Psychopharmacology (Berl.) 132(2):107–24. 19. Olivier, B., et al., 2001. The DBA/2J strain and prepulse inhibition of startle: A model system to test antipsychotics? Psychopharmacology (Berl.) 156(2–3):284–90. 20. Zhang, M., et al., 2006. Effect of dopamine D3 antagonists on PPI in DBA/2J mice or PPI deficit induced by neonatal ventral hippocampal lesions in rats. Neuropsychopharmacology 31(7):1382–92. 21. Geyer, M. A., and Braff, D. L. 1987. Startle habituation and sensorimotor gating in schizophrenia and related animal models. Schizophr. Bull. 13(4):643–68. 22. Geyer, M. A., et al., 1990. Startle response models of sensorimotor gating and habituation deficits in schizophrenia. Brain Res. Bull. 25(3):48598. 23. Paylor, R., and Crawley, J. N. 1997. Inbred strain differences in prepulse inhibition of the mouse startle response. Psychopharmacology (Berl.) 132(2):169–80. 24. Adler, L. E., Waldo, M. C., and Freedman, R. 1985. Neurophysiologic studies of sensory gating in schizophrenia: Comparison of auditory and visual responses. Biological Psychiatry 20(12):1284–1296. 25. Jin, Y., and Potkin, S. G. 1996. P50 changes with visual interference in normal subjects: A sensory distraction model for schizophrenia. Clinical EEG (electroencephalography) 27(3):151–154. 26. Lebib, R., Papo, D., de Bodes, S., and Bandonnière, P. M. 2003. Evidence of a visualto-auditory cross-modal sensory gating phenomenon as reflected by the human P50 event-related brain potential modulation. Neuroscience Letters 341(3):185–188. 27. Moxon, K. A., Gerhart, G. A., Brickford, P. C., et al. 1999. Multiple single units and population responses during inhibitory gating of hippocampal auditory response in freely-moving rats. Brain Research 825(1–2):75–85. 28. Moxon, K. A., Gerhart, G. A., Gwinetto, M., and Alder, L. E. 2003. Inhibitory control of sensory gating in a computer model of the CA3 region of the hippocampus. Biological Cybernetics 88(4):247. 29. Ellenbroek, B. A. 2004. Pre-attentive processing and schizophrenia: Animal studies. Psychopharmacology 174(1):65–74. 30. Miyazato, H., et al., 1995. A middle-latency auditory-evoked potential in the rat. Brain Research Bulletin 37(3):247–255. 31. Martin, L. F., Freedman, R., and Anissa AbiDargham, G., and Olivier. 2007. Schizophrenia and the 7 Nicotinic Acetylcholine Receptor. International review of neurobiology. ed. 78:225–246. 32. Alder, L. E., et al., 1993. Normalization of auditory physiology by cigarette smoking in schizophrenic patients. American Journal of Psychiatry 150:185–61.


176


33. Olincy, A., Harris, J. G., Johnson, L. L. et al., 2006. Proof-of-concept trial of and 7 nicotinic agonist in schizophrenia. Arch. Gen. Psychiatry 63(6):630–638. 34. Stevens, K. E., and Wear, K. D. 1997. Normalizing effects of nicotine and a novel nicotinic agonist on hippocampal auditory gating in two animal models. Pharmacology Biochemistry and Behavior 57(4):869–874. 35. Bitner, R. S., Bunnelle, W. H., Anderson, D. J., et al. 2007. Broad-spectrum efficacy across cognitive domains by alpha-7 nicotinic acetylcholine receptor agonism correlates with activation of ERK1/2 and CREB phosphorylation pathways. Journal of Neuroscience 27(39):10578–10587. 36. Platel, A., and Porsolt, R. D. 1982. Habituation of exploratory activity in mice: A screening test for memory enhancing drugs. Psychopharmacology (Berl.) 78(4): 346–52. 37. Costall, B., et al., 1988. Actions of buspirone in a putative model of anxiety in the mouse. J. Pharm. Pharmacol. 40(7):494–500. 38. Fox, G. B., LeVasseur, R. A., and Faden, A. I. 1999. Behavioral responses of C57BL/6, FVB/N, and 129/SvEMS mouse strains to traumatic brain injury: Implications for gene targeting approaches to neurotrauma. J. Neurotrauma 16(5): 377–89. 39. Fox, G. B., et al. 1998. Sustained sensory/motor and cognitive deficits with neuronal apoptosis following controlled cortical impact brain injury in the mouse. J. Neurotrauma 15(8):599–614. 40. Hamm, R. J., et al. 1994. The rotarod test: An evaluation of its effectiveness in assessing motor deficits following traumatic brain injury. J. Neurotrauma 11(2):187–96.



177

APPENDIX: EQUIPMENT SUPPLIERS AccuScan Instruments, Inc. 5098 Trabue Road Columbus, OH 43228 USA Tel: 614-878-6644; 800-822-1344 (USA/Canada) Fax: 866-650-8265 E-mail: [email protected]

Columbus Instruments 950 N. Hague Avenue Columbus, OH 43204 USA Tel: 614-276-0861; 800-669-5011 Fax: 614-276-0529 Email: [email protected]

Coulbourn Instruments 7462 Penn Drive Allentown, PA 18106 USA Tel: 610-395-3771 E-mail: [email protected]

Kinder Scientific Michael Kinder, President 12655 Danielson Court, Suite 308 Poway, CA 92064 USA Tel: 858-679-1515 Fax: 858-679-4811 E-mail: [email protected]

Clever Sys., Inc. 11425 Isaac Newton Square, Suite 202 Reston, VA 20190 USA Tel: 703-787-6946 Fax: 703-757-7467 www.cleversysinc.com

Noldus Information Technology, Inc. 1503 Edwards Ferry Road, Suite 201 Leesburg, VA 20176 USA Tel: 703-771-0440; 800-355-9541 Fax: 703-771-0441 E-mail: [email protected]

Source: Data reproduced with permission from Fox, G. B., LeVasseur, R. A., and Faden, A. I. 1999. Behavioral responses of C57BL/6, FVB/N, and 129/SvEMS mouse strains to traumatic brain injury: Implications for gene targeting approaches to neurotrauma. J. Neurotrauma 16(5): 377–89.


Drug 9 Intravenous Self-Administration in Nonhuman Primates Leonard L. Howell and William E. Fantegrossi CONTENTS 9.1 9.2 9.3

Introduction................................................................................................. 179 Surgical Procedures .................................................................................... 180 Schedules of Reinforcement........................................................................ 181 9.3.1 Initial Training................................................................................. 181 9.3.2 Fixed-Ratio Schedules ..................................................................... 182 9.3.3 Fixed-Interval Schedules ................................................................. 182 9.3.4 Second-Order Schedules.................................................................. 183 9.3.5 Progressive-Ratio Schedules............................................................ 183 9.4 Research Application and Data Interpretation............................................ 184 9.5 Discussion ................................................................................................... 191 References.............................................................................................................. 194

9.1

INTRODUCTION

The abuse of psychoactive drugs such as cocaine and heroin has spanned several decades and continues to be widespread in the United States. Currently, research efforts have focused on the development of therapeutics to treat drug abuse. Drug self-administration studies have done much to help us understand the behavioral and pharmacological mechanisms underlying drug abuse. An understanding of these mechanisms will in turn aid in the development of effective therapeutic agents. Important to the study of drug effects on behavior is the understanding that drugs can function as stimuli to control behavior.1 Based on the principles of operant conditioning, presentation of a stimulus as a consequence of behavior may either increase or decrease the probability that a behavior will occur again.2 If the presentation of a stimulus increases the probability that a behavior will recur, then that stimulus is defined as a positive reinforcer.2 Stimuli such as food and water function as positive reinforcers, and data from self-administration studies indicate that most drugs of abuse, most notably psychostimulants and opioids, can also function as positive reinforcers under the appropriate schedule contingencies. Drug self-administration procedures in animals have been used extensively to evaluate the reinforcing effects of drugs. The first studies examining the reinforcing effects of drugs in the 179


180


1950s and 1960s focused on morphine self-administration in morphine-dependent animals.3,4 Later studies demonstrated that dependence was not necessary to initiate self-administration.5,6 Since these early studies, self-administration procedures have been used as a model of drug taking that can be studied under controlled laboratory conditions and applied to human drug use. Drug self-administration studies in animals have contributed substantially to our knowledge of the neuropharmacological mechanisms controlling drug abuse. For example, studies with opioids have shown that drugs with high affinity for μ-opioid receptors function as positive reinforcers,7,8 whereas opioids with high affinity for P-opioid receptors generally do not.8,9 Additionally, the self-administration of psychomotor stimulants and opioids has been found to be affected by the administration of antagonists either systemically or centrally (cf.10,11). If administration of an antagonist shifts the dose-response function for a self-administered drug to the right, then it can be assumed that the site of action of the antagonist is important for the reinforcing effects of the drug.12–15 In addition to the administration of antagonists, self-administration of drugs has been affected by lesions of certain brain neurotransmitter systems (cf.10,11). Studies have also found that animals will self-administer drugs directly into certain brain areas, suggesting a neuropharmacological mechanism for their reinforcing effects (cf.10). Over the years, drug self-administration procedures in animals have been found to be valid and reliable for determining the abuse liability of drugs in humans. It is well established that animals will self-administer most drugs that are abused by humans.16,17 In particular, studies in nonhuman primates have made a significant contribution to the field of drug abuse research. Nonhuman primates are ideal subjects since they are phylogenetically more closely related to humans than are other species.18 Potential species differences in drug metabolism also illustrate the importance of nonhuman primate models in substance abuse research. Thus, we can apply information obtained from nonhuman primates to problems of human drug abuse with greater accuracy. This chapter discusses methods of self-administration in nonhuman primates, including different preparations and schedules of drug reinforcement. While the focus is primarily on self-administration of psychoactive stimulants such as cocaine, the methodology and general principles apply to other pharmacological classes including opiates, benzodiazepines, and alcohol.

9.2

SURGICAL PROCEDURES

Protocols for intravenous drug self-administration require the surgical implantation of a chronic intravenous catheter to permit infusion of the drug solution. Typically, a superficial vessel, such as the external jugular or femoral vein, is accessed via a surgical cut-down procedure.19 Using appropriate anesthesia, either inhaled anesthetics (e.g., isoflurane) or injected ketamine in combination with a benzodiazepine, and under aseptic conditions, one end of a catheter is implanted into the vessel while the other end is routed subcutaneously to a point of access. If the distal end of the catheter is externalized, an appropriate jacket is used to prevent the animal from damaging the preparation,20 and the catheter is sealed with a stainless-steel obturator when not in use. An alternative means of access involves the attachment of the


Intravenous Drug Self-Administration in Nonhuman Primates

181

distal end of the catheter subcutaneously to a vascular access port.21 A Huber needle designed to minimize insult to the skin or port membrane is inserted perpendicular to the port to allow for injection of drug solution. Lastly, a tethering system can be used to protect the catheter while providing convenient access.5,22 The preparation requires continuous housing in an experimental chamber, and restraint by a harness and a spring arm attached to the top or back of the chamber. However, movement of the animal within the chamber is not restricted by the tethering system. The distal end of the catheter is routed subcutaneously to exit between the monkey’s scapulae, and is threaded through the spring arm. For each of the preparations, the catheter is connected via plastic tubing to a motor-driven syringe located outside the test chamber during experimental sessions. At least twice weekly, catheters are flushed with sterile saline or water, and filled with heparinized saline (100 units of heparin per mL of saline). All solutions that come in contact with the catheter are prepared with sterile components and stored in sterile glassware.

9.3

SCHEDULES OF REINFORCEMENT

9.3.1

INITIAL TRAINING

Drug self-administration involves operant behavior that is reinforced and maintained by drug delivery. Animals acquire drug injections by emitting a discrete response, such as pressing a lever or key. The number and pattern of responses required for each injection are defined by the schedule of reinforcement. Availability of drug under a given schedule typically is signaled by an environmental stimulus, such as the illumination of a stimulus light located proximal to the response lever. Schedule parameters and stimulus conditions are controlled by computers, while responses emitted by the animal are recorded simultaneously. The primary dependent measures are number of drug injections and rate of responding during each session. As with behavior maintained by nondrug reinforcers such as food, responding maintained by drug injections is determined by the schedule parameters and the behavioral history of the animal. Daily experimental sessions are conducted in the home cage or in a standard primate chair either custom designed22 or commercially available.24,25 If a primate chair is used, location of the chair within a ventilated, sound-attenuating chamber will minimize distractions and interference from daily laboratory activities. Typically, responding is initiated using a 1-response, fixed-ratio schedule so that each response in the presence of a stimulus light will result in the intravenous injection of a drug solution. The drug dose is determined by the concentration and volume of solution, and should be sufficient to maintain reliable drug self-administration in a well-trained animal. The saliency of the drug injection is enhanced by a change in the stimulus lights during the injection period. It is critical to avoid excessive drug intake and toxicity during training sessions. Drug intake can be limited by scheduled timeout periods following each injection, during which stimulus lights are extinguished and responding has no scheduled consequence. Defined limits on the number of injections per session are also recommended. Once the animal has acquired the lever press response and behavior is reliably maintained by drug


182


injections, the response requirement can be gradually increased under a variety of intermittent schedules of reinforcement.

9.3.2

FIXED-RATIO SCHEDULES

The most basic schedule of reinforcement is the fixed-ratio (FR) schedule, which defines the number of responses required per drug injection. Once responding on the lever is engendered, the response requirement is gradually increased to the terminal value. Nonhuman primates rapidly acquire drug self-administration behavior under FR schedules, and stable daily performances can be obtained in several weeks. FR schedules typically generate high response rates and a “break and run” pattern of responding characterized by a brief pause in responding after each drug injection, followed by an abrupt change to a steady high rate of responding until the next FR is completed. It is important to note that total session intake of drug is a direct function of response rate under FR schedules. Typically, higher unit doses are required to maintain behavior at higher FR values. Drug intake can be limited by scheduling timeouts following each injection and by restricting the total number of drug injections per session. The duration of the timeout value following each injection can also have significant effects on behavior.

9.3.3

FIXED-INTERVAL SCHEDULES

In contrast to FR schedules, fixed-interval (FI) schedules are time based and specify a minimal inter-injection interval. They represent a suitable alternative to FR schedules because they engender high levels of behavioral output. Typically, a stimulus light is illuminated in the test chamber during the FI to serve as a discriminative stimulus. Once the FI has elapsed, a single response is required for drug delivery. A limited hold can be imposed following the FI to restrict the time period during which a response is reinforced, resulting in higher rates of responding. Temporal control over behavior is enhanced if a timeout is scheduled following each injection. Once responding on the lever is engendered at a very short FI (1–5 sec), the interval is gradually increased to the terminal value. In contrast to the “break and run” pattern engendered by FR schedules, FI schedules engender a “scalloped” pattern of responding characterized by little or no responding early in the interval and increased rates of responding as the interval elapses. Nonhuman primates often require several months of training before a stable pattern of responding develops. Also, response rate can vary markedly with little or no change in the total number of injections per session. It is important to emphasize that quantitative aspects of selfadministration are dictated by the schedule of reinforcement. For example, nicotine maintained i.v. self-administration under an FR schedule in rhesus monkeys, but at response rates much lower than those maintained by cocaine.26 In contrast, nicotine maintained i.v. self-administration in squirrel monkeys under an FI schedule with peak response rates much more similar to those maintained by cocaine. Hence, the apparent strength of nicotine to maintain behavior was markedly influenced by the schedule of reinforcement.



9.3.4

183

SECOND-ORDER SCHEDULES

Environmental stimuli that are paired with reinforcement can substitute for the reinforcer itself through Pavlovian conditioning. Moreover, these conditioned stimuli can reinforce behavior that results in their presentation through the process of second-order conditioning.27 When a stimulus light that has been paired with drug injection is presented following an operant response, the frequency of that response increases.28,29 Second-order schedules involve a contingency arrangement under which a series of responses under a schedule of conditioned reinforcement is treated as a unit response under a second schedule that is simultaneously in effect. Second-order schedules of drug self-administration can generate very high behavioral outputs for a single injection of drug. If the stimuli are presented early in the drug-taking history of the animal, they can also enhance the acquisition of drug self-administration. In a typical example of a second-order schedule, responding is initiated using a 1-response FR schedule so that each response in the presence of a stimulus light (e.g., red) will produce an intravenous drug injection and the brief illumination of a different stimulus light (e.g., white), followed by a timeout. The ratio value is gradually increased as responding increases. When the schedule value reaches a terminal value, drug injection no longer follows completion of each FR and, instead, is arranged to follow an increasing number of FR components during a predetermined interval of time. As the interval duration is extended during training, a greater number of FR components will be completed per drug injection. Ultimately, the terminal schedule will arrange for drug injection following the first FR component completed after the FI has elapsed. Drug administration is accompanied by a change in the stimulus light (e.g., from red to white), followed by a timeout. The drug-paired stimulus light is also presented briefly upon completion of each FR component. Daily sessions can consist of several consecutive FIs depending on the interval and session duration. By using this second-order procedure and limiting the daily session to approximately 1 hr, any direct effects the self-administered drug might have on rate and pattern of responding will be absent during the first component and minimized during the experimental session. Hence, performance measures can be related directly to the reinforcing effects of the drug. Cumulative records typical of performance engendered by a second-order FI schedule with FR components nicely illustrate that introducing an imbedded schedule of conditioned reinforcement results in much higher and persistent rates of self-administration with the same dose of cocaine and the same FI value.30

9.3.5

PROGRESSIVE-RATIO SCHEDULES

Progressive-ratio self-administration procedures are designed to quantify the reinforcing effects of drugs and to determine their reinforcing strength. Reinforcing strength is often referred to as the maximum reinforcing effect of a drug or other reinforcer.31 Generally, it has been inferred from the strength of the behavior maintained by the drug. In a progressive-ratio procedure, the number of responses required to obtain a reinforcer progressively increases over the duration of the session. Eventually, responding for the reinforcer will cease when the response requirement becomes too great. This point, termed a break point, is a measure of a drug’s



500 Responses

184

15 Minutes

FIGURE 9.1 A cumulative record of lever pressing maintained in a rhesus monkey under a progressive-ratio schedule of cocaine (0.1 mg/kg/injection) self-administration over a daily session. The daily session consisted of five components, each made up of four trials at a particular response requirement. The response requirement began at a fixed ratio (FR) of 120 and doubled in subsequent components (i.e., 120, 240, 480, 960, 1920). A trial ended with a drug injection or the expiration of a limited hold. The session ended if the limited hold expired two consecutive times. Abscissa: time. Ordinate: cumulative number of responses. The response pen reset vertically upon completion of the FR or when the pen reached the top of the paper. Injections are indicated by a deflection of the response pen.

reinforcing efficacy. Under a progressive-ratio schedule, the response requirement can increase either following the delivery of the drug32 or at the beginning of each daily session.33,34 If the response requirement increases following the delivery of the drug, it will be incremented within a daily session, and completion of the response requirement one time will result in the delivery of drug. If the response requirement increases at the beginning of a daily session, it will be fixed over the duration of a daily session. The same response requirement will be in effect for several days (i.e., until stability criteria are met) before progressing to the next response requirement, allowing multiple determinations of self-administration at a particular response requirement. More recent progressive-ratio procedures combine both of these approaches and require that the animal respond a given number of times at a particular response requirement before proceeding to the next response requirement within a daily session.35,36 Thus, these procedures have the advantage of collecting multiple determinations of self-administration at a particular response requirement within a daily session while still allowing the response requirement to be increased within the session. A cumulative record typical of performance engendered by a progressive-ratio schedule is shown in Figure 9.1.

9.4

RESEARCH APPLICATION AND DATA INTERPRETATION

The primary focus of drug self-administration research in nonhuman primates has been to establish the reinforcing properties of drugs of abuse and to identify neu© 2009 by Taylor & Francis Group, LLC


185

rochemical mechanisms underlying drug use. A better understanding of the neurochemical basis of drug self-administration is essential for the development of treatment medications for human drug abusers. The key feature of drug-reinforced behavior is control of behavior by response-contingent drug delivery.37 Hence, drug-reinforced behavior should be distinguished from drug self-administration. A number of control procedures have been described to demonstrate that increases in behavior that result in drug delivery are caused specifically by the reinforcing effects of the drug.6 The most commonly used procedure is to substitute saline for the drug solution and determine whether the behavior undergoes extinction. The rate and pattern of responding maintained by drug delivery depends on a number of variables including the schedule of reinforcement, drug dose, the volume and duration of injection, and the duration of drug self-administration sessions. Drug self-administration studies have consistently obtained an inverted U-shaped dose-effect curve relating the unit dose of drug delivered per injection and response rate or number of injections delivered. The dose-effect function reflects a combination of reinforcing effects and unconditioned stimulus effects such as sedation or marked hyperactivity. Typically, the ascending limb of the dose-effect curve reflects the reinforcing effects, and response rate increases with drug dose. In contrast, the descending limb of the curve reflects a nonspecific disruption of operant behavior as excessive drug accumulates over the session, and response rate decreases with drug dose. It should be noted that the dose-effect curve relating the unit dose of drug delivered per injection and drug intake in mg/kg is typically a monotonic increasing function. Lastly, an inverse relationship has been obtained between infusion duration and reinforcing effects.38,39 The longer the infusion time required to deliver a constant volume of drug solution, the less effectively the drug functions as a reinforcer. However, the latter relationship is typically not observed until the infusion duration is extended to a minute or more. A study by Glowa et al.40 illustrates the use of an FR schedule of drug selfadministration to characterize the effectiveness of a dopamine reuptake inhibitor to alter the reinforcing effects of cocaine in rhesus monkeys. A standard tethered-catheter, home-cage system was used for i.v. drug delivery.5 Animals were trained to selfadminister cocaine under an FR 10 schedule of drug delivery during 90-min daily sessions. Pretreatment with the high-affinity dopamine reuptake inhibitor, GBR 12909, dose-dependently decreased rates of cocaine-maintained responding, and the effect was larger when lower doses of cocaine were used to maintain responding. Moreover, the rate-decreasing effects of GBR 12909 were greater on cocaine-maintained responding than on food-maintained responding under a multiple schedule of drug and food delivery. The results obtained were consistent with previous reports demonstrating that drugs with dopamine agonist effects can decrease cocaine-maintained responding.41,42 This type of drug interaction has been attributed to a satiation of cocaine-maintained responding by pretreatment with a drug having dopaminergic effects. The latter approach to cocaine medication development has been referred to as substitute agonist pharmacotherapy.43 Hence, response-independent delivery of a dopamine reuptake inhibitor may have decreased cocaine self-administration by substituting for the reinforcing effects of response-produced cocaine. This interpretation is supported by studies showing that GBR 12909 will substitute for cocaine as a reinforcer in squirrel monkeys.44–46


186


Note that Glowa et al.40 incorporated several important design features in their self-administration study. First, multiple unit doses of cocaine were self-administered on separate occasions in order to establish a complete dose-effect curve for cocaine. Hence, pretreatment effects of GBR 12909 could be assessed over a broad range of cocaine doses. Second, multiple pretreatment doses of GBR 12909 were administered in order to establish dose-dependency of pretreatment effects and to identify the optimal pretreatment dose that lacked overt behavioral toxicity. Lastly, the specificity of pretreatment effects on cocaine-maintained behavior was assessed by comparing drug effects on food-maintained behavior. The multiple schedule that alternated cocaine and food as maintaining events during separate components was well suited for this application. Moreover, cocaine dose was manipulated to match response rate to that obtained during the food component of the multiple schedule. The finding that GBR 12909 suppressed cocaine-maintained responding at doses that had little or no effect on food-maintained responding under identical schedules and comparable response rates provides convincing evidence that GBR 12909 selectively attenuated the reinforcing effects of cocaine. A study by Woolverton47 provides another example of cocaine self-administration under an FR schedule in rhesus monkeys. The objective was to characterize the effectiveness of dopamine antagonists to alter the reinforcing effects of cocaine. A standard tethered-catheter, home-cage system was used for i.v. drug delivery. Animals were trained to self-administer cocaine under an FR 10 schedule of drug delivery during 2-hr daily sessions. When responding was stable, the animals were pretreated with the D1 antagonist SCH 23390, or the D2 antagonist pimozide. Intermediate doses of pimozide generally increased cocaine self-administration, whereas SCH 23390 either had no effect or decreased cocaine self-administration. High doses of both antagonists decreased the rate of cocaine self-administration, but also produced pronounced catalepsy. Hence, the latter effects could not be attributed to a selective interaction with the reinforcing effects of cocaine. The author concluded that the selective increase in responding maintained by cocaine following pimozide pretreatment suggested a role for the D2-receptor in cocaine self-administration. Strengths of the Woolverton47 study design included multiple unit doses of cocaine and multiple pretreatment doses of both dopamine antagonists. Extinction of cocaine self-administration when saline was substituted for cocaine was also characterized. Note that response rate for cocaine increased following pretreatment with the D2-selective antagonist. The latter effect is interpreted as a behavioral compensation to overcome the attenuation of the reinforcing effects of cocaine by pimozide. Since drug intake is a direct function of response rate under FR schedules, an increase in rate will result in greater session intake of cocaine, which may effectively surmount the dopamine antagonist effects of pimozide. The finding that the pattern of responding following pimozide was virtually identical to that seen in the first session of extinction supports the view that pimozide was attenuating the reinforcing effects of cocaine. However, alternative interpretations were acknowledged, largely because specificity of pretreatment effects on cocaine-maintained behavior was not assessed by comparing drug effects on behavior maintained by nondrug reinforcers. Nader et al.48 used an FI schedule of drug self-administration to characterize the effectiveness of a novel cocaine analog to alter the reinforcing effects of cocaine



187

in rhesus monkeys. A standard tethered-catheter, home-cage system was used for intravenous drug delivery. Animals were trained to self-administer cocaine under an FI 5-min schedule during 4-hr daily sessions. Under this schedule, the first response after 5 min produced a 10-sec cocaine injection. Pretreatment with the high-affinity dopamine reuptake inhibitor 2G-propanoyl-3G-(4-tolyl)-tropane (PTT) dose-dependently decreased rates of cocaine-maintained responding and total session intake of cocaine. The reinforcing effects of PTT were also evaluated in a separate group of animals. When substituted for cocaine, PTT maintained response rates that were similar to those maintained by saline and significantly lower than rates maintained by cocaine. The results demonstrated that a long-acting dopamine reuptake inhibitor could effectively decrease cocaine self-administration in nonhuman primates. Also, failure of PTT to maintain rates of self-administration greater than those obtained during extinction conditions suggested that PTT may have limited abuse liability. The study of Nader et al.48 was consistent with previous findings using dopamine reuptake inhibitors to decrease cocaine self-administration under FR schedules of drug self-administration.37 Hence, a generality of pretreatment effects has been demonstrated across experimental conditions, further supporting a substitute agonist approach to cocaine medication development. Both studies included multiple unit doses of cocaine and multiple pretreatment doses of the dopamine reuptake inhibitors. In addition, assessment of the reinforcing properties of PTT provided critical information concerning the abuse liability of the candidate medication. The fact that PTT did not reliably maintain self-administration behavior, whereas GBR 12909 has been shown to function effectively as a reinforcer in monkeys,44–46 illustrates the potential importance of pharmacokinetic factors in drug self-administration studies. It is possible that low rates of PTT self-administration were a result of its relatively long duration of action at inhibiting dopamine uptake. Hence, its long duration of action compared with cocaine may have required lower session intake to produce cocaine-like reinforcing effects. It should be noted, however, that the rate of onset appears to play a more prominent role in the reinforcing effects of psychostimulants than does duration of action.49–51 Human drug use often involves a ritualized sequence of behaviors that occurs in a specific environment. The environmental stimuli associated with drug use are believed to play a major role in the maintenance of drug-seeking behavior.29 Secondorder schedules of drug self-administration have been used in nonhuman primates to maintain extended sequences of responding between drug injections20,45,46,52 analogous to patterns of drug use in humans. The second-order schedule is well suited for drug-interaction and drug-substitution experiments because response rate increases as a direct function of the unit dose administered at low and intermediate doses (Figure 9.2). Note that high doses of drug can disrupt performance during the latter components of a session as multiple doses accumulate. In drug-interaction experiments, changes in the positioning of the cocaine dose-effect curve leftward or rightward will indicate altered potency of cocaine to function as a reinforcer. A downward shift in the cocaine dose-effect curve will indicate an insurmountable attenuation of cocaine self-administration. In drug-substitution experiments, maximum rates of responding maintained over a range of drug doses can be used to compare reinforcing effectiveness.


188

Methods of Behavior Analysis in Neuroscience, Second Edition 1.00 N =

3

Responses/S econd

0.75

0.50

0.25

0.00 0.03

0.1 0.3 Cocaine (mg/inj ection)

1.0

FIGURE 9.2 Mean (± SEM) rate of responding maintained in a group of three squirrel monkeys under a second-order fixed interval 900-sec schedule of cocaine intravenous selfadministration with fixed ratio 20 components. Data for each dose of cocaine were derived from at least five consecutive sessions on two separate occasions. Abscissae: dose, log scale. Ordinate: mean response rate expressed as responses per second.

A study by Howell et al.53 provides an example of cocaine self-administration under a second-order FI schedule in squirrel monkeys. The objective was to characterize the effectiveness of a phenyltropane analog of cocaine to alter the reinforcing effects of cocaine. The distal end of the catheter was externalized and exited between the scapulae, and a nylon-mesh jacket protected the catheter when not in use. Animals were trained to self-administer cocaine under a second-order FI 15min schedule with FR 20 components during 1-hr daily sessions. Pretreatment with the dopamine reuptake inhibitor RTI-113 significantly decreased rates of cocaine self-administration, and the effect was not surmounted by increasing the unit dose of cocaine (Figure 9.3). The latter findings are consistent with previous studies using dopamine reuptake inhibitors to decrease cocaine self-administration under FR40 and FI48 schedules of drug self-administration. Hence, the generality of pretreatment effects has been demonstrated over a range of experimental conditions and in two different primate species. Note that low doses of RTI-113 actually increased rates of cocaine self-administration at the low unit dose of cocaine, providing evidence of additivity of effects. The latter finding is an important consideration when conducting drug interaction studies with two drugs that have a similar mechanism of action.



Percent Control

350

350

0.1 mg/injection Cocaine

300

300

250

250

200

200

150

150

100

100

50

*

189

0.3 mg/injection Cocaine

50 *

0

0.03 RTI

0.1 113

0.3 (mg/kg)

0

0.03 RTI

0.1 113

0.3 (mg/kg)

FIGURE 9.3 Mean (± SEM) rate of responding in a group of three squirrel monkeys maintained under a second-order fixed interval 900-sec schedule of cocaine (0.1 and 0.3 mg/injection) intravenous self-administration with fixed ratio 20 components. Cocaine was self-administered alone (dashed lines) or following pretreatment with RTI-113 (closed symbols). Subjects were pretreated with each dose of RTI-113 for three consecutive sessions, and each subject received all drug combinations on two separate occasions. Abscissae: dose, log scale. Ordinates: mean response rate expressed as a percentage of control rate obtained when subjects were pretreated with saline. Asterisks indicate a significant (p < 0.05) effect of RTI113 pretreatment.

Similar to other self-administration schedules, the reinforcing potencies of drugs can be determined under progressive-ratio schedules.33,36 For example, cocaine is 10-fold more potent than the local anesthetic procaine under a progressive-ratio procedure.36 However, progressive-ratio procedures are most useful for determining the reinforcing strength of self-administered drugs. Drugs can be rank-ordered based on their relative reinforcing effects as determined by break point in the progressive ratio.33,36 For example, cocaine has been found to maintain higher break-point values than diethylpropion, chlorphentermine, and fenfluramine in baboons.33 More recently, cocaine has been found to maintain higher break-point values than procaine in rhesus monkeys (Figure 9.4).36


190

Methods of Behavior Analysis in Neuroscience, Second Edition Procaine

Cocaine

20

FR 1920

Mean inj/Session

16 12 (4)

8

FR 960 (5)

(3)

(5)

(2)

(5) (5)

(3)

4 0

(5)

(5)

(5)

(3)

FR 480

(3)

FR 240

(5)

Sal 0.01

FR 120 0.1

1.0

10

Dose (mg/kg/inj)

FIGURE 9.4 Break-point values and injections/session maintained by cocaine (closed symbols) and procaine (open symbols) under a progressive-ratio schedule in rhesus monkeys. Data are the mean (± SEM) for the number of monkeys indicated in parentheses above each dose. The daily session consisted of five components, each made up of four trials at a particular response requirement. The response requirement began at a fixed ratio of 120 and doubled in subsequent components (i.e., 120, 240, 480, 960, 1920). Absicssae: dose, log scale. Left ordinate: mean injections/session. Right ordinate: break-point values. Dashed lines represent the mean number of injections/session taken at a particular break-point value.

As mentioned above, break point typically is used as the dependent measure to assess reinforcing effectiveness under a progressive-ratio procedure. However, break-point data violate the assumption of homogeneity of variance necessary for reliable statistical analysis. Variability is greater at high break-point values than at low break-point values, making it difficult to determine effects based on drug dose at high break points.54,55 Therefore, some researchers have applied a data transformation to break-point data before analysis (see Rowlett et al.55). In addition, the number of injections per session has been found to be a reliable measure of reinforcing strength and does not violate the assumption of homogeneity of variance.36,55 With intravenous self-administration paradigms, it is important to consider that effects other than reinforcing effects may influence responding for drug injections when high doses of a drug are available. Downward turns in dose-response curves have been explained by drug accumulation. To address this issue in the progressive ratio, researchers have used a timeout after each injection. The idea is that the timeout will allow the effects of the drug to dissipate before another injection can be obtained. A timeout length of 30 min is effective for studying cocaine in the progressive-ratio procedure.36,55 In addition to progressive-ratio procedures, choice procedures are used to study the reinforcing strength of drugs. The choice paradigm allows animals access to two reinforcers and evaluates the preference of one reinforcer over the other. Typically,



191

animals choose between a food and a drug reinforcer or two drug reinforcers.56,57 Reinforcing strength can be determined based on the preference of one reinforcer over the other. For example, rhesus monkeys given a choice between a high and a low dose of cocaine will prefer the higher cocaine dose.57 A study by Johanson and Aigner58 suggested a difference in the maximum reinforcing effects of cocaine and procaine using a choice procedure. They evaluated the preference for an i.v. injection of cocaine versus an i.v. injection of procaine in rhesus monkeys. At equipotent doses for reinforcing effects, monkeys chose i.v. injections of cocaine more than 80% of the time.52 These results are consistent with those of the Woolverton33 progressive-ratio study mentioned above. Thus, choice paradigms are reliable for studying reinforcing efficacy. Lastly, behavioral economics provides a means to quantify the reinforcing effects of drugs independent of dose.59 Such studies apply microeconomic concepts including consumer demand and labor supply theories to help understand how behavior is maintained by various reinforcers, referred to as “commodities” in economic parlance. Behavioral economic studies use total daily consumption of a commodity, rather than response rate, as the primary indicator of demand for that commodity. In drug self-administration experiments, subjects regulate their consumption by responding to obtain multiple presentations of the commodities of interest. The function generated by assessing consumption across increasing “cost” of a commodity is known as a “demand curve,” and these functions generally reveal that consumption decreases as the cost of a commodity increases. Cost is manipulated by increasing the work requirement—in the simplest case, increasing the FR value required to receive an injection. As the FR value is increased, consumption levels decrease, reflecting the behavioral sensitivity to price. By comparing consumption at a given price, relative to the level of consumption at the lowest price (i.e., at FR 1), one can gauge the “elasticity of demand” of a given commodity.60 Demand is “inelastic” when consumption is defended across large increases in price. In contrast, demand is “elastic” when consumption declines rapidly with increasing price. An example of the relationship between demand and onset of drug action was demonstrated with the drugs fentanil, alfentanil, and remifentanil. All three compounds are full agonists at μ opioid receptors and have immediate onsets of action following i.v. administration, but the durations of action for these compounds differ markedly, with remifentanil having the shortest duration of action and fentanil having the longest duration of action. Despite differences in durations of action, and apparent differences in the absolute rates of responding maintained by these three compounds in self-administration experiments, demand curve analysis suggests that these drugs do not differ in their reinforcing effectiveness.61 Thus, duration of action does not seem to contribute to the reinforcing effectiveness of opioids, or, perhaps, for other drug classes as well.

9.5

DISCUSSION

Nonhuman primate models of drug self-administration provide a rigorous, systematic approach to characterize the reinforcing effects of psychoactive drugs. The longevity of nonhuman primates is an important consideration, allowing for long-term


192


studies to be conducted and repeated-measures designs to be employed. A single venous catheter can be readily maintained for over a year, and multiple implants permit the conduct of self-administration experiments for several years in individual subjects. Long-term studies with repeated measures are well suited for comprehensive drug-interaction experiments. While rodent models of drug self-administration have substantially contributed toward an understanding of neuropharmacology, the nonhuman primate represents an animal model with unique relevance to understanding the neurochemical basis of substance abuse in humans. For example, the complexity of the topographical organization of the striatum and its connections with surrounding areas in primates62–64 complicates extrapolations from rodents to primates. Moreover, a large number of brain regions respond differently to acute drug administration in monkeys65 compared to rodents.66,67 Both the topography of altered brain metabolism and the direction of metabolic responses differ markedly.65,67 The metabolic effects reported in monkeys are more consistent with data on functional activity in humans.68,69 These findings, in conjunction with documented species differences in drug metabolism,18 illustrate the importance of nonhuman primate models in substance abuse research. Research efforts that have used nonhuman primate models of drug self-administration have focused primarily on the identification of neurochemical mechanisms that underly drug reinforcement, and the development of pharmacotherapies to treat drug addiction. In clinical evaluations of new medications, a decrease in drug self-administration is the goal of treatment.70–72 Preclinical evaluations of pharmacotherapies require the establishment of stable baseline patterns of drug self-administration prior to drug-interaction studies. Subsequently, the treatment medication is administered as a pretreatment before the conduct of self-administration sessions. It is critical to study several doses of the treatment medication to determine an effective dose range and a maximally effective dose that lacks overt behavioral toxicity. The effects of the treatment medication typically are evaluated first in combination with a dose of the self-administered drug on the ascending limb of the doseeffect curve that maintains high rates of self-administration. However, a complete dose-effect curve should be characterized for the self-administered drug because pretreatment effects can differ depending on the unit dose of the drug self-administered. A rightward shift in the dose-effect curve suggests that drug pretreatment is antagonizing the reinforcing effects of the self-administered drug. A downward displacement of the dose-effect curve indicates an insurmountable attenuation of the reinforcing effects. Alternatively, a leftward shift is consistent with an enhancement of the reinforcing effects. Medications that shift the dose-effect curve downward and decrease self-administration over a broad range of unit doses are most likely to have therapeutic utility. Medications that shift the dose-effect curve to the right and simply alter the potency of the self-administered drug may prove to be ineffective at higher unit doses. Clinically, most medications are administered on a chronic basis and may require long-term exposure before therapeutic effects are noted.73,74 Accordingly, preclinical studies should include repeated daily exposure to the medication to characterize peak effectiveness and to document continued effectiveness over multiple sessions.75 Figure 9.5 illustrates the effects of chronic amphetamine treatment on cocaine self-administration in rhesus monkeys. Note that amphetamine maintained


193

80

100

60

75

40

50

20

25

0

c 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 P1 P2 P3 P4 P5 P6 P7

Pellets/Day

Injections/Day


0

Days of Treatment

FIGURE 9.5 Time course of effects of saline or d-amphetamine (0.01–0.1 mg/kg per hr) on responding for 0.01 mg/kg per injection cocaine and food pellets. Abscissae: consecutive days of treatment. Left ordinate: number of cocaine injections (0.01 mg/kg per injection) delivered on each day of treatment (filled triangles, maximum = 80). Right ordinate: number of food pellets delivered on each day of treatment (open circles, maximum = 100). Each point shows mean data from four monkeys, and error bars show the SEM.

its effectiveness to reduce cocaine self-administration over multiple weeks. Also, there was an initial disruption of food-maintained behavior, but responding for food returned to baseline values over the first week of amphetamine treatment. It is also critical to reestablish baseline levels of drug self-administration between successive exposures to the medication to ensure that the catheter preparation is functional and that persistent effects of the pretreatment drug do not interfere with the interpretation of drug interactions obtained. The primary treatment outcome measures in drug self-administration studies are rate of responding and the number of drug injections delivered per session. Both measures are influenced by the schedule of reinforcement, drug dose, the volume and duration of injection, and the duration of the self-administration session. Moreover, most drugs that are self-administered have direct effects on rate of responding that may be distinct from their reinforcing effects. For example, cocaine injections may increase rate of responding early in the session, but suppress behavior later in the session as total drug intake accumulates. Another important consideration in evaluating medication effectiveness is the selectivity of effects on drug self-administration. If the drug pretreatment decreases drug self-administration at lower doses or to a greater extent than behavior maintained by a nondrug reinforcer such as food, the outcome is indicative of selective interactions with the reinforcing properties of the self-administered drug. In contrast, a nonspecific disruptive effect on operant behavior will likely suppress drug- and food-maintained responding to a comparable extent. Lastly, the reinforcing properties and abuse potential of the medication should be evaluated by substituting a range of doses of the medication for the self-administered drug. Since reinforcing effects in preclinical studies are correlated with abuse liability in humans, reliable self-administration of the medication is usually considered undesirable. While this chapter focuses on the i.v. route of drug self-administration, the reinforcing properties of drugs have been studied effectively in nonhuman primates via the oral and inhalation routes. For example, orally delivered cocaine can function as a reinforcer in rhesus monkeys, and persistent and orderly responding is obtained when dose and FR size are varied.76 Orally delivered phencyclidine and ethanol also


194


maintain self-administration behavior in rhesus monkeys under progressive-ratio schedules.77 However, establishing drugs as reinforcers via oral administration can be difficult because of metabolic effects associated with the gastrointestinal system and delayed onset of CNS activity associated with slow absorption and distribution. In addition, drug solutions often have a bitter taste that may be aversive to nonhuman primates. Accordingly, complex induction procedures are frequently used to establish oral self-administration of drug solutions. Studies that have demonstrated cocaine’s ability to function as a reinforcer have used a fading procedure from an initial baseline of ethanol-maintained responding,76 although concurrent access to cocaine and vehicle solution is sufficient to establish oral self-administration.78 Lastly, cocaine and heroin are self-administered by rhesus monkeys via smoke inhalation under FR and progressive-ratio schedules.79–81 Although initial training is difficult because of the aversive characteristics of smoke, and drug dose is difficult to quantify, rhesus monkeys can rapidly learn to self-administer the drugs via the inhalation route. Given the above considerations, the advantages of intravenous selfadministration procedures are clearly evident. Drug dose is easily manipulated and quantified, metabolic effects in the gastrointestinal system and slow absorption are avoided, and onset of CNS activity is rapid. Importantly, orderly and reliable doseeffect curves are obtained that are sensitive to pharmacological manipulation.

REFERENCES 1. Thompson, T. and Pickens, R., eds. 1971. Stimulus properties of drugs. New York: Appleton-Century-Crofts. 2. Skinner, B. F. 1938. The behavior of organisms. New York: Appleton-Century-Crofts. 3. Headlee, C. P., Coppock, H. W., and Nichols, J. R. 1955. Apparatus and technique involved in laboratory method of detecting the addictiveness of drugs. J. Am. Pharm. Assoc., Sci. Ed., 44:229. 4. Thompson, T., and Schuster, C. R. 1964. Morphine self-administration, food-reinforced, and avoidance behaviors in rhesus monkeys. Psychopharmacologia 5:87. 5. Deneau, G., Yanagita, T., and Seevers, M. H. 1969. Self-administration of psychoactive substances by the monkey: A measure of psychological dependence. Psychopharmacologia 16:30. 6. Pickens, R., and Thompson T. 1968. Cocaine-reinforced behavior in rats: Effects of reinforcement magnitude and fixed-ratio size J. Pharmacol. Exp. Ther. 161:122. 7. France, C. P., Winger, G. D., Medzihradsky, F., Seggel, M. R., Rice, K. C., and Woods, J. H. 1991. Mirfentanil: Pharmacological profile of a novel fentanyl derivative with opioid and nonopioid effects. J. Pharmcol. Exp. Ther. 258:502. 8. Young, A. M., Stephens, K. R., Hein, D. W., and Woods, J. H. 1984. Reinforcing and discriminative stimulus properties of mixed agonist-antagonist opioids. J. Pharmacol. Exp. Ther. 229:118. 9. Tang, A. H., and Collins, R. J. 1985. Behavioral effects of a novel kappa-opioid analgesic, U-50488, in rats and rhesus monkeys. Psychopharmacology 85:309. 10. Koob, G. F., and Bloom, F. E. 1988. Cellular mechanisms of drug dependence. Science 242:715. 11. Koob, G. F., and Weiss, F. 1990. Pharmacology of drug self-administration. Alcohol 7:193.



195

12. Bergman, J., Kamien, J. B., and Spealman, R. D. 1990. Antagonism of cocaine selfadministration by selective dopamine D1 and D2 antagonists. Behav. Pharmacol. 1:355. 13. Bertalmio, A. J., and Woods, J. H. 1989. Reinforcing effects of alfentanil is mediated by mu opioid receptors: Apparent pA2 analysis. J. Pharmacol. Exp. Ther. 251:455. 14. Dewit, H., and Wise, R. A. 1977. Blockade of cocaine reinforcement in rats with the dopamine receptor blocker pimozide, but not with the noradrenergic blockers phentolamine or phenoxybenzamine. Can. J. Psychol. 31:195. 15. Wilson, M. C., and Schuster, C. R. 1972. The effects of chlorpromazine on psychomotor stimulant self-administration in the rhesus monkey. Psychopharmacologia 26:115. 16. Griffiths, R. R., Bigelow, G. E., and Henningfield, J. E. 1980. Similarities in animal and human drug-taking behavior. In Advances in substance abuse, Vol. 1, ed. N. K. Mello, 1. Greenwich, CT: JAI Press. 17. Mello, N. K. 1979. Behavioral pharmacology of narcotic antagonists. In The international challenge of drug abuse, NIDA research monograph series 19, ed. R. C. Peterson, 126. Washington, DC: U.S. Government Printing Office. 18. Weerts, E. M., Fantegrossi, W. E., and Goodwin, A. K. 2007. The value of nonhuman primates in drug abuse research. Exp. Clin. Psychopharmacol. 15:309. 19. Herd, J. A., Morse, W. H., Kelleher, R. T., and Jones, L. G. 1969. Arterial hypertension in the squirrel monkey during behavioral experiments. Am. J. Physiol. 217:24. 20. Howell, L. L., and Byrd, L. D. 1995. Serotonergic modulation of the behavioral effects of cocaine in the squirrel monkey. J. Pharmacol. Exp. Ther. 275:1551. 21. Wojnicki, F. H. E., Rothman, R. B., Rice, K. C., and Glowa, J. R. 1999. Effects of phentermine on responding maintained under multiple fixed-ratio schedules of food and cocaine presentation in the rhesus monkey. J. Pharmacol. Exp. Ther. 288:550. 22. Byrd, L. D. 1979. A tethering system for direct measurement of cardiovascular function in the caged baboon. Am. J. Physiol.: Heart Circ. Physiol. 5:H775. 23. Byrd, L. D. 1979. The behavioral effects of cocaine: Rate dependency or rate constancy. Eur. J. Pharmacol. 56:355. 24. Howell, L. L., and Landrum, A. M. 1994. Behavioral and pharmacological modulation of respiration in rhesus monkeys. J. Exp. Anal. Behav. 62:57. 25. Howell, L. L., and Landrum, A. M. 1997. Effects of chronic caffeine administration on respiration and schedule-controlled behavior in rhesus monkeys. J. Pharmacol. Exp. Ther. 283:190. 26. Slifer, B. L., and Balster, R. L. 1985. Intravenous self-administration of nicotine: With and without schedule-induction. Pharmacol. Biochem. Behav. 22:61. 27. Rescorla, R. A. 1980. Pavlovian second-order conditioning: Studies in associative learning, 120. Hillsdale, NJ: Lawrence Erlbaum. 28. Schindler, C. W., Katz, J. L., and Goldberg, S. R. 1988. The use of second-order schedules to study the influence of environmental stimuli on drug-seeking behavior. In Learning factors in substance abuse, NIDA research monograph series 84, ed. B. A. Ray, 180. Washington, DC: U.S. Government Printing Office. 29. Katz, J. L., and Goldberg, S. R. 1975. Second-order schedules of drug injection: Implications for understanding reinforcing effects of abused drugs. Adv. Subst. Abuse (4)205:1991. 30. Kelleher, R. T. 1975. Characteristics of behavior controlled by scheduled injections of drugs. Pharmacol. Rev. 27:307. 31. Hodos, W. 1961. Progressive ratio as a measure of reward strength. Science 134:943. 32. Bedford, J. A., Baily, L. P., and Wilson, M. C. 1978. Cocaine reinforced progressive ratio performance in the rhesus monkey. Pharmacol. Biochem. Behav. 9:631.


196


33. Griffiths, R. R., Brady, J. V., and Snell, J. D. 1978. Progressive-ratio performance maintained by drug infusions: Comparison of cocaine, diethylproprion, chlorphentermine, and fenfluramine. Psychopharmacology 56:5. 34. Griffiths, R. R., Bradford, L. D., and Brady, J. V. 1979. Progressive-ratio and fixed-ratio schedules of cocaine-maintained responding in baboons. Psychopharmacology 65:125. 35. Rowlett, J. K., and Woolverton, W. L. 1997. Self-administration of cocaine and heroin combinations by rhesus monkeys responding under a progressive-ratio schedule. Psychopharmacology 133:363. 36. Woolverton W. L. 1995. Comparison of the reinforcing efficacy of cocaine and procaine in rhesus monkeys responding under a progressive-ratio schedule. Psychopharmacology 120:296. 37. Young, A. M., and Herling, S. 1986. Drugs as reinforcers: Studies in laboratory animals. In Behavioral analysis of drug dependence, eds. S. R. Goldberg and I. P. Stolerman, I. P., 9. San Diego: Academic Press. 38. Balster, R. L., and Schuster, C. R. 1973. Fixed-interval schedule of cocaine-reinforcement: Effect of dose and infusion duration. J. Exp. Anal. Behav. 20:119. 39. Kato, S., Wakasa, Y., and Yanagita, T. 1987. Relationship between minimum reinforcing doses and injection speed in cocaine and pentobarbital self-administration in crabeating monkeys. Pharmacol. Biochem. Behav. 28:407. 40. Glowa, J. R., Wojnicki, F. H. E., Matecka, D., et al. 1995. Effects of dopamine reuptake inhibitors on food- and cocaine-maintained responding. I: Dependence on unit dose of cocaine. Exp. Clin. Psychopharmacol. 3:219. 41. Caine, S. B., and Koob, G. F. 1993. Modulation of cocaine self-administration in the rat through D3 dopamine receptors. Science 260:1814. 42. Skjoldager, P., Winger, G., and Woods, J. H. 1993. Effects of GBR 12909 and cocaine on cocaine-maintained behavior in rhesus monkeys. Drug Alcohol Depend. 33:31. 43. Carroll, F. I., Howell, L. L., and Kuhar, M. J. 1999. Pharmacotherapies for treatment of cocaine abuse: Preclinical aspects. J. Med. Chem. 42:2721. 44. Bergman, J., Madras, B. K., Johnson, S. E., and Spealman, R. D. 1989. Effects of cocaine and related drugs in nonhuman primates. III. Self-administration by squirrel monkeys. J. Pharmacol. Exp. Ther. 251:150. 45. Howell, L. L., and Byrd, L. D. 1991. Characterization of the effects of cocaine and GBR 12909, a dopamine uptake inhibitor, on behavior in the squirrel monkey. J. Pharmacol. Exp. Ther. 258:178. 46. Howell, L. L., Czoty, P. W., and Byrd, L. D. 1997. Pharmacological interactions between serotonin and dopamine on behavior in the squirrel monkey. Psychopharmacology 131:40. 47. Woolverton, W. L. 1986. Effects of a D1 and D2 dopamine antagonist in the self-administration of cocaine and piribedil by rhesus monkeys. Pharmacol. Biochem. Behav. 24:351. 48. Nader, M. A., Grant, K. A., Davies, H. M. L., Mach R. H., and Childers, S. R. 1997. The reinforcing and discriminative stimulus effects of the novel cocaine analog 2Gpropanoyl-3G-(4-tolyl)-tropane in rhesus monkeys. J. Pharmacol. Exp. Ther. 280:541. 49. Kimmel, H. L., O’Connor, J. A., Carroll, F. I., and Howell, L. L. 2007. Faster onset and dopamine transporter selectivity predict stimulant and reinforcing effects of cocaine analogs in squirrel monkeys. Pharmacol. Biochem. Behav. 86:45. 50. Lile, J. A., Wang, Z., Woolverton, W. L., et al. 2003. The reinforcing efficacy of psychostimulants in rhesus monkeys: The role of pharmacokinetics and pharmacodynamics. J. Pharmacol. Exp. Ther. 307:356. 51. Woolverton, W. L., Ranaldi, R., Wang, Z., et al. 2002. Reinforcing strength of a novel dopamine transporter ligand: Pharmacodynamic and pharmacokinetic mechanisms. J. Pharmacol. Exp. Ther. 303:211.



197

52. Kelleher, R. T., and Goldberg, S. R. 1977. Fixed-interval responding under secondorder schedules of food presentation or cocaine injection. J. Exp. Anal. Behav. 28:221. 53. Howell, L. L., Czoty, P. W., Kuhar, M. J., and Carroll, F. I. Comparative behavioral pharmacology of cocaine and the selective dopamine uptake inhibitor, RTI-113, in the squirrel monkey. J. Pharmacol. Exp. Ther., in press. 54. Depoortere, R. Y., Li, D. H., Lane, J. D., and Emmett-Oglesby, M. W. 1993. Parameters of self-administration of cocaine in rats under a progressive-ratio schedule. Pharmacol. Biochem. Behav. 45:539. 55. Rowlett, J. K., Massey, B. W., Kleven, M. S., and Woolverton, W. L. 1996. Parametric analysis of cocaine self-administration under a progressive-ratio schedule in rhesus monkeys. Psychopharmacology 125:361. 56. Iglauer, C., and Woods, J. H. 1974. Concurrent performances: Reinforcement by different doses of intravenous cocaine in rhesus monkeys. J. Exp. Anal. Behav. 22:79. 57. Johanson, C. E. 1976. Pharmacological and environmental variables affecting drug preference in rhesus monkeys. Pharmacol. Rev. 27:343. 58. Johanson, C.-E., and Aigner, T. 1981. Comparison of the reinforcing properties of cocaine and procaine in rhesus monkeys. Pharmacol. Biochem. Behav. 15:49. 59. Hursh, S. R., Galska, C. M., Winger, G., and Woods, J. H. 2005. The economics of drug abuse: A quantitative assessment of drug demand. Mol. Interv. 5:20. 60. Bickel, W. K., Marsch, L. A., and Carroll, M. E. 2000. Deconstructing relative reinforcing efficacy and situating the measures of pharmacological reinforcement with behavioral economics: A theoretical proposal. Psychopharmacology 153:44. 61. Ko, M. C., Terner, J., Hursh, S., Woods, J. H., and Winger, G. 2002. Relative reinforcing effects of three opioids with different durations of action. J. Pharmacol. Exp. Ther. 301:698. 62. Haber, S. N., Kunishio, K., Mizobuchi, M., and Lynd-Balta, E. 1995. The orbital and medial prefrontal circuit through the primate basal ganglia. J. Neurosci. 15:4851. 63. Lynd-Balta, E., and Haber, S. N. 1994. The organization of midbrain projections to the ventral striatum in the primate. Neuroscience 59:609. 64. Lynd-Balta, E., and Haber, S. N. 1994. Primate striatonigral projections: A comparison of the sensorimotor-related striatum and the ventral striatum. J. Comp. Neurol. 3345:562. 65. Lyons, D., Friedman, D. P., Nader, M. A., and Porrino, L. J. 1996. Cocaine alters cerebral metabolism within the ventral striatum and limbic cortex of monkeys. J. Neurosci. 16:1230. 66. Porrino, L. J. 1993. Functional effects of cocaine depend on route of administration. Psychopharmacology 112:343. 67. Porrino, L. J., Domer, F. R., Crane, A. M., and Sokoloff, L. 1988. Selective alterations in cerebral metabolism within the mesocorticolimbic dopaminergic system produced by acute cocaine administration in rats. Neuropsychopharmacoalogy,1:109. 68. London, E. D., Cascella, N. G., Wong, D. F., et al. 1990. Cocaine-induced reduction of glucose utilization in human brain. Arch. Gen. Psychiat. 47:567. 69. Pearlson, G. D., Jeffery, P. J., Harris, G. J., Ross, C. A., Fischman, M. W., and Camargo, E. E. 1993. Correlation of acute cocaine-induced changes in local cerebral blood flow with subjective effects. Am. J. Psychiat. 150:495. 70. Mello, N. K., and Mendelson, J. H., 1980. Buprenorphine suppresses heroin use by heroin addicts. Science 27:657. 71. Mello, N. K., Mendelson, J. H., and Bree, M. P. 1981. Naltrexone effects on morphine and food self-administration in morphine-dependent rhesus monkeys. J. Pharmacol. Exp. Ther. 218:550. 72. Mello, N. K., Mendelson, J. H., and Kuehnle, J. C. 1982. Buprenorphine effects on human heroin self-administration. J. Pharmacol. Exp. Ther. 230:30.


198


73. Gawin, F. H. 1991. Cocaine addiction: Psychology and neurophysiology. Science 251:1580. 74. Gawin, F. H., and Ellinwood, E. H. 1988. Cocaine and other stimulants: Actions, abuse and treatment. N. Engl. J. Med. 318:1173. 75. Negus, S. S., and Mello, N. K. 2003. Effects of chronic d-amphetamine treatment on cocaine- and food-maintained responding under a second-order schedule in rhesus monkeys. Drug Alcohol Depend. 70:39. 76. Meisch, R. A., Bell, S. M., and Lemaire, G. A. 1993. Orally self-administered cocaine in rhesus monkeys: Transition from negative or neutral behavioral effects to positive reinforcing effects. Drug Alcohol Depend. 32:143. 77. Rodefer, J. S., and Carroll, M. E. 1996. Progressive ratio and behavioral economic evaluation of the reinforcing efficacy of orally delivered phencyclidine and ethanol in monkeys: Effects of feeding conditions. Psychopharmacology 128:265. 78. Macenski, M. J., and Meisch, R. A. 1995. Oral cocaine self-administration in rhesus monkeys: Strategies for engendering reinforcing effects. Exp. Clin. Psychopharmacol. 3:129. 79. Mattox, A. J., Thompson, S. S., and Carroll, M. E. 1997. Smoked heroin and cocaine base (speedball) combinations in rhesus monkeys. Exp. Clin. Psychopharmacol. 5:113. 80. Carroll, M. E., Krattiger, K. L., Gieske, D., and Sadoff, D. A. 1990. Cocaine-base smoking in rhesus monkeys: Reinforcing and physiological effects. Psychopharmacology 102:443. 81. Siegel, R. K., Johnson, C. A., Brewster, J. A., and Jarvik, M. E. 1976. Cocaine selfadministration in monkeys by chewing and smoking. Pharmacol. Biochem. Behav. 4:461.


Induced 10 Contextually Drug Seeking During Protracted Abstinence in Rats Jerry J. Buccafusco and Laura Shuster CONTENTS 10.1 10.2

Introduction................................................................................................. 199 General Methods.........................................................................................200 10.2.1 Animal Subjects...............................................................................200 10.2.2 Use of Food to Shape Responding...................................................200 10.2.3 Implantation of the i.v. Infusion Line ............................................. 201 10.2.4 The Morphine Regimen................................................................... 201 10.2.5 The Cocaine Regimen .....................................................................202 10.2.6 Spontaneous Morphine Withdrawal Syndrome...............................202 10.2.7 Reinstatement of Lever Pressing .....................................................202 10.3 Methodological Details...............................................................................204 10.3.1 Things to Prepare Before Surgery ...................................................204 10.3.2 Installing a Permanent Intravenous Line.........................................205 10.3.3 Self-Administration Dose Calculations ...........................................206 10.3.4 Ordering Information.......................................................................207 10.3.5 Coulbourn Instruments—Required Equipment ..............................208 10.4 Actual Data .................................................................................................208 10.4.1 Morphine Self-Administration ........................................................208 10.4.2 Context-Induced Post-Withdrawal Lever Responding..................... 210 10.5 Discussion ................................................................................................... 210 10.5.1 The Drug Abuse Cycle and Pharmacological Intervention ............. 210 References.............................................................................................................. 212

10.1

INTRODUCTION

Over the past half century great strides have been made in the development of useful animal models for the drug abuse triad—self-administration, physical or psychologi199


200


cal dependence, and withdrawal. In fact, the compulsion to self-administer cocaine even in the face of adverse consequences is not limited to human beings.1,2 Practically, it is not that difficult to detoxify a drug addict, but the problem lies in the propensity for former addicts to relapse to drug-seeking behavior, a risk factor that does not appear to decrease in potency over time. Recently there has been an increasing focus on the issue of protracted withdrawal. This feature of drug addiction mirrors classical conditioning in that certain contextual cues or environmental stimuli associated with drug taking can readily initiate a form of withdrawal or craving in addicts that often leads to renewed drug seeking and relapse (for review, see3–5). Indeed, both the rat and human share common triggers of relapse, including the drug of abuse itself, stress, and stimuli or the environment conditioned to the drug of abuse.6 Rodent models of human drug craving and relapse have used paradigms of extinction and reinstatement. Such models have shown predictive validity by demonstrating that clinically effective anti-craving drugs reduce drug-seeking behavior as a component of the model.7

10.2

GENERAL METHODS

10.2.1 ANIMAL SUBJECTS Male Wistar rats (Harlan, Indianapolis, Indiana, USA), weighing 300 to 380 g, are housed and tested in environmentally controlled rooms on a 12/12-hr day/night cycle, and they are maintained on standard rat chow and tap water (unlimited). All current animal protocols are approved by the Augusta Veterans Administration Animal Care and Use Committee. Initially each rat is maintained at about 85% of freefeeding levels for about 5 days. During this time the animals are acclimated to the operant chamber and trained for lever pressing. Once a rat is assigned to a particular operant chamber they are maintained there on a 24-hr basis except during the withdrawal phase (see below).

10.2.2 USE OF FOOD TO SHAPE RESPONDING Some investigators use food reinforcement to shape animals for lever responding. The advantage is that animals that are poor responders can be weeded out before they are prepared for i.v. self-administration of the drug of interest. The disadvantage is that the investigator must take care to insure that subsequent lever responding, whether during the i.v. self-administration phase or the post-withdrawal phase, is not reflecting the expectation or the habit of obtaining food rewards. Presently we prefer not to shape animals using food reinforcement, but for those that prefer this approach, and for those that plan to study food reinforcement as the sole reinforcing agent, we describe the method below. We generally train animals on an operant food-reinforcement fixed ratio-1 (FR1) schedule during 2-hr daily sessions. Lever presses are reinforced by the automated delivery of a 45-mg food pellet. The lever is signaled active by the illumination


Contextually Induced Drug Seeking During Protracted Abstinence in Rats

201

of a stimulus light mounted above the lever. The only time the stimulus light is extinguished is during a post-reward 50-sec timeout period. Training and testing are accomplished in a Coulbourn Instruments (Allentown, Pennsylvania, USA) computer-controlled operant system that includes 16 operant chambers (represents an upgrade from current six-station system) with light cues and retractable levers. Each operant chamber is housed in a sound-attenuated and fan-cooled environmental compartment. Rats that maintain at least 100 responses for three consecutive sessions are surgically prepared for i.v. self-administration sessions as described below. The pellet feeder is removed from the operant chamber (to be replaced by i.v. infusion of morphine), but throughout the remainder of the study, the rats have unlimited access to standard rat chow and water.

10.2.3 IMPLANTATION OF THE I.V. INFUSION LINE The trained rats are anesthetized with sodium methohexital (65 mg/kg, i.p.) and under aseptic conditions a midline incision is made ventrally over the neck region. The jugular vein is exposed by blunt dissection and a small nick made to allow introduction of a non-thromogenic, softening, vascular implant tubing (Data Sciences, St. Paul, Minnesota, USA), which is filled with dilute heparinized (20 units/mL) sterile saline. The tubing is advanced about 2.5 cm and then it is tied off and secured to surrounding fascia. The tubing is tunneled under the skin to emerge at the nape of the neck. There the tubing is stabilized to a subcutaneous plastic anchor button and fixed to a water-tight swivel cannula mounted at the top of the operant chamber. The swivel is connected to the computer-controlled infusion pump. Two days later the patency of the venous infusion system is tested by the rapid i.v. administration of the short-acting anesthetic agent sodium methohexital (2.0 mg). Intravenous administration of methohexital leads to immediate loss of muscle tone and righting reflex in patent animals. The heparin-saline solution is maintained in the catheter until the start of morphine/cocaine self-administration (third day after surgery). It is important to maintain each rat in its previously assigned operant chamber.

10.2.4 THE MORPHINE REGIMEN Rats are permitted to self-administer morphine sulfate according to an FR1 schedule with a 50-sec timeout instituted after each infusion. An illuminated stimulus light signifies the beginning of the session and indicates that the lever is active (one press, one infusion). The light is extinguished and the lever is made inactive (presses elicit no infusion) for 50 sec after a reward is delivered. The pump is set to deliver morphine sulfate over a 5-sec period in 0.165 mL of saline. An experimental cohort usually consists of eight rats (usually provides adequate statistical power). The starting dose of morphine in a single infusion is 0.25 mg/kg. Animals are permitted to self-administer 0.25 mg/kg/infusion over the first three days. During the next three days animals self-administer 0.5 mg/kg/infusion, and during the next four days they self-administer 1.0 mg/kg/infusion. The only interruptions in the 24-hr access schedule are the brief periods needed to replace empty infusion syringes between the


202


changes in drug concentrations. Over the final five days, the morphine levels in the infusion solution are tapered to 0.25 mg/kg/infusion (on days 10, 11, 12, 13, and 14 the morphine concentration is adjusted accordingly to 0.75, 0.75, 0.5, 0.5, and 0.25 mg/kg/infusion, respectively).

10.2.5 THE COCAINE REGIMEN The procedure for cocaine i.v. self-administration is similar to that for morphine except that the first dose of cocaine to be self-administered is 0.5 mg/kg/infusion, and the timeout period after each infusion is 280 sec. The timeout period of 280 sec is instituted so that the animal cannot self-administer more than 300 doses per day. During the next three days animals will self-administer 1.0 mg/kg/infusion, and during the next four days they will self-administer 2.5 mg/kg/infusion. In practice, the animals will maximally self-administer no more than about 150 doses in 24 hr (Figure 10.1). Over the final five days, the cocaine levels in the infusion solution are tapered to 0.5 mg/kg/infusion (on days 10, 11, 12, 13, and 14 the cocaine concentration is adjusted accordingly to 2.0, 2.0, 0.5, 1.0, and 0.5 mg/kg/infusion, respectively).

10.2.6 SPONTANEOUS MORPHINE WITHDRAWAL SYNDROME On the final day of self-administration rats continue to have access to the morphine infusion lever until 1700 hr, at which time the i.v. infusion line is disconnected and plugged. Body weight and core temperature (rectal temperature measured by using a thermistor probe) are recorded (0 hr post-withdrawal) and the animals are placed back into their individual home cages. At 0900 hr on the following day (16 hr postwithdrawal) body weight and core temperature are again measured. Next the rats are placed in a standard open-field environment to assess abstinence signs associated with spontaneous morphine withdrawal by using a standardized withdrawal checklist.8,9 These symptoms are scored by a “blinded” rater during 30-min observation periods. Withdrawal symptoms include withdrawal body (wet-dog) shakes, escape attempts (attempting to leap out of the cage), writhing, defecation/diarrhea, and chromodacryorrhea (reddish tears). This procedure is initiated three more times at consecutive 2-hr intervals, and the incidences of the scored symptoms over the four observation periods are totaled. In our previous studies, morphine withdrawal symptoms were shown to peak between 12 and 20 hr after withdrawal and they ended by about 100 hr.10,11 Body weight and core (rectal) temperature are measured after the conclusion of the last observation period (1700 hr). Thereafter, body weight and temperature are measured at 900 hr and at 1700 hr each of the next two days (withdrawal symptoms will no longer need to be recorded), and body weight (which requires the longest period to recover, Figure 10.2) is recorded once daily for the next three days. After the last measurements, the animals are left undisturbed in their individual home cages for the remainder of the 6 wk post-withdrawal period.

10.2.7 REINSTATEMENT OF LEVER PRESSING After the 6-wk post-withdrawal period the subjects are returned to the operant chambers. The condition of the chambers is identical to that during the morphine self-


Lever Responses

mg/kg/Infusion

Contextually Induced Drug Seeking During Protracted Abstinence in Rats N: 4 3 2 1 0

400 350 300 250 200 150 100 50 0

203

21

21

21

21

21

21

15

15

15

3

3

3

2

1

1

2

3

4

5

6

7

8 (a)

9

10

11

12

13

14

1

2

3

4

5

6

7

8

9

10

11

12

13

14

9

10

11

12

13

14

5 6 7 8 9 10 11 Days of Morphine Self-administration (d)

12

13

14

Dose SA (mg/kg/24 hr)

Number of Infusions

(b) 200 180 160 140 120 100 80 60 40 20 0

400 200 120 100 80 60 40 20 0

1

2

3

4

1

2

3

4

5

6

7

8 (c)

FIGURE 10.1 The self-administration of an escalating dose regimen of i.v. morphine infusion by 21 rats under a contingent FR1 schedule of reinforcement with 50-sec timeouts. Access to the reinforcement response lever was available 24 hr per day. (a) The dose of morphine self-administered with each infusion. The integers above the panel indicate the number of animals completing the regimen to that point. (b) The number of reinforcement lever responses per 24 hr. (c) The number of morphine infusions as a consequence of contingent lever responses per 24 hr. (d) The dose of morphine self-administered per 24 hr. Error bars refer to the SEM.


204

Methods of Behavior Analysis in Neuroscience, Second Edition 360

Body Weight (g)

340 320 300 280 260 240

0

20

40 60 80 100 Hr Post-withdrawal

120

140

FIGURE 10.2 The change in body weight in morphine-dependent rats after discontinuation of self-administration.

administration phase, and each rat will always be returned to its original chamber. Again rats are allowed to lever press according to the 24-hr access schedule used during morphine or cocaine self-administration, including the (contingent) cue light. The animals have unlimited access to standard rat chow and water. In this case the i.v. line is not reconnected, and lever pressing will not result in a reward. Rats are maintained in the operant chamber for at least seven days.

10.3

METHODOLOGICAL DETAILS

10.3.1 THINGS TO PREPARE BEFORE SURGERY

1. Order male Wistar rats, 300–324 g, from Harland, Indianapolis, Indiana, USA. Allow the animals at least 1 wk to acclimate after shipping. &RQQHFWWKH3(WXELQJWRWKHERWWRPRIWKHVZLYHO7KLVFDQEHGLI¿FXOW ,QVHUWDVPDOOJDXJHQHHGOHLQLW¿UVWWRVWUHWFKLWDOLWWOH7KHQLQVHUWD piece of 22-gauge wire. This can help open the tubing. Attach the swivel to the tubing. By doing this before surgery it can be reattached easily to save time. 3. The surgical instruments are sterilized in a glass bead sterilizer (Fine SciHQWL¿F7RROV)RVWHU&LW\&DOLIRUQLD86$ %HIRUHSODFLQJWKHLQVWUXPHQWV in the sterilizer they should be cleaned and scrubbed in rubbing alcohol. Insert the dry instruments into the beads at 250°C (it requires about 20 min for the sterilizer to reach 250°& IRUDWOHDVWPLQ$OORZWKHLQVWUXPHQWV to cool before starting surgery. The sterilizer does not need to be turned off EHWZHHQVXUJLFDOSURFHGXUHV*ORYHVVXUJLFDOJRZQDQGPDVNVKRXOGEH worn during all surgical procedures. 4. Dilute hospital-grade sodium heparin in sterile normal saline to 20 units/mL.



205

10.3.2 INSTALLING A PERMANENT INTRAVENOUS LINE One hour before surgery rats are administered carprofen sterile injectable solution purchased in 50 mg/mL vials (Pfizer Animal Health, Exton, Pennsylvania, USA). Carprofen is an analgesic agent administered by subcutaneous injection at a dose of 5 mg/kg. Rats are anesthetized by i.p. injection with methohexital sodium (Brevital) 60 mg/kg. Brevital (purchased as 500 mg of the dry powder in 50 mL vial to provide a working solution of 10 mg/mL) is a short-acting anesthetic and in most cases the entire surgical procedure can be accomplished after a single injection. However, if the animal begins to recover (assess response to toe pinch), an additional 5 mg of Brevital should be administered. The fur should be clipped ventrally over the neck and on the area dorsally over the neck just behind the head after the animal is anesthetized. Next, the exposed skin in the surgical fields should be swabbed with Betadine antiseptic solution. A midline incision is then made in the skin over the ventrolateral aspect of the neck. The incision is about 2-cm long. A small pair of round-tipped scissors can be used to bluntly dissect the fascia without cutting. The right exterior jugular vein will be exposed. Care should be taken not to overly stretch the vein as it will become narrower and more difficult to cannulate. The vein can be isolated from the surrounding fascia by using curved forceps, but care must be taken not to puncture the vein. Place a small forceps under the vein to secure it. Place two pieces of 3-0 black braided suture at the top and bottom of the cleared vessel. Tie a knot on the cranial aspect of the vein to seal it off. Make the venotomy (incision) approximately 5 mm cranial to the site of crossover of the pectoralis major muscle. Before inserting the small animal vascular catheter into the vein, cut a bevel on the end to be inserted. Make sure that the tip is not too sharp. The catheter should be about 20-cm long. Fill the cannula with heparinized saline (20 units/mL). Insert a #7 Dumont tweezer into the vein and lift slightly, i.e., insert the right tip of the forceps into the vein and then grasp the vein. Slowly insert the small animal tubing into the vein for about 1.5 cm. Hold the vein and tubing with the Dumont tweezer until insertion is complete. (If nick in the vein is difficult to see, the vein can be “milked” by gentle rubbing and getting the blood to flow again. Application of saline to the cut end could also help.) Tie the vein and tubing in with the 3-0 suture that was placed there earlier. Both sutures should be tied to the vein to secure the catheter. A subcutaneous tunnel should be created from the neck area to the dorsum. A small incision (about 1.5 mm) is made in the skin just behind the head. Make it a pocket by inserting the scissors and opening them to clear the fascia away. Pass a trochar (point-sharpened 14-gauge stainless steel tubing) between the skin and muscle layers. (Note: Do not pass through the muscle.) around to the back of the neck behind the head and out the small incision. Pass the catheter through the trochar. Remove the stainless steel tubing. Pull the catheter through the anchor button and place the button under the skin. Suture the skin to the button with 3-0 black braided suture. Attach a connector made from 26-gauge stainless steel tubing to the catheter. Next, place a piece of PE 20 tubing filled with heparin saline to the connector. Place a piece of Vardex tubing about 4-in long over the spring support. (This is optional but keeps the rat from chewing into the spring support.) Feed the tubing through


206


the spring support and attach the spring to the button. The tubing from the bottom of the swivel to the top of the animal should be long enough to include a loop in the top before attaching the catheter to the swivel (approximately 13-in long—you can always shorten it by cutting some from the end that joins to the connector). The loop should be small, about 2.5 cm in diameter. The loop absorbs tension on the catheter as the animal moves. If the loop is too large it can get caught on the swivel holder. Note: Coulbourn tethers have attachments at the bottom to fit their rodent harnesses. We do not use the harness and so the attachments are clipped off with a wire cutter. Tethers are cut to 32 cm. With a dull pair of scissors, squeeze between turns on the spring to create an offset. The output end of the swivel is twisted tight into the entry of the offset and the looped PE 20 tubing from the rat connects to the swivel output. This offset allows the rat to move more freely in the Habitest cage. Place a 5-in piece of Tygon micro-bore tubing, 0.2 in inner diameter (id) × 0.6 in outer diameter (od), on the input of the swivel. Fill the swivel and tubing with heparinized saline. Attach the swivel to the spring and then attach the looped tubing to the bottom of the swivel. Fill a 60-mL syringe with 30–40 mL of heparin saline. Insert a blunt 22gauge needle into the end of the syringe and attach it to 0.2 in id × 0.6 in od Tygon tubing long enough to reach the top of the swivel. Place a 22-gauge stainless steel connector on the end of the tubing. Fill the tubing with heparin saline or drug. Connect it to the tubing from the swivel input. Infuse heparin saline at a rate of about 7.5 mL/day. Place the rat in the Habitest cage. Hook the swivel to the swivel holder. A weight at the back of the balance arm can be moved to make the line taut. Place the water bottle on the cage and place food in bottom of cage. (Note: Place 35 g of rodent chow per day.) Food consumption should be recorded on a daily basis. The Habitest Linc program for controlling the operant aspects of the task and for recording lever responses can be initiated at any time.

10.3.3 SELF-ADMINISTRATION DOSE CALCULATIONS Morphine Self-Administration Day 1–3 Day 4–6 Day 7–9

0.25 mg/kg/day 0.50 mg/kg/day 1.00 mg/kg/day

Cocaine Self-Administration Day 1–3 Day 4–6 Day 7–9

0.5 mg/kg/day 1.0 mg/kg/day 1.5 mg/kg/day

Sample Calculations for Preparing Stock Solution of Drugs for SelfAdministration: For a rat with average body weight of 300 g and a required dose of 0.25 mg/kg/infusion:



207

Infusion pump is set to 0.165 mL/infusion Dose (mg/kg/infusion)/0.165 mL/infusion × weight in kg = mg/mL 0.25 mg/kg/infusion × 0.3 kg/0.165 mL/infusion = 0.455 mg/mL (concentration of stock solution) Prepare enough drug solution to fill all infusion syringes. To calculate daily (24 hr) dose self-administered, divide the dose infused (mg/ kg/infusion) by the number of infusions self-administered per 24 hr.

10.3.4 ORDERING INFORMATION Small animal vascular catheter

Data Sciences #277-0011-002 St. Paul, MN 55126-6164 USA

Button for DC95 tethers

Instech #DC95BS www.instechlabs.com

Tygon tubing 0.02 w 0.06

VWR 63018-044 or Fisher 14-170-15B

Stainless steel tubing and wire 14-gauge stainless steel tubing

Small Parts HTX-14 www.smallparts.com

26-gauge stainless steel tubing

Small Parts HTX-26

22-gauge stainless steel tubing

Small Parts HTX-22

22-gauge stainless steel wire

Small Parts J-SWX-022

PE20 tubing 0.015 w 0.043

VWR 63019-025

Male Wistar rats 300–324 g

Harlan, Inc. Indianapolis, IN, USA

Glass bead sterilizer

Fine Scientific Tools FST 250 sterilizer [email protected]

Rodent 22 g swivel

Braintree Scientific RS-22G

(Need this or the ones from Coulbourn)

www.braintreesci.com

Optional Vardex interbraided tubing 0.25 id w 0.453 od

Newage Industries #140-0070-100 Southampton, PA 18966 USA www.Newageindustries.com

Utility cutter short-angled blade scissors

Fisher Scientific 14-277

SuperCut iris scissors, straight, 4.5 in

Braintree Scientific SC528 www.braintreesci.com


208


10.3.5 COULBOURN INSTRUMENTS—REQUIRED EQUIPMENT Description

Part Number

Cue, single high bright light—rat

H11-03R

House light

H11-01R

Balance arm

H-29-01

Lever

H21-03R

Swivel

A73-51

Panel, blank metal assortment

H-90-00R-M-KT01

Pump, infusion—programmable

E73-02

Habitest power base w/lid

H01-01

Habitest Linc

H02-08 (for two rats)

Environmental control board

H03-04

Test cage

H10-11R-TC

Non-shock floor

H10-11R-TC-NSF

Catheter protection and tethers

A73-59R

Rat harness to fit 150–500 g rat

A71-21R-350/500

Graphic State software, version 3.03

GS3.03

PCI-3 computer interface card

PCI-3-Kit

Computer controller requirements

Sys Control 1F P4, 3.2 GHz , 1GB RAM, 250 GB HD, 17-in LCD, DVD-RW (May use Windows XP with PC1 slot and turn-key package)

Note:7RVHOIDGPLQLVWHUIRRGSHOOHWVDIHHGHUDQGWKHZLUHVWRFRQQHFWWKHPWRWKH board are required. There may be other cables and accessories required depending RQWKHFKRVHQV\VWHPFRQ¿JXUDWLRQ7KLVLQIRFDQEHREWDLQHGIURP&RXOERXUQ ,QVWUXPHQWVZZZFRXOERXUQFRP

10.4

ACTUAL DATA

10.4.1 MORPHINE SELF-ADMINISTRATION These data reflect the trial of different morphine self-administration regimens. Twenty-one rats initially participated in the first experimental series, and each animal was trained to self-administer 0.25 mg/kg doses of morphine. These data are presented in Figure 10.1. Animals generally maintained their level of lever responding (about 100 responses/24 hr) that carried over from the earlier lever training experiments where food pellets provided the response motivation. That the animals transferred this behavior to morphine-reinforced responding was insured by the removal of the food hopper (the space was covered by a flat insert indistinguishable from the surrounding wall), and by the continuous availability of food in the operant chamber.



209

Also, in separate studies in which rats shaped on food rewards were transferred to saline self-administration, the lever responding that carried over extinguished over the same time period.12 Note that it is possible that rats can learn to self-administer without the use of prior shaping with food reinforcement. This is because with 24-hr access, inadvertent lever responses occur with sufficient frequency to help encourage the behavior. Should you use this approach, you should be prepared to encounter some animals that fail to lever respond sufficiently during the first few days to the extent that they are removed from the study. As indicated in Figure 10.1A, lever responding and the daily dose self-administered increased over the first 3 days. Lever responding became relatively constant over the next 6 days during the self-administration of the 0.5 mg/kg and the 1 mg/kg doses. Though the numbers of animals remaining in the study decreased dramatically over the last 4 days (the self-administration phase was terminated at different times to enhance the variability in the total amount of morphine consumed prior to withdrawal), there was a dramatic decrease in responding when the infusion dose was increased to 2 mg/kg. The level of responding recovered even for the two rats that self-administered 4 mg/kg/infusion. The daily dose of morphine was maintained fairly constantly during the self-administration of the 0.5 mg/kg and 1 mg/kg doses per infusion (Figure 10.1D). This was evident in the observation that after day 6 (the last day of 0.5 mg/kg/infusion), when the dose of morphine was increased to 1 mg/kg/infusion, responding decreased slightly so that the average total dose self-administered could be maintained at about 70 mg/kg/day. This profile of responses, and the amount of morphine self-administered, was again apparent in transitioning from the 1 mg/kg to the 2 mg/kg doses per infusion. Two animals continued to self-administer 4 mg/kg morphine per infusion with additional fall-off in the number of lever responses. By varying the number of days of selfadministration, and allowing some animals to self-administer high concentrations of morphine, we were able to obtain a broad spectrum of total morphine doses as well as the associated total number of lever responses. For morphine self-administration, we allow rats to self-administer only up to 1 mg/kg/infusion. If the animals maintain a good level of responding (> 70 responses per day) they will become dependent on the drug after about 4–5 days self-administering this dose. At the completion of the self-administration phase of the study, animals are returned to their home cages and allowed to undergo withdrawal. Figure 10.2 shows the change in body weight as a function of time after withdrawal. There was a characteristic sharp decrease in body weights averaging 16.2 g measured 36 hr after withdrawal. Thereafter, body weight gradually increased to near control levels by 84 hr post-withdrawal. The animals continued to gain weight through the last observation period at 6 days after withdrawal. More importantly, the withdrawal-associated decrease in body weight was shown to be linearly related to the total dose of morphine self-administered.12 These data therefore relate the quantity of morphine consumed during the dependence phase to magnitude of the expression of this withdrawal symptom. In general, other withdrawal symptoms were not as dramatic or intense as with opiate antagonist-precipitated withdrawal, and the most prevalent of the visually observed symptoms was withdrawal body shakes. Of the other symp-



Lever Responses

210

700 600 500 400 300 200 100 0

1

2 3 4 5 6 Days Post Lever Reinstatement

7

FIGURE 10.3 &RQWH[WLQGXFHGUHLQVWDWHPHQWRIOHYHUUHVSRQGLQJZNDIWHUGLVFRQWLQXDtion of morphine self-administration in dependent rats. The number of lever responses (per KU GXULQJWKHGD\OHYHUUHLQVWDWHPHQWSHULRGZLWKOHYHUUHVSRQGLQJRQWKHODVWGD\RI the morphine self-administration regimen.

toms, defecation and diarrhea were noted most often, though these are not necessarily characteristic withdrawal symptoms.

10.4.2 CONTEXT-INDUCED POST-WITHDRAWAL LEVER RESPONDING After completing the 6-wk withdrawal period, rats were placed back into their original operant environment and allowed to make lever responses with no reward consequences (even though the illuminated stimulus light continued to signal an active lever). These data are presented in Figure 10.3. Returning the animal to the operant chamber resulted in a doubling of the average 24-hr lever response rate that was measured on the last day of the self-administration schedule. Average responding decreased over the next two days, but it rebounded during test days 4 and 5. By day 7 the response rate extinguished to that measured during the last day of self-administration. The differences among the means for each day of testing relative to the pre-withdrawal level of responding was statistically significant (P < 0.01).

10.5

DISCUSSION

10.5.1 THE DRUG ABUSE CYCLE AND PHARMACOLOGICAL INTERVENTION Animals that self-administered morphine according to our standard protocol were shown to be physically dependent on morphine. This was evidenced by the appearance of characteristic symptoms of abstinence, and more specifically by the precipitous decrease in body weight that was maximal on the second day after morphine withdrawal. After monitoring body weight for 6 days, the rats were returned to their home cages to complete the 6-wk protracted abstinence period. Harris and AstonJones13 reported that the preference for a morphine-paired environment in formerly



211

dependent rats was maintained from 2–5 wk post-withdrawal. In fact, increased drugseeking behavior after a protracted term of abstinence was noted for several drugs of abuse.14 Likewise, in the present study, returning formerly dependent animals to the self-administration environment resulted in an initial doubling of the 24-hr response rate as compared with the last few days of self-administration. Extinction of enhanced lever-pressing activity came slowly, but self-administration levels were attained by day 7. The 24-hr access model described here provides a step closer in relevance to realworld conditions than studies that rely on one- or two-hour daily test sessions that often occur during the animals’ sleep cycle. Another important feature of the paradigm is that treatment interventions can be studied within the same model for each component of the drug abuse cycle: self-administration, dependence, withdrawal, protracted withdrawal, and renewed drug-seeking behavior. Figure 10.4 illustrates the days of administration for each treatment intervention (arrowheads) across the three regimens. The regimen outlined in the uppermost graph of Figure 10.4 permits the evaluation of treatment intervention administered during the self-administration phase on subsequent acute and protracted withdrawal behaviors. Note that the first treatment intervention occurs on day 9—the last day of the highest concentration self-administered. This paradigm is designed to examine the direct effect of treatment intervention on self-administration behavior. At the conclusion of day 10, self-administration is maintained over the following 5 days. Treatment intervention can continue to be administered up until the start of withdrawal at the end of day 14. This paradigm of interdiction after the development of physical dependence is more clinically relevant than beginning the treatment intervention simultaneously with the start of self-administration, though the latter paradigm can be used to assess the effects of treatment interventions designed to inhibit self-administration behavior. When treatment intervention is initiated at the start of the self-administration period, if lever responding is decreased, the expression of downstream withdrawal symptoms will automatically be reduced. Thus the regimen outlined in the upper graph of Figure 10.4 circumvents this limitation. The regimen outlined in the middle graph of Figure 10.4 permits the evaluation of treatment intervention during the acute withdrawal period on acute and protracted withdrawal behaviors. The regimen outlined in lowermost graph of Figure 10.4 permits the evaluation of treatment intervention during the protracted withdrawal period on protracted withdrawal behavior (contextually induced lever responding). Therefore, insight can be gained into the specificity of each treatment intervention on the component of the drug abuse cycle, and information can be obtained regarding the role of each preceding component on the expression of the subsequent components of the cycle.


212


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 40 41 42 43 44 45 46 47 48 49 Self-administration (Dependence)

Acute Protracted Withdrawal Withdrawal

Contextual Reinstatement (drug seeking)


Acute Protracted Withdrawal Withdrawal

Contextual Reinstatement (drug seeking)


Acute Protracted Withdrawal Withdrawal Contextual Reinstatement (drug seeking)

FIGURE 10.4 The phases of the drug-abuse cycle as provided by the 24-hr access model for self-administration. Arrows indicate the days in which a treatment intervention is administered.

REFERENCES 1. Deroche-Gamonet, V., Belin, D., and Piazza, P. V. 2004. Evidence for addiction-like behavior in the rat. Science 305:1014–17. 2. Vanderschuren, L. J. M. J., and Everitt, B. J. 2004. Drug seeking becomes compulsive after prolonged cocaine self-administration. Science 305:1017–19. 3. Koob, G. F., and Le Moal, M. 2001. Drug addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology 24:97–129. 4. Shalev, U., Grimm, J. W., and Shaham, Y. 2002. Neurobiology of relapse to heroin and cocaine seeking: A review. Pharmacological Rev. 54:1–42. 5. Aston-Jones, G., and Harris, G. C. 2004. Brain substrates for increased drug seeking during protracted withdrawal. Neuropharmacology 47(suppl 1):167–79. 6. Vorel, S. R., Liu, X., Hayes, R. J., Spector, J. A., and Gardner, E. L. 2001. Relapse to cocaine-seeking after hippocampal theta burst stimulation. Science 292:1175–78. 7. Fuchs, R. A., Tran-Nguyen, L. T. L., Specio, S. E., Groff, R. S., and Neisewander, J. L. 1998. Predictive validity of the extinction/reinstatement model of drug craving. Psychopharmacology 135:151–60.



213

8. Buccafusco, J. J., Marshall, D. C., and Turner, R. M. 1984. A comparison of the inhibitory effects of clonidine and guanfacine on the behavioral and autonomic components of morphine withdrawal in rats. Life Sci. 35:1401–08. 9. Marshall, D. C., and Buccafusco, J. J. 1985. A comparison of the cardiovascular and the behavioral changes following naloxone as measures of the degree of physical dependence on morphine in rats. Drug Devel. Res. 5:271–80. 10. Buccafusco, J. J. 1983. Cardiovascular changes during morphine withdrawal in the rat: Effects of clonidine. Pharmacol. Biochem. Behav. 18:209–15. 11. Zhang, L. C., and Buccafusco, J. J. 1998. Prevention of morphine-induced muscarinic (M2) receptor adaptation suppresses the expression of withdrawal symptoms. Brain Res. 803:114–21. 12. Buccafusco, J .J., and Bain, J. N. 2007. A 24-hour access i.v. self-administration schedule of morphine reinforcement and the estimation of recidivism: Pharmacological modification by arecoline. Neuroscience 149:487–89. 13. Harris, G., and Aston-Jones, G. 2003. Enhanced morphine preference following prolonged abstinence: Association with increased Fos expression in the extended amygdale. Neuropsychopharmacology 28:292–99. 14. Harris, G., and Aston-Jones, G. 2001. Augmented accumbal serotonin levels decrease the preference for a morphine associated environment during withdrawal. Neuropsychopharmacology 28:75–85.


Analysis 11 Operant of Fronto-striatal Function in Rodents Máté D. Döbrössy, Simon Brooks, Rebecca Trueman, Peter J. Brasted, and Stephen B. Dunnett CONTENTS 11.1 11.2

Introduction................................................................................................. 215 The Neuropathological and Behavioral Profile of HD ............................... 216 11.2.1 HD Pathology................................................................................... 216 11.2.2 HD Symptomatology ....................................................................... 217 11.3 Animal Models of HD ................................................................................ 218 11.4 Operant Conditioning and Operant Chambers ........................................... 220 11.4.1 Operant Chambers ........................................................................... 220 11.4.2 Operant Tasks to Assess Striatal Function in Rodents .................... 222 11.5 Operant Analysis of Motor Responding: Striatal Lesioned and HD Transgenic Animals .................................................................................... 223 11.5.1 Operant Analysis of the Sensory and Motor Aspects of “Sensorimotor” Striatal Neglect ...................................................... 223 11.5.2 Operant Tasks to Delimit the Specificity of Striatal Neglect .......... 225 11.6 Operant Analysis of Cognitive Tasks: Striatal Lesioned and Genetically Modified HD Models............................................................... 228 11.6.1 Delayed Matching Tasks.................................................................. 229 11.6.2 Delayed Alternation Tasks............................................................... 230 11.6.3 5-Choice Reaction Time Task.......................................................... 235 11.6.4 Serial Implicit Learning Task .......................................................... 236 11.7 Operant Analysis of Striatal Lesions: Deficits in Motivational State......... 238 11.8 Conclusion...................................................................................................240 References.............................................................................................................. 241

11.1

INTRODUCTION

The basal ganglia were once believed to function as part of an “extrapyramidal” motor system, operating separately from the pyramidal tract.1,2 However, this concept has been discarded for two fundamental reasons. First, the basal ganglia have been shown to be an intrinsic part of well-defined anatomical circuits that not only receive cortical input but also send projections, via the thalamus, back to those 215


216


cortical areas that control motor output. Second, a wealth of experimental work has shown that the striatum, the main input structure for the basal ganglia, can no longer be regarded purely as a “motor” structure. The observation that striatal damage could induce deficits in cognitive function led researchers such as H. Enger Rosvold and Ivan Divac to state that the striatum may reflect the function of those areas of neocortex that project to it.3 These pioneers investigating striatal function laid the foundation for the “functional loop” concept that proposes multiple, topographically arranged basal ganglia circuits that serve as substrates for motor, oculomotor, prefrontal, and limbic functions.4 The theory that the striatum may mediate a wide variety of functions reflecting its diverse cortical innervation has become evident in studies of patients with basal ganglia disorders. Thus, impairments in cognitive function are now well documented in patients with neurodegenerative diseases such as Huntington’s disease (HD) or Parkinson’s disease (PD), disorders which were once regarded as entirely “movement” related. Attempts to examine disease states such as HD in experimental animals can provide both insight into normal brain function and a means by which to assess potential therapeutic strategies. In either scenario, an operant analysis of behavior can prove particularly powerful. The detailed functional analyses that are permitted by operant paradigms not only allow more specific questions to be asked of normal brain function, but can also provide experimental paradigms that are extremely sensitive to brain insults and subsequent recovery.

11.2

THE NEUROPATHOLOGICAL AND BEHAVIORAL PROFILE OF HD

11.2.1 HD PATHOLOGY Originally reported by George Huntington in 1872,5 HD is a fatal inherited neurodegenerative disorder, the genetic basis of which has recently been identified.6 The predominant pathological signature of the disease is the early and progressive loss of GABAergic medium spiny projection neurons from within the striatum (caudate nucleus and putamen); however, anatomical changes in other regions have been described in preclinical stages of the disease.7 The degeneration begins in the caudate nucleus and progresses through the entire striatum in a medial-to-lateral and dorsalto-ventral fashion.8,9 Striatal degeneration involves, in particular, loss of the medium spiny projection neurons, with relative sparing of the large aspiny interneurons. There is post mortem evidence that the earliest striatal neurons affected are those in the striosomes, projecting to the substantia nigra pars compacta, and Hedreen and Folstein have proposed that more diverse striatal projections via this nigral feedback are an essential component in the spread of the disease.10 As the disease progresses, striatal atrophy, gliosis, and cell loss becomes progressively more marked, which has been characterized by Vonsattel in a widely used five-point grading system.8 In advanced disease, not just the striatum but widespread areas of the forebrain—in particular areas such as the neocortex or substantia nigra pars reticulata that are sites of afferent and efferent connections with the striatum—also undergo atrophy


Operant Analysis of Fronto-striatal Function in Rodents

217

and cell loss. Other changes accompanying the disease include loss of overall brain weight and ventricle enlargements. One of the pathological hallmarks of HD is the appearance of nuclear aggregates containing a truncated fragment of the expanded mutant polyglutamine repeat of the huntingtin protein. The gene and its protein product have been the subject of a great wealth of research since its discovery in 1993; nevertheless, the mechanism of its toxicity remains yet unresolved.6 Transgenic models of the disease replicate the formation of abnormal nuclear inclusions of N-terminal truncated fragments of huntingtin,11–14 which have now been confirmed as being widely distributed in the brains of affected individuals.15 However, previously thought of as a predictor of cellular dysfunction, the balance of evidence currently points to the truncated huntingtin fragment containing aggregates as a consequence of the disease process, rather than a cause, and some even argue that they might be neuroprotective.16 Evidence is growing that the mutant form of huntingtin is directly responsible for the disruption of a wide range of essential cellular processes, including transcription and the transport of trophic support to the striatum, protease cascades, and mitochondrial energy metabolism.17

11.2.2 HD SYMPTOMATOLOGY The uncontrollable movements (or “chorea”) that characterize HD are now recognized to be only one part of the disease’s behavioral profile. In fact, HD presents with a triad of motor, cognitive, and affective symptoms, all of which worsen as the disease progresses inexorably, in parallel with the progress of the underlying degeneration. Indeed, the introduction of genetic screening in conjunction with more sensitive imaging and clinical tests has led to the suggestion that subtle cognitive and psychiatric aspects of the disease are apparent before the onset of chorea.7,18 A large multi-center longitudinal study, PREDICT-HD, is now in progress with the aim of characterizing early, preclinical, and presymptomatic anatomical, motor, and cognitive changes in patients that carry the expanded mutant form of the huntingtin gene. The aim of the study is to promote better design and outcome measures for preventive clinical trials in HD.19 The most striking aspect of HD is the chorea that originally gave its name to the disorder, until the diverse nature of impairments in HD was acknowledged. However, these unwanted choreic actions often mask an underlying bradykinesia, and deficits in initiating responses in reaction time paradigms20,21 are indicative of impairments in initiating and selecting motor programs. Consequently, it is now recognized that both hypokinetic and hyperkinetic symptoms coexist in HD.22–24 Almost four decades ago, Divac proposed that the striatum has a role in both motor and higher order functions,25,26 and it has now become widely accepted that HD patients express a profile of cognitive and neuropsychological deficits similar to that seen in patients with prefrontal cortical damage.27,28 This includes impairments in learning29,30 and working memory,30,31 as well as deficiencies in “executive” tasks that assess planning and attentional control.31,32 A number of psychiatric symptoms are also present in HD, such as depression and anxiety.33


218

11.3


ANIMAL MODELS OF HD

HD is a uniquely human predicament and the experimental exploration of the disease, and of potential therapies, necessitates access to animal models. Numerous models are available. However, the advantages and disadvantages of each needs to be understood so that the appropriate model is used to shed light on particular questions.34 By recreating a milieu in experimental animals that resembles the pathology of diseases such as HD, we can attempt to define the specific functional role of particular neural mechanisms more precisely than can be achieved in the human condition. These animal “models” of human disease can also provide a basis for assessing potential strategies for repair (e.g., neural transplantation, neuroprotective agents, or gene therapy) by giving rise to measurable changes against which the functional efficacy of any particular strategy can be evaluated. The behavioral impact of striatal damage on motor and cognitive function, as well as the motivational state, can all be examined experimentally in the rat and the mouse. The two main classes of rodent models currently being used to investigate fronto-striatal function in HD, induced lesion (excitotoxic and metabolic toxins) and genetically modified models, are the subject of a brief analysis below. Striatal function was initially studied in experimental animals with the use of basal ganglia lesions.2,35 However, there were major difficulties in interpreting the consequences of lesions made by electrolysis, radiofrequency, or direct surgical excision because of the inevitable damage to the immediately adjacent afferent and efferent fibers of the internal capsule connecting the cortex to subcortical structures including the thalamus. However, this changed dramatically with the introduction of excitotoxic lesions in the mid 1970s, opening the way for the modern era of basal ganglia research. The primary excitotoxins are amino acids (such as monosodium glutamate, N-methyl-D-aspartic acid and kainic acid), which are glutamate agonists that can be toxic above physiological doses by acting on glutamate-receptor-bearing neurons, a feature of most neurons of the nervous system. When administered directly into the striatum, excitotoxins specifically target and kill neurons within the striatum without damaging the axons of the corticofugal and corticopetal pathways passing through and adjacent to the striatum. Furthermore, injections of excitotoxins into the striatum produce neurochemical and pathological changes similar to that seen in HD. Initially kainic and ibotenic acid were used for this purpose.36–38 However, quinolinic acid has become the toxin of choice on account of numerous neurochemical studies that demonstrate a more selective neuronal loss within the striatum, with the medium spiny GABA neurons being particularly vulnerable, and the large aspiny cholinergic, neuropeptide Y and NADPH-diaphorase–positive interneurons being relatively resisitant to this toxin, corresponding to the profile of degeneration observed in HD.39–41 While a single neurotoxic insult is able to mimic the neuropathology of HD, it cannot reproduce the slow and progressive degeneration that is a characteristic feature of the human disease. These features can be better mimicked by metabolic toxins, such as 3-nitropropionic acid, which target the striatal neurons selectively, even when administered peripherally.42,43 Nevertheless, excitotoxins continue to be widely



219

used because of the fact that they typically produce more convenient, consistent, and reproducible lesions than appear achievable with the metabolic toxins.44 The identification of the mutant huntingtin gene has permitted the production of genetically modified animal models, predominantly, but not exclusively, based on mice, and include transgenic, knock-in, knockout, and virally inserted polyQ tract models.34 These models have the potential to be more authentic to HD on the grounds that any neuropathology and behavioral deficits are caused by the expression of the mutant huntingtin gene, and the onset of the “disease state” is progressive. However, there are significant differences between models of genetically modified animals regarding both behavioral and cellular consequences of the expression of the mutant gene, the rate of onset of the pathology, the distribution pattern of the inclusions, the degree of neuronal death, and the expected life span of the animals. The variability between models is attributed to several factors, including the diverse length of the CAG repeat present on the mutant huntingtin gene, whether an exon 1 or the full length insert is used, and the technical method used for the insertion of the repeat, as well as the characteristics of the specific background strain used to generate the animal model. As a consequence, the suitability of the genetically modified model will depend on the issues on which the investigator is focusing. For example, studying the process of formation and modification of the nuclear inclusions, or the changes in energy metabolism induced by the mutant huntingtin protein, or the subsequent behavioral consequences, might require a different HD animal model. The best characterized transgenic mouse models are the R6/2 lines generated by Gill Bates and colleagues.45 These mice show a clear profile of motor and cognitive deficits.46,47 However, the broad extra-striatal profile of the pathology and very rapid progression of the disease48 make detailed analysis of the behavioral impairment difficult. By contrast, the knock-in models show a slower, more progressive impairment, often with focal striatal pathology, making them more suitable for detailed analysis of specific cognitive deficits. The best characterized knock-in mouse in our hands for behavioral studies is the HdhQ92/Q92 (Q92) mouse. These knock-in mice have 90 CAG repeats inserted into their endogenous huntingtin gene sequence resulting, on average, in 92 glutamine repeats.49 The animals develop nuclear inclusions and behavior impairments, which are the subject of further discussion later on in the chapter. The destruction of striatal cells in genetically modified models or with excitotoxins not only produces some of the pathological hallmarks of HD, but can also give rise to behavioral sequelae, which reflect many of the symptoms seen clinically. Both approaches have advantages, and the use of one should not exclude the other. The first use of excitotoxins to model the pathology of HD showed unilateral striatal lesions to induce a marked rotation towards the ipsilateral side 48 hr after surgery.38 This motor asymmetry reflected the inability of the lesioned striatum to mediate contralateral movement, and this biasing of motor output to the side ipsilateral to the lesioned striatum is evident in many indices of striatal dysfunction such as amphetamine-induced rotation50,51 or the elevated body swing test.52 An additional advantage of unilateral striatal lesions is that they can allow a within-subject analysis of dysfunction and recovery. Paw-reaching,53,54 as well as several of the operant tasks elaborated below, typically take advantage of this asymmetry and allow performance mediated by the intact striatum to be compared with performance that


220


is under the control of the lesioned striatum. However, this laterality of motor function is less applicable in tests of cognitive function or motivation, and paradigms that assess these aspects of behavior typically employ bilateral lesions. On the other hand, the main advantage of some of the genetically modified models is that they offer a more mechanistic understanding of the abnormalities of HD by reproducing specific aspects of the pathogenetic process of the human disease. Studying the onset, the progression, and the severity of the behavioral consequences of the disease, in conjunction with the cellular and molecular events in the genetically modified HD models will promote understanding of the relationship between mechanism of cell death, the expanded polyglutamine repeat, the formation of intranuclear inclusions, and the behavioral symptoms.

11.4

OPERANT CONDITIONING AND OPERANT CHAMBERS

Although many standard tests, such as rotation, can provide a useful index of functional capacity, it is often desirable to examine a subject’s ability to perform an action, or series of actions, that is more purposeful, or goal directed. Thus, rather than assess a general and poorly defined motor capacity, one can examine the capability of an animal to produce specific motor responses that are required to achieve a particular outcome. Operant conditioning refers to this ability to train animals to perform purposeful actions, and the underlying learning processes involved. In an operant task, a subject learns to respond in a particular way to gain reward (or to avoid punishment) when a discrete cue, or stimulus, signals that this response will be positively reinforced. The principal advantage of modern operant testing is the absence of interference from the investigator, as the tests are conducted in isolated, soundproof boxes controlled by a computer. As it is the investigator who designs the computer program, and hence the task, the variety of paradigms one can use are almost without limit. Furthermore, operant tasks also permit the collection and study of a large number of response parameters, enhancing the analysis of the behavioral performance.

11.4.1 OPERANT CHAMBERS A standard operant chamber will typically contain: • The operandum, such as a lever, on which an animal can “operate,” i.e., act on or respond to. • Reinforcers, stimuli that increase the likelihood of responding. Animals may either act to obtain positive reinforcers (e.g., food or water), or alternatively they may act to terminate or postpone negative reinforcers (e.g., electric shock). • Discriminative stimuli, typically lights, sounds, or olfactory cues, the properties of which signal the timing and location of reinforcers and thereby control the animal’s responding.



221

FIGURE 11.1 Schematic illustration of a two-retractable lever operant chamber (Skinner box).

The operant chamber is an automated apparatus designed to present discriminative stimuli (e.g., lights that differ in color, location, or intensity) to record and measure responses to the operanda (e.g., presses of the lever, presses of the panel covering the food well, licks at a drinking tube) and deliver reinforcements (e.g., by operating a dispenser to deliver food pellets). The contingencies for particular experiments can be specifically included in the software running the task. The classic test apparatus for evaluating operant behaviors is the Skinner box, an automated test apparatus first devised and developed by B. F. Skinner when analyzing the behavior of rats responding to obtain food reward.55 As illustrated in Figure 11.1, a typical Skinner box provides one or two levers as operanda to which the rat may respond. The timing of responding into discrete trials can be achieved by making the levers retractable and only available at discrete points within the trial. Discriminative stimuli are provided by a variety of different lights located above the levers, above and within the food hopper, and in the roof of the test chamber. A loudspeaker in the chamber can also present auditory stimuli either as white noise or discrete tones of controlled frequency and intensity. A variety of different reinforcers can be built in. This is most typically either a dispenser to deliver food pellets or a liquid dipper to present water into the reward chamber. These will only be effective if the animal is suitably motivated by hunger or thirst, achieved by some hours of food or water deprivation, respectively, prior to the training session. However, other reinforcers are also possible, such as presentation of a receptive female rat to a male rat in studies of hormonal control of sexual motivation.56 An alternative type of operant chamber that has proved highly effective, in particular for mice, is the nine-hole box (9-HB) (Figure 11.2). The 9-HB is conceptually


222

Methods of Behavior Analysis in Neuroscience, Second Edition Stimulus Lights

Photocell Detectors

Well Blanks

Food Well

FIGURE 11.2

Schematic illustration of the nine-hole box operant chamber.

similar to the standard Skinner box except that instead of levers, the box is supplied with an arc of nine square-shaped holes. Discriminative stimuli are provided by lights at the rear of each hole, responses (nose pokes) are monitored by infrared beams at the entrance to each hole, and food pellets or liquid reinforcements are delivered to a well positioned at the rear of the chamber. Rats typically investigate stimulus lights associated with food reward by producing a nose poke into individual holes, which is arguably a more ethologically natural action for a rat than pressing or releasing a lever. Although originally designed to assess attentional function, the physical configuration of the apparatus in the 9-HB allows great specificity in defining both stimuli and responses, and this has allowed for the laterality of motor function evident in structures such as the striatum to be analyzed with great precision (see below). Operant chamber paradigms enable far more precise control of the factors determining behavior than can be achieved by conventional observational and hand testing methods. Using different stimuli to signal the class of responses that will be reinforced, it is possible determine the nature of the sensory discriminations that an animal can make, and subsequently its performance on cognitive tasks, as well as the effects of changes in reward value or magnitude.

11.4.2 OPERANT TASKS TO ASSESS STRIATAL FUNCTION IN RODENTS Tasks that are administered in operant chambers usually require animals to perform a number of intermediate training sessions before they are able to perform the task in full. Since it is important to design and use tasks correctly to assess different specified functions, the rationale for a variety of tasks that assess striatal function



223

is outlined below. Reference is made to those sources that contain more detailed descriptions of how to accomplish individual behavioral tasks. Behavioral testing in operant chambers allows both a high degree of experimental control and a detailed and thorough behavioral analysis. Consequently, operant conditioning has proved to be a valuable way in which to assess cognition, motor function, and motivation in the rat. Simple operant responses, such as pressing a lever to gain food reward, are unaffected by striatal lesions or in transgenic animals.57,58 In addition, due to the capacity to precisely control spatial and visual cues, more elaborate schedules requiring conditional responses are also possible.59,60 However, more complex operant tasks turn out to reveal subtle but specific and robust behavioral impairments in many functional domains in animals with striatal damage. Indeed, it is often not possible to even detect, let alone to precisely define, the nature of such impairments with alternative observational or manual testing methods.

11.5

OPERANT ANALYSIS OF MOTOR RESPONDING: STRIATAL LESIONED AND HD TRANSGENIC ANIMALS

The unilateral disruption of striatal function, either through targeting the striatal projecting neurons or through depletion of striatal dopamine by central injection of 6-OHDA, is known to cause a general sensorimotor impairment on the side contralateral to the lesion. This impairment takes the form of an ipsilateral rotation,61 clumsy and inefficient use of the contralateral paw,62–64 and also a failure to respond to stimuli that are presented to the side of the rat contralateral to the lesion,65 a phenomenon that has been named “striatal neglect.” This syndrome of impairments has many similarities to the “sensorimotor” syndrome produced by electrolytic lesions of the lateral hypothalamus.66,67 Marshall and colleagues suggested in the 1970s that the neglect that resulted from electrolytic lesions of the lateral hypothalamus might in fact be the product of damage to the nigrostriatal projection.64 Thus, tasks that used lateralized stimuli and responses that were first introduced to define the precise nature of deficits resulting from hypothalamic lesions66,68 came to influence subsequent behavioral paradigms that sought to analyze nigrostriatal and striatal function. Assessing lateralized behavioral deficits in operant tasks can provide the most sensitive within-subjects dependent variables in the context of unilateral lesion models. However, transgenic animals show bilateral striatal pathology and symptoms where the overall level of performance compared to the controls provides the main between-subjects dependent variables.

11.5.1 OPERANT ANALYSIS OF THE SENSORY AND MOTOR ASPECTS OF “SENSORIMOTOR” STRIATAL NEGLECT Carli and others sought to distinguish the sensory and motor aspects that constituted the sensorimotor components of striatal neglect by designing a visual choice reaction time task in the 9-HB apparatus that allowed the spatial location of the discriminative stimuli and conditioned responses to be separated.69,70 In this task, only the central three holes were exposed, the remaining holes being covered with a masking plate (Figure 11.3). Two groups of rats were trained to make a sustained nose poke


224


Hold

Detect

Withdraw (RT)

Move (MT) Correct Error

SAME

Error

OPPOSITE

Correct

FIGURE 11.3 Schematic illustration of the SAME and OPPOSITE versions of the Carli choice reaction time task. In addition to measures of accuracy and response bias, the speed of initiating (reaction time) and executing (movement time) of correct responses to the two sides are also recorded. Source: Carli, M., Evenden, J. L., and Robbins, T. W. 1985. Depletion of unilateral striatal dopamine impairs initiation of contralateral actions and not sensory attention. Nature 313:679–82.

into the middle of the three holes for a variable period until the presentation of a brief light cue, which flashed unpredictably in one of the side holes, either to the left or the right of the center hole. Rats had to make a rapid lateralized nose-poke response in order to gain food reward, but the rule defining a correct response was different for the two groups. The rats of one group were required to make a nose poke into the same response hole at which the stimulus was presented (the “SAME” condition), whereas the rats of the second group had to respond on the side that was not signaled (the “OPPOSITE” condition). For animals trained in the SAME condition, because of the crossover of connections between the brain and the periphery, we would predict that unilateral lesions— whether of the dopamine system or the striatum itself—would produce deficits on the contralateral side of the body. This is equally true whether the deficit is sensory, motor, or associative in nature. However, the dissociation between the location of the stimuli and the response holes in the OPPOSITE condition allows differential predictions of the outcome depending on the nature of the underlying deficit. Thus, if the animals have a sensory impairment in the detection of the stimuli, then we would expect the rats with unilateral lesions to be impaired making an ipsilateral response to a contralateral stimulus, whereas a response to an ipsilateral stimulus would be unaffected. Conversely, if the deficit was primarily in the selection or initiation of motor response, then we would expect the animal to be impaired making a contralateral response to an ipsilateral stimulus, but be unimpaired in responding on the



225

ipsilateral side even though the discriminative stimuli are presented in contralateral space. Carli and colleagues70 reported that in both the SAME and the OPPOSITE condition, rats were impaired in effecting responses to the side contralateral to the lesion, while neither group was impaired in producing ipsilateral responses (Figure 11.4). This pattern of impairments was not consistent with either a sensory impairment or a sensorimotor integration deficit; rather, the ipsilateral bias induced by unilateral striatal dopamine depletion was interpreted as a bias in responding. The extent of this ipsilateral bias has subsequently been shown to correlate with the extent of dopamine depletion within the striatum.71 Furthermore, the pattern of results suggested that the general motor deficits reported following striatal damage may be caused by an increase in the latency to execute responses to the contralateral side. However, a detailed analysis of this action showed that contralateral movement was not uniformly impaired. The time taken to execute a response is considered to have two components: “reaction time,” defined as the latency to initiate a response by withdrawing the nose from the central hole (which therefore contains no lateralized component), and the “movement time,” defined as the subsequent latency to complete the lateralized nose poke response into the response hole. Animals with unilateral striatal damage, including nigrostriatal lesions, are particularly impaired in the reaction time.69–71 This indicates that the deficit is attributable to an impairment in the planning, selection, or initiation of the lateralized response rather than in its execution, suggesting an “executive” impairment, similar to that seen after frontal lesions, rather than a pure motor deficit per se.

11.5.2 OPERANT TASKS TO DELIMIT THE SPECIFICITY OF STRIATAL NEGLECT The study of Carli et al.70 demonstrated that unilateral striatal damage impaired animals in responding toward their contralateral side, while at the same time showing that, once initiated, movements made in contralateral space were not impaired. This suggested that if the motor actions that comprised the response itself were not themselves impaired, perhaps the striatum was more involved in some more abstract elements of responding that influence motor output at an early stage of response preparation. For example, it was possible that the coordinate frame in which responses are organized were disrupted by striatal damage.72 We therefore sought to modify the experimental design to define the basis of this “response space”; what is the “contralateral” deficit seen in striatal neglect actually contralateral to? The nature of this neglect has been quantified using both unilateral lesions of the nigrostriatal dopamine neurons and excitotoxic lesions of intrinsic striatal neurons. Animals were trained to perform two discriminations, independently, on alternate days. As in the Carli et al.70 study, the task comprised a central hole and two response holes. However, unlike the Carli et al.70 study, both response holes were on the same side. So, on one day, animals were required to respond to the two holes on the left, and on the next day to the two holes on the right (Figure 11.5).73 All responses required rats to detect a stimulus light in one of the two response holes, and to make a nose poke response in the same hole. Once trained, animals received unilateral striatal lesions with central injections of quinolinic acid.


226


100

Ipsilateral Response Contralateral Response

% Contralateral Bias

% Correct Responses

75

50

25

0

Pre-op Post-op

100

75

50

25

0

Same Opposite Accuracy (a)

Reaction Time (sec)

1.00

Same Opposite Contralateral Response Bias (b)

Ipsilateral Response Contralateral Response

0.75

0.50

0.25

0.00

Same Opposite Reaction Time (RT) (c)

FIGURE 11.4 Unilateral 6-hydroxydopamine lesions of the nigrostriatal pathway produces marked deficits in initiating action (reaction time) specifically for contralateral responses in the Carli task. (a) Postoperative accuracy of responding to the ipsilateral and contralateral sides in the SAME and OPPOSITE task contingencies; (b) Degree of contralateral response bias preop and post-op; (c) Postoperative reaction times to initiate ipsilateral and contralateral responses in the SAME and OPPOSITE task contingencies. Source: Data from Carli, M., Evenden, J. L., and Robbins, T. W. 1985. Depletion of unilateral striatal dopamine impairs initiation of contralateral actions and not sensory attention. Nature 313:679–82.



227

Hold

Detect

Withdraw (RT)

Respond (MT)

Error !!

FIGURE 11.5 Schematic illustration of the Brasted lateralized choice reaction time task in the nine-hole box. Source: Brasted, P. J., Humby, T., Dunnett, S. B., and Robbins, T. W. 1997. Unilateral lesions of the dorsal striatum in rats disrupt responding in egocentric space. J. Neurosci. 17: 8919–26.

When testing resumed a week later, the lesioned rats showed a severe impairment responding on the contralateral side. This impairment took the form of a marked bias toward the “near” hole, i.e., the hole closer to the center, when the holes were on the side contralateral to the lesions. This “response bias” was so severe that lesioned animals were rarely able to produce responses to the “far” hole on the contralateral side. In stark contrast to this impairment, lesioned rats were able to respond efficiently and correctly when the holes were on the side ipsilateral to the lesion.73 The design of this operant task allowed a specific comparison to be made between two specific hypotheses concerning the nature of a striatally mediated “response space.” If responses were coded relative to an external reference within the animals’ environment (allocentric coding) then animals would be expected to always neglect the relatively contralateral hole, regardless of which side of the space the holes were presented. Allocentric coding is often seen in perceptual neglect, when patients with cortical lesions neglect the contralateral side of an object, regardless of where the object is located in space.74,75 In this task, an allocentric-based deficit would manifest itself as a bias toward the far hole when the task is performed to the ipsilateral side, and a bias toward the near hole when the task is performed to the contralateral side. Alternatively, if responses were coded with respect to the subject’s body (egocentric coding), then one would predict responding to be disrupted only on the contralateral side. The data clearly show that striatal neglect is not seen uniformly in all parts of space, but is restricted to the contralateral side and thus consistent with the latter, egocentric hypothesis. When responding to the ipsilateral holes, animals showed no evidence of biasing their responding toward the far (i.e., relatively contralateral) hole.


228


Control rats Unilateral striatal lesions Near Hole Bias (%)

100

80 70 60 50 40 ipsi contra Pre-lesion

ipsi contra Post-lesion

FIGURE 11.6 Unilateral striatal lesions produce a marked postoperative ipsilateral response bias, which is more marked for discriminations on the contralateral than on the ipsilateral side. Source: Data from Brasted, P. J., Humby, T., Dunnett, S. B., and Robbins, T. W. 1997. Unilateral lesions of the dorsal striatum in rats disrupt responding in egocentric space. J. Neurosci. 17: 8919–26.

In contrast, animals were markedly impaired when performing on the contralateral side and were completely unable to select responses to the far (i.e., relatively contralateral) hole (Figure 11.6). A similar impairment was seen in studies that examined unilateral striatal dopamine lesions using a between-subject design.72

11.6

OPERANT ANALYSIS OF COGNITIVE TASKS: STRIATAL LESIONED AND GENETICALLY MODIFIED HD MODELS

Rosvold’s experimental work in the 1950s seriously challenged the concept of the striatum as a structure involved purely in motor function. Based on the topographical nature of projections from the prefrontal cortex to the caudate nucelus, it was shown that caudate lesions in monkeys produced impairments on the same tasks that were known to be sensitive to frontal lesions.3 In particular, bilateral lesions of the caudate nucelus were seen to impair accuracy on Jacobsen’s classic tasks of frontal function designed to assess spatial working memory, such as spatial alternation and delayed response.76,77 A corresponding functional organization was demonstrated in the rat only when the prefrontal cortex came to be defined in terms of the projection areas of the mediodorsal nucleus of the thalamus—namely the medial and orbital walls of the frontal cortex rather than the pole of the frontal lobe, as had previously been assumed.78,79 Lesions in the rostral medial striatal areas that were innervated by the medial wall prefrontal cortex again produced deficits in delayed alternation and spatial navigation tasks.80–82 It is these advances in functional neuroanatomy, as well as the neuropsychological deficits reported in basal ganglia disorders such as HD and



229

PD, that provide the theoretical foundation for operant tasks designed specifically to assess the impact of striatal lesions on cognitive function.

11.6.1 DELAYED MATCHING TASKS The automation of delayed matching procedures represented one such attempt to assess the impact of striatal lesions on working memory. This requires an animal to be presented initially with a sample stimulus, and then after a variable delay, to be presented with a choice between two stimuli, one being the earlier sample and the other novel. Memory of the earlier stimulus presentation is then tested by requiring the animal to choose either the initial sample (delayed-matching-to-sample) or the novel stimulus (delayed-non-matching-to-sample). A correct response results in the delivery of food reward, whereas an incorrect response is signalled by a timeout or some other error signal. The introduction of a variable delay between sample presentation and choice response allows the rate of forgetting to be determined from the plot of decline in choice as the length of the delay interval increases. DMTS was first developed for assessing memory in primates and required monkeys to discriminate between objects primarily on the basis of the visual properties (e.g., shape, color) of objects.83 Procedures for rats, however, can require animals to discriminate between objects in a maze84 or between different odors. Alternatively, choice discriminations can be made in the spatial modality, and this has led us to develop a delayed-matching-to-position (DMTP) task for use in rats.85,86 Animals are trained in standard two-retractable-lever Skinner boxes (Figure 11.1). On each trial, one of the two retractable levers is inserted into the chamber as the sample, which the rat must press to register. The lever is then retracted and the rat must press the central panel until, after a random variable delay period, the next panel press causes both levers to be extended back into the chamber. A correct matching response on the same lever as that produced in the sample stage is rewarded with the delivery of a food pellet, whereas an incorrect response to the other lever results in a timeout (all lights are turned off for a short period to signal an error). After a further short interval, the next trial commences. Delayed-matching-to-sample is sensitive to prefrontal cortex (PFC) damage in primates.87–89 Consequently, we have developed DMTP to investigate the comparative contributions of the medial PFC and medial striatum in a working memory task in rats. Cortical lesions that are restricted to the anterior medial PFC result in a progressive deficit such that accuracy is increasingly impaired at progressively longer delays.90 This delay-dependent pattern of impairment suggests a rather specific disturbance in short-term memory. However, larger lesions that extend into the anterior cingulate cortex produce a broader impairment at all delays, reflecting a more generalized deficit in the animal’s ability to perform the matching rule (Figure 11.7).90 Similarly, when we looked at impairments following striatal lesions, lesions in the ventral striatum (which receives restricted prefrontal inputs) exhibited a clear delaydependent deficit, whereas lesions in the dorsal striatum (which receives cingulate as well as frontal inputs) disrupted animals’ performance at all delays.90–92 These studies illustrate, first, the way in which an operant task may be designed to tap discrete aspects of cognitive function—in this case short-term working mem-


230


Controls Prefrontal cortex lesion Neostriatal lesion Ventral striatal lesion

100

% Correct

90 80 70 60 50 0

2

4

8 12 Delay Interval (sec)

18

24

FIGURE 11.7 Prefrontal cortex and dorsal and ventral striatal lesions produce marked deficits on the DMTP task. Note that while prefrontal and ventral striatal lesions produce a delaydependent deficit, the neostriatal lesions induce a more global deficit at immediate as well as long delays. Source: Data from Dunnett, S. B. 1990. Role of prefrontal cortex and striatal output systems in short-term memory deficits associated with ageing, basal forebrain lesions, and cholinergic-rich grafts. Can. J. Psychol. 44:210–32.

ory—and second, that selective lesions within the fronto-striatal circuitry yield distinctive patterns of cognitive deficit associated with the particular cortical loop(s) disturbed.

11.6.2 DELAYED ALTERNATION TASKS The spatial delayed alternation task (DA) is another task that involves short-term working memory and requires animals to alternate their responding between two spatially distinct locations. Like the DMTP task, it is very sensitive to damage of the medial PFC. Indeed, deficits in delayed alternation in Wisconsin boxes (for monkeys) and in T-mazes (for rats) was one of the defining features of the prefrontal deficit described by Jacobsen in his classic primate studies in the 1930s93,94 and replicated since.30 Rats similarly exhibit clear deficits in delayed alternation after prefrontal lesions when tested in a T-maze.92,95,96 There have been several attempts to adapt this classic task to the operant box,97– 100 although with varying degrees of success. In our adaptation,101 rats are trained to press the centrally located food panel until the end of a variable delay period (5–20 sec). A panel press subsequent to the end of the delay period results in the extension of both the left and the right levers. On the first trial of the day, pressing either lever produces a food pellet reward. On all subsequent trials, the rat is required to press the lever that was not pressed on the previous trial (Figure 11.8). A correct press is rewarded with a food pellet, whereas an incorrect press (repetition of the same



231

$)')' " $)'+"( $%"+'(%'" )( '())' "&'($)%)"+'( ')'(&%$(")%'','

%'')'(&%$( " +'%%&"") &$"" )%$ , )*$) "$%(&%! $)')' " $)'+"( $%"+'(%'" )( $"" )%$ &)$%(&%!( (*"%+'/(

&( &$"" )%. "+'(-)$

&&%( )'(&%$( &$"" )%$" +'','

#'(&%$( """ )(%.) #%*)

&$(%$%'') %'''%''(&%$(

-) $)')' " $)'+" $%"+'(%'" )(

FIGURE 11.8 Schematic illustration of the delayed operant spatial alternation test in a tworetractable-lever Skinner box.

lever as on the previous trial) has no consequence. In either case, after pressing one lever, both levers are withdrawn and the timer for the next variable delay interval is started. The distinctive feature of our variant of operant-delayed alternation, as in the DMTP/DNMTP task described above, is that the animal is required to nose poke at the central panel during the delay in order to trigger presentation of the two choice levers. This serves to keep the rat centralized between the two response locations and reduces the opportunity for it to adopt a simple mediating response strategy during the delay (i.e., simply waiting at the location where the correct lever will next appear). We vary the delay interval on each trial and thereby accumulate information about the animal’s level of accuracy over different lengths of time that the last trial response must be held in memory. In recent studies we have begun to investigate differential roles of the PFC and the medial aspect of the striatum in this task. We find that lesions both of the medial prefrontal cortex (mPFC) and of the medial striatum disrupt performance on this task (Figure 11.9A). However, detailed analysis of the impairments suggest slightly different reasons for the deficit after each lesion.101 In particular, the mPFC animals exhibit a relatively straightforward impairment in task accuracy that may be related to an executive deficit in determining the correct response based on short-term


232


A. Previous Trial Correct

Correct (%)

90

Control Prefrontal lesions Striatal lesions Chance (50%)

80 70 60 50 40

B. Previous Trial Incorrect

Correct (%)

90 80 70 60 50 40 Pre-lesion

Post-lesion

Probe Trials

FIGURE 11.9 Prefrontal and striatal lesions both produce a marked decline in response accuracy in the operant delayed alternation test. The upper and lower panels illustrate choice accuracy depending on whether the previous trial was correct or incorrect. While the prefrontal lesions induced a similar deficit on all trials irrespective of performance on previous trials, the striatal lesions induced a deficit whereby a deficit on the previous trial increased the chance of a deficit on the present trial. This is directly against an interference effect between trials and suggests a perseverative tendency of the rats with striatal lesions. Source: Data from Dunnett, S. B., Nathwani, F., and Brasted, P. J. 1999. Medial prefrontal and neostriatal lesions disrupt performance in an operant delayed alternation task in rats. Behav. Brain Res. 106:13–28.

memory for the last response. By contrast, the rats with the striatal lesions exhibit a tendency to preseverate their responses. Thus, for example, if we analyze the errors from trial to trial, whereas the conditional probability of an error on a particular trial is, after prefrontal lesions, independent of how the animal performed on the previous trial, the chance of an error (involving repetition rather than alternation of the previous response) after a striatal lesion increases as the animal makes a run of errors in a row (Figure 11.9B). It is worth noting that this pattern of errors is quite different from that which would be expected if the animals’ deficits were caused by a memory failure, for example by an increased susceptibility to proactive interference. Furthermore, analyses of other behavioral measures indicate that the time taken to collect food reward is unaffected, suggesting that neither a general motor deficit nor a motivational deficit are the basis for these impairments.


Operant Analysis of Fronto-striatal Function in Rodents Midline knife-cut lesions

90

Unilateral striatal lesions

233 Ipsi/contra prefrontal lesions

Accuracy (%)

80

70

60 Controls Single striatal lesions

50 4

8 12 16

Lpsilat double lesions Crossed double lesions

20 24 28 32 36 40 44 48 52 56 60 Test Days (in 2-day blocks)

64 68 72 76 80

FIGURE 11.10 Delayed alternation performance accuracy over the period of initial training and recovery after midline knife cut lesions in all rats, after additional unilateral striatal lesions, and after further lesions of the ipsilateral or contralateral prefrontal cortex. All animals rapidly recovered after each of the first two surgeries. The effects of double lesions depended on the side of the second, prefrontal cortical lesions: those rats receiving lesions in the hemisphere contralateral to the earlier striatal lesions (crossed lesions) exhibited lasting impairments, whereas lesions in the same hemisphere (ipsilateral lesions) produced no impairment. Source: Data from White, A., and Dunnett, S. B. 2006. Fronto-striatal disconnection disrupts operant delayed alternation performance in the rat. Neuroreport 17:435–41.

Thus, the range of measures of different aspects of task performance allow not only a dissociation between different lesions—even though they all disrupt task performance—but also the beginnings of an analysis of the precise nature of the functional impairment that results following disturbance of each neuroanatomical component in a connected fronto-striatal circuit. The role of the fronto-striatal/cortico-striatal system in mediating the performance in delayed alternation was recently further tested by using a crossover lesion paradigm.102 A midline transection of the corpus callosum was made to separate the hemispheres, followed by crossed lesions of the striatum on one side and the PFC on the other side. This crossover lesion produced a significant and long-term deficit in delayed alternation. Detailed analysis showed that the double-lesion affected the working-memory aspects of cortico-striatal function in a delay-dependent fashion, without effecting response bias. Interestingly, in a control group in which similar striatal and cortical lesions were made but on the same side, the intervention had little detectable effect. The crossover lesion disrupted the cortico-striatal system completely, while the same side double-lesion retained the system intact on one side. This disconnection paradigm elegantly demonstrated that efficient performance on


Methods of Behavior Analysis in Neuroscience, Second Edition A Trial Numbers

Trials Initiated (n)

250

Wild-type mice Q92 Transgenics

200 150 100

B Accuracy

100 80 60 40

50

20

0

0

Percentage Correct (%)

234

FIGURE 11.11 Delayed alternation testing of the Q92 mouse model. When tested on the delayed alternation task, with no delays present, the knock-in Q92 (Hdh Q92/Q92) mice initiated fewer trials compared to their wild-type littermates (A) and exhibited a severe deficit in performance accuracy (B). Source: Data produced by Rebecca Trueman.

the classical prefrontal delayed alternation task is dependent upon an intact corticostriatal system (Figure 11.10). The delayed alternation paradigm has also been used to investigate the Q92 mouse model of HD, in this instance using mouse nine-hole operant chambers. To adapt the task for these boxes the mouse is required to respond to the illuminated center hole (hole 5), until this hole is extinguished and two lateral lights are illuminated (hole 3 and 7; the remaining 6 holes are blocked). The center hole therefore acts like the panel in the Skinner boxes to try to reduce any mediating response strategies that the mouse may make, and the lateral lights act as levers with the mouse being required to alternate responding between the two locations. We have found a severe disruption in responding, evident from both accuracy and total trials measures when testing naive 12-mo-old Q92 mice on this task. This was before any delay was introduced into the task. However, unlike striatal lesioned rats, there was no increase in perseveration to the response holes (when adjusted for the number of correct trials) and panel latencies were significantly longer, indicating possible motor and/or motivational deficits and that the dysfunction in these mice may not be wholly attributed to striatal dysfunction. When we examined a second group of Q92 mice trained at 5 mo of age and then retested at 12 mo, the pretraining had improved the performance of these mice in such a way that it was possible to introduce delays into the task. With this group of Q92 mice, increasing delays had a deleterious effect on accuracy of both the wildtype and knock-in groups; however, overall the knock-in mice were less accurate than their wild-type littermates. As in the previous group of Q92 mice there was no evidence for increased perseveration and panel latencies were longer (Figure 11.11).



235

11.6.3 5-CHOICE REACTION TIME TASK The 5-Choice Reaction Time Task (5-CRTT), initially developed by Robbins,103 is a task that measures the sustained visual attention of an animal, and the animal’s subsequent ability to respond to the identified stimuli. These integrated attentional/ motor processes rely on intact cortical (especially anterior regions) and striatal brain areas, with damage to either producing profound behavioral deficits on the task. Consequently, this task is an ideal probe of fronto-striatal dysfunction in animal models that could have discrete frontal cortex or striatal neuropathology, as would be expected in HD, for example. The integrity of the underlying attentional/motor processes are assessed through the ability of the animal to attend and respond to visual stimuli randomly presented across five of the nine holes of the 9-HB. In the 5-CRTT, five holes (1, 3, 5, 7, and 9) are available, while holes 2, 4, 6, and 8 are masked. A stimulus light is presented randomly in one of the five holes, and a correct response to the light extinguishes it and produces a reward delivery signaled by the illumination of the food magazine. On collection of the reward and subsequent removal of the head from the magazine, a short inter-trial interval (ITI) (2 sec) is followed by the next trial. By presenting the stimulus light randomly across the array, the animal must attend to the whole of the array to make a correct nose-poke response. Response accuracy, presented as the percentage of correct trials, and reaction time, the time between the light stimulus being presented and the correct response, are the two main dependent variables on which behavior is assessed. But several error types are also measured to provide information as to why one group of animals performs better/worse than the other. Of particular relevance to HD would be perseverative errors, akin to compulsive responding, where the individual is unable to refrain from making a response, despite knowing that that particular response is inappropriate, which on this task is measured as a nose poke in the correct location, but after the stimulus light has been extinguished. As with most operant tasks, the task parameters can be manipulated to increase/ decrease task difficulty. The following example using the Q92 HD mouse demonstrates the flexibility of the apparatus and task in teasing out subtle performance deficits in this knock-in mouse line. The Q92 mouse has a normal life span and to the trained observer looks normal. When introduced to the 9-HB with the parameters set to their easiest settings on the 5-CRTT (2-sec stimulus light duration), no differences in accuracy are found between Q92 mice and the wild-type controls, but a small difference in response latencies were demonstrated in the Q92 mice. By decreasing the duration of the stimulus light from 2 sec to 0.5 sec, differences between the groups on both reaction time and accuracy measures become more apparent because of the increased difficulty of the task. Running a further experimental session where the duration of the stimulus light varies between 0.5 and 2 sec (presented in a pseudo-random fashion), response latencies between the two groups diverged with the Q92 mice becoming slower at the task, while the wild-type animals reduced their response latencies in response to the new conditions. The variable stimulus light durations also uncovered differences in the overall levels of accuracy between the groups, with the wild-type animals responding with greater accuracy for each of the stimulus light durations. The


236


introduction of the variable stimulus light duration increased the overall difficulty of the task and provided a more sensitive measure of behavioral deficit in the Q92 mice than the single-light duration condition, and clearly demonstrates the breakdown in the integration of attentional and motor aspects of behavior in the response pattern. This effect also demonstrates the sensitivity of the task and the utility of the task for use with mice, which has important implications for the use of transgenic and knockin/knockout animals.

11.6.4 SERIAL IMPLICIT LEARNING TASK The impetus for designing the Serial Implicit Learning Task (SILT) was the wish to identify a selective HD deficit that could then be probed for in animal models of HD, with the goal being the reversal of the deficit with a novel therapeutic approach. Implicit learning is the ability to learn information without explicit knowledge of the learning experience. The classic example of implicit learning is the ability of a young child to acquire the rules of grammar and syntax of language, which are generally not taught formally until the child is around 5 yr of age, by which time some language has developed. People with HD have been found to be deficient in learning tasks with an implicit element,104 and this learning deficit has been demonstrated to be independent of any motor abnormalities the person may have. Typically, implicit learning tasks are procedural learning tasks, whereby strings of stimuli are repeated in blocks and reaction times to respond to the stimuli are recorded, with the inference being that familiar sequences of stimuli would elicit shorter response latencies than randomly presented stimuli. This is, in fact, the case. Repeated sequences of stimuli do produce shorter response latencies than randomly presented stimuli, and importantly, the subjects must report no awareness of the sequential nature of the predictable stimuli, making the sequences implicitly learned. The SILT uses the 9HB for presenting random two-phase sequences of light stimuli to the animals, with an embedded, predictable, two-step sequence, which is our implicit learning probe. Within the 9-HB, five of the nine stimulus lights are available, designated A, B, C, D, and E (corresponding to holes 1, 3, 5, 7, and 9 in the 9-HB, if counting from the left) with the remaining four holes masked. The SILT is a two-phase task, whereby the animal has to respond correctly to both the S1 and S2 stimuli to receive a reward. The S1 stimulus is presented randomly in any of the five available holes, and a correct response to the S1 stimulus results in this light being extinguished and the randomly chosen S2 stimulus light being illuminated. A correct nose poke to this light results in the reward presentation in the food magazine, which is signaled by the magazine light being lit. Removal of the head from the magazine initiates the ITI (2 sec) prior to the onset of the next trial and the illumination of the next S1. In order to probe for implicit learning, a predictable two-phase sequence is embedded into the random stimuli presentation. The predictable sequence that is generally used in our experiments is hole B (S1) to hole D (S2). This particular sequence has the advantage of having a direct nonpredictable comparison of hole D (S1) to hole B (S2), so that performance of the predictable option can be directly compared with performance levels of the comparable nonpredictable option. As with other 9-HB tasks, task dif-



% Correct

90 80 70

*

*

60

2.0

A

*

% Correct

90

B

C

D Holes (a)

S2 Accuracy *

*

*

Predicted Unpredicted

80 70 60 50 40

1.5 1.0

0.0

E

Control mice Striatal lesions 1

2

3

2.0

Latency (secs)

100

Intact Lesion

0.5

50 40

S1 Reaction Time Control mice Striatal lesions

2.5

Intact Lesion Latency (secs)

S1 Accuracy Control mice Striatal lesions * * *

100

237

4 Steps (c)

Intact Lesion

1.5

A

B

D Holes (b) S2 Reaction Time

*

C

*

*

*

E

Predicted Unpredicted

1.0 0.5 0.0

Control mice Striatal lesions 1

2

3

4 Steps (d)

Intact Lesion

FIGURE 11.12 Performance on the serial choice discrimination task by sham-operated (control) and striatal lesioned mice, collapsed over the 20 days of postoperative testing. (a and b) Response accuracy and reaction times, respectively, to the first stimulus are plotted separately for trials in which S1 was presented in the different response locations A-E, with average performance on trials shown as vertical bars for the intact and lesion groups. Significant differences in accuracy between control and lesioned animals at each hole were demonstrated. (c and d) Response accuracy and reaction times, respectively, to the second are plotted separately for the number of steps 1–4, between S1 and S2. Control mice demonstrated significantly greater accuracy and significantly quicker reaction times than lesioned mice for each of the step distances (d). The two-step trials are then subdivided into predictable and unpredictable trials, shown as vertical bars (within group analysis). Source: Adapted from Trueman, R. C., Brooks, S. P., and Dunnett, S. B. 2005. Implicit learning in a serial choice visual discrimination task in the operant 9-hole box by intact and striatal lesioned mice. Behav. Brain Res. 159:313–22.

ficulty can be manipulated through the shortening of the stimulus duration of the S2 stimuli. Two measures of predictability are recorded: accuracy for, and reaction time to, the predictable sequence. In addition, the SILT measures several other performance parameters. Responding to S1 stimuli is assessed by the accuracy and reaction time


238


measures for each individual hole, as this S1 responding is essentially the 5-CRTT. The typical response pattern for S1 accuracy and reaction times is illustrated by the control animals in Figure 11.12A and B, respectively, which show greater accuracy and reduced response latencies for the center holes. Responding to the S2 stimuli can be broken down into accuracy of response and reaction times for the two-phase movements from S1 to S2, which are of varying lengths. For example, if S1 = hole A and S2 = hole E, this is a four-step movement (B > C > D > E) to make a correct response, whereas if S1 = hole D and S2 = hole C, this is a one-step movement. Typically, animals are more accurate and quicker to respond to shorter movement steps than longer (Figure 11.12C and D, respectively). Finally, in our experiments to date, animals with striatal lesions and genetically modified animals have been able to use the predictable information embedded in the sequences, resulting in greater accuracy and shorter response latencies for the predictable trials (see bars in Figure 11.12C and D).105

11.7

OPERANT ANALYSIS OF STRIATAL LESIONS: DEFICITS IN MOTIVATIONAL STATE

One of the hallmarks of HD is that patients present with psychiatric as well as motor and cognitive disturbances. A true psychiatric impairment is, of course, difficult to evaluate in primates, let alone in the laboratory rat. However, as an alternative to trying to determine the animal’s emotional state, it is certainly possible to evaluate motivational state, in particular the effects of striatal manipulations on changes in responding to stimuli with motivational significance. For example, the hyperactivity that is apparent following lesions of the medial striatum is not independent of the animals’ motivational state, but is particularly associated with food deprivation.106–108 Traditionally, it is the ventral striatum that is believed to play a central role in reward-related processes.109,110 More recently, research interest has turned to whether the ventral striatum not only mediates the evaluation of reward, but also the “effort” expended in obtaining it.111,112 One way in which to assess this “cost–benefit” analysis is to employ a progressive ratio (PR) schedule of operant lever pressing.113 Motivational deficits are a well-established symptom in HD and often present at an early stage in the disease, and as such these deficits are more associated with damage in the dorsal striatum. It is primarily this clinically based rationale that has led us to investigate reward-related processes in the dorsal striatum using a PR schedule.114 PR schedules require the rat to simply press a single lever a number of times to receive a food pellet reward. At first, each lever press results in a reward, then after five rewards three or five presses are required for each reward, then 10 presses per reward, and so on. As the session progresses, a progressively greater amount of work (e.g., number of lever presses) is required in order to gain an unchanging amount of reward (e.g., a single food pellet each time). Such a schedule makes it possible to examine a number of motivational measures that reflect the willingness of a rat to work for reward. These measures typically include the breakpoint of each animal (e.g., the greatest number of lever presses that an animal is prepared to make in order to obtain a single food pellet). A reduction in breakpoint is regarded as a general indication of lower levels of motivation.113,115 A second useful measure is the “post-



Last Ratio Completed

25

239

Wild-type mice Q92 transgenics

20 15 10 5 0

FIGURE 11.13 Progressive ratio testing of the Q92 mouse model. The last ratio completed by the knock-in mice (Hdh Q92/Q92) was significantly lower than that attained by the wild-type mice (Hdh+/+), demonstrating a motivational deficit in the Q92 knock-in mouse line. Source: Data produced by Rebecca Trueman.

reinforcement pause,” which describes the latency to resume lever pressing following the presentation of food. This is believed to reflect the reluctance to resume lever pressing as the “cost” of reward increases. In contrast to lesions of the ventral striatum, we have found that focal lesions of the dorsal striatum do not induce deficits as revealed by these primary motivational measures.114 Neither lesions of the dorsomedial striatum nor lesions of the dorsolateral striatum produced any changes in either breakpoint or the post-reinforcement pause. Nevertheless, these restricted striatal lesions did induce some specific performance deficits. Animals in both lesion groups took significantly longer to collect food rewards once a food pellet was delivered at the completion of a schedule. Moreover, rats with dorsolateral striatal lesions also continued to press the lever once a schedule had been completed and a food reward was available for consumption.114 Thus, although striatal lesions did not cause any overall deficit in motivation, rats with striatal lesions again demonstrated a perseverative deficit. This suggested that while striatal lesions did not affect the ability of rats to regulate their rates of responding with changing reward cost, there was evidence that striatal lesions compromised the ability of rats to sequence and switch responding efficiently and appropriately. Recently we have also tested the knock-in Q92 mice on the PR task, using the mouse nine-hole operant chambers. In this version of the task the mouse was required to respond to the illuminated center hole with one nose poke for three trials; for the proceeding three trials three nose pokes were necessary in order to receive the reward; and for the next three trials, six nose pokes were required, and so on. Unlike the striatal lesioned rats, the Q92 mice had a severe decrease in breakpoint attained compared to wild-type littermates and an increase in post-reinforcement pause. However, no increase in perseveration was evident, showing that these mice have a motivational deficit and suggesting that the dysfunctions seen in this HD model are not classical of striatal lesions (Figure 11.13).


240

11.8


CONCLUSION

By reviewing a handful of recent studies examining striatal function in rats and mice, this chapter aims to demonstrate the value of operant tasks in detecting specific deficits in the fronto-striatal system. However, new tasks are constantly being developed with the objective of shedding light on striatal function in both intact and pathological states, particularly trying to view the impact of the rodent studies in the context of ongoing primate and clinical research. There are many advantages to using operant tasks to assess function. The impressive degree of experimental control afforded by such paradigms provides not only an extensive stimulus control over an animal’s behavior, but also permits the quantification of the varied response options that an animal can choose to make. In addition, the automation of such paradigms overcomes the inherent biases in the observational recording of behavior, and also allows for greater efficiency in collecting and processing data. In addition to allowing detailed functional studies, operant tests allow a functional assessment of a wide variety of those surgical, cellular, or pharmacological interventions with potential clinical relevance. While hand testing and observational techniques may be more appropriate if the evaluation of a novel therapy is at an early stage, operant tasks allow for a fuller evaluation of the functional efficacy of treatments. Moreover, an understanding of how particular neural structures mediate function is crucial to the design of such interventions.116 The use of genetically modified animals has posed a challenge on several grounds. The development of transgenic, knock-in and knockout animal lines to recapitulate diseases has produced numerous mouse lines (less so in rats) for most major diseases. In the case of HD, the mouse lines, of which there are several, exhibit neuropathology that varies between lines in severity, anatomical location, and pace of development, resulting in a wide range of behavioral deficits that also vary in severity and age of onset. As a general rule, transgenic animals demonstrate a greater degree of behavioral and neuronal pathology than the knock-in models of HD. The severity and age of onset of the disease in any given mouse line has important implications for operant testing generally, and should be taken into account prior to the onset of experiments. Some mouse lines (for example, the R6/2) have an especially aggressive phenotype development that would make operant testing and subsequent therapeutic intervention extremely difficult because of the operant training times required. A further complication is the background strain of the mice that carry the genetic modification. Typically, transgenic animals are bred from strains where the mouse strains chosen to create the new mouse line are chosen for reasons other than behavioral performance. Consequently, in several genetically modified mouse lines it would be very difficult to produce good behavioral readouts, as they have some characteristic that confounds testing, an example being the HD YAC mouse lines117 that were created on an FVB background strain and consequently have severe retinal degeneration. Other mouse lines display normal behavioral profiles generally, but particular features of their behavior are at the extreme limit of what would be considered normal. In terms of spontaneous locomotor activity, DBA mice are very active (possibly hyperactive), whereas the 129/S2 mouse exhibits relatively little sponta-



241

neous motor activity. Both of these mouse lines are used as background strains. However, several mouse lines are very suitable for behavioral testing, and our recent experiences with Q92 mice has clearly demonstrated the utility of using genetically modified animals in an operant setting. Genetically modified animals in HD, and lesion models to a lesser degree, have the potential to recapitulate the disease process with biological authenticity, permitting the testing and validation of novel therapeutic interventions. Operant testing of fronto-striatal function is an essential part of analyzing the behavioral sequelae of basal ganglia pathology and must be continually addressed.

REFERENCES 1. Wilson, S. A. K. 1914. An experimental research into the anatomy and physiology of the corpus striatum. Brain 492. 2. Jung, R., and Hassler, R. 1960. The handbook of physiology. I. Neurophysiology, Vol. 2. 863. Washington, DC: The American Physiological Society. 3. Divac, I., Rosvold, H. E., and Szwarcbart, M. K. 1967. Behavioral effects of selective ablation of the caudate nucleus. J. Comp. Physiol. Psychol. 63:184–90. 4. Alexander, G. E., Crutcher, M. D., and DeLong, M. R. 1990. Basal ganglia-thalamocortical circuits: Parallel substrates for motor, oculomotor, “prefrontal” and “limbic” functions. Prog. Brain Res. 85:119–46. 5. Huntington, G. 1872. On chorea. Adv. Neurol. 1. 6. Huntington’s Disease Collaborative Research Group. 1993. A novel gene containing a trinucleotide repeat that is expended and unstable on Huntington’s disease. Cell 72:971. 7. Paulsen, J. S., et al. 2006. Brain structure in preclinical Huntington’s disease. Biol. Psychiatry 59:57–63. 8. Vonsattel, J. P., et al. 1985. Neuropathological classification of Huntington’s disease. J. Neuropathol. Exp. Neurol. 44:559–77. 9. Myers, R. H., et al. 1991. Decreased neuronal and increased oligodendroglial densities in Huntington’s disease caudate nucleus. J. Neuropathol. Exp. Neurol. 50:729–42. 10. Hedreen, J. C., and Folstein, S. E. 1995. Early loss of neostriatal striosome neurons in Huntington’s disease. J. Neuropathol. Exp. Neurol. 54:105–20. 11. Hackam, A. S., Singaraja, R., Zhang, T., Gan, L., and Hayden, M. R. 1999. In vitro evidence for both the nucleus and cytoplasm as subcellular sites of pathogenesis in Huntington‘s disease. Hum. Mol. Genet. 8:25–33. 12. Reddy, P. H., et al. 1999. Transgenic mice expressing mutated full-length HD cDNA: A paradigm for locomotor changes and selective neuronal loss in Huntington’s disease. Philos. Trans. R. Soc. Lond B Biol. Sci. 354:1035–45. 13. Ordway, J. M., et al. 1997. Ectopically expressed CAG repeats cause intranuclear inclusions and a progressive late onset neurological phenotype in the mouse. Cell 91:753–63. 14. Davies, S. W., et al. 1997. Formation of neuronal intranuclear inclusions underlies the neurological dysfunction in mice transgenic for the HD mutation. Cell 90:537–48. 15. DiFiglia, M. et al. 1997. Aggregation of huntingtin in neuronal intranuclear inclusions and dystrophic neurites in brain. Science 277:1990–93. 16. Van Raamsdonk, J. M., Pearson, J., Murphy, Z., Hayden, M. R., and Leavitt, B. R. 2006. Wild-type huntingtin ameliorates striatal neuronal atrophy but does not prevent other abnormalities in the YAC128 mouse model of Huntington disease. BMC. Neurosci. 7:80.


242


17. Li, S., and Li, X. J. 2006. Multiple pathways contribute to the pathogenesis of Huntington disease. Mol. Neurodegener. 1:19. 18. Paulsen, J. S., et al. 2001. Clinical markers of early disease in persons near onset of Huntington’s disease. Neurology 57: 658–62. 19. Paulsen, J. S., et al. 2006. Preparing for preventive clinical trials: The Predict-HD study. Arch. Neurol. 63:883–90. 20. Girotti, F., Marano, R., Soliveri, P., Geminiani, G., and Scigliano, G. 1988. Relationship between motor and cognitive disorders in Huntington’s disease. J. Neurol. 235:454–57. 21. Jahanshahi, M., Brown, R. G., and Marsden, C. D. 1993. A comparative study of simple and choice reaction time in Parkinson’s, Huntington’s and cerebellar disease. J. Neurol. Neurosurg. Psychiatry 56:1169–77. 22. Bradshaw, J. L., et al. 1992. Initiation and execution of movement sequences in those suffering from and at-risk of developing Huntington’s disease. J. Clin. Exp. Neuropsychol. 14:179–92. 23. Thompson, P. D., et al. 1988. The coexistence of bradykinesia and chorea in Huntington’s disease and its implications for theories of basal ganglia control of movement. Brain 111(Pt 2):223–44. 24. Penney, J. B. Jr., et al. 1990. Huntington’s disease in Venezuela: 7 years of follow-up on symptomatic and asymptomatic individuals. Mov. Disord. 5:93–9. 25. Divac, I. 1968. Effects of prefrontal and caudate lesions on delayed response in cats. Acta. Biol. Exp. (Warsz. ) 28:149–67. 26. Divac, I. 1972. Neostriatum and functions of prefrontal cortex. Acta Neurobiol. Exp. (Warsz. ) 32:461–77. 27. Stout, J. C., and Johnson, S. A. 2005. Cognitive impairment and dementia in basal ganglia disorders. Curr. Neurol. Neurosci. Rep. 5:355–63. 28. Hoth, K. F., et al. 2007. Patients with Huntington’s disease have impaired awareness of cognitive, emotional, and functional abilities. J. Clin. Exp. Neuropsychol. 29:365–76. 29. Knopman, D., and Nissen, M. J. 1991. Procedural learning is impaired in Huntington‘s disease: Evidence from the serial reaction time task. Neuropsychologia 29:245–54. 30. Butters, N., Sax, D., Montgomery, K., and Tarlow, S. 1978. Comparison of the neuropsychological deficits associated with early and advanced Huntington’s disease. Arch. Neurol. 35:585–89. 31. Lange, K. W., Sahakian, B. J., Quinn, N. P., Marsden, C. D., and Robbins, T. W. 1995. Comparison of executive and visuospatial memory function in Huntington’s disease and dementia of Alzheimer type matched for degree of dementia. J. Neurol. Neurosurg. Psychiatry 58:598–606. 32. Lawrence, A. D., et al. 1996. Executive and mnemonic functions in early Huntington’s disease. Brain 119(Pt 5):1633–45. 33. Harper, P. S. 1996. Huntington’s Disease. London: W. B. Saunders. 34. Wang, L. H., and Qin, Z. H. 2006. Animal models of Huntington‘s disease: Implications in uncovering pathogenic mechanisms and developing therapies. Acta Pharmacol. Sin. 27:1287–1302. 35. Laursen, A. M. Corpus Striatum. 1963. Acta Physiol. Scand. Suppl. (suppl)211–106. 36. McGeer, E. G., and McGeer, P. L. 1976. Duplication of biochemical changes of Huntington’s chorea by intrastriatal injections of glutamic and kainic acids. Nature 263:517–19. 37. Schwarcz, R., and Coyle, J. T. 1977. Striatal lesions with kainic acid: Neurochemical characteristics. Brain Res. 127:235–49. 38. Coyle, J. T., and Schwarcz, R. 1976. Lesion of striatal neurones with kainic acid provides a model for Huntington‘s chorea. Nature 263:244–46.



243

39. Beal, M. F., Ferrante, R. J., Swartz, K. J., and Kowall, N. W. 1991. Chronic quinolinic acid lesions in rats closely resemble Huntington’s disease. J. Neurosci. 11:1649–59. 40. Schwarcz, R., et al. 1979. Ibotenic acid-induced neuronal degeneration: A morphological and neurochemical study. Exp. Brain Res. 37:199–216. 41. Schwarcz, R., Whetsell, W. O. Jr., and Mangano, R. M. 1983. Quinolinic acid: An endogenous metabolite that produces axon-sparing lesions in rat brain. Science 219:316–18. 42. Beal, M. F. et al. 1993. Neurochemical and histologic characterization of striatal excitotoxic lesions produced by the mitochondrial toxin 3-nitropropionic acid. J. Neurosci.13:4181–92. 43. Borlongan, C. V., Koutouzis, T. K., and Sanberg, P. R. 1997. 3-Nitropropionic acid animal model and Huntington’s disease. Neurosci. Biobehav. Rev. 21:289–93. 44. Meldrum, A., Page, K. J., Everitt, B. J., and Dunnett, S. 1999. Mitochondrial inhibitors as tools for neurobiology. In Mitochondrial Inhibitors and Neurodegenerative Disorders, eds. P. R. Sanberg, H. Nishino,H, and C. Borlongan. Totowa, NJ: Human Press, 201–208. 45. Mangiarini, L., et al. 1996. Exon 1 of the HD gene with an expanded CAG repeat is sufficient to cause a progressive neurological phenotype in transgenic mice. Cell 87:493–506. 46. Lione, L. A., et al. 1999. Selective discrimination learning impairments in mice expressing the human Huntington’s disease mutation. J. Neurosci. 19:10428–37. 47. Carter, R. J., et al. 1999. Characterization of progressive motor deficits in mice transgenic for the human Huntington’s disease mutation. J. Neurosci. 19:3248–57 48. Morton, A. J., Lagan, M. A., Skepper, J. N., and Dunnett, S. B. 2000. Progressive formation of inclusions in the striatum and hippocampus of mice transgenic for the human Huntington’s disease mutation. J. Neurocytol. 29:679–702. 49. Wheeler, V. C., et al. 1999. Length-dependent gametic CAG repeat instability in the Huntington’s disease knock-in mouse. Hum. Mol. Genet. 8:115–22. 50. Schwarcz, R., Fuxe, K., Agnati, L. F., Hokfelt, T., and Coyle, J. T. 1979. Rotational behaviour in rats with unilateral striatal kainic acid lesions: A behavioural model for studies on intact dopamine receptors. Brain Res. 170:485–95. 51. Dunnett, S. B., Isacson, O., Sirinathsinghji, D. J., Clarke, D. J., and Bjorklund, A. 1988. Striatal grafts in rats with unilateral neostriatal lesions--III. Recovery from dopamine-dependent motor asymmetry and deficits in skilled paw reaching. Neuroscience 24:813–20. 52. Borlongan, C. V., Randall, T. S., Cahill, D. W., and Sanberg, P. R. 1995. Asymmetrical motor behavior in rats with unilateral striatal excitotoxic lesions as revealed by the elevated body swing test. Brain Res. 676:231–34. 53. Montoya, C. P., Astell, S., and Dunnett, S. B. 1990. Effects of nigral and striatal grafts on skilled forelimb use in the rat. Prog. Brain Res. 82:459–66. 54. Montoya, C. P., Campbell-Hope, L. J., Pemberton, K. D., and Dunnett, S. B. 1991. The “staircase test”: A measure of independent forelimb reaching and grasping abilities in rats. J. Neurosci. Methods 36:219–28. 55. Skinner, B. F. 1938. The behavior of organsims. New York: Appleton-Century-Crofts. 56. Everitt, B. J., Fray, P., Kostarczyk, E., Taylor, S., and Stacey, P. 1987. Studies of instrumental behavior with sexual reinforcement in male rats (Rattus norvegicus): I. Control by brief visual stimuli paired with a receptive female. J. Comp. Psychol. 101:395–406. 57. Dunnett, S. B., and Iversen, S. D. 1982. Neurotoxic lesions of ventrolateral but not anteromedial neostriatum in rats impair differential reinforcement of low rates (DRL) performance. Behav. Brain Res. 6:213–26.


244


58. Sanberg, P. R., Pisa, M., and Fibiger, H. C. 1979. Avoidance, operant and locomotor behavior in rats with neostriatal injections of kainic acid. Pharmacol. Biochem. Behav. 10:137–44. 59. Dobrossy, M. D., Svendsen, C. N., and Dunnett, S. B. 1995. The effects of bilateral striatal lesions on the acquisition of an operant test of short term memory. Neuroreport 6:2049–53. 60. Reading, P. J., Dunnett, S. B., and Robbins, T. W. 1991. Dissociable roles of the ventral, medial and lateral striatum on the acquisition and performance of a complex visual stimulus-response habit. Behav. Brain Res. 45:147–61. 61. Ungerstedt, U., and Arbuthnott, G. W. 1970. Quantitative recording of rotational behavior in rats after 6-hydroxydopamine lesions of the nigrostriatal dopamine system. Brain Res. 24:485–93. 62. Whishaw, I. Q., O’Connor, W. T., and Dunnett, S. B. 1986. The contributions of motor cortex, nigrostriatal dopamine and caudate- putamen to skilled forelimb use in the rat. Brain 109(Pt 5):805–43. 63. Evenden, J. L., and Robbins, T. W. 1984. Effects of unilateral 6-hydroxydopamine lesions of the caudate-putamen on skilled forepaw use in the rat. Behav. Brain Res. 14:61–68. 64. Marshall, J. F., Richardson, J. S., and Teitelbaum, P. 1974. Nigrostriatal bundle damage and the lateral hypothalamic syndrome. J. Comp. Physiol. Psychol. 87:808–30. 65. Ljungberg, T., and Ungerstedt, U. 1976. Sensory inattention produced by 6-hydroxydopamine-induced degeneration of ascending dopamine neurons in the brain. Exp. Neurol. 53:585–600. 66. Marshall, J. F., Turner, B. H., and Teitelbaum, P. 1971. Sensory neglect produced by lateral hypothalamic damage. Science 174:523–25. 67. Marshall, J. F., and Teitelbaum, P. 1974. Further analysis of sensory inattention following lateral hypothalamic damage in rats. J. Comp. Physiol. Psychol. 86:375–95. 68. Turner,B.H. 1973. Sensorimotor syndrome produced by lesions of the amygdala and lateral hypothalamus. J. Comp Physiol Psychol. 82: 37-47. 69. Robbins, T. W., Muir, J., Killcross, A. S., and Price, B. H. 1993. In Behavioural neuroscience, Vol. I, ed. A. Sahgal. Oxford: IRL Press. 70. Carli, M., Evenden, J. L., and Robbins, T. W. 1985. Depletion of unilateral striatal dopamine impairs initiation of contralateral actions and not sensory attention. Nature 313:679–82. 71. Carli, M., Jones,G. H., and Robbins, T. W. 1989. Effects of unilateral dorsal and ventral striatal dopamine depletion on visual neglect in the rat: A neural and behavioural analysis. Neuroscience 29:309–27. 72. Brown, V. J., and Robbins, T. W. 1989. Deficits in response space following unilateral striatal dopamine depletion in the rat. J. Neurosci. 9:983–89. 73. Brasted, P. J., Humby, T., Dunnett, S. B., and Robbins, T. W. 1997. Unilateral lesions of the dorsal striatum in rats disrupt responding in egocentric space. J. Neurosci. 17: 8919–26. 74. Heilman, K. M. 1979. In Clinical neuropsychology, ed. E. S. Valenstein. Oxford: Oxford University Press. 75. Bisiach, E., and Luzzatti, C. 1978. Unilateral neglect of representational space. Cortex 14:129–33. 76. Rosvold, H. E. 1972. The frontal lobe system: Cortical-subcortical interrelationships. Acta Neurobiol. Exp. (Warsz. ) 32:439–60. 77. Rosvold, H. E., and Delgado, J. M. 1956. The effect on delayed-alternation test performance of stimulating or destroying electrically structures within the frontal lobes of the monkey’s brain. J. Comp. Physiol. Psychol. 49:365–72.



245

78. Krettek, J. E., and Price, J. L. 1977. The cortical projections of the mediodorsal nucleus and adjacent thalamic nuclei in the rat. J. Comp. Neurol. 171:157–91. 79. Leonard, C. M. 1969. The prefrontal cortex of the rat. I. Cortical projection of the mediodorsal nucleus. II. Efferent connections. Brain Res. 12:321–43. 80. Dunnett, S. B., and Iversen, S. D. 1981. Learning impairments following selective kainic acid-induced lesions within the neostriatum of rats. Behav. Brain Res. 2:189–209. 81. Divac, I., Markowitsch, H. J., and Pritzel, M. 1978. Behavioral and anatomical consequences of small intrastriatal injections of kainic acid in the rat. Brain Res. 151:523–32. 82. Sanberg, P. R., Lehmann, J., and Fibiger, H. C. 1978. Impaired learning and memory after kainic acid lesions of the striatum: A behavioral model of Huntington‘s disease. Brain Res. 149:546–51. 83. D’Amato, M. R., and O’Neill, W. 1971. Effect of delay-interval illumination on matching behavior in the capuchin monkey. J. Exp. Anal. Behav. 15:327–33. 84. Aggleton, J. P. 1985. One-trial object recognition by rats. Quart. J. Exp. Psychol. B. 37:279. 85. Dunnett, S. B. 1993. In Behavioural neuroscience: A technical approach, ed. A Sahgal, 123. Oxford: IRL Press. 86. Dunnett, S. B. 1985. Comparative effects of cholinergic drugs and lesions of nucleus basalis or fimbria-fornix on delayed matching in rats. Psychopharmacology (Berl.) 87:357–63. 87. Goldman-Rakic, P. S. 1989. Handbook of physiology: The nervous system V, 373. Baltimore: American Physiological Association. 88. Kowalska, D. M., Bachevalier, J., and Mishkin, M. 1991. The role of the inferior prefrontal convexity in performance of delayed nonmatching-to-sample. Neuropsychologia 29:583–600. 89. Mishkin, M., and Manning, F. J. 1978. Non-spatial memory after selective prefrontal lesions in monkeys. Brain Res. 143:313–23. 90. Dunnett, S. B. 1990. Role of prefrontal cortex and striatal output systems in short-term memory deficits associated with ageing, basal forebrain lesions, and cholinergic-rich grafts. Can. J. Psychol. 44:210–32. 91. Dobrossy, M. D., Svendsen, C. N., and Dunnett, S. B. 1996. Bilateral striatal lesions impair retention of an operant test of short- term memory. Brain Res. Bull. 41:159–65. 92. Dunnett, S. B. 1990. Is it possible to repair the damaged prefrontal cortex by neural tissue transplantation? Prog. Brain Res. 85:285–96. 93. Jacobsen, C. F. 1936. Studies of cerebral function in primates. I. The functions of the frontal association areas in monkeys. Comp. Psychol. Monogr. 13:3. 94. Jacobsen, C. F. 1937. Studies of cerebral function in primates. IV. The effect of frontal lobe lesions on the delayed alternation habit in monkeys. J. Comp. Psychol. 23:101. 95. Brandt, J., et al. 1984. Clinical correlates of dementia and disability in Huntington’s disease. J. Clin. Neuropsychol. 6:401–12. 96. Georgiou, N., Bradshaw, J. L., Phillips, J. G., and Chiu, E. 1997. Effect of directed attention in Huntington’s disease. J. Clin. Exp. Neuropsychol. 19:367–77. 97. van Haaren, F., de Bruin, J. P., Heinsbroek, R. P., and van de Poll, N. E. 1985. Delayed spatial response alternation: Effects of delay-interval duration and lesions of the medial prefrontal cortex on response accuracy of male and female Wistar rats. Behav. Brain Res. 18:41–49. 98. Numan, R., and Quaranta, J. R. Jr. 1990. Effects of medial septal lesions on operant delayed alternation in rats. Brain Res. 531:232–41. 99. Heise, G. A., Conner, R., and Martin, R. A. 1976. Effects of scopolamine on variable intertrial interval spatial alternation and memory in the rat. Psychopharmacology (Berl.) 49:131–37.


246


100. Mogensen, J., Iversen, I. H., and Divac, I. 1987. Neostriatal lesions impaired rats‘ delayed alternation performance in a T-maze but not in a two-key operant chamber. Acta Neurobiol. Exp. (Wars. ) 47:45–54. 101. Dunnett, S. B., Nathwani, F., and Brasted, P. J. 1999. Medial prefrontal and neostriatal lesions disrupt performance in an operant delayed alternation task in rats. Behav. Brain Res. 106:13–28. 102. White, A., and Dunnett, S. B. 2006. Fronto-striatal disconnection disrupts operant delayed alternation performance in the rat. Neuroreport 17:435–41. 103. Robbins, T. W. 2002. The 5-choice serial reaction time task: Behavioural pharmacology and functional neurochemistry. Psychopharmacology (Berl.)163:362–80. 104. Knopman, D., and Nissen, M. J. 1991. Procedural learning is impaired in Huntington‘s disease: Evidence from the serial reaction time task. Neuropsychologia 29:245–54. 105. Trueman, R. C., Brooks, S. P., and Dunnett, S. B. 2005. Implicit learning in a serial choice visual discrimination task in the operant 9-hole box by intact and striatal lesioned mice. Behav. Brain Res. 159:313–22. 106. Isacson, O., Dunnett, S. B., and Bjorklund, A. 1986. Graft-induced behavioral recovery in an animal model of Huntington disease. Proc. Natl. Acad. Sci. USA 83:2728–32. 107. Jacobsen, C. F. 1936. Studies of cerebral function in primates. III. A note on the effect of motor and premotor lesions on delayed response in monkeys. Comp. Psychol. Monogr. 13:66. 108. Sanberg, P. R., and Coyle, J. T. 1984. Scientific approaches to Huntington’s disease. CRC Crit. Rev. Clin. Neurobiol. 1:1–44. 109. Berridge, K. C. 1996. Food reward: Brain substrates of wanting and liking. Neurosci. Biobehav. Rev. 20:1–25. 110. Mogenson, G. J., Jones, D. L., and Yim, C. Y. 1980. From motivation to action: Functional interface between the limbic system and the motor system. Prog. Neurobiol. 14:69–97. 111. Salamone, J. D., Cousins, M. S., and Snyder, B. J. 1997. Behavioral functions of nucleus accumbens dopamine: Empirical and conceptual problems with the anhedonia hypothesis. Neurosci. Biobehav. Rev. 21:341–59. 112. Salamone, J. D., Kurth, P., McCullough, L. D., and Sokolowski, J. D. 1995. The effects of nucleus accumbens dopamine depletions on continuously reinforced operant responding: Contrasts with the effects of extinction. Pharmacol. Biochem. Behav. 50:437–43. 113. Hodos, W., and Kalman, G. 1963. Effects of increment size and reinforcer volume on progressive ratio performance. J. Exp. Anal. Behav. 6:387–92. 114. Eagle, D. M., Humby, T., Dunnett, S. B., and Robbins, T. W. 1999. Effects of regional striatal lesions on motor, motivational, and executive aspects of progressive-ratio performance in rats. Behav. Neurosci. 113:718–31. 115. Skjoldager, P., Pierre, P. J., and Mittleman, G. 1993. Reinforcer magnitude and progressive ratio responding in the rat: Effects of increased effort, prefeeding and extinction. Learn. Motiv. 24:303 116. Dunnett, S. B., and Everitt, B. J. 1998. Cell transplantation for neurological disorders, eds. T. B. Freeman and J. H. Kordower, 135. Totowa, NJ: Humana Press. 117. Hodgson, J. G., et al. 1999. A YAC mouse model for Huntington’s disease with fulllength mutant huntingtin, cytoplasmic toxicity, and selective striatal neurodegeneration. Neuron 23:181–92.


Memory 12 Working Delayed Response Tasks in Monkeys Jesse S. Rodriguez and Merle G. Paule CONTENTS 12.1 Introduction................................................................................................. 247 12.2 Methods.......................................................................................................248 12.2.1 Animal Subjects...............................................................................248 12.2.2 Equipment ........................................................................................ 249 12.2.3 Delayed Response Tasks.................................................................. 250 12.2.4 Delayed Alternation Tasks............................................................... 251 12.2.5 Delayed Matching-to-Sample Tasks ................................................ 251 12.2.6 Delayed Non-Matching-to-Sample Tasks ........................................ 252 12.2.6.1 Trial-Unique Versus Repetitive Stimuli ............................ 252 12.3 Data Analysis and Interpretation ................................................................ 252 12.4 Typical Applications ................................................................................... 255 12.5 Representative Data .................................................................................... 256 12.6 Limitations and Conclusions....................................................................... 258 References.............................................................................................................. 262

12.1

INTRODUCTION

Accepted taxonomies of memory typically distinguish among different kinds of remembering depending upon the information that must be remembered. A basic dichotomy distinguishes between the retention of factual or experiential information on the one hand, and the retention of habits and motor skills on the other. Factual memory can be further differentiated into working and reference memory. As first described by Werner Honig’s group,1 working memory is required when “different stimuli govern the criterion response on different trials, so that the cue that the animal must remember varies from trial to trial.” Thus, working memory is required for remembering information that varies unpredictably in time and/or in content: it is this type of memory that is decimated in Alzheimer’s disease and other dementias.2 In contrast, reference memory is used to retain information that remains constant over time (e.g., removing the cup from a baited well provides access to food). The study of working memory processes is generally accomplished using delayed response (DR) tasks and, within the confines of even relatively short test sessions, one can readily assess processes associated with short-term memory using these 247


248


procedures. In such tasks, one presents a bit of information (a sample) to a subject, withdraws that information, waits for a period of time (recall delay), then presents that same bit of information along with a comparison bit and asks the subject to identify (choose) which bit of information was presented previously. This process is then repeated across a number of trials. DR tasks using nonhuman primates as surrogates are used primarily to determine the biological underpinnings of human learning and memory processes and their associated mechanisms. The complex brain functions associated with the performance of these tasks can be assessed using a variety of approaches, and the careful monitoring of behavioral outputs provides important experimental advantages. Many of the different types of assessments of memory processes have evolved from studies ranging from those employing neuroanatomical lesions to electrophysiological recordings and, more recently, neuroimaging techniques. Goldman-Rakic et al. have shown the importance of the prefrontal cortex in the performance of DR tasks in nonhuman primates by employing lesions and electrophysiological and neuroimaging techniques.3–6 Brain lesion experiments in monkeys have also demonstrated the importance of the hippocampus and its relevance to performance in DR tasks.7 Through the use of lesions, Zola et al. (2000) and Squire (2004) have also demonstrated the importance of the medial temporal lobe in performance of these types of tasks in monkeys.8,9 Taken together these and other studies have elucidated the importance of the prefrontal cortex in visual-spatial functions, inhibition of behavior (temporal mechanisms), decision making, working memory, problem solving, planning, and organizing. Likewise, the findings that the hippocampal formation (medial temporal lobe) is important in memory consolidation, associative memory formation, declarative memory, and recognition memory stem from these and similar studies. The prefrontal cortex and the hippocampal formation are two brain areas intricately involved in the performance of DR tasks. The understanding of short-term memory and, more specifically, working memory has benefited greatly from this work.

12.2

METHODS

12.2.1 ANIMAL SUBJECTS Animal models are essential components of basic science and preclinical research, and their use in behavioral experiments is often more practical than is the use of human subjects. While the most commonly used research animals are rodents, nonhuman primates are phylogenetically the most similar to humans. Goldman-Rakic et al. have observed that “the organization of the cortical dopamine system is essentially the same in macaque monkey and human and that the nonhuman primate is a suitable animal model for analysis of dopamine function in prefrontal cortex.”10 Nonhuman primates are excellent models for studying behavior during different periods of development and for use in pharmacological and toxicological studies, and the ethics of using these animals in research has been eloquently addressed.11 Since DR tasks often use food reinforcement, food restriction is commonly used as a means of increasing motivation and positive behavioral output.12,13 Caloric intake is usually reduced by about 15%–20% from that of free-feeding animals and


Working Memory

249

can result in many positive effects such as enhanced quality and length of life.14–17 Studies performed in nonhuman primates are easily relatable to studies conducted in lower species, such as rodents, and in humans.18

12.2.2 EQUIPMENT Most of the early DR tasks were conducted using the Wisconsin General Test Apparatus or WGTA (Figure 12.1). In this apparatus a monkey sits in a cage or a restraint chair in front of a tray that contains recessed food wells. The experimenter baits a well with food, covers it, and then lowers a screen to block the experimental tray from the monkey’s view. Subjects can retrieve the food reinforcer after the screen is removed at some later time. This approach, while very productive, is labor intensive and prone to the vagaries of experimenter–subject interactions. More recently, however, automated behavioral systems have become increasing popular. In a typical primate behavioral test system, the subject is either placed in a behavior chamber in which it interacts with a response panel, or a test panel is positioned so that the animal can interact with it; for example, a panel can be temporarily affixed to its home cage during test sessions. The response panels can be outfitted with a variety of manipulanda such as response levers or bars or press-plates on which visual stimuli can be presented. In these configurations, there is generally a food cup or trough into which food reinforcers are delivered when correct responses are made. An example of the behavioral panel used in one such system, in this case the National Center for Toxicological Research (NCTR) Operant Test Battery or OTB,19 is shown in Figure 12.2. Recently, a touch-screen-based system, the CANTAB (Cambridge Neuropsychological Test Automated Battery) system was developed for the assessment of cognitive deficits in humans with neurodegenerative diseases or brain damage. It is now

One-way vision screen

Forward opaque screen

Transport cage

Stimulus tray

FIGURE 12.1 Wisconsin General Test Apparatus. Source: Buccafusco, J. J. 2001. Methods of behavior analysis in neuroscience, First Edition, Boca Raton, FL: Taylor and Francis., with permission.


250


FIGURE 12.2 Operant Test Battery panel used for nonhuman primate and human experiments.

being used by some laboratories to test nonhuman primates.20,21 The battery consists of computerized tests of memory, attention, and executive function, one of which is a delayed matching-to-sample (DMTS) task for the assessment of working memory. The CANTAB apparatus, like all of the other systems discussed here, is nonverbal in nature, making it language independent and largely culture-free. CANTAB performance has been standardized in an elderly human population and validated in neurosurgical patients and in patients with basal ganglia disorders, Alzheimer’s disease, depression, and schizophrenia.

12.2.3 DELAYED RESPONSE TASKS As mentioned earlier, DR tasks have historically been performed using the WGTA. Initially, in full view of the subject, the experimenter baits one of two or three reinforcer wells with food, covers all food wells with identical items (e.g., cardboard plaques), then lowers an opaque screen to block the experimental tray from the monkey’s view. After a delay period the screen is lifted, allowing the monkey to recall from memory and choose the baited food well. This DR task measures mnemonic processes associated with working memory.22,23 Reinforcers are randomly distributed between the food wells over a number of trials (e.g., 30) that make up a daily test session. During the initial training phase, delays are held constant at short values and are gradually increased according to a stepwise procedure as animals demonstrate mastery of the task.24 DR task performance has been used to examine the involve-


Working Memory

251

ment of specific neurotransmitters with aspects of working memory. For example, it has been shown that guanfacine, a norepinephrine agonist, improves performance in young adult rhesus monkeys,25 suggesting that the norepinephrine system is important in the modulation of working memory.

12.2.4 DELAYED ALTERNATION TASKS There are several variations of delayed alternation tasks, for example, delayed spatial alternation and delayed object alternation (nonspatial). For both of these tasks, the trials are temporally related to one another: a correct response is dependent upon the previous response. The delayed spatial alternation task is a two-choice task in which the monkey has to alternately displace a left or right plaque to retrieve a reward, i.e., if the right food well was baited on one trial, then the left food well will be baited on the next trial. This task is typically used with a delay or recall duration of at least 5 sec. The delayed object alternation task is also a two-choice task in which the monkey needs to correctly select an object that alternates between trials. Levy et al.26 have reported that delayed spatial alternation tasks increase neural metabolic activity, as measured by local cerebral glucose utilization, in the head of the caudate nucleus where efferents from the dorsolateral prefrontal cortex project most densely. Performance of a delayed object alternation task increase neural metabolic activity in the body of the caudate nucleus, which is innervated by the temporal cortex. These findings show that spatial and nonspatial cognitive operations are subserved by distinct cortico-striatal circuits.

12.2.5 DELAYED MATCHING-TO-SAMPLE TASKS For DMTS tasks, as with other DR tasks, each trial begins with the presentation of a sample stimulus. As used in the NCTR OTB, this involves illumination of the center one of three horizontally aligned press-plate manipulanda (Figure 12.2) with one of seven white-on-black geometric shapes. Subjects make an observing response to the initial shape (sample stimulus) by pushing the illuminated plate, after which it is immediately extinguished. Following an interval (recall delay) that varies randomly (from 2 to 32 sec, for example), all three press-plates are illuminated, each with a different stimulus shape, but one of which matches the sample stimulus. A choice response to the plate matching the sample stimulus results in food reinforcer delivery. Incorrect choices are followed by a 10-sec timeout, then initiation of a new trial. As indicated by lesion studies,27 this task28 and other DMTS procedures are thought to depend upon the prefrontal and inferior temporal cortices. Damage to the higher visual area inferior temporal cortex interferes with the performance of the task for visual stimuli,27 while lesions of the prefrontal cortex still allow successful completion of the task but only for short recall delay periods.29 The use of distractors in DMTS tasks has been employed to increase task difficulty (for review, see30). Distractors are thought to inhibit the subject’s ability to sustain attention and serve to impair working memory. Distractors are usually either auditory or visual stimuli presented during the delay or recall interval to distract the monkey from relevant test stimuli. It is believed that the presentation of distractors during the delay or recall interval, a time during which selective attention and


252


rehearsing are thought to be important, disrupts the cognitive processes subserving working memory.

12.2.6 DELAYED NON-MATCHING-TO-SAMPLE TASKS These procedures are conceptually similar to DMTS paradigms, however, in delayed non-matching-to-sample (DNMTS) tasks, the subject is required to choose the stimulus that does not match the test (sample) stimulus that was presented before the recall delay. This task has been used extensively in monkeys to identify the brain regions involved in recognizing previously presented stimuli.8,31 In a typical DNMTS task, the subject is presented with a trial-unique (unfamiliar) sample stimulus followed by a recall delay during which the sample is removed from sight, and then presentation of the sample and a novel stimulus item. Choosing the novel stimulus is reinforced as the correct response. It is thought that monkeys learn to perform DNMTS tasks much more rapidly than they learn to perform DMTS tasks because of their natural tendency to preferentially attend to novel stimuli, in this case, the non-matching stimulus. Lesion studies in monkeys have revealed a number of interconnected areas involved in the encoding, retention, and retrieval of stimulus representations within DNMTS trials. This memory circuit consists principally of the ventromedial and ventrolateral prefrontal cortices, rhinal (entorhinal and perirhinal) cortex, thalamus, and the inferotemporal cortex.31–34 The hippocampus, located in the medial temporal cortex, might also be a component of this circuit, but its precise role is currently the subject of debate.8,31 Recent findings have suggested that an intact hippocampal formation is critical for acquisition of DNMTS task performance, and specifically for the delay component.35 12.2.6.1 Trial-Unique Versus Repetitive Stimuli Trial-unique stimuli are stimuli that do not appear in more than one trial during a test session or during many test sessions (i.e., they are unfamiliar). Repetitive stimuli, on the other hand, may repeat in multiple trials during a given test session. Tasks that employ trial-unique stimuli activate the medial temporal lobe more than tasks that employ repetitive stimuli.36 This suggests a stronger role for the medial temporal lobe in working memory for complex, novel, trial-unique stimuli, relative to working memory for familiar stimuli. However, repetitive stimuli tasks activate the prefrontal and parietal cortices more than tasks that employ trial-unique stimuli.36 This suggests that the prefrontal and parietal cortices play a stronger role in working memory for familiar stimuli. These differences are thought to reflect the engagement of medial temporal lobe regions in tasks that require the formation and maintenance of new short-term representations; whereas the prefrontal cortex is preferentially engaged when prior representations already exist in the brain but must be selectively updated and monitored to avoid interference effects.36

12.3

DATA ANALYSIS AND INTERPRETATION

The analyses of data obtained using the working memory tasks described here sometimes vary between laboratories, but, generally, common endpoints are used. Ideal-


Working Memory

253

Percent Accuracy

100 75 50 25

B

0

D 0

FIGURE 12.3

A

C

5 10 15 20 25 30 35 Delay Intervals (seconds)

Idealized delayed response task data

ized data for typical DR tasks are shown in Figure 12.3, where response accuracy is plotted on the ordinate, and length of recall delay is plotted on the abscissa. Typical data from normal subjects might be represented by line A, where it can be seen that at zero—or very short—delays recall accuracies are very high. The point where these data intercept the y axis is thought to be related to the ability of subjects to attend to the task, discriminate the stimuli, and encode the information relevant to problem solution. Thus, if aspects of attention, discriminability, or encoding are degraded, accuracy at zero or very short delays will decrease. The slope of this line indicates the normal rate of short-term/working memory decay. Line B represents data showing a decrease in initial attention and/or encoding, with a normal rate of forgetting; similar observations have been noted after the administration of the hallucinogen lysergic acid diethylamide (LSD) (see also Figure 12.7).37 The data in line C represent a circumstance under which the initial level of attention and/or encoding is no different from that of the normal condition (line A), but under which the rate of forgetting has been increased (slope is steeper). This kind of effect can be seen after surgical ablations of the hippocampus and amygdala (Figure 12.4),8 after treatment with certain drugs, such as tetrahydrocannabinol (THC),38 and when distractors are used.39 Line D represents data showing a decrease in both initial attention and/or encoding and an increase in the rate of forgetting. These data examples are relevant to DR tasks whether or not they have time limitations (predetermined session lengths), and whether or not they include the measurement of response speed (latencies). By setting maximum session lengths and measuring response speed, however, several additional important metrics of task performance can be had. The typical measure used by our lab for DNMTS and DMTS tasks is the percent task completed (PTC) measure. This measure is a function of both response accuracy and speed, so changes in either of those measures can affect the PTC. Conceivably, an experimental treatment (drug or toxicant exposure, brain lesion, other stressor, etc.) could increase response rate while decreasing accuracy and, thus, have no effect on PTC. Conversely, response rate could be decreased and accuracy increased, again resulting in no effect on PTC. Practically speaking, these effect combinations have not been seen in our lab. Typically, if a treatment has an effect, it will manifest in


254


100

Delayed Nonmatching to Sample *

Percent Correct

90

*

*

80

*

70

H (18a)

60 50

N (10)

8s

15 s

1 m 10 m Delay

40 m

FIGURE 12.4 Data are from hippocampal lesioned monkeys (closed squares) as compared to nonlesioned animals (open squares) for a delayed non-matching-to-sample task. Lesioned animals performed significantly lower in accuracy for most delay intervals as compared to the control group. Source: From Zola, S. M., Squire, L. R., Teng, E., Stefanacci, L., Buffalo, E. A., and Clark, R. E. 2000. Impaired recognition memory in monkeys after damage limited to the hippocampal region. J. Neurosci 20:451–63, with permission.

the PTC metric, alerting one to look further for more information as to the specific nature of the effect. Thus, overall accuracy (collapsed across all recall delays) and overall response latencies (both observing and choice) are examined next. Since latencies are inverses of response rates, they provide metrics of speed of responding. Observing response latency is defined as the time elapsed before the subject initiates a trial by responding to or “observing” the initial sample stimulus. Choice response latency is defined as the time to respond to a choice stimulus following the presentation of choices. Choice response latency can be determined for each recall delay, whereas observing response latency is generally independent of recall delay. An increase or decrease in overall accuracy is indicative of short-term or working memory effects, particularly if this effect is seen in the absence of any effect on response latencies. This effect can manifest during a particular delay interval and may or may not be delay dependent. Delay-dependent effects would be those that change as a function of recall delay. For example, a treatment may have no effect on response accuracy at short delays (no or little effect on attention and/or encoding), but have significant effects on accuracy at the longer delays (increased rate of forgetting or distractibility; see also hypothetical line C in Figure 12.3). An increase or decrease in observing response latency following a pharmacological challenge or other experimental manipulation can be indicative of effects on reaction time (psychomotor speed), motivation, and/or motoric capabilities. An increase or decrease in overall choice response latency can be indicative of an effect on attention, reaction time, motivation, or motoric capabilities. If a treatment effect on choice response latency increases with increasing length of recall delay, then that


Working Memory

255

effect is likely related to attentional processes/distractibility. This stems from the fact that there is increasing opportunity for distraction with increasing recall delay.

12.4

TYPICAL APPLICATIONS

There is a wide range of applications for which DR tasks are useful. Many studies have investigated the effects of pharmacological challenges on DR tasks in the developing monkey (for review, see40). Other studies have observed the effects of brain lesions,41 environmental factors,42,43 and human diseases such as Alzheimer’s disease and attention deficit hyperactivity disorder (ADHD).44–46 Old monkeys can sometimes serve as good models for age-related cognitive decline and Alzheimer’s disease because they show impaired performance in the DMTS task as compared with younger monkeys.47 Some of the earliest findings of drug effects on DMTS task performance demonstrated the importance of the norepinephrine system in performance of DR tasks. Jackson and Buccafusco48 showed that the norepinephrine agonist, clonidine, when administered to either young or aged monkeys, resulted in a significant improvement across all trials in DMTS task performance. Similarly, Franowicz and Arnsten25 reported that guanfacine, another norepinephrine agonist, improved DR task performance in young adult rhesus monkeys. The function of the acetylcholine system has, however, remained the focus of memory and Alzheimer’s disease research because of its suspected role in learning and memory processes and in the etiology of Alzheimer’s disease. Applicably, a study by Decker et al.49 showed that administration of ABT-089 (a nicotinic acetylcholine receptor agonist) to aged monkeys produced a robust improvement in DMTS accuracy at all delay intervals. This effect was not age-specific because task improvement was also seen in younger adult monkeys. Similarly, Prendergast et al.50 reported improvement in accuracy in a delayed recall task in both aged and younger adult monkeys after administration of the nicotinic receptor agonist, ABT418. Additionally, Jackson et al.51 found that the acetylcholinesterase inhibitor, velnacrine, improved DMTS performance in aged monkeys. These findings, relevant to the study and treatment of Alzheimer’s disease, clearly demonstrate the importance of the acetylcholine system in working memory processes and age-associated memory decline. Monkey subjects have also been used to evaluate aspects of attention and focus using DR tasks. ADHD patients exhibit difficulties in sustaining focus/attention. Therefore, the DMTS task has been modified to include a component in which distractors (flashing sample and choice stimuli) are presented during the recall delay intervals. Distractors inhibit the subject’s ability to sustain attention and impair working memory during DR tasks. Prendergast et al.52 found that nicotine, ABT089, and ABT-418 (all acetylcholine agonists) attenuated the effects of distractors in the DMTS task by preventing distractor-induced declines in recall accuracy in adult monkeys. Other potentially beneficial drugs derive from a class of serotonin (5-HT) receptor antagonists. Terry et al.53 reported that the 5-HT3 receptor antagonist RS56812 enhances DMTS accuracy in monkeys at long recall delays. This compound presumably acts through 5-HT3 receptors on acetylcholine axon terminals


256


where 5-HT receptor inactivation is thought to lead to increases in acetylcholine release. Additionally, Terry et al.54 found that the 5-HT4 receptor antagonist RS17017 enhances DMTS accuracy in both young and old macaque monkeys. These findings suggest the potential development of new treatments for ADHD and other memory disorders that would be alternatives to the psychostimulant medications currently in common use. In addition to the cholinergic agonists and serotonin antagonists that enhance performance on DR tasks, there are, not unexpectedly, also a host of drugs that degrade such behavior in nonhuman primates. Schulze et al.55,56 investigated the acute affects of delta-9-THC (the active ingredient in marijuana smoke) and marijuana smoke itself in rhesus monkeys as measured by performance in the NCTR OTB. The results for the DMTS task showed that THC decreased both the number of reinforcers earned and the percent task completed, primarily by increasing the time it took subjects to begin each trial (increased mean observing response latencies). Marijuana smoke administration, at exposure levels that produced plasma THC levels similar to those seen in humans after marijuana smoke exposure, also significantly increased response latencies (increased time to initiate trials and to make recall choices). Similarly, this lab reported that diazepam, a gamma-amino butyric acid (GABA) agonist, significantly decreased DMTS task accuracy in rhesus monkeys across several different time delays.56 Additionally, the μ opiate receptor agonist, morphine, significantly decreased the number of reinforcers earned and percent task completed and increased response latencies, while having little effect on recall accuracy.57 Finally, the psychostimulant amphetamine, while having no effects on DMTS task performance at low doses, significantly decreased percent task completed, increased observing response latencies, and decreased accuracy at the longer recall delays.58

12.5

REPRESENTATIVE DATA

In this section representative nonhuman primate data for all of the tasks described in this chapter are briefly discussed. Figure 12.5A and B show data for a DR task in which performance has been enhanced: overall accuracy (Figure 12.5A) was increased and rate of forgetting (Figure 12.5B) was decreased following pretreatment with bextaxol, a G-1 adrenergic receptor antagonist.59 These data reveal a role of the adrenergic system in DR performance. Figure 12.6 shows representative data for monkey performance in a delayed alternation task,60 showing an impairment in recall accuracy after the administration of the anxiogenic drug FG 7142 (a Gcarboline, GABAA receptor partial inverse agonist), and the amelioration of that effect by pretreatment with three different dopamine receptor antagonists (haloperidol, SCH23390, and clozapine). Additionally, a benzodiazepine receptor antagonist was administered along with FG 7142 to illustrate the GABA agonist’s receptor specificity. These data demonstrate the involvement of the GABA and dopamine systems in the performance of delayed alternation tasks. Figure 12.7 shows a decrease in delayed matching-to-sample task accuracy following treatment with LSD, a serotonin receptor partial agonist.37 These data illustrate how this compound preferentially affects discriminability, encoding, or


257

Percent Correct

80

*

70 60 50

Saline

.00011

.0011

Betax (mg/kg) (a)

.011

# of Correct Choices (out of 6)

Working Memory 6

*

5

*

4 3 A

B C D Delay Length

E

(b)

FIGURE 12.5 (a) The effect of betaxolol (G-1 adrenergic receptor antagonist) enhanced delayed response performance in monkeys (n = 10). Data are shown as mean percent correct ± SEM (out of 30 trials) following systemic administration of saline, .00011, .0011, or .011 mg/ kg of betaxolol. *Significant difference from saline (p = .008). (b) The effect of betaxolol on the delayed response performance of monkeys at different recall delays. The most effective dose was selected for each monkey (n = 8). Data are shown as mean number correct ± SEM (out of six trials/delay) for five different delays (A, B, C, D, and E) following betaxolol treatment (closed squares). *Denotes significant difference from saline (open squares). Source: From Ramos, B. P., Colgan, L., Nou, E., Ovadia, S., Wilson, S. R., and Arnsten, A. F. 2005. The beta-1 adrenergic antagonist, betaxolol, improves working memory performance in rats and monkeys. Biol. Psychiatry 58:894–900, with permission.

attention, while not affecting rate of memory decay. Additionally, a recent report has demonstrated an enhanced performance accuracy in the DMTS task following treatment with a serotonin receptor antagonist.61 In that report, the length of recall delays were adjusted subject to attain similar levels of performance accuracy for all subjects: (1) a least difficult zero delay (85%–100% accuracy), (2) a short delay (75%–84% accuracy), (3) a medium delay (65%–74% accuracy), and (4) a long delay representing chance performance (55%–64% accuracy). Figure 12.8A shows representative data of drug-enhanced DMTS task accuracy in young monkeys at a medium-difficulty recall delay. This increase in accuracy resulted from treatment with EMD 281014, a serotonin 2A receptor antagonist.61 Figure 12.8B shows data for this same compound where it is shown to improve delayed matching performance in aged rhesus monkeys at both medium- and long-recall delays.61 Figure 12.9 shows data from animals performing a DNMTS task using the CANTAB system. Here a decrease in accuracy of task performance was clear following treatment with the muscarinic cholinergic receptor antagonist scopolamine.62 Figure 12.10, on the other hand, demonstrates that the cholinesterase inhibitor physostigmine can enhance accuracy of DNMTS task performance.63 These examples of representative data serve to show how different drugs from a variety of pharmacological classes can either degrade or enhance performance in different DR tasks. These data also suggest that numerous neurotransmitter systems are involved in performance of DR tasks.


258


Delayed Response, Percent Correct

100

90

**

80

70

**

*

** ** *

*

60

50

VEH VEH RO RO HAL HAL CLZ CLZ SCH SCH + + + + + + + + + + VEH FG VEH FG VEH FG VEH FG VEH FG (n = 4) (n = 4) (n = 4) (n = 4) (n = 4) (n = 4) (n = 4) (n = 4) (n = 3) (n = 3)

FIGURE 12.6 Effects of FG 7142 (a G-carotine, partial inverse agonist of the benzodiazepine receptor) and dopamine receptor antagonists on delayed alternation performance in the monkey. FG 7142 produced a significant impairment in response accuracy when compared with vehicle performance. Although there was no change in performance with R015-1788 (a benzodiazepine receptor antagonist) when given alone, pretreatment with R015-1788 prevented the FG 7142-induced impairment. Haloperidol and SCH23390 (both dopamine receptor antagonists) significantly impaired cognitive performance when given alone. Clozapine (another dopamine receptor antagonist) produced a small nonsignificant impairment in performance when given alone. Haloperidol, clozapine, and SCH23390 all ameliorated the FG 7142–associated cognitive impairment when given as a pretreatment. Source: From Murphy, B. L., Arnsten, A. F., Goldman-Rakic, P. S., and Roth, R. H. 1996. Increased dopamine turnover in the prefrontal cortex impairs spatial working memory performance in rats and monkeys. Proc. Natl. Acad. Sci. USA 93:1325–9, with permission.

12.6

LIMITATIONS AND CONCLUSIONS

DR tasks fulfill many of the criteria needed to measure short-term or working memory. There are, however, some aspects of these paradigms that pose problems if not considered. First, in tasks employing few response locations, subjects frequently develop a position bias, which is evidenced by a majority of their choice responses being restricted to one of the locations, for example, to either the right or left response position in a two-choice paradigm. As a result, on approximately 50% of all trials the subject’s response to the right-hand location can result in a correct response and reinforcement.64 In addition, even when such biases are not observed under control conditions, they can be seen following drug administration, making interpretation of dose-response curves and drug effects difficult.65 DR tasks can also suffer from the occurrence of prominent ceiling and/or floor effects. If the task is not challenging enough, response accuracies even at long delays can be very high, making detection


Working Memory

259 Short-Term Memory Task

120 100

Accuracy

80 60 0 0.0003 0.001 0.003 0.01 0.03

40 20 0

2

8

16 32 Time Delay (seconds)

48

64

FIGURE 12.7 Data from a delayed-matching-to-sample task comparing vehicle (shaded area represents 95% confidence interval after saline administration) to lysergic acid diethylamide (LSD, serotonin receptor partial agonist) in monkeys. The highest dose of LSD shows a significant effect on accuracy of performance indicative of a decrease in attention and/or encoding with no effect on rate of forgetting (slope of decay is unaffected). Source: From Frederick, D. L., Gillam, M. P., Lensing, S., and Paule, M. G. 1997. Acute effects of LSD on rhesus monkey operant test battery performance. Pharmacol. Biochem. Behav. 57:633–41, with permission.

of treatment-induced increases in memory impossible. This problem can usually be overcome by lengthening the delays and/or increasing the complexity of the stimuli so that discrimination between sample and choice stimuli becomes more difficult. Conversely, if the task is too difficult, a floor effect can be apparent, in which case delays can be shortened or the difficulty of the discrimination can be made less demanding. In summary, DR tasks in nonhuman primates are very useful for assessing and elucidating the biological underpinnings of working memory that are relevant to humans. The clinical relevance of these types of tasks is further supported by the observation that DMTS performance in humans correlates significantly with IQ.66 By inference, then, use of these tasks in animals would seem to provide direct access to important aspects of animal intelligence.


260


Matching Performance (Percent Correct)

100 90

90

80

80

70

70

60

60

50 80

Medium Delays

60

60

100

0.1

1.0

3.0

10.0

Veh Dose (mg/kg) (a) Aged Monkeys 100

Zero Delays

90

80

80

70

70

60

60

*

60 50

70

0.1

1.0

3.0

10.0

Short Delays

50 80

Medium Delays

70

Vehicle EMD Compound

50

90

50 80

Long Delays

* 70

Veh

Short Delays

50 80

70

50

Matching Performance (Percent Correct)

Young Monkeys 100

Zero Delays

Long Delays Vehicle EMD 281014

*

60

Veh

0.1

1.0

3.0

10.0

50 Dose (mg/kg) (b)

Veh

0.1

1.0

3.0

10.0

FIGURE 12.8 (a) Representative data of drug-treatment-enhanced accuracy of delayedmatching-to-sample (DMTS) task performance in young monkeys. Increased accuracy is observed for medium recall delays after treatment with the selective serotonin 5-HT 2A receptor antagonist EMD 281014. (b) The effect of EMD 281014 to improve DMTS performance in aged rhesus monkeys at both medium and long recall delays. Delay durations were titrated for each subject in order to equate task performance among subjects. Source: From Terry, A. V. Jr., Buccafusco, J. J., and Bartoszyk, G. D. 2005. Selective serotonin 5-HT2A receptor antagonist EMD 281014 improves delayed matching performance in young and aged rhesus monkeys. Psychopharmacology (Berl.) 179:725–32, with permission. © 2009 by Taylor & Francis Group, LLC

Working Memory

Percent Correct Choices

100%

Simultaneous 0s 16s 32s 64s

90% 80% 70% 60% 50%

Baseline

Vehicle

3 10 Scopolamine (µg/kg, i.m.)

14

17

FIgure . Effect of scopolamine on mean (n = 6, except for the 14 μg/kg dose; ± SEM) choice accuracy in a delayed-non-matching-to-sample task expressed as the percent of trials completed on which a correct choice was made showed impairment. Data are shown for the simultaneous condition as well as for 0-, 16-, 32-, and 64-sec retention intervals. Random responding corresponds to a choice accuracy of 50%. There was a significant main effect of both retention interval and drug condition (p < 0.05). These data were generated using a touch screen apparatus, i.e., CANTAB. Source: From Taffe, M. A., Weed, M. R., and Gold, L. H. 1999. Scopolamine alters rhesus monkey performance on a novel neuropsychological test battery. Brain Res. Cogn. Brain Res. 8:203–12, with permission.

Percent Correct

90 *

80

70

60

50

S

3.2

10

32

FIgure .0 The effect of physostigmine, a cholinesterase inhibitor, was to enhance monkey accuracy on a delayed non-matching-to-sample task but only at a specific dose (s = saline, 3.2, 10, and 32 μg/kg). Scores are group means (± SEM) as a function of dose. Monkeys received saline or the indicated dose of physostigmine i.m. 20 min before testing. *p < 0.05 vs. saline treatment. Source: From Ogura, H., and Aigner, T. G. 1993. MK-801 impairs recognition memory in rhesus monkeys: comparison with cholinergic drugs. J. Pharmacol. Exp. Ther. 266:60–4, with permission. © 2009 by Taylor & Francis Group, LLC

262


REFERENCES 1. Hulse, S. H. and Honig, W. K. 1978. Studies in working memory in the pigeon. In Cognitive processes in animal behavior, eds. S. H. Hulse, H. Fowler, and W. K. Honig, 211–248. Hillsdale, NJ: Lawrence Erlbaum Associates. 2. Sullivan, E. V., Sagar, H. J., Gabrieli, J. D., Corkin, S., and Growdon, J. H. 1989. Different cognitive profiles on standard behavioral tests in Parkinson’s disease and Alzheimer’s disease. J. Clin. Exp. Neuropsychol. 11:799–820. 3. Davachi, L., and Goldman-Rakic, P. S. 2001. Primate rhinal cortex participates in both visual recognition and working memory tasks: Functional mapping with 2-DG. J. Neurophysiol. 85:2590–601. 4. Constantinidis, C., Franowicz, M. N., and Goldman-Rakic, P. S. 2001. The sensory nature of mnemonic representation in the primate prefrontal cortex. Nat. Neurosci. 4:311–6. 5. Goldman-Rakic, P. S. 1990. Cellular and circuit basis of working memory in prefrontal cortex of nonhuman primates. Prog. Brain Res. 85:325–35; discussion 335–6. 6. Goldman-Rakic, P. S. 2002. The “psychic cell” of Ramon y Cajal. Prog. Brain Res. 136:427–34. 7. Murray, E. A., and Mishkin, M. 1998. Object recognition and location memory in monkeys with excitotoxic lesions of the amygdala and hippocampus. J. Neurosci. 18:6568–82. 8. Zola, S. M., Squire, L. R., Teng, E., Stefanacci, L., Buffalo, E. A., and Clark, R. E. 2000. Impaired recognition memory in monkeys after damage limited to the hippocampal region. J. Neurosci. 20:451–63. 9. Squire, L. R. 2004. Memory systems of the brain: A brief history and current perspective. Neurobiol. Learn. Mem. 82:171–7. 10. Goldman-Rakic, P. S., Lidow, M. S., Smiley, J. F., and Williams, M. S. 1992. The anatomy of dopamine in monkey and human prefrontal cortex. J. Neural. Transm. Suppl. 36:163–77. 11. Evans, H. L. 1990. Nonhuman primates in behavioral toxicology: Issues of validity, ethics and public health. Neurotoxicol. Teratol. 12:531–6. 12. Weed, J. L., Lane, M. A., Roth, G. S., Speer, D. L., and Ingram, D. K. 1997. Activity measures in rhesus monkeys on long-term calorie restriction. Physiol. Behav. 62:97–103. 13. Taffe, M. A. 2004. Effects of parametric feeding manipulations on behavioral performance in macaques. Physiol. Behav. 81:59–70. 14. Pugh, T. D., Klopp, R. G., and Weindruch, R. 1999. Controlling caloric consumption: Protocols for rodents and rhesus monkeys. Neurobiol. Aging 20:157–65. 15. Lane, M. A., Black, A., Handy, A., Tilmont, E. M., Ingram, D. K., and Roth, G. S. 2001. Caloric restriction in primates. Ann. NY Acad. Sci. 928:287–95. 16. Roth, G. S., Ingram, D. K., and Lane, M. A. 2001. Caloric restriction in primates and relevance to humans. Ann. NY Acad. Sci. 928:305–15. 17. Mattison, J. A., Black, A., Huck, J., et al. 2005. Age-related decline in caloric intake and motivation for food in rhesus monkeys. Neurobiol. Aging 26:1117–27. 18. Dellinger, J. A. 1991. Pharmacologic challenges for establishing interspecies extrapolation models in neurotoxicology. Neurosci. Biobehav. Rev. 15:21–3. 19. Paule, M. G. 1990. Use of the NCTR Operant Test Battery in nonhuman primates. Neurotoxicol. Teratol. 12:413–8. 20. Fray, P. J., and Robbins, T. W. 1996. CANTAB battery: Proposed utility in neurotoxicology. Neurotoxicol. Teratol. 18:499–504.


Working Memory

263

21. Weed, M. R., Taffe, M. A., Polis, I., et al. 1999. Performance norms for a rhesus monkey neuropsychological testing battery: Acquisition and long-term performance. Brain Res. Cogn. Brain Res. 8:185–201. 22. Friedman, H. R., and Goldman-Rakic, P. S. 1988. Activation of the hippocampus and dentate gyrus by working-memory: A 2-deoxyglucose study of behaving rhesus monkeys. J. Neurosci. 8:4693–706. 23. Goldman-Rakic, P. S. 1987. Development of cortical circuitry and cognitive function. Child Dev. 58:601–22. 24. Arnsten, A. F., Cai, J. X., and Goldman-Rakic, P. S. 1988. The alpha-2 adrenergic agonist guanfacine improves memory in aged monkeys without sedative or hypotensive side effects: Evidence for alpha-2 receptor subtypes. J. Neurosci. 8:4287–98. 25. Franowicz, J. S., and Arnsten, A. F. 1998. The alpha-2a noradrenergic agonist, guanfacine, improves delayed response performance in young adult rhesus monkeys. Psychopharmacology (Berl.) 136:8–14. 26. Levy, R., Friedman, H. R., Davachi, L., and Goldman-Rakic, P. S. 1997. Differential activation of the caudate nucleus in primates performing spatial and nonspatial working memory tasks. J. Neurosci. 17:3870–82. 27. Gaffan, D., and Weiskrantz, L. 1980. Recency effects and lesion effects in delayed nonmatching to randomly baited samples by monkeys. Brain Res. 196:373–86. 28. Paule, M. G., Bushnell, P. J., Maurissen, J. P., et al. 1998. Symposium overview: The use of delayed matching-to-sample procedures in studies of short-term memory in animals and humans. Neurotoxicol. Teratol. 20:493–502. 29. Mishkin, M., and Manning, F. J. 1978. Non-spatial memory after selective prefrontal lesions in monkeys. Brain Res. 143:313–23. 30. Buccafusco, J. J. 2001. Methods of Behavior Analysis in Neuroscience. Boca Raton, FL: Taylor and Francis. 31. Murray, E. A., Bussey, T. J., Hampton, R. R., and Saksida, L. M. 2000. The parahippocampal region and object identification. Ann. NY Acad. Sci. 911:166–74. 32. Meunier, M., Bachevalier, J., and Mishkin, M. 1997. Effects of orbital frontal and anterior cingulate lesions on object and spatial memory in rhesus monkeys. Neuropsychologia 35:999–1015. 33. Kowalska, D. M., Bachevalier, J., and Mishkin, M. 1991. The role of the inferior prefrontal convexity in performance of delayed nonmatching-to-sample. Neuropsychologia 29:583–600. 34. Buffalo, E. A., Ramus, S. J., Clark, R. E., Teng, E., Squire, L. R., and Zola, S. M. 1999. Dissociation between the effects of damage to perirhinal cortex and area TE. Learn. Mem. 6:572–99. 35. Beason-Held, L. L., Rosene, D. L., Killiany, R. J., and Moss, M. B. 1999. Hippocampal formation lesions produce memory impairment in the rhesus monkey. Hippocampus 9:562–74. 36. Stern, C. E., Sherman, S. J., Kirchhoff, B. A., and Hasselmo, M. E. 2001. Medial temporal and prefrontal contributions to working memory tasks with novel and familiar stimuli. Hippocampus 11:337–46. 37. Frederick, D. L., Gillam, M. P., Lensing, S., and Paule, M. G. 1997. Acute effects of LSD on rhesus monkey operant test battery performance. Pharmacol. Biochem. Behav. 57:633–41. 38. Hampson, R. E., and Deadwyler, S. A. 1999. Cannabinoids, hippocampal function and memory. Life Sci. 65:715–23. 39. Buccafusco, J. J., Terry, A. V. Jr., Decker, M. W., and Gopalakrishnan, M. 2007. Profile of nicotinic acetylcholine receptor agonists ABT-594 and A-582941, with differential subtype selectivity, on delayed matching accuracy by young monkeys. Biochem. Pharmacol. 74:1202–11.


264


40. Paule, M. G. 2005. Chronic drug exposures during development in nonhuman primates: Models of brain dysfunction in humans. Front. Biosci. 10:2240–9. 41. Zola, S. M., and Squire, L. R. 2001. Relationship between magnitude of damage to the hippocampus and impaired recognition memory in monkeys. Hippocampus 11:92–8. 42. Burbacher, T. M., and Grant, K. S. 2000. Methods for studying nonhuman primates in neurobehavioral toxicology and teratology. Neurotoxicol. Teratol. 22:475–86. 43. Rice, D. C. 2000. Parallels between attention deficit hyperactivity disorder and behavioral deficits produced by neurotoxic exposure in monkeys. Environ. Health Perspect. 108,suppl 3:405–8. 44. Coghill, D. R., Rhodes, S. M., and Matthews, K. 2007. The neuropsychological effects of chronic methylphenidate on drug-naive boys with attention-deficit/hyperactivity disorder. Biol. Psychiatry 62(9):954–62. 45. Chelonis, J. J., Edwards, M. C., Schulz, E. G., et al. 2002. Stimulant medication improves recognition memory in children diagnosed with attention-deficit/hyperactivity disorder. Exp. Clin. Psychopharmacol. 10:400–7. 46. McCarten, J. R., Kovera, C., Maddox, M. K., and Cleary, J. P. 1995. Triazolam in Alzheimer’s disease: Pilot study on sleep and memory effects. Pharmacol. Biochem. Behav. 52:447–52. 47. Arnsten, A. F., and Goldman-Rakic, P. S. 1985. Catecholamines and cognitive decline in aged nonhuman primates. Ann. NY Acad. Sci. 444:218–34. 48. Jackson, W. J., and Buccafusco, J. J. 1991. Clonidine enhances delayed matchingto-sample performance by young and aged monkeys. Pharmacol. Biochem. Behav. 39:79–84. 49. Decker, M. W., Bannon, A. W., Curzon, P., et al. 1997. ABT-089 [2-methyl-3-(2-(S)-pyr rolidinylmethoxy)pyridine dihydrochloride]: II. A novel cholinergic channel modulator with effects on cognitive performance in rats and monkeys. J. Pharmacol. Exp. Ther. 283:247–58. 50. Prendergast, M. A., Terry, A. V. Jr., Jackson, W. J., et al. 1997. Improvement in accuracy of delayed recall in aged and non-aged, mature monkeys after intramuscular or transdermal administration of the CNS nicotinic receptor agonist ABT-418. Psychopharmacology (Berl.) 130:276–84. 51. Jackson, W. J., Buccafusco, J. J., Terry, A. V., Turk, D. J., and Rush, D. K. 1995. Velnacrine maleate improves delayed matching performance by aged monkeys. Psychopharmacology (Berl.) 119:391–8. 52. Prendergast, M. A., Jackson, W. J., Terry, A. V. Jr., Decker, M. W., Arneric, S. P., and Buccafusco, J. J. 1998. Central nicotinic receptor agonists ABT-418, ABT-089, and (-)-nicotine reduce distractibility in adult monkeys. Psychopharmacology (Berl.) 136:50–8. 53. Terry, A. V. Jr., Buccafusco, J. J., Prendergast, M. A., et al. 1996. The 5-HT3 receptor antagonist, RS-56812, enhances delayed matching performance in monkeys. Neuroreport 8:49–54. 54. Terry, A. V. Jr., Buccafusco, J. J., Jackson, W. J., et al. 1998. Enhanced delayed matching performance in younger and older macaques administered the 5-HT4 receptor agonist, RS 17017. Psychopharmacology (Berl.) 135:407–15. 55. Schulze, G. E., McMillan, D. E., Bailey, J. R., et al. 1988. Acute effects of delta-9tetrahydrocannabinol in rhesus monkeys as measured by performance in a battery of complex operant tests. J. Pharmacol. Exp. Ther. 245:178–86. 56. Schulze, G. E., McMillan, D. E., Bailey, J. R., et al. Acute effects of marijuana smoke on complex operant behavior in rhesus monkeys. Life Sci. 45:465–75. 57. Schulze, G. E., and Paule, M. G. 1991. Effects of morphine sulfate on operant behavior in rhesus monkeys. Pharmacol. Biochem. Behav. 38:77–83.


Working Memory

265

58. Schulze, G. E., and Paule, M. G. 1990. Acute effects of d-amphetamine in a monkey operant behavioral test battery. Pharmacol. Biochem. Behav. 35:759–65. 59. Ramos, B. P., Colgan, L., Nou, E., Ovadia, S., Wilson, S. R., and Arnsten, A. F. 2005. The beta-1 adrenergic antagonist, betaxolol, improves working memory performance in rats and monkeys. Biol. Psychiatry 58:894–900. 60. Murphy, B. L., Arnsten, A. F., Goldman-Rakic, P. S., and Roth, R. H. 1996. Increased dopamine turnover in the prefrontal cortex impairs spatial working memory performance in rats and monkeys. Proc. Natl. Acad. Sci. USA 93:1325–9. 61. Terry, A. V. Jr., Buccafusco, J. J., and Bartoszyk, G. D. 2005. Selective serotonin 5HT2A receptor antagonist EMD 281014 improves delayed matching performance in young and aged rhesus monkeys. Psychopharmacology (Berl.) 179:725–32. 62. Taffe, M. A., Weed, M. R., and Gold, L. H. 1999. Scopolamine alters rhesus monkey performance on a novel neuropsychological test battery. Cogn. Brain Res. 8:203–12. 63. Ogura, H., and Aigner, T. G. 1993. MK-801 impairs recognition memory in rhesus monkeys: Comparison with cholinergic drugs. J. Pharmacol. Exp. Ther. 266:60–4. 64. Angeli, S. J., Murray, E. A., and Mishkin, M. 1993. Hippocampectomized monkeys can remember one place but not two. Neuropsychologia 31:1021–30. 65. Baron, S. P., and Wenger, G. R. 2001. Effects of drugs of abuse on response accuracy and bias under a delayed matching-to-sample procedure in squirrel monkeys. Behav. Pharmacol. 12:247–56. 66. Paule, M. G., Chelonis, J. J., Buffalo, E. A., Blake, D. J., and Casey, P. H. 1999. Operant test battery performance in children: Correlation with IQ. Neurotoxicol. Teratol. 21:223–30.


Navigation 13 Spatial (Water Maze) Tasks Alvin V. Terry Jr. CONTENTS 13.1 13.2

Introduction................................................................................................. 267 Standard Procedures ................................................................................... 269 13.2.1 Methodology .................................................................................... 270 13.2.1.1 Testing Apparatus............................................................... 270 13.2.1.2 Hidden Platform Test.......................................................... 271 13.2.1.3 Transfer Test (Probe Trials)................................................ 272 13.2.1.4 Visible Platform Tests ........................................................ 272 13.2.1.5 Relearning Phases .............................................................. 273 13.2.2 Statistical Analyses.......................................................................... 273 13.2.2.1 Hidden Platform Test.......................................................... 273 13.2.2.2 Transfer Test (Probe Trials)................................................ 273 13.2.2.3 Visible Platform Test .......................................................... 274 13.2.2.4 Relearning Phases .............................................................. 274 13.2.3 Representative Data ......................................................................... 274 13.3 Alternative Procedures................................................................................ 277 13.3.1 Place Recall Test.............................................................................. 277 13.3.2 Platform Discrimination Procedures ............................................... 277 13.3.3 Working Memory Procedures.......................................................... 278 13.3.4 Extinction......................................................................................... 278 13.4 Summary and Conclusions ......................................................................... 278 References.............................................................................................................. 279

13.1

INTRODUCTION

Since the early part of the 20th century, a variety of experimental procedures have been developed for animals that employ the escape from water as a means to motivate learning and memory processes.1–4 Water maze tasks primarily designed to measure spatial learning and recall have become quite useful for evaluating the effects of aging, experimental lesions, and drug effects, especially in rodents. For more than 25 years the Morris water maze (MWM)5 has been the task most extensively used and accepted by behavioral physiologists and pharmacologists. A cursory literature search revealed that well over 2500 journal articles have been published since 1982 in which this model (or variations of the model) was used to assess and compare spatial learning and memory in rodents. 267


268


The MWM, while simple at first glance, is a challenging task for rodents that employs a variety of sophisticated mnemonic processes. These processes encompass the acquisition and spatial localization of relevant visual cues that are subsequently processed, consolidated, retained, and then retrieved in order to successfully navigate and thereby locate a hidden platform to escape the water5 (see also review6). The general processes used for “visuospatial navigation” in rats also contribute considerably to human day-to-day cognitive processes. Importantly, several lines of evidence confirm the utility of the model for investigations relevant to the study of neurodegenerative and neuropsychiatric illnesses where cognition is impaired (e.g., Alzheimer’s disease, Parkinson’s disease, schizophrenia). While one would readily acknowledge the differences in complexity between human and rodent behaviors, several salient observations regarding the utility of the MWM are notable: (1) The functional integrity of forebrain cholinergic systems, which are essential for efficient performance of the MWM, appears to be consistently disrupted in patients who suffer from AD. This disruption correlates well with the degree of dementia (see reviews7,8) and is also present in many PD patients who suffer cognitive decline.9,10 (2) Cortical and hippocampal projections from the nucleus basalis magnocellularis (NBM) and medial septum (MS), respectively, are reproducibly devastated in AD (reviewed7) and accordingly, reductions in central cholinergic activity in rodents resulting from brain lesions (e.g., NBM, MS, etc.) and age reproducibly impair spatial learning in the MWM (reviewed6). (3) Other data implicate the hippocampus as an essential structure for place learning,11which, incidentally, is commonly atrophic in patients with AD.12,13 It is interesting to note that the hippocampal formation (in particular the hippocampal-dentate complex and the adjacent entorhinal cortex), which undergoes significant degeneration with age (and particularly so in the setting of dementia), is believed to be intimately involved in cognitive mapping and the facilitation of context-dependent behavior in a changing spatio-temporal setting (reviewed14). Evidence to support this premise is now available from living humans where computerized “virtual water maze tasks” have been shown to be highly sensitive to hippocampal dysfunction. For example, in a virtual analogue of the classic MWM hidden platform task (with a three-dimensional pool), patients with unilateral hippocampal resections were severely impaired in their performance relative to agematched controls and age-matched patients who had extra-hippocampal resections.15 (4) Anticholinergic agents (e.g., scopolamine), which are routinely used to impair performance in the MWM, also impair memory in humans and worsen the dementia in those with AD16 (see also review17). (5) Finally, it is also important to note that spatial orientation, navigation, learning, and recall (which are used extensively in the MWM) are quite commonly disrupted in patients with dementia. Visuospatial and visuoperceptual deficits and topographic disorientation are detectable very early in the course of AD and become more pronounced as the disease progresses.18–20 The common observations of spatial and visual agnosia in AD patients also indicate the disruption of complex processes that involve both visual pathways and mnemonic processing.21,22 The MWM procedure offers a number of advantages as a means of assessing cognitive function in rodents when compared to others methods: (1) It requires no pretraining period and can be accomplished in a short period of time with a relatively


Spatial Navigation (Water Maze) Tasks

269

modest number of animals. For example, young adult, unimpaired (control) rats can accomplish the most commonly employed versions of the task with asymptotic levels of performance achieved in 10–20 trials, generally requiring no more than a few days of testing. (2) Through the use of “training” as well as “probe” or “transfer” trials, learning as well as retrieval processes (spatial bias)5 can be analyzed and compared between groups. (3) The confounding nature of olfactory trails or cues is eliminated. (4) Through the use of video tracking devices and the measure of swim speeds, non-mnemonic behaviors or strategies (i.e., taxon, praxis, thygmotaxis, etc.) can be delineated and motoric or motivational deficits can be identified. (5) Visible platform tests can identify gross visual deficits that might confound interpretation of results obtained from standard MWM testing. (6) By changing the platform location, both learning and relearning experiments can be accomplished. Accordingly, several doses of experimental drugs can be tested in the same group of animals. (7) While immersion into water may be somewhat unpleasant, more aversive procedures such as food deprivation or exposure to electric shock are circumvented. (8) Through the use of curtains, partitions, etc., operation of the video tracking system by the experimenter out of site of the test subjects also reduces distraction. (9) Finally, the MWM is quite easy to set up in a relatively small laboratory, is comparatively less expensive to operate than many types of behavioral tasks, and is easy to master by research and technical personnel. We have found the method quite useful in drug discovery and development studies for screening compounds for potential cognitive enhancing effects,23 as well as delineating deleterious effects of neurotoxicants on cognition.24 For a more extensive discussion of the various MWM procedures and their advantages, see Morris5 and reviews.6,25,26

13.2

STANDARD PROCEDURES

The MWM generally consists of a large circular pool of water maintained at room temperature (or slightly above) with a fixed platform hidden just below (i.e., ~ 1.0 cm) the surface of the water. The platform is rendered invisible by one of several means: (1) adding an agent (i.e., powdered milk or a nontoxic dye or food coloring agent) to render the water opaque; (2) having a clear Plexiglas platform in clear water; (3) or having the platform painted the same color as the pool wall and floor (e.g., black on black). Rats are tested individually and placed into various quadrants of the pool and the time elapsed and/or the distance traversed to reach the hidden platform is recorded. Various objects or geometric images (e.g., circles, squares, triangles) are often placed in the testing room or hung on the wall so that the rats can use these visual cues as a means of navigating in the maze. With each subsequent entry into the maze the rats progressively become more efficient at locating the platform, thus escaping the water by learning the location of the platform relative to the distal visual cues. The learning curves are thus compared between groups. An illustration of a typical MWM setup (as used in our laboratory) appears in Figure 13.1. The inset at the top right illustrates typical learning behavior (under vehicle control conditions) on day 1 of a two trial per day × 6 day hidden platform task when test subjects search throughout the pool before locating the escape platform. The inset at the middle right illustrates the search behavior on day 6 when the subject has learned the task and


270

Methods of Behavior Analysis in Neuroscience, Second Edition Day 1

Water Maze Testing

Camera

Light

Day 6

Visual Cue

Morris Water Maze Hidden Platform

Day 7 Probe Trials

FIGURE 13.1 Diagrammatic illustration of the Morris water maze testing room and apparatus.

can easily locate the platform in a matter of seconds. Finally, the inset on the bottom right illustrates the clear bias for the previous platform location during the probe trial on day 7 of testing after the escape platform has been removed.

13.2.1 METHODOLOGY 13.2.1.1 Testing Apparatus 1. Maze testing should be conducted in a large circular pool (e.g., rats, diameter: 180 cm, height: 76 cm; mice, diameter: 100–120 cm, height: 76 cm) made of plastic (e.g., Bonar Plastics, Noonan, Georgia, USA) and painted black. 2. Fill the pool to a depth of 35 cm of water (maintained at 25°C + 1.0°C) to cover an invisible (black) 10-cm square platform. The platform should be submerged approximately 1.0 cm below the surface of the water and placed in the center of the northeast quadrant. Note: We have found that using a black platform in a pool with the sides and floor painted black obviates the need for addition of agents to render the water opaque. If the experimenter is unsure whether or not the platform is still visible, closing the curtains to eliminate spatial cues and subsequently testing a few rats will resolve this question. While rats can use egocentric cues to eventually acquire the location of the platform, they will not rapidly (or efficiently) become more successful with each entry into the pool if the



271

platform is invisible and room lighting is diffuse (i.e., when most of the allocentric cues are eliminated). 3. The pool should be located in a large room with a number of extramaze visual cues, including highly visible (reflective) geometric images (squares, triangles, circles, etc.) hung on the wall, diffuse lighting, and black curtains to hide the experimenter and the awaiting rats. Swimming activity of each rat may be monitored via a television camera mounted overhead, which relays information including latency to find the platform, total distance traveled, time and distance spent in each quadrant, etc., to a video tracking system. Tracking may be accomplished via a white rat on a black background. Note: We have found the Noldus EthoVision¥ system (Leesburg, Virginia, USA) to be a very reliable system that is also easy to set up. Several other vendors market similar systems (e.g., San Diego Instruments, Columbus Instruments). 13.2.1.2 Hidden Platform Test We commonly employ a method in which each rat is given two trials per day for six consecutive days. 1. Each day, a trial is initiated by placing each rat in the water facing the pool wall in one of the four quadrants (designated NE, NW, SE, SW), which are set up on the computer software so that each quadrant is equal in area. The daily order of entry into individual quadrants is randomized so that all four quadrants are used once every two days. Note: Do not place the rat in adjacent quadrants sequentially since the rat may adopt a positional or other non-mnemonic strategy (e.g., all right turns) to locate the platform. Further, the order should be changed on each subsequent day of testing. 2. For each trial, the rat is allowed to swim a maximum of 90 sec to find the hidden platform. When successful, the rat is allowed a 30-sec rest period on the platform (timed manually with a stopwatch). If unsuccessful within the allotted time period, the rat is given a score of 90 sec and is then physically placed on the platform and allowed the 30-sec rest period. In either case the rat is immediately given the next trial (inter-trial interval = 30 sec) after the rest period. Note: In some cases the rat may fall or jump off of the platform and resume swimming before the elapsed 30-sec interval. When this occurs, the stopwatch should be immediately stopped and the rat retrieved and placed on the platform again. The stopwatch should be reactivated so that the remainder of the time interval (30 sec) is enforced. This assures that each rat has equal time to observe spatial cues after each trial.


272


13.2.1.3 Transfer Test (Probe Trials) On day 7 (i.e., 24 hr following the last hidden platform trial) a probe trial is conducted in which the platform is removed from the pool to measure spatial bias for the previous platform location.5 This is accomplished by measuring the percentage of time spent (and distance swam) in the previous target quadrant as well as the number of crossings over the previous platform location. These assessments provide a second estimate of the strength and accuracy of the memory of the previous platform location. 1. Place each rat in the pool and track the animal for 90 sec. This may be repeated one time (if necessary), since in some cases an unusual level of variance in performance will be observed in this first trial. It is assumed that some of the rats are in some way disoriented after the change in testing conditions. Note: More than two trials may result in “extinction” effects (see section “Alternative Procedures” below) with less time spent in the target quadrant, and is thus undesirable for a measure of spatial bias. 2. The time elapsed and distance swam in the previous target quadrant is recorded. An annulus ring can be circumscribed around the previous target location (on the computer screen) to localize it more closely. The number of crossings through this region may be recorded. Alternatively, crossings of the actual 10-cm square platform target outlined in the previous trials can be recorded and compared between groups. 13.2.1.4 Visible Platform Tests A visible platform test may be performed to determine if a drug or other experimental manipulation results in crude alterations in visual acuity that might confound the analyses of data that depend on the use of distal visual cues for task performance. One must be aware, however, of certain behaviors that might be interpreted as impaired visual acuity. For example, the absence of search behaviors or thymgotaxis (swimming constantly along the perimeter of the pool) might be misinterpreted as visual deficits since the animal does not locate the platform in a reasonable period of time. Thus, animals must make attempts to cross the pool and then be impaired at locating the platform in order for an interpretation of visual deficits to be made. 1. Immediately following the probe trial on day 7, place the platform into the pool in the quadrant located diametrically opposite the original position (SW quadrant). 2. A cover (available from San Diego Instruments, Inc. and other vendors), which is rendered highly visible (i.e., with light-reflective glossy or neon paint), is attached to the platform to raise the surface above the water level (approximately 1.5 cm). 3. Room lighting may be changed so that the extramaze cues are no longer available and the visible platform is more highly illuminated.



273

Note: The video tracker is not necessary for this procedure and only a stopwatch is needed. 4. Allow each rat one trial in order to acclimate to the new set of conditions and locate the platform visually. This is accomplished by lowering the rat into the water in the NE quadrant and allowing the rat to locate the platform. No time limit is placed on this first trial. Once the platform is located, allow the rat 30 sec on the platform. The rat should then immediately be given a second trial in the same manner and the latency to find the platform measured as a comparison of visual acuity. Note: This procedure may be repeated additional times; however, the platform location should be changed on each subsequent trial to ensure that visual location of the platform is actually made from a distance and the rat is not first using nearby stationary visual cues. 13.2.1.5 Relearning Phases After completion of the first seven days of water maze testing and a rest period (generally at least 1 wk and often longer), a second series of trials (phase 2) may be conducted as described above (hidden platform test section), except that the location of the platform is changed to a different quadrant. Daily performances (average of two trials/day/rat) are then compared as described above. This method may be used in order to compare different drug doses or other additional manipulations with the same groups of animals. Note: It must be realized that learning curves will generally be steeper than in the first phase of testing since a number of factors not associated with the actual platform location will have been previously learned (e.g., use of visual cues to navigate, the fact that escape is not associated with the pool wall, etc.).

13.2.2 STATISTICAL ANALYSES 13.2.2.1 Hidden Platform Test For the hidden platform test, we generally average the latencies and the distances swam across the two trials for each rat each day. These means are then analyzed across the six days of testing. A two-way repeated measures analysis of variance (ANOVA) is used for main effects (i.e., group or treatment comparisons) with day as the repeated measure and latency or distance swam as the dependent variable. The Student Newman-Keuls test is used for post-hoc analyses. 13.2.2.2 Transfer Test (Probe Trials) For probe trials the means are compared between groups via a one-way ANOVA and again, the Student Newman-Keuls test is used for post-hoc analyses.


274


13.2.2.3 Visible Platform Test For the visible platform test, the means are also compared between groups via a oneway ANOVA and the Student Newman-Keuls test is used for post-hoc analyses. 13.2.2.4 Relearning Phases The relearning phase is analyzed identically to the hidden platform test described above.

13.2.3 REPRESENTATIVE DATA Several representative MWM hidden platform studies under vehicle control conditions from our laboratory appear in Figure 13.2. The acquisition curves for rats given one trial per day for 14 consecutive days, two trials per day for six consecutive days, or four trials per day for four consecutive days are illustrated. We have used each of these methods in our laboratory in previous studies. Using each of these approaches, the rats learned to locate the hidden platform with progressively shorter latencies over the course of the study. We have found that young vehicle-treated test subjects (i.e., not age impaired or impaired by an amnestic drugs) given only one trial per day are somewhat less efficient at learning the task, but more sensitive to pro-cognitive agents (e.g., nicotine, see reference27) than subjects given multiple trials per day. Further, we have found the two- and four-trial-per-day methods to be useful for amnestic-reversal studies (see references28,29). An MWM study conduced in our laboratory in young (3–4 mo) and aged (22–24 mo) male Fisher 344 rats is presented in Figure 13.3. Figure 13.3A illustrates the efficiency of each experimental group to locate a hidden platform in a water maze task on 10 consecutive days of testing (two trials per day). As expected, under saline conditions the young rats learned to locate the hidden platform with progressively shorter latencies until the end of the study, while the aged rats administered saline were less efficient. For the latency comparisons, there was a highly significant main effect (p < 0.001), a significant trial effect (p < 0.001), and a significant group × trial interaction (p < 0.01). Post-hoc analyses indicated that performance by the young animals was superior to that of the aged animals across a number of days of testing. Further, the acetylcholinersterase inhibitor (and commonly prescribed AD therapeutic agent) donepezil (0.75 mg/kg) (in aged rats) was associated with superior performance over aged saline controls across several days of testing. In addition, all rats treated with donepezil reached a near-asymptotic level of performance (i.e., latencies less that 20 sec) by day 10 of testing, whereas this was not the case for aged rats administered saline. Figures 13.3B and 13.3C illustrate the performance of probe trials by the various test groups. As noted above, these experiments are performed after hidden platform tests (in this case 48 hr later) and reflect a “spatial bias” of animals toward the previous location of the hidden platform. The results are analyzed separately from the hidden platform tests and offer a second, easily performed method of estimating the strength and accuracy of the original learning process.6 It is important to note that since the pool is divided into four quadrants of equal area, a chance level of



275

60 40 20 2

4

6

8 10 12 14 Session

2000 1500 1000 500 0

60

1400

50

1200

40 30 20 10 0

1

2

3 4 Session

5

200 0

50

1200

10 1

2 3 Session

3 4 Session

14

400

1400

20

2

12

600

1

(b)

30

6 8 10 Session

800

6

40

4

1000

60

0

2

(a)

Distance to Platform (sec)

Latency to Platform (sec)


80

0


2500



100

5

6

1000 800 600 400 200 0

4 (c)

1

2 Session

3

4

FIGURE 13.2 Illustration of acquisition curves for several versions of the Morris water maze hidden platform test in young adult Wistar rats. The latency in seconds (left) and the distance swam in centimeters (right) to find the hidden platform are presented for each study. (a) A one-trial-per-day procedure conducted for 14 consecutive days; (b) A two-trial-per-day procedure conducted for six consecutive days; (c) A four-trial-per-day procedure conducted for four consecutive days. Each point represents the mean ± SEM, N = 10–12 rats per group. © 2009 by Taylor & Francis Group, LLC


% Time in Target Quadrant

276

70

50 40

+

50 40

*

30 20 10 0

30

Young Aged Aged Vehicle Vehicle Donepezil (b)

20

6 Aged Vehicle Aged Donepezil Young Vehicle

10 0 1

2

3 4 5 Day of Testing (a)

6

7

Platform Area Crossings

Latency Platform (sec)

60

60

5 4

+

3 2

*

1 0 Young Aged Aged Vehicle Vehicle Donepezil (c)

FIGURE 13.3 Effects of age and the Alzheimer’s disease therapeutic agent, donepezil, on performance of the MWM. (a) Hidden platform test. Each point represents the mean latency in sec ± SEM of two trials per day for 10 consecutive days of testing. (b and c) Probe trials. The percent of total time spent (in sec) in the previous target quadrant and the number of crossings over the previous platform area, respectively, 48 hr after the last hidden platform trial. Each bar represents the mean ± SEM. +=*=significantly different from vehicle-treated young rats significantly different from vehicle-treated aged rats (one-way ANOVA, p < 0.05, Student Neuman-Keuls post-hoc test), N = 14–22 rats per group.

performance would mean that the percent of time or distance swam (of the total) in the previous target quadrant would generally approximate 25%. As indicated in both Figures 13.3B and 13.3C, there were statistically significant (group-related) effects on performance (i.e., percent of time spent in the previous target quadrant and crossings over the previous platform area, respectively). Namely, aged vehicle-treated rats demonstrated less spatial bias than young vehicle-treated subjects, and donepezil partially reversed this impairment in aged subjects. In summary, these data support the argument that the MWM (as conducted in our laboratory) is sensitive to the impairing effects of aging on spatial navigation, learning, and recall, and further, that the procedure is sensitive to the positive effects of a well-known pro-cognitive agent (i.e., a positive control).



13.3

277

ALTERNATIVE PROCEDURES

A number of variations of the water maze tasks described above have been employed for the study of memory processes in rats and a full review of these procedures in beyond the scope of this chapter. A short summary of a few of these procedures is outlined below, however. For a more detailed overview of these and additional water maze procedures see Morris5 and reviews.6,25

13.3.1 PLACE RECALL TEST In this procedure, hidden platform tests are first performed as described above in intact animals so that the location of the platform is well learned. Subsequently, the rats are experimentally manipulated (i.e., given brain lesions, drugs, or other physiological manipulations, etc.) and then retested with either additional hidden platform tests or probe trials. Thus, the effects of the experimental manipulations on all processes used to solve the task, with the exception of learning and memory formation, may be studied. Namely, processes such as memory retrieval and spatial bias, as well as motoric, sensory, and motivational effects of the manipulations may be delineated.

13.3.2 PLATFORM DISCRIMINATION PROCEDURES These methods require rats to discriminate between two visible platforms in order to successfully escape the water (Figure 13.4, left). One of the platforms is rigid and

Water Maze Variations

Day 1

Day 4

Discrimination Tasks

Day 3

Day 2

Working Memory Tasks

FIGURE 13.4 Illustration of platform discrimination and working memory procedures in the Morris water maze.


278


able to sustain the weight of the rat, while the other platform is floating (often made of styrofoam) and not able to sustain the rat’s weight. Both spatial and nonspatial versions of this task have been used. In the spatial version of the task, the platforms appear identical (visually) and rats are required to discern the viable platform by learning its location relative to distal visual cues in the room. In the nonspatial version of the task, the rats learn to visually discriminate between two platforms of different appearance. For example, discrimination between platforms may be engendered via a difference in shape, brightness, or painted pattern. Curtains are drawn to exclude the influence of extramaze cues.

13.3.3 WORKING MEMORY PROCEDURES Working memory procedures in the MWM (sometimes referred to as spatial “matching to sample” procedures) generally involve a two-trials-per-day paradigm in which a hidden platform is located in one of four quadrants and randomly relocated on each of several subsequent days of testing (Figure 13.4, right). The assumption drawn is that each rat will obtain information regarding the location of the platform on the first trial, which will be of benefit for discerning its position on trial two. The ITI can be manipulated in order to alter the difficulty of the task.

13.3.4 EXTINCTION While not commonly used for this purpose, the behavioral process known as extinction can also be assessed in the MWM. Extinction occurs when the relations among stimuli recognized during acquisition are no longer valid and the previously established responses are suppressed. Accordingly, preferences for a spatial location decrease in the water maze as the animal learns that the cues no longer predict the location of the hidden platform.30 Extinction in this context is considered a type of cognitive flexibility, a form of fluid intelligence that encompasses the ability to inhibit strong response preferences in order to explore alternative solution paths.31 In contrast to the more common MWM studies where acquisition (hidden platform testing) and retention (probe trials) are the focus, in extinction experiments subjects are first trained in the hidden platform test to an asymptotic level of performance (defined as a latency to find the hidden platform of less than 10–15 sec for four consecutive trials). We have found in unpublished studies that 10–12 days (two trials per day) is more than sufficient to reach this asymptotic level in young vehicle-control subjects. Subsequently (i.e., on the following day after the last hidden platform test), four or more consecutive probe trials are conducted to assess the subject’s ability to decrease (i.e., extinguish) its spatial bias for the previous platform location.

13.4

SUMMARY AND CONCLUSIONS

The MWM equipped with a video tracking system has become a commonly used and well-accepted behavioral task for rodents. It is quite easy to set up in a relatively small laboratory, is comparatively less expensive to operate than many types of behavioral tasks, and is easy to master by research and technical personnel. It uses a number of mnemonic processes in rats that are relevant to the study of human learn-



279

ing and memory and disorders thereof. In addition, it is a very versatile paradigm, which can be used to study both spatial and nonspatial (discriminative) learning, as well as working memory processes and extinction, and offers several means of delineating and dissociating confounding non-mnemonic processes.

REFERENCES 1. Glaser, OC. 1910. The formation of habits at high speed. J. Comp. Neurol., 20, 165–184. 2. Wever, EG. 1932. Water temperature as an incentive to swimming activity in the rat. J. Comp Psychol, 14, 219–224. 3. Waller, MB, Waller, PF, and Brewster, LA. 1960. A water maze for use in studies of drive and learning. Psychol Rep, 7, 99–102. 4. Woods, PJ, Davidson, EH and Peters, R.J., 1964. Instrumental escape conditioning in a water tank: effects of variation in drive stimulus intensity and reinforcement magnitude. J. Comp. Psychol, 57, 466–470. 5. Morris, RGM. 1984. Development of a water-maze procedure for studying spatial learning in the rat. J Neurosci Meth 11, 47–60. 6. McNamara RK, and Skelton RW, 1993. The neuropharmacological and neurochemical basis of place learning in the Morris water maze. Brain Res Rev. 18, 33–49. 7. Perry E, Walker M, Grace J, Perry R. 1999. Acetylcholine in mind: a neurotransmitter correlate of consciousness? Trends Neurosci, 22, 273–280. 8. Francis PT, Palmer AM, Snape M, Wilcock GK. 1999. The cholinergic hypothesis of Alzheimer’s disease: a review of progress. J Neurol Neurosurg Psychiatry 66,137–147. 9. Whitehouse PJ, Hedreen JC, White CL 3d, Price DL. 1983. Basal forebrain neurons in the dementia of Parkinson disease. Ann Neurol 13, 243–248. 10. Perry EK, Curtis M, Dick DJ, Candy JM, Atack JR, Bloxham CA, Blessed G, Fairbairn A, Tomlinson BE, Perry RH. 1985. Cholinergic correlates of cognitive impairment in Parkinson’s disease: comparisons with Alzheimer’s disease. J Neurol Neurosurg Psychiatry 48, 413–421. 11. Sunderland T, Tariot PN, Newhouse PA. 1988. Differential responsivity of mood, behavior, and cognition to cholinergic agents in elderly neuropsychiatric populations. Brain Res 472, 371–389. 12. Ebert U, Kirch W. 1998. Scopolamine model of dementia: electroencephalogram findings and cognitive performance. Eur J Clin Invest 28, 944–949. 13. McDonald RJ, and White NM. 1995. Hippocampal and nonhippocampal contributions to place learning in rats. Behavi Neurosci; 109, 579–593. 14. Terry RD, Katzman R. Senile dementia of the Alzheimer type. Ann Neurol 14, 497-506, 1983. 15. Mann DM. 1991. The topographic distribution of brain atrophy in Alzheimer’s disease. Acta Neuropathol (Berl) 83, 81–86. 16. Scheibel AB. 1979. The hippocampus: organizational patterns in health and senescence. Mech Ageing Dev. 9, 89-102. 17. Eslinger PJ, Benton AL. 1983. Visuoperceptual performances in aging and dementia: clinical and theoretical implications. J Clin Neuropsychol 5, 213–220. 18. Huber SJ, Shuttleworth EC, Freidenberg DL. 1989. Neuropsychological differences between the dementias of Alzheimer’s and Parkinson’s diseases. Arch Neurol 46, 1287–1291. 19. Morris JC, McKeel DW Jr, Storandt M, Rubin EH, Price JL, Grant EA, Ball MJ, Berg L. 1991. Very mild Alzheimer’s disease: informant-based clinical, psychometric, and pathologic distinction from normal aging. Neurology 41, 469–478.


280


20. Henderson VW, Mack W, Williams BW. 1989. Spatial disorientation in Alzheimer’s disease. Arch Neurol 46, 391–394. 21. Mendez MF, Tomsak RL, Remler B. 1990. Disorders of the visual system in Alzheimer’s disease. J Clin Neuroophthalmol 10, 62–69. 22. Terry, A.V., Jr., M. Gattu, M., Buccafusco, J.J., J.W. Sowell, J.W., and Kosh, J.W. 1999. Ranitidine Analog, JWS-USC-75IX, Enhances Memory-Related Task Performance in Rats. Drug Dev Res, 47, 97–106. 23. Prendergast, M.A., Terry, A.V., Jr., and Buccafusco, J.J. 1997. Chronic, low-level exposure to diisopropylfluorophosphate causes protracted impairment of spatial navigation learning. Psychopharmacol, 129, 183–191. 24. Brandeis R, Brandys Y, Yehuda S. L. 1989. The use of the Morris Water Maze in the study of memory and learning. Int J Neurosci 48, 29–69. 25. Astur RS, Taylor LB, Mamelak AN, Philpott L, Sutherland RJ. 2002. Humans with hippocampus damage display severe spatial memory impairments in a virtual Morris water task. Behav Brain Res 132:77-84. 26. Vorhees CV, Williams MT. 2006. Morris water maze: procedures for assessing spatial and related forms of learning and memory. Nat Protoc 1: 848–58. 27. Lattal KM, Abel T. 2001. Different requirements for protein synthesis in acquisition and extinction of spatial preferences and context-evoked fear. J Neurosci 21(15):5773–5780. 28. Beversdorf DQ, Hughes JD, Steinberg BA, Lewis LD, Heilman KM. 1999. Noradrenergic modulation of cognitive flexibility in problem solving. Neuroreport 10(13):2763–2767. 29. Hernandez, C.M, and Terry, A.V., Jr. 2005. Repeated Nicotine Exposure in Rats: Effects on Memory Function, Cholinergic Markers and Nerve Growth Factor. Neuroscience 130:997–1012. 30. Terry, A.V., Jr. 2001. “Spatial Navigation (Water Maze) Tasks” in J. J. Buccafusco (Ed.) Behavioral Methods in Neuroscience. CRC Press: Boca Raton, Chapter 10, pages 153–166. 31. Terry, AV., Jr., Parikh V, Gearhart DA, Pillai, Hohnadel EJ, Warner, S, Nasrallah, HA, and Mahadik SP. 2006. A Time Dependent Effects of Haloperidol and Ziprasidone on Nerve Growth Factor, Cholinergic Neurons, and Spatial Learning in Rats. Journal of Pharmacology and Experimental Therapeutics 318:709–724.


Maze 14 Water Tasks in Mice Special Reference to Alzheimer’s Transgenic Mice Dave Morgan CONTENTS 14.1 14.2

Introduction................................................................................................. 281 Methods....................................................................................................... 283 14.2.1 Animal Subjects............................................................................... 283 14.2.2 Equipment ........................................................................................284 14.2.3 Working Memory Procedure ...........................................................284 14.2.4 Reference Memory Procedure ......................................................... 285 14.2.5 Visible Platform in an Open Pool .................................................... 286 14.3 Representative Data .................................................................................... 287 14.4 Analysis and Interpretation......................................................................... 287 Acknowledgments.................................................................................................. 289 References.............................................................................................................. 289

14.1

INTRODUCTION

Water maze tasks have been used for over a quarter century in testing rodent spatial navigation memory.1 Although initially developed for rats, they have also been useful in evaluating memory in mice, often using scaled down pool sizes. The major advantage of the water maze tasks over dry mazes is increased motivation to escape, and hence more rapid performance within the maze. Typical trials in water mazes are limited to 60 sec, while dry maze trials often last much longer. This permits higher throughput and increased efficiency when large numbers of animals require evaluation. The original Morris maze used an open pool with a hidden platform just below the water level midway between the pool wall and the center of the pool. The rodent is placed in the pool, typically facing the wall, in one of four arbitrarily defined quadrants, and permitted to explore the pool. Extramaze cues surround the pool to orient the rodent as it navigates within the pool. Initially animals stumble upon the platform, climb onto it and are forced to remain for a short period before being removed to consolidate the experience. They are then removed from the platform and placed into a different quadrant from the first trial and again given the opportunity 281


282


to explore the pool. Once again the platform is encountered and the animal escapes the pool by climbing onto the platform. Often a third and in some versions up to six trials are performed. The time spent prior to finding the platform is recorded as “latency to escape” and is averaged for each day’s performance. The procedure is repeated over 2–14 days with the platform remaining in the same location each day, making this a reference memory task. After 3–10 days of training, the rodents are administered a “probe” trial (actually an extinction trial) in which the platform is removed and memory for platform location assessed. A number of measurements have been proposed to infer the strength of the “memory” of the mouse for the platform location. The simplest is time spent in the “target” quadrant (i.e., the one that previously contained the platform). More elaborate measurements include the average swim distance from the previous platform location or the number of crossings over the exact location of the platform. Many of these measurements involve videotaping of the rodent’s performance and application of computerized software to analyze the performance. However, given that the mice must still be shuttled manually into the pool and off the platform (and rescued if drowning), there is no meaningful personnel efficiency achieved by the use of computerized analysis (the behaviorist must remain at the pool for each rodent). There are many variations on these procedures. Some have used intermediate probe trials after days 3, 6, and 9, for example, and used comparisons of these performances as an index of rate of learning.2 Others have converted the normal reference memory version of the water maze to a working memory model by measuring the number of trials to reach a latency criterion at one location and then measuring trials to criterion at a new platform location.3 In general, this open pool Morris water maze approach is useful in discriminating memory dysfunction in amyloid precursor protein (APP) transgenic mice.4–8 In our own work with the water maze task, we found in some cases that mice were impaired when measuring latency, but not on the probe trial.9 In the Barnes maze, these mice showed no significant deficits. However, when the same mice were tested on the radial arm water maze, the APP transgenic mice were significantly impaired. Although we originally included both the open pool Morris water maze and the radial arm water maze (and Barnes maze) as components of a 6-wk behavioral test battery,10 we have now abbreviated this to a 2-wk battery in which a shortened version of the radial arm water maze is the primary cognitive task.11 The radial arm water maze involves the imposition of a radial arm maze onto a pool. This approach was first developed for rats.12,13 This is implemented by insertion of triangular wedges into the pool that reach above the surface of the water, forming swim alleys surrounding a central open region (Figure 14.1). The platform is placed within one of the alleys (goal arm) and the mouse is started in one of the other swim arms. Although our initial work focused on a working memory version of this task,14,15 we have found a reference memory variant of the radial arm water maze that can consistently reveal deficits in transgenic mouse memory performance with as few as 2 days of training, increasing the flexibility of scheduling behavioral testing. This latter adaptation, developed in consultation with David Diamond, takes advantage of optimal spacing of trials to minimize the time needed for acquisition of the task. Moreover, the measurement of errors does not require use of video cam-


Water Maze Tasks in Mice

283

FIGURE 14.1 The radial arm water maze. Shown are the pool used for behavioral testing with metal inserts/dividers in place forming swim alleys and a central swim area. The platform shown is the visible platform that protrudes just slightly above the water and is striped for salience. Also note the visual cues outside the pool consisting of two shower curtains (visible), a plain wall (to the right outside of frame), and the remainder of the room (behind camera).

eras or computers to obtain reliable data regarding performance. Depending on the pool size, up to 16 arms can been used and the contingencies organized to separately detect reference versus working memory errors.16 The design flexibility of the dry radial arm maze can be combined with the motivational advantages of the water maze format.

14.2

METHODS

14.2.1 ANIMAL SUBJECTS Our work has focused exclusively on transgenic mouse models of amyloid deposition or tau pathology. Our APP mice have been derived from the Tg2576 line4 bred with a mutant PS1 line 5.117 as described by Holcomb et al.18 As a result these mice are of a mixed genetic background. It should be noted that many inbred mouse lines carry a retinal degeneration gene mutation19,20 that does not impair performance on many murine behavioral tests (including the visual cliff 21), but does cause severe deficits in spatial navigation tasks.22 The JAX laboratories Web site indicates whether a given strain is known to possess one of these rd mutations and provides primer pairs to detect the most prevalent rd1 mutation in individual mice when genotyping. It is essential that mouse lines either be investigated for presence of a background strain carrying an rd mutation, or that individual mice be tested for this mutation. Our Tg2576 line carried the rd mutation via inclusion of the SJL strain. However, genotyping and selective breeding have eliminated this mutation from the background of our APP animals. Mice should be generally healthy and free of open wounds that might become infected by exposure to water. Thus, we do not test mice within 7 days of a surgical procedure. For the APP-only mice, we can detect behavioral deficits in modest-sized


284


cohorts (6–8) around 12–15 mo of age. For many studies we prefer older mice (20– 24 mo) as this more closely resembles conditions of aged Alzheimer’s disease (AD) patients. We always include a cohort of untreated nontransgenic littermate mice in any drug/therapy trials to act as a positive control (if the nontransgenic mice fail to learn, there is a problem with the behavioral testing procedure).

14.2.2 EQUIPMENT Pool size is not an essential variable, but should be constrained for practical reasons (e.g., ability of the experimenter to reach all parts of the pool). For mice we have used a 1 m pool that is 30 cm deep. We constructed pie-shaped wedges out of a sheet of stainless steel (plastic or sheet aluminum may also be suitable) that was 24 cm wide and 60 cm long. These were then bent at the center of the long axis to form a 60° angle. They were placed into the pool to form a “V” 24 cm high with a vertex 30 cm from the edge of the pool. By equally spacing six of these inserts into the pool, we form six swim alleys of 30 cm in length with a 40-cm wide central region (Figure 14.1). The pool is then filled with water to a depth of 14 cm (10 cm from the top of the inserts) at a temperature of 20.5°C. A platform should be placed in one swim alley just below the water line. We use inverted terra cotta pots (10 cm diameter) that are painted the same color as the inside of the pool and positioned 1 cm beneath the surface of the water. A pool liner may be used instead of paint to achieve a uniform color that can be replaced instead of cleaned and repainted (black works very nicely). We do not find it necessary to add paint or milk to the water to increase opacity.

14.2.3 WORKING MEMORY PROCEDURE Prior to cognitive testing mice are administered a small neurological test battery consisting of wire hang and balance beam (day 1), Y-maze testing (day 2), and 3 days of accelerating rotorod testing. Mice failing to perform adequately in these tasks are removed from the cognitive testing group. All of these tasks are administered by the same individual who will perform the cognitive testing. Mice appear somewhat more sensitive to changes in experimenter than rats are, suggesting this induces a stress response that interferes with normal cognitive abilities. We have found that simply transporting mice up and down an elevator impairs performance on these cognitive function tasks. The general radial arm water maze procedure involves placing the mouse into one arm of the maze other than the goal arm, and releasing the mouse to begin swimming. Most mice swim readily and explore the maze. When a mouse enters a swim arm other than the goal arm, the mouse is charged with one error (a mouse is considered to enter the arm when all four limbs move into the swim alley). Occasionally, mice stop swimming and float, or they swim in the central regions without making an arm entry. For each 15-sec period a mouse fails to enter an arm for whatever reason it is charged one error. In this manner, a mouse failing to swim accumulates four errors, which is a score typical of mice that have not learned the platform location. Mice that consistently fail to swim are removed from the study. The trial continues for 60 sec or until the mouse ascends the platform. If a mouse does not locate the platform within 60 sec, it is guided to the platform. The mouse is removed after



285

15 sec on the platform and either started in another trial, or dried with a towel and placed in its home cage (with a heat lamp available in one corner). Both error number and latency to find the platform are recorded. In order to test working memory, the goal arm location within the maze was changed each day. Within each day, a mouse was given four consecutive 60-sec acquisition trials, followed 30 min later by a fifth (retention) trial. The next day, the platform was moved to a new location, and the mouse had to learn the new platform location. The rationale for the 30-min delay on the retention trial was that short-term forgetting is common in AD patients. It was hoped that the mice would learn the new platform location during the first four trials when the inter-trial interval was 15 sec (registration of the material to be learned), and then demonstrate poor performance at the 30 min time point (the recall point in testing for memory deficits clinically). Thus far we have not found mice that learned location by trial 4 but failed to remember on trial 5, as we had hoped might occur. Instead we find that APP transgenic mice fail to improve over the acquisition trials, and, as expected, perform poorly on the retention trial as well. One of the limitations to this procedure was that mice were slow to acquire the procedural aspects of the testing (understanding there was a platform and that the platform moved each day). This may be a result of the ethologically unlikely possibility that escape location in a natural environment would change daily. As a general criterion, we felt that when the mice as a group reached a criterion of one or fewer errors on trials 4 and 5, they had learned the task. On some occasions, nontransgenic cohorts would reach this criterion within 10 days of continuous testing. Other cohorts could require 15 days to reach this learning criterion. Thus, in order to maintain consistent performance, the same investigator must be available for a period of up to 2 wk for 3–4 hr at the same time of day. Although it is conceivable that training could be suspended for the weekend, we never fully investigated this variable. Instead, to simplify the testing procedure we opted to examine the reference memory version of the maze described below.

14.2.4 REFERENCE MEMORY PROCEDURE For reference memory testing we began by running mice for 15 trials on each of 2 days. The goal arm was constant for these 2 days, and the mouse waas placed pseudorandomly (no repeats) in a different start arm for each trial. Moreover, the trials on day 1 alternated between using a visible platform above the water and a hidden platform in the same arm. On day 2, all trials used the hidden platform. Moreover, the goal arm for each mouse was different (to minimize possible effects of odor trails). This was predetermined on a score sheet that the experimenter used to determine the start arm and goal arm for each trial for each mouse (examples of these score sheets are available from the author). One problem with 15 trials per day is that older mice can get fatigued from swimming for this long a period without rest. Thus we designed a testing schedule whereby the mice had a rest period after each trial. Mice were assigned to groups of four (treatment conditions should be equally distributed in these testing groups). Typically two groups of four mice were tested in parallel. First, mouse 1 of group 1 was


286


administered trial 1, then mouse 2 of group 1, mouse 3, and mouse 4. After mouse 4 of group 1 was tested on trial 1, mouse 1 of group 1 was administered trial 2. Mice 2–4 of that group then followed. After each trial, mice were returned to their home cages with a heat lamp available in the corner (one lamp served all four cages). After all mice in group 1 received six trials, a second group of four mice were administered their first six trials in the same fashion as group 1. First, mouse 1, trial 1, then mouse 2, trial 1, etc. After all four mice were administered six trials, the first group of four mice was administered trials 7–12. Then group 2 was administered trials 7–12. Finally, group 1 was administered trials 13–15, and then group 2 was administered trials 13–15. The entire process can be accomplished in 3–4 hr. This permits a second series of eight mice to be tested on the same day. On day 2 the entire process was repeated, except the platform was hidden for all trials. We have never fully investigated whether the alternation of visible and hidden platforms on day 1 is essential for good learning to occur, thus this may be considered optional. For most cohorts of mice, this resulted in average scores of one error or less for the “positive” control groups (usually nontransgenic mice). On some occasions the control mice may not have reached this criterion (for example old mice or occasionally some inbred lines). In these circumstances we ran a reversal trial on day 3 (a new goal arm location for each mouse not adjacent to the initial goal arm; all trials used the hidden platform). This also sometimes revealed deficits in performing the reversal task in treatment groups that were not easily distinguished in the first 2 days of testing. If performance is still poor after the first day of reversal testing, a second day of reversal testing can be performed. The 2-day reference memory version of the radial arm water maze is the most efficient method we have found for testing in this procedure. Most cohorts of control mice learn the task within 30 trials. For the working memory version, 50–75 trials are necessary for the mice to demonstrate solid learning of platform location. Similar numbers apply to the Morris open pool version of the water maze. We feel that this procedure optimally spaces trials so that mice have some immediate recollection of the events and a rest period so that fatigue is not a factor, and that longer rest periods during testing permit some consolidation to occur within the day, rather than between days.

14.2.5 VISIBLE PLATFORM IN AN OPEN POOL Irrespective of whether reversal training is performed, the last day of testing used a visible platform in an open pool (inserts removed). The visible platform has ensigns located above the water while the platform remains slightly below the water. The mouse was started in the same location for each trial, and the location of the visible platform was moved for each mouse. Latency to reach the platform was recorded. Mice were shuttled just as on day 1 of radial arm maze testing (mouse 1, trial 1; mouse 2, trial 1; etc.). Fifteen trials were performed. The purpose of the visible platform task is to assess if mice have the performance skills necessary for the water maze tasks. Mice failing to reach a criterion of 20 sec latency for the last three trials of the visible platform task were considered to be impaired. These mice may have been blind or



287

FIGURE 14.2 Typical data for the working memory version of the radial arm water maze. Fifteen-mo-old nontransgenic or APP+PS1 transgenic mice were given five trials daily as described in the text. Four trials were continuous (solid line) and the fifth trial was administered after a 30-min delay (dashed line). Data are presented as the number of errors for each trial averaged over 3-day blocks. The learning criterion of one error is shown as the dashed horizontal line across the graph. *P < 0.01.

impaired motorically and thus not capable of being evaluated for cognitive function. Very few mice completing the testing protocol fail to meet this criterion.

14.3

REPRESENTATIVE DATA

Figure 14.2 shows results from the working memory version of the radial arm water maze. Shown are three blocks of results summed over 3 days each. The first block represents data from days 1–3, the second block from days 4–6, and the third block from days 7–9. On the first trial of each block, mice are performing at chance levels as the platform is in a new location. In all cases, the transgenic mice show only modest (and not significant) improvement in their performance over the five trials (the last trial being a retention trial). However, by the last block of trials (days 7–9) we found that the nontransgenic mice reached the criterion of less than one error (on the retention trial 5). At this point there was also a significant difference between the transgenic and nontransgenic mice. Figure 14.3 shows the results from the 2-day reference memory version of the water maze. Note that on day 1 both groups improve slightly in their performance. However, by day 2 the nontransgenic mice are able to find the platform with few errors. The performance of the nontransgenic mice is significantly better than the transgenic mice on blocks 6–10 of the radial arm water maze task.

14.4

ANALYSIS AND INTERPRETATION

One of the issues regarding the radial arm maze results is that individual mouse data is noisy. Some mice simply by fortune find the platform on their first arm entry of the


288

Methods of Behavior Analysis in Neuroscience, Second Edition Non Tg 25 mo

App 25 mo 8 7

Errors

6 5 4 3 2 1 0 1

2

3 Day 1

4

5

6

7

8 Day 2

9

10

Blcok Number

FIGURE 14.3 Typical data for the 2-day reference version of the radial arm water maze. Data shown are for 25-mo-old nontransgenic (NonTg) and untreated APP Tg 2576 derived mice (APP). Data presented are averages of three trial blocks. The horizontal dashed line represents the one error per trial learning criterion. On day 2, nontransgenic mice perform significantly better than transgenic mice for all trial blocks (P < 0.01). Source: Data are redrawn from Wilcock, D. M., Rojiani, A., Rosenthal, A., et al. 2004. Passive immunotherapy against Abeta in aged APP-transgenic mice reverses cognitive deficits and depletes parenchymal amyloid deposits in spite of increased vascular amyloid and microhemorrhage. J. Neuroinflammation 1:24, with permission.

first day. As a result, the data are portrayed most favorably with some degree of summation over trials and/or days. If large sample sizes are used (> 25 mice), it would seem plausible to include data for every trial when presenting the data. However, in most studies using transgenic or aged mice, numbers are a limiting resource. While we aim for a sample size of 10 in most experimental designs, we sometimes are limited to final sample sizes as low as five after attrition because of death, or culling because of motoric deficiencies (rare) or skin lesions (more common in older mice). There are many ways of accomplishing this averaging for presentation purposes. In Figure 14.2, we collapse over 3-day blocks in the working memory version of the maze, as each trial reflects a different stage of learning. In most of our published studies with this method,9,10,14,15,21,23,24 we averaged the final 2–3 days of testing after the nontransgenic mice had reached the learning criterion. We typically discarded the first 5–10 days of training from data analysis as this was the time when the mice were still acquiring procedural aspects of the task. However, this is not the only method to demonstrate clear differences in transgenic mice. The group led by Ottavio Arancio averages all days for each of the five trials, and still observes clear differences caused by the presence of amyloid.25,26 Thus, there can be several alternative means of presenting these results. Although we collect the latency data, we feel latencies are affected by variables other than mnemonic functions (swim speed) and reporting significant effects in latency when there were no differences in errors seems deceptive to us.



289

For the 2-day water maze, we average over blocks of three trials for each mouse. These three trial blocks become 10 data points used for statistical analysis. For all studies (working and reference), we first perform a repeated measures analysis of variance (ANOVA) to seek a main effect of genotype and trials. We then perform post-hoc means comparisons using Fischer’s LSD test with the statistical program Statview (SAS) to identify group differences on specific trials or blocks. A final comment on statistical analysis regards experiments testing for drug or other therapeutic effects in mouse models of neurodegeneration. We emphasize in these studies that the inclusion of the positive control group (in our case, nontransgenic mice) is simply to validate the success of the behavioral testing process. However, we do not include these mice in the statistical analysis to determine the effect of the therapeutic modality. These analyses should directly compare the treated and untreated disease model mice, without reference to the nontransgenic data. Only if the treated and untreated transgenic groups differ is there truly an effect of the treatment. We have witnessed and reviewed manuscripts that show a significant difference between untreated disease model mice (transgenic) and positive control (nontransgenic) mice, but fail to reach significance in comparing treated transgenic mice and nontransgenic mice. The authors sometimes attempt to conclude (erroneously) that there was then an effect of their treatment. This violates a cardinal rule of statistics that failure to detect a difference does not mean there is no difference, only that the study was unable to detect it. Statistically significant differences in performance between treated and untreated disease model groups are essential to argue for benefits of the therapy.

ACKNOWLEDGMENTS We thank David Diamond and Gary Arendash for years of assistance in developing these methods and collecting data relevant to this technique. We thank Jennifer Alamed, our laboratory behaviorist, for collecting data and aiding in the figures for the manuscript. DGM is supported by the following awards from the National Institutes of Health: AG04418, AG15490, AG18478, AG 25509, AG25711, and NS48355, and is a supervisor for AG031291.

REFERENCES 1. Morris, R. G., Garrud, P., Rawlins, J. N., and O’Keefe, J. 1982. Place navigation impaired in rats with hippocampal lesions. Nature 297:681–83. 2. Westerman, M. A., Cooper-Blacketer, D., Mariash, et al. 2002. The relationship between Abeta and memory in the Tg2576 mouse model of Alzheimer’s disease. J. Neurosci. 22:1858–67. 3. Chen, G., Chen, K. S., Knox, J., et al. 2000. A learning deficit related to age and betaamyloid plaques in a mouse model of Alzheimer’s disease. Nature 408:975–79. 4. Hsiao, K., Chapman, P., Nilsen, S., et al. 1996. Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science 274:99–102. 5. Puolivali, J., Wang, J., Heikkinen, T., et al. 2002. Hippocampal A beta 42 levels correlate with spatial memory deficit in APP and PS1 double transgenic mice. Neurobiol. Dis. 9:339–47.


290


6. Palop, J. J., Jones, B., Kekonius, L., et al. 2003. Neuronal depletion of calcium-dependent proteins in the dentate gyrus is tightly linked to Alzheimer’s disease-related cognitive deficits. Proc. Nat. Acad. Sci. USA 100:9572–77. 7. Kelly, P. H., Bondolfi, L., Hunziker, D., et al. 2003. Progressive age-related impairment of cognitive behavior in APP23 transgenic mice. Neurobiol. Aging 24:365–78. 8. Jankowsky, J. L., Melnikova, T., Fadale, D. J., et al. 2005. Environmental enrichment mitigates cognitive deficits in a mouse model of Alzheimer’s disease. J. Neurosci. 25:5217–24. 9. Arendash, G. W., King, D. L., Gordon, M. N., et al. 2001. Progressive behavioral impariments in transgenic mice carrying both mutant APP and PS1 transgenes. Brain Res. 891:45–53. 10. Austin, L., Arendash, G. W., Gordon, M. N., et al. 2003. Short-term beta-amyloid vaccinations do not improve cognitive performance in cognitively impaired APP + PS1 mice. Behav. Neurosci. 117:478–84. 11. Wilcock, D. M., Rojiani, A., Rosenthal, A., et al. 2004. Passive immunotherapy against Abeta in aged APP-transgenic mice reverses cognitive deficits and depletes parenchymal amyloid deposits in spite of increased vascular amyloid and microhemorrhage. J. Neuroinflammation 1:24. 12. Diamond, D. M., Park, C. R., Heman, K. L., and Rose, G. M. 1999. Exposing rats to a predator impairs spatial working memory in the radial arm water maze. Hippocampus 9:542–51. 13. Bimonte, H. A., and Denenberg, V. H. 1999. Estradiol facilitates performance as working memory load increases. Psychoneuroendocrinology 24:161–73. 14. Morgan, D., Diamond, D. M., Gottschall, P. E., et al. 2000. A beta peptide vaccination prevents memory loss in an animal model of Alzheimer’s disease. Nature 408:982–85. 15. Gordon, M. N., King, D. L., Diamond, D. M., et al. 2001. Correlation between cognitive deficits and Aß deposits in transgenic APP+PS1 mice. Neurobiology of Aging 22:377–85. 16. Bimonte, H. A., Hyde, L. A., Hoplight, B. J., and Denenberg, V. H. 2000. In two species, females exhibit superior working memory and inferior reference memory on the water radial-arm maze. Physiol. Behav. 70:311–17. 17. Duff, K., Eckman, C., Zehr, C., et al. 1996. Increased amyloid-beta42(43) in brains of mice expressing mutant presenilin 1. Nature 383:710–13. 18. Holcomb, L., Gordon, M. N., McGowan, E., et al. 1998. Accelerated Alzheimer-type phenotype in transgenic mice carrying both mutant amyloid precursor protein and presenilin 1 transgenes. Nat. Med. 4:97–100. 19. Chang, B., Hawes, N. L., Hurd, R. E., Davisson, M. T., Nusinowitz, S., and Heckenlively, J. R. 2002. Retinal degeneration mutants in the mouse. Vision Res. 42:517–25. 20. Clapcote, S. J., Lazar, N. L., Bechard, A. R., Wood, G. A., and Roder, J. C. 2005. NIH Swiss and Black Swiss mice have retinal degeneration and performance deficits in cognitive tests. Comp. Med. 55:310–16. 21. Garcia, M. F., Gordon, M. N., Hutton, M., et al. 2004. The retinal degeneration (rd) gene seriously impairs spatial cognitive performance in normal and Alzheimer’s transgenic mice. NeuroReport 15:73–77. 22. Alamed, J., Wilcock, D. M., Diamond, D. M., Gordon, M. N., and Morgan, D. 2006. Two-day radial-arm water maze learning and memory task: Robust resolution of amyloid-related memory deficits in transgenic mice. Nat. Protoc. 1:1671–79. 23. Morgan, D. 2003. Learning and memory deficits in APP transgenic mouse models of amyloid deposition. Neurochem. Res. 28:1029–34.



291

24. Joseph, J. A., Denisova, N. A., Arendash, G., et al. 2003. Blueberry supplementation enhances signaling and prevents behavioral deficits in an Alzheimer disease model. Nutr. Neurosci. 6:153–62. 25. Gong, B., Vitolo, O. V., Trinchese, F., Liu, S., Shelanski, M., and Arancio, O. 2004. Persistent improvement in synaptic and cognitive functions in an Alzheimer mouse model after rolipram treatment. J. Clin. Invest. 114:1624–34. 26. Trinchese, F., Liu, S., Battaglia, F., Walter, S., Mathews, P. M., and Arancio, O. 2004. Progressive age-related development of Alzheimer-like pathology in APP/PS1 mice. Ann. Neurol. 55:801–14.


Neuroscience 15 Behavioral of Zebrafish Edward D. Levin and Daniel T. Cerutti CONTENTS 15.1 15.2 15.3

Introduction................................................................................................. 293 Use of Fish Models in Behavioral Neuroscience ........................................ 294 Procedures and Processes ........................................................................... 295 15.3.1 Assessment of Swimming Activity in Newly Hatched Zebrafish ... 297 15.3.2 Reflexes and Habituation ................................................................. 297 15.3.3 Pavlovian Conditioning....................................................................300 15.3.4 Operant Conditioning and Mazes....................................................300 15.3.5 Testing Anxiety and Stress Response.............................................. 303 15.4 Conclusions .................................................................................................306 Acknowledgement..................................................................................................306 References..............................................................................................................306

15.1

INTRODUCTION

Models are used to represent complex problems in simplified forms—physics, chemistry, and biology all make good use of models. The most familiar are the mathematical sorts that form the basis of natural science theory. In the life sciences, the concept of modeling can extend further to include experimental procedures and nonhuman subjects. For example, a neuroscientist might employ a rat running in a radial-arm maze to study working memory processes, or a mouse in an open-field test to study anxiety. The value of a model is primarily a function of its fidelity: in the case of a theoretical model, fidelity is measured in terms of predicted findings; in the case of biological models, the issue is couched in terms of validity. It is this second kind of model that concerns us in this chapter on neuroscience methods, where the challenge of model species is particularly acute because behavioral and brain processes are both extraordinarily complex, and the problem is to find species that display both interesting behavior and easily accessible neural processes. Rats and mice, unquestionably the most successful models in neuroscience, have been extremely effective in helping determine which mammalian brain regions and neurotransmitter systems involved in cognition, learning, and other varieties of behavioral function. But the invertebrate Aplysia, a marine mollusk, has also served as a molecular model of memory processes.1 Such seemingly unrelated model species are useful to the extent that they balance external validity, simplicity, and cost. Most recently these considerations have led researchers in behavioral neuroscience 293


294


to use fish, a sort of middle ground between rodents and mollusks. In this chapter we review progress in the behavioral neuroscience of the diminutive zebrafish (Danio rerio), a species that has already firmly established itself as a model of vertebrate development, and now opens new doors for the investigation of brain mechanisms. Zebrafish are sometimes identified as an alternative model (relative to classic rodent models), but the term complementary model might be more appropriate since it addresses the use of fish in addition to classic mammalian models. Some questions, such as about the role of frontal cortical and hippocampal structures in learning and memory, cannot be studied with fish since these are not evident (but see2). But other attributes of fish make them valuable models in behavioral neuroscience research. Developmental processes can be continuously visualized in species that have a clear chorion (egg sack). Reporter systems can highlight specific neural systems so that their proliferation, differentiation, migration, and projections can be easily discerned. Reversible genetic suppression through the morpholino technique can determine the importance of specific molecular mechanisms for neurodevelopment. Numerous mutants available also help with the evaluation of molecular mechanisms throughout life. Finally, fish are easily bred in great numbers and develop rapidly, reducing the cost of experimentation and significantly increasing research throughput—potentially, more experiments can be run in less time to answer any number of questions. The merit of fish models is now a matter of record. Zebrafish, in particular, have been well used in genetics, neuroscience, pharmacology, and toxicology (e.g., see3–7). The next and ongoing step is to extend the zebrafish model to pursue questions of behavioral neuroscience, an undertaking that requires valid, reliable, and efficient methods of behavioral assessment.

15.2

USE OF FISH MODELS IN BEHAVIORAL NEUROSCIENCE

Fish are the obvious ancestral form of existing tetrapods, so it is not terribly surprising to find that they show most of the behavior seen in terrestrial species in some form or other. In social behavior alone, there are species known to show monogamous mating for life (e.g., angelfish8), individual recognition of conspecifics by sight or odor,9 socially mediated learning,10 intricate mate-selection strategies,11 ritualized displays of aggression,12 and communication of danger.13,14 With respect to cognition and adaptive behavior, fish show highly developed spatial navigation abilities,15 nonassociative learning such as habituation,16,17 precise timing abilities,18–20 Pavlovian conditioning (e.g., see21), operant behavior motivated by aversive stimuli such as shuttle box behavior,22 negatively reinforced avoidance,23 and food-reinforced lever pressing positively reinforced responding.24 In terms of sensory processes, fish have excellent color vision;25 some species generate and detect weak electrical currents, a sense that they use to detect predators and prey;26 and have lateral-line organs that allow them to resolve the location, size, and features of distal objects by sensing their pressure shadows. Behavioral research with fish began with ethologists and comparative psychologists asking questions about the evolution of learning, cognition,27–29 and brain function.30–33 As in other species, the understanding of the teleost brain has been driven


Behavioral Neuroscience of Zebrafish

295

in large part by the development of appropriate behavioral assays (e.g., see31). The extent to which basic behavioral and brain processes in mammals and fish are analogous remains an open question—there are clear similarities and differences—and, as with all animal models, the validity of a fish model hinges on the particular question being asked. Many species of fish have been used in models of cognitive impairment, for example, the Japanese medaka (Oryzias latipes) is being used in toxicological studies on effects of the insecticide diazinon (e.g., see34), and walleye (Stizostedion vitreum) have been used to demonstrate the adverse impacts of insecticides on cholinergic systems.35 Goldfish (Carassius auratus) have historically been used to study learning and memory processes.26,36,37 Fish have not been widely used in pharmacology but there is no reason to believe that they would not be suitable (e.g., see3). Zebrafish have rapidly become a prominent model for studying the molecular basis of vertebrate neurodevelopment.4,38,39 The scientific potential of the zebrafish was discovered by George Streisinger.40 The clear chorion of the zebrafish allows continuous visualization of neuroanatomy; their rapid development and accessibility to genetic analysis make the zebrafish an excellent model system for molecular and mechanistic studies of neurodevelopment. Since its introduction, many genetic mutants have become available, including varieties that can help determine the molecular mechanisms of neurobehavioral function. More recently, the availability of morpholino techniques, whereby specific parts of the genome can be reversibly suppressed during early development, provides a unique way to explore the molecular biology of development. Zebrafish have been critical in the identification of a variety of genes affecting various aspects of neural development and function (e.g., see partial list in41). As a result, the genetics and physiology of learning and memory are now being more widely studied in zebrafish (e.g., see42). Many tasks are now able to tap behavioral processes previously only studied with rodents and goldfish.3,25,43–48

15.3

PROCEDURES AND PROCESSES

It might seem a simple matter to develop a valid battery of behavioral tests to study learning and cognition in fish, but it has not been so. One problem is translating between terrestrial and aquatic habitats; another problem is finding reliable and valid dependent measures; nor are theorists always in agreement about how to classify behavioral processes.49 A somewhat simpler question involves distinguishing between procedures: those that involve stimulus presentations (e.g., to study reflexes and fixed-action patterns), and those that involve arranging consequences for behavior (e.g., to study instrumental or operant behavior). All other behavioral preparations derive from these—Pavlovian conditioning involves signaling a stimulus presentation (e.g., a tone that signals a shock), and operant discrimination involves signaling a consequence (e.g., a color that signals which arm of a maze contains food). Further subtle variants of these basic procedures can answer any number of questions about processes;50 for example, a rat’s visual contrast sensitivity can be tested with great accuracy by arranging an operant discrimination between sin-wave gratings and gray patches.51 Four cases of apparatuses adapted to study behavioral processes in zebrafish are illustrated in Figure 15.1. At the top left (1) is an aquatic version of the T-maze, an operant task used to study problems in discrimination


296

Methods of Behavior Analysis in Neuroscience, Second Edition 1. T-Maze

a.

2. Escape b.

Start Favorable Habitat

Rotation 4. Place Preference

3. Bite Test

d. c.

g. e.

f.

FIGURE 15.1 Four apparatuses that have been used to study learning and memory in the zebrafish. (1) T-maze. The T-maze can be used to study a variety of questions in learning and cognition including discrimination,25 and spatial and nonspatial navigation (e.g., with goldfish52). The version shown here was employed by Darland and Dowling3 with zebrafish in an experiment in which the primary datum was latency to reach the favorable habitat. (2) Visual escape. Li and Dowling3,53 used elicited escape from a moving stimulus (a) to study visual function in zebrafish. In this apparatus, rotation of the dark band (a) surrounding the swim area elicits defensive hiding behavior behind a central pole (b). (3) Exploratory biting. In this procedure, a zebrafish is trained to enter the raised platform through the door (c) to explore a small, submerged stimulus (d) such as a colored bead. Miklosi and Andrew17 employed this apparatus to study lateralization in the zebrafish and found habituation of biting and exploratory behavior elicited by a bead. (4) Place preference. The place-preference procedure is used to assess affinity for conditioned stimuli. In a typical procedure, a test space is divided into two distinctive halves (e and f) with a partition between them (g); the subject is exposed to an unconditioned stimulus in one half, and then later with the partition opened, is tested for side preference. For example, Darland and Dowling3 found that zebrafish show a preference for a conditioned stimulus previously paired with cocaine.

including attention, memory, and reinforcement. In the case of fish, the T-maze has been used to study color discrimination in zebrafish,25 problems in navigation (e.g., in goldfish52), and effects of genetic manipulations on habitat selection as in the maze shown here in which the dependent measure was latency to reach the favorable habitat.3 The top-right illustration (2) depicts a rotating drum apparatus that has been used to study reflexive escape (a variant of the opto-kinetic reflex test). In this test, a typical fish will flee the rotating band (a) by hiding behind the central pole (b), a visually guided escape taxis.3,53 The lower-left illustration (3) depicts a setup used to study novelty-elicited exploratory behavior. A fish placed in the tank will visit the raised platform through the door (c) to explore a small, submerged stimulus (d) such as a colored bead;17 exploration shows habituation to familiar stimuli and dishabituation with the introduction of new stimuli. The lower-right illustration (4)



297

depicts an aquatic version of the place-preference procedure used to measure conditioned appetitive stimuli. In this test, a subject is first exposed to an unconditioned stimulus, e.g., cocaine,3 in one of two distinctive halves (e and f) of the tank, and then later with the partition opened, it is given a preference test. In the sections that follow we present these tests and others in greater detail, emphasizing behavioral processes as much as procedures.

15.3.1 ASSESSMENT OF SWIMMING ACTIVITY IN NEWLY HATCHED ZEBRAFISH It is important to determine the motor behavior function in young zebrafish for studies of development as well as for higher throughput tests of the adverse effects of early toxicant exposure. Figure 15.2 (top inset) shows how a dissecting microscope can be used to image the movement of newly hatched zebrafish. Either through manual scoring of videotapes using a grid system or a computerized digital video tracking system, the swimming activity of newly hatched zebrafish can be reliably indexed. The lower graphs in Figure 15.2 shows the significant reduction in swimming activity with 100 ng/mL of chlorpyrifos from fertilization through hatching on day 5 when the behavioral test was conducted on day 6 or day 9.54

15.3.2 REFLEXES AND HABITUATION Much research on the physiological mechanisms of zebrafish behavior has focused on sensory-motor development (e.g., vision, swimming, and touch-elicited reflexes) in larvae or young fish (review in55,56). The simplest investigations are those of the tap-elicited startle reflex, the so called “C-start” response, which has been found to show an increased latency with early alcohol exposure.57,58 The development of touch-elicited escape behavior has been detailed by Granato et al.55: “Although the embryo is resting most of the time, touching the tail tip induces a fast and straight movement away from the stimulus source. In contrast, mechanical stimuli near the head of the embryo induce a fast escape response, where the embryo turns 180° along its horizontal body axis. At 96 hours the larva is freely swimming, changes swimming directions spontaneously, and is able to direct its swimming towards targets” (p. 399). We have recently examined habituation of tap-elicited swimming in unrestrained zebrafish to evaluate the effects of toxicants and drugs on a nonassociative learning process. Figure 15.3 (upper inset) illustrates a fully automated procedure using commercially available video tracking software (Ethovision, Noldus, Inc., Wageningen, The Netherlands). Fish were studied individually in a test battery consisting of eight 50-mm diameter tanks. The test arranged a “step up” transition in stimulus rates, with 20 taps presented with an inter-stimulus interval of 10 sec, followed immediately by 20 additional taps with an inter-stimulus interval of 20 sec. The graph depicts the effect of scopolamine (fish were immersed for 5 min in 200 mg/L of scopolamine prior to testing) on swim distance in the 5 sec after each tap (previously unpublished data). Both control and scopolamine-treated fish showed habituation of tap-elicited swimming, but only the control fish showed a reliable recovery in the taps immediately following the “step up” transition, a finding in the scopolamine


298

Methods of Behavior Analysis in Neuroscience, Second Edition %!")% +), )*""-.*

+"(&),".*

,)'"-+% %"0 &))+ #+%!

)*%"0 "+4,$'+2)(% $&)+*2+%*$),1*),.+" 3" -,)(- $&%(#0%''%(# -%/%-2 2

2

"#'"(-+),,%(#,

*

*

(#'

(#'

FIGURE 15.2 Swim test to evaluate motor function in newly hatched zebrafish. The left side of the upper inset (A) shows a video microscope setup with five arenas; the right side (B) shows a close-up of the cylindrical arena and grid pattern used to measure distance traveled (segment crossings). The graphs show results of a study on chlorpyrifos effects on swimming on newly hatched fish, control versus 100 ng/mL on day 6 (p < 0.01) and on day 9 (p < 0.05) after fertilization.54

treated fish that is consistent with a selective disruption in short-term memory (for a theoretical treatment of short- and long-term memory in habituation, see59). Zebrafish show a highly developed visually guided escape reflex, which may be related to the opto-kinetic response in other species,53 escaping a stimulus behind a place of concealment. This concealment reflex may be analogous to the targeted



%!( +"'(

299

&#(!

$ "& /$&-$#(! +" &#

&&,

)'$!#$ %#'"

%'$!#$'

$%$!"#0('$#$&(&""$&,

*&+"'(# '

..'

.. '

$#(&$!..' "$% ..' $#(&$!.. ' "$% .. '

&!' %!$ '

FIGURE 15.3 Tap-elicited swim test used to study habituation in the zebrafish. The left side of the upper inset (A) shows a horizontal array of eight arenas below a digital camera; the right side shows the push-solenoid used to deliver sharp taps under the cylindrical arenas. The dependent measure is swim distance in the 5 sec following taps, as measured by a video tracking system. The graph compares habituation in 16 control fish and 16 fish following a 10min immersion in 200 mg/L of scopolamine on habituation. In this procedure, the fish were exposed to 20 taps with an inter-stimulus interval (ISI) of 10 sec, immediately followed by 20 more taps with an ISI of 20 sec. The control fish, but not the scopolamine fish, show a brief recovery at the transition (t-test, one tail, p < .025), suggesting that scopolamine selectively disrupted short-term memory.

response concealment behavior described in mice by Blanchard,60 where if mice are familiarized with a container containing a place of concealment, they flee directly to that place when threatened. Figure 15.1(2) shows an apparatus developed to study this visually guided escape reflex in zebrafish.3,53 Fish are tested by rotating the outer cylinder of the apparatus, which contains a vertical black band (a), and observing the subject’s orientation with respect to the band and a central cylinder (b) behind which


300


it can hide. The test can be adapted to test visual function61,62 and has been used to measure visual contrast sensitivity of zebrafish.63 Exploratory behavior in novel environments has been used to assay anxiety in rodent models (e.g., see64–66) and analogous procedures have entered the zebrafish literature. Several experiments show that the fish first explores a stimulus predominantly using the right eye and subsequently approaches the stimulus favoring the left eye.67 Figure 15.1(3) shows an apparatus employed by Miklosi and Andrew17 to study lateralization of visual exploration in the zebrafish. Subjects are first trained to visit a box suspended in their home tanks by entering a door (c) to eat. After they reliably enter the box, a colored bead (d) is lowered into the water with the behavior of the fish recorded on video. Right eye use and biting were highly probable the first time a stimulus was presented and declined in probability in two subsequent trials, demonstrating habituation (see also16,68–70).

15.3.3 PAVLOVIAN CONDITIONING Zebrafish have shown Pavlovian learning in several experiments. Figure 15.1(4) illustrates a “place-preference” task used by Darland and Dowling3 to screen zebrafish for cocaine sensitivity (see also71). The apparatus consists of a tank divided into two distinctive chambers by a screen. During training, the screen is sealed and a zebrafish is exposed to cocaine in one of the chambers. In subsequent preference tests, the fish showed an appetitive conditioning effect by approaching and staying in the chamber in which they had previously received cocaine. Several studies with zebrafish have used shuttle-box procedures in which they learn to avoid an aversive conditioned stimulus by swimming to alternate sides of an elongated tank.44,45,72 Among the earliest demonstrations of associative learning in zebrafish used a shock deletion procedure to reinforce swimming away from a shock signal.73 More recently, Pradel et al.74 used a shuttle box and shock avoidance to study the role of cell adhesion molecules in memory consolidation. Technically speaking, swimming in these procedures resembles an operant response—the Pavlovian process involves the pairing of the conditioned stimulus with shock. However, without additional investigation it is difficult to say whether the “avoidance” swimming is elicited or operant in nature. This ambiguity also appears in appetitive procedures such as in the food-reinforced T-maze discrimination tasks (e.g., see25). Suboski and colleagues13,14 demonstrated Pavlovian conditioning of fear by pairing morpholine and alarm substance (a chemical secreted by frightened or injured fish) and subsequently showing conditioned fear to morpholine alone.14 The Pavlovian nature of their learning was later confirmed by showing that the conditioned alarm response could also be transferred between stimuli by sensory- and secondorder conditioning. The last finding in particular highlights the subtlety of learning possible in this unassuming, diminutive fish.

15.3.4 OPERANT CONDITIONING AND MAZES Although it might be assumed that this predominance of aversive procedures is because aversive procedures are more rapid than appetitive procedures, there are exceptions such as that shown by Williams et al.46 who trained fish to alternate



301

between two feeding sites in an average of 14 trials. The task is essentially an appetitive version of the shuttle box discussed above, except that trials are initiated by the experimenter tapping on the center of the tank and 5 sec later dropping a small amount of food in one end of the tank (the location of food is alternated between trials); the dependent measure is the position of the fish immediately before the delivery of food. Carvan et al.57 used this task to show dose-dependent detrimental effects of ethanol on learning and memory in zebrafish. Perhaps the earliest example of behavioral research with zebrafish is a maze learning study in which negotiation of a left-right-left-right maze and approach to black or white stimuli was trained by eliciting an anode galvanotaxic reflex that elicited approach to the target stimulus, a procedure that is somewhat difficult to implement.75 Colwill et al.25 recently trained color discrimination in zebrafish by placing different colors at the end of each arm of a T-maze (green vs. purple and red vs. blue) and feeding the fish only at one arm. These researchers unambiguously demonstrated discrimination of color by arranging discrimination reversals (i.e., a crossover design) and experimenter-blind testing. In a similar T-maze apparatus as shown in Figure 15.1(1), Darland and Dowling3 reinforced choice of one arm by providing it with a goal box containing deep water, artificial grass, and marbles (however, the dependent measure was the reduction in latency to reach the enriched arm, a result that could be caused by habituation of fear in the novel maze apparatus). The three-chamber maze shown in Figure 15.4 was developed by Arthur and Levin43 to assess learning and memory in the zebrafish. The three-chamber maze can be thought of as a simplification of the T-maze, but one in which aversive consequences follow errors. The start area is the middle “start chamber,” and there are vertically sliding doors on either side of this central start area leading to left and right choice areas. At the outset of a trial the fish is placed in the start chamber and allowed to move about for a brief period. In the choice phase, the vertical sliding doors to the left- and right-choice chambers are opened and the fish is allowed time to swim to one or the other; if it persists in the start chamber, a fish net is waved in the chamber (a “threatening stimulus”) until it makes a choice. After making a choice, both vertical sliding doors are closed. If the choice is correct (i.e., to the goal side) the fish is permitted to swim for a short period of time; if the choice is incorrect the sliding partition is moved to the “restricting position” for a short period of time. This procedure is repeated for a fixed number of trials. Dependent measures in the three-chamber shuttle maze include latency to escape the start chamber and correct choices.7,43 Initial tests with the maze43 showed that zebrafish could be trained to turn in a particular direction (spatial learning) or to approach a particular color regardless of location (nonspatial learning). We have used the three-chamber maze to show that the delayed spatial alternation behavior is a sensitive index of the persisting cognitive impairment caused by developmental exposure to the organophosphate pesticide chlorpyrifos (Figure 15.5).7 A parallel line of investigation (Figure 15.6)76 found that acute nicotine administration causes a significant improvement in delayed spatial alternation at low doses but impairs performance at high doses. The biphasic effect of nicotine improving memory function at low doses and having less improvement at higher doses is a common finding across a wide variety of species including rats, mice, monkeys, and


302


A. Choice Phase

B. Correct Choice

Vertical sliding door (open) Left-Choice Chamber

Vertical sliding door (closed)

Sliding partition and track Right-Choice Chamber

Start Chamber

Sliding partition in restriction position

2. Red-Blue Color Discrimination Learning Reversal

1. Spatial Discrimination Learning 6 Linear Trend p

Methods of Behavior Analysis in Neuroscience, Second Edition (Frontiers in Neuroscience)

Methods of Behavior Analysis in Neuroscience (Frontiers in Neuroscience)

Methods in Genomic Neuroscience (Frontiers in Neuroscience)