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COGNITIVE COGNITIVE SCIENCE SCIENCE PERSPECTIVES PERSPECTIVES ON ON PERSONALITY AND EMOTION PERSONALITY AND EMOTION
ADVANCES ADVANCES IN IN PSYCHOLOGY PSYCHOLOGY 124 124 Editors: Editors:
G. E. E. STELMACH G. STELMACH VROON P. A. A. VROON E
� m
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ELSEVIER ELSEVIER Amsterdam A m s t e r d a m-- Lausanne Lausanne -- New New York Y o r k-- Oxford O x f o r d-- Shannon Shannon -- Singapore S i n g a p o r e-- Tokyo Tokyo
COGNITIVE COGNITIVE SCIENCE SCIENCE PERSPECTIVES PERSPECTIVES ON PERSONALITY AND AND EMOTION ONPERSONALITY EMOTION
edited by editedby
Gerald MATTHEWS MATTHEWS Gerald University University of of Dundee Dundee Dundee, Scotland Dundee, Scotland
Ji!! m � 1997
ELSEVIER ELSEVIER Amsterdam Amsterdam - Lausanne Lausanne-- New New York Y o r k- Oxford O x f o r d- Shannon Shannon-- Singapore Singapore-- Tokyo Tokyo
NORTH-HOLLAND NORTH·HOLLAND ELSEVIER ELSEVIERSCIENCE SCIENCEB.V. B.V. SaraBurgerhartstraat Burgerhartstraat25 25 Sara p.o. P.O.Box Box211, 21l,1000 I OOOAE AEAmsterdam, Amsterdam,The TheNetherlands Netherlands
ISBN: 0 444 82450 2
t;)9 11997 997 Elsevier Science B.V. B.V. All All rights reserved. No No part part of this publication may may be be reproduced, stored stored in in aa retrieval retrieval system system or transmitted transmitted in in any any form or by any means, means, electronic, electronic, mechanical, mechanical, photocopying, photocopying, recording or otherwise, otherwise, without without the the ermissions prior prior written permission permission of the publisher, publisher, Elsevier Science Science B.V., B.V., Copyright & & PPermissions Department, Department, P.O. EO. Box Box 52 52 1l,, 1000 1000AM AM Amsterdam, Amsterdam, The The Netherlands. Netherlands. Special Special regulations regulations for readers readers in in the the U.S.A. U . S . A . -- This This publication publication has has been been registered registered with with the the Copyright Copyright Clearance Center Inc. Inc. (Ccq, (CCC), 222 222 Rosewood Rosewood Drive, Drive, Danvers, Danvers, MA MA 01923. 01923. Information Information can be be obtained from from the CCC CCC about about conditions conditions under under which which photocopies photocopies of of parts parts of of this this publication publication may may be be made made in in the the U.S.A. U.S.A. All All other other copyright copyright questions. questions, including including photocopying photocopying outside outside of of the the U.S.A., U.S.A., should should be be referred referred to to the the copyright copyright owner, owner, Elsevier Elsevier Science Science B.V., B.V., unless unless otherwise otherwise specified. specified. No No responsibility responsibility is is assumed assumed by by the the publisher publisher for for any any injury injury and/or and/or damage damage to to persons persons or or property property as as aa matter matter of of products products liability. liability, negligence negligence or or otherwise, otherwise, or or from from any any use use or or operation operation of of any any methods, methods, products, products, instructions instructions or or ideas ideas contained containedin in the thematerial material herein. herein. This This book bookis is printed printed on on acid-free acid-freepaper. paper. Transferred Transferred to todigital digital printing printing2005 2005
List List of of Contributors Contributors
Jean P. P. Banquet·. Banquet*. Neuroscience Neuroscience et et Modelisation, Modrlisation, Institut lnstitut des des Neurosciences, Neurosciences, Jean UPMC, UPMC, 99 quai quai St St Bernard, Bernard, 75252 75252 Paris Paris cedex, cedex, France. France.
Anthony Beech·. Beech*. Department Department of of Forensic Forensic Psychology, Psychology, Fair Fair Mile Mile Hospital, Hospital,
Wallingford, Oxfordshire Oxfordshire OXIO OX 10 9H, 9H, England. England. Wallingford, Jean Claude Dreher. Equipe Equipe de de Traitement Traitement des des Images Images et et du du Signal Signal (ETIS), (ETIS), ENSEAlUCP, ENSEA/UCP, Universite Umversit6 de de Cergy-Pontoise, Cergy-Pontoise, 66 Avenue Avenue du du Ponceau, Ponceau, 95014 Cergy-Pontoise Cergy-Pontoisecedex, cedex, France. France. 95014
Kevin M M. Carlsmith. Department Department of of Psychology, Psychology, Princeton Princeton University, University,
Princeton, NJ 08544, 08544, U.S.A. Princeton, Gerald L. Clore. Clore. Deparment Deparment of Psychology, Psychology, University University of Illinois Illinois at Urbana UrbanaChampaign, Champaign, 603 East Daniel Daniel Street, Street, Urbana-Champaign, Urbana-Champaign, IL 61820, 61820, U.S.A.
Doug/as Douglas Derryberry·. Derryberry*. Department Department of Psychology, Psychology, Oregon Oregon State State University, University,
Corvallis, OR 97331, 97331, U.S.A. Chabot. Department Department of Psychology, University of New Heather Frasier Chabot. Psychology, University
Hampshire, Durham, Durham, NH 03824, 03824, U.S.A. Philippe Gaussier. Equipe Equipe de Traitement Traitement des Images Images et du Signal Signal (ETIS), ENSEAlUCP, Universit6 Universite de Cergy-Pontoise, Avenue du Ponceau, ENSEMUCP, Cergy-Pontoise, 6 Avenue 95014 Cergy-Pontoise Cergy-Pontoise cedex, France.
Wilfried Gtinther. Gunther. Neuroklinik Neuroklinik Bamberg, Bamberg, St Getreu Getreu Strasse Strasse 14-18, Wilfried 14-18, 8600
Bamberg, Germany. Rick E. Ingram. Department Department of Psychology, Psychology, San Diego Diego State University, University, San Rick
Diego, CA 92182-0551, U.S.A. C~dric Cedric Joulain. Joulain. Equipe Equipe de Traitement Traitement des Images Images et du Signal Signal (ETIS), ENSEAlUCP, Universit6 Universite de Cergy-Pontoise, 6 Avenue Avenue du Ponceau, ENSEA/UCP, 95014 95014 Cergy-Pontoise eedex, cedex, France.
Timothy Timothy Ketelaar*. Ketelaar·. Center Center for Adaptive Adaptive Behavior Behavior and Cognition, Cognition, Max Planck Institute Institute for for Psychological Research, Research, Leopoldstrasse Leopoldstrasse 24, 80802 Planck Munich, Germany. Germany.
Contributors
vi Vi
Kitayama*. Faculty Faculty of Integrated Integrated Human Human Studies, Studies, Kyoto Kyoto University, Shinobu Kitayama·. University,
Kyoto 606-01, 606-01, Japan. Kyoto Gerald GeraM Matthews·. Matthews*. Department Department of Psychology, Psychology, University University of Dundee, Dundee, Dundee Dundee DD11 4HN, 4HN, Scotland.
Mayer*. Department Department of Psychology, Psychology, University University of New Hampshire, Hampshire, John D. Mayer·.
03824, U.S.A. Durham, NH 03824, Edward Necka·. Necka*. Instytut Instytut Psychologii, Psychologii, Uniwersytet Uniwersytet Jagiellonski, Jagiellonski, ul. Golebia Golebia
13, 31-007 Krakow, Krak6w, Poland. 13,31-007 Mar jorie A. Reed. Marjorie Reed. Department Department of Psychology, Psychology, Oregon Oregon State State University, University, Corvallis, Corvallis, OR 97331, 97331, U.S.A.
Carien M M. van Reekum. Reekum. Department Department of Psychology, Psychology, Universite Universit6de Geneve, Gen6ve, 9, 9,
Drize, CH CH-- 1227 1227 Carouge-Geneva, Carouge-Geneva, Switzerland. route de Drize, Arnaud Revel. Revel
Equipe Traitement des Images Equipe de Traitement Images et du Signal Signal (ETIS), (ETIS), ENSEAlUCP, Universite de Cergy-Pontoise, ENSEA/UCP, Universit6 Cergy-Pontoise, 6 Avenue Avenue du Ponceau, Ponceau, 95014 Cergy-Pontoise Cergy-Pontoisecedex, cedex, France.
Klaus R. Scherer·. Scherer*. F.P.S.E. F.P.S.E. Section Section Psychologie, Psychologie, Universite Universit6 de Geneve, Gen6ve, 9,
Drize, CH CH-- 1227 1227 Carouge-Geneva, Carouge-Geneva, Switzerland. route de Drize, Siegle*. Doctoral Doctoral Training Facility, San Diego Diego State State University, 6363 Greg Siegle·. Training Facility, University, 6363
Alvarado Court, Court, San Diego, Diego, CA 92120, 92120, U.S.A. Tryon·. Tryon*. Department Department of Psychology, Psychology, Fordham Fordham University, University, Rose Rose Hill Campus, 441 East Fordham Fordham Road, Road, Bronx, Bronx, New York, York, NY 10458-5198, 10458-5198, Campus, U.S.A.
W. W. W.W.
Leanne Williams. University of New England, Williams. Psychology Psychology Department, Department, University England, Arrnidale NSW 2351, Armidale 2351, Australia.
*
* Corresponding Corresponding author
Preface Preface
We are are all cognitive cogmtlve scientists scientists now. now. Researchers Researchers routinely use the We language of cognition cognition in developing models of personality and emotion. emotion. Constructs such as as automatic processing, schemas, working memory, Constructs resources and the like are now part part of the essential fabric of attentional resources theory. The The popularity of information-processing models offers both a promise and a threat. threat. The The promise is that of a true true understanding understanding of how the faculties of perception, attention, memory and so forth different psychological faculties integrated are inter-woven to create the whole person, and to create the mtegrat~ adaptive reactions we call emotions. emotions. Contemporary cognitive science is at ease levels of description and explanation, ease with with multiple levels explanation, and so is especially well-suited to explaining the origins and expressions of emotion and personality. personality. But do we really speak a common language, or are we heading for a new Babel? Constructs Constructs such as schemas and strategies sometimes seem plastic enough to fit almost any theoretical conception, so that the verbal labels become private rather than shared. shared. As subjects of inquiry, emotion and personality are particularly vulnerable to the use of language as artifice rather than as scientific discourse. discourse. The decline of psychoanalysis as a scientific threat. In contemporary research, there enterprise illustrates the nature of the threat. is an evident risk of "cognitivism", dressing up untestable ideas in cognitive jargon. of cognitive jargon. The differing perspectives provided by different strands of research are a strength, not a weakness, but communication between different perspectives requires us to work from common scientific bases. This book aims to highlight the vigour, diversity and insight of the various cognitive science perspectives on personality and emotion. It aims also to emphasise the rigorous scientific basis for research to be found in the integration of experimental psychology with neuroscience, connectionism and the new evolutionary psychology. Collectively, the contributors to this book provide a wide-ranging survey of leading-edge research topics. It is, a little arbitrarily, divided into three parts, on general frameworks for cognitive science, on perspectives from emotion research, and on perspectives from studies of personality traits. In the first, introductory chapter, I begin Part I with a personal view of the impact of the cognitive revolution, and apply the "classical theory" of cognitive science to issues in personality and emotion. As the book took shape, I came to appreciate how much a cognitive science of personality and emotion is necessarily a science of motivation too. In
Pref ace Preface
Vlll
viii
Chapter 2, Mayer, Frasier Frasicr Chabot and Carlsmith inter-relate inter-relate these three constructs constructs in the context of the traditional "trilogy of mind": mind": conation, affect and cognition.
They procr~ proceed to outline a new "quatemity "quatcrnity of mind",
encompassing consciousness consciousness also. One of the most radical and exciting innovations of cognitive science is the use of connectionist models, and the innovations remaining two contributors to Part I provide two different perspectives on their application. Bidirectional Associative Memory (BAM) uses the application. Tryon's Bidirectional conncctionist metaphor of memory as wells in an energy surface as a source connectionist of insight into normal emotion and pathological conditions (Chapter 3). He also outlines how psychotherapy may be directed towards re-Iandscaping re-landscaping the energy surface, by shrinking memory wells whose diameter gives them too much power over the person's experiences, for example. In Chapter 4, Drehcr, Joulain, Revel and Gunther Banquet, Gaussier, Dreher, G0nthcr describe a more ncurologically-orientod conncctionist perspective on personality. They neurologically-oriented connectionist discuss how the person's sense of identity in space and time derives from spatio-tcmporal circuits in hippocampus and prefrontal cortex, supporting spatio-temporal processing, working memory, planning and goal propagation. Part II reviews perspectives derived primarily from emotion research, which explore the interplay between emotion as a common human characteristic and individual difference factors. One of the flaws in an overly unconscious, preattentive prcattcntivc cognitivistic conception of emotion is neglect of unconscious, processes which guide later, attentive processing. Kitayarna Kitayama (Chapter 4) presents the amplification model of affect-cognition affect-cognition interaction in early perceptual processing. The model model describes how the emotional content of rccognition, stimuli may either enhance or impede subsequent conscious recognition, "perceptual defence". dcfencc". Van Reekum Rcckum and explaining phenomena such as "perceptual Schcrcr of Scherer (Chapter 5) also address distinctions between different levels of processing, in the context of appraisal, which may be supported by sensory sensorymotor, schematic or conceptual conceptual processing routines. routincs. They review ncuroscicncr neuroscience bases for appraisal, and link personality to different appraisal Sicgle and Ingram explore connectionist conncctionist characteristics. In Chapter 6, Siegle modelling of the negative biases in cognition characteristic of of depression and other emotional disorders, expressed in appraisal, attention and memory. lcxical decision and valence identification as tasks They focus especially on lexical which bring to thc processing underlying the surface the abnormalities of processing pathology. The pcrspcctivc perspective from evolutionary psychology is presented in Chapter 7 (Ketelaar (Kctelaar and Clore), Clorc), which discusses the long-term adaptive significance of emotions, as informative and motivational signals. The significance authors review evidence suggesting that analysis of the evolved functions of of
Pref ace Preface
IX ix
emotions helps us to understand their more immediate effects on cognition in experimental studies. Part III is oriented towards research on personality traits, within a
superloosely Eysenckian framework, with contributions relating to the three super extraversion-introversion, neuroticism (anxiety) and psychotir factors of extraversion-introversion, psychoticism (schizotypy). Perhaps a future volume of this kind will be able also to cover
additional
dimensions
from
the five factor model; conscientiousness, agreeableness and openness to experience. In Chapter 9, 9, I present a cognitive cognitiveadaptive model of extraversion, extraversion, which reviews information-processing correlates of the trait in the context of adaptive specialisation. Extraverts may be superior in verbal facilities such as short-term recall, retrieval and multi multitasking because these cognitive characteristics contribute to coping with their preferred environments. Derryberry and Read (Chapter 10) discuss the relationship between motivational and attentional aspects of anxiety, anxiety, from the standpoint of cognitive neuroscience. Experimental data illustrate anxietyanxiety related biasing of specific attentional functions which may contribute to anxious individuals. shaping the higher-level cognitions and motivations of anxious Beech and Williams (Chapter 11) assess the cognitive bases for schizophrema schizophrenia and schizotypal personality. They develop a model of activation and inhibition processes which explains priming data obtained experimentally, and the positive symptomatology of schizophrenia such as delusions and hallucinations. Finally, Finally,· contemporary trait researchers are increasingly engaged with exploring the relationships between personality and ability traits. In Chapter 12, Necka links intelligence, extraversion and neurotir neuroticism to an attentional resource model. Both personality and ability arousal processes, processes, whose impact on cognition is shown in traits are related to arousal experimental studies of dual-task performance and memory scanning. scanning. I am grateful to the Medical Medical Research Council for their support for my research while this to thank the this book was in preparation. I would also like to contributing reading and re-reading re-reading the chapters, contributing authors. I have enjoyed reading chapters, and my schemas and networks networks are greatly enriched. This This is the book I would have liked to to have have read read when I first began began researching personality personality and emotion as as a doctoral doctoral student in the early 1980s. I hope it will serve as as an inspiration and a guide guide to to all those with an an interest in this this exciting new research area.
(Jerald Matdlews Gerald Matthcws
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Contents Contents
PART P A R T I. I. FRAMEWORKS F R A M E W O R K S FOR F O R COGNITIVE C O G N I T I V E SCIENCE SCIENCE
Chapter 1. 1. An Introduction to to the Cognitive Science Science of Chapter An Introduction Personality and Emotion
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Gerald Matthews Landmarks the Cognitive Landmarks of of the Cognitive Revolution Revolution .............................................. 3 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... . . . . .
A Cognitive Science A Cognitive Science Framework Framework
...................................................... 77 Towards aa Cognitive Neuroscience of Personality and Towards Cognitive Neuroscicnce of Personality and Emotion? Emotion? ......... 13 13 Developing Adaptive Adaptive Explanations Developing Explanations .................................................. 15 15 An Anxiety and An Example: Example: Explaining Explaining Anxiety and Cognition Cognition .............................. 20 20 Conclusions Conclusions .................................................................................... 24 24 . . . . . . . . . . . . . . . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . . . . . . ... . . . . .
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Chapter 2. Conation, 31 Conation, Affect, and Cognition Cognition in Personality................... ................... 31
M. Carlsmith John D. Mayer, Heather Frasier Chabot and Kevin M The Relational The Relational Model Model of of Personality Personality .................................................. 32 32 Understanding and Cognition Understanding Conation, Conation, Affect, Affect, and Cognition ................................. 39 39 The of Mind Mind and and Personality The Quatemity Quaternity of Personality Dynamics Dynamics ............................ 52 52 Conclusions Conclusions and and Other Other Considerations Considerations .............................................. 60 60 . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Chapter 3. Introduction to the Bidirectional Associative Memory Model: Implications for Psychopathology,
Treatment, and Research ............... ....................................................................... 65 Treatment, ... . .... . . . . .. .. ...... ........... . . .. 65 .
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�arren Warren � W. T�on Tryon Bidirectional Associative Memory Memory (BAM) Bidirectional Associative (BAM) ......................................... 67 67 . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .
Encoding Emotion Emotion ............................................................................. 70 70 Encoding . . . . . . . . . . . . . . . . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Implications for for DSM-IV DSM-IV Disorders Disorders .................................................. 75 75 Implications Treatment .........................................................................................92 Treatment 92 Research Strategies ........................................................................... 99 99 Research Strategies Conclusions .................................................................................... 1101 0I Conclusions Appendix: Description Description of of the Bidirectional Associative Associative Memory Appendix: the Bidirectional Memory ....... 109 109 . . . . . . . . . . . . . . . . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . .
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xii XII
Contents Chapter Chapter 4. 4. Space-Time, Space-Time, Order, Order, and Hierarchy Hierarchy in FrontoFronto-
...................... 123 Hippocampal Hippocampal System: A A Neural Neural Basis of of Personality Personality .... .......................... Jean dean P. Banquet, Banquet, Philippe Gaussier, Jean Claude Dreher, Dreher, Cedric Cddric Joulain, /fried Gunther Joulam, Arnaud Revel and Wi Wilfried G~tnther Hipp Hippocampal ocampal Function: Function: An Extended Extended View View ...................................... .. . .. 126 126 .
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Working Memory as Both aa Cortical Working Memory as Both Cortical and and aa Hippocampal Hippocampal
System ...................................................................................... 129 . ..... . . . . ... ..... . . . .... . 129 System .
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Neuropsychology, Neuropsychology, Brain Brain Imaging Imaging and and Working Working Memory Memory ................... 135 135 ...................
Neurophysiology: Neurophysiology: Human Human Versus Versus Animal Animal Working Working Memory Memory ............ 148 148 ............
Spatio-Temporal Processing Processing in in Hipp Hippocampus and Prefrontal Prefrontal Spatio-Temporal ocampus and
Cortex ...................................................................................... 151 Cortex 151 .... ............................. ............ ........ . . ................. . . . . . .. . . .....
Functional ... . .. .. ... ... . . . .. .... . . .. . 159 Functional Model Model .............................................................................. 159 ...
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Fronto-Hipp ocampal Function . .... .. . . . 176 Fronto-Hippocampal Function and and Personality Personality ................................ 176 ......
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Conclusion . . . .. . ... . .. . 179 Conclusion ..................................................................................... 179 ...........
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PART II. PERSPECTIVES PERSPECTIVES FROM FROM EMOTION EMOTION RESEARCH RESEARCH PART Chapter Chapter
5. Affective Affective Influence in Perception:
.................................... 193 Some Implications Implications of of the Amplification Amplification Model ...................................... Some
Shinobu Kitayama The Model of of Affect-Cognition Affect-Cognition Interaction Interaction ................. 196 The Amplification Amplification Model ..... .. 196 Evaluation Criteria Criteria of of the the Amplifi cation Model . ... . 202 Evaluation Amplification Model ................................ Experiment Experiment 11 .................................................................................. .................................................................................. 212 Experiment Experiment 2 .................................................................................. .................................................................................. 221 221 The Amplification Model .. . 230 The Amplification Model Evaluated Evaluated ................................................. Relations with with Extant Extant Theories Theories of of Attention Attention ..................................... Relations . .. . . . . . .... 232 Amplification Attention in in Other Other Domains Domains ................................... Amplification of of Attention .. .. . . 235 Perceptual Defense Defense and and Vigilance? Vigilance? .................................................... Perceptual . .. . 238 Future . . ...... .. .. .. 240 Future Research Research Directions Directions ............................................................. Concluding . . .. . . ... . 242 Concluding Remarks Remarks ... ....................................................................... .
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Contents Contents
Xlll xiii
Chapter 6. Levels Levels of of Processing Processing in in Emotion-Antecedent Emotion-Antecedent Chapter Appraisal Appraisal
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Carien M M. van van Reelcum Reekum and Klaus R. R. Scherer Scherer Carien of Appraisal Notions ......................................................... ......................................................... 260 260 Critique of of Processing in in Appraisal .................................................... ........................... : ........................ 263 263 Levels of in Related Traditions Traditions .......................... .......................... 266 266 Hierarchical Process Notions in in Rewriting Appraisal Theory .............................................. .............................................. 277 277 Issues in in Appraisal Appraisal Processes Processes .................................. .................................. 280 280 Individual Differences in Conclusions .................................................................................... .................................................................................... 289 289 Conclusions
Modeling Individual Differences in Negative Chapter 7. Modeling Information Processing Processing Biases Information
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Greg.1. J Siegle and Rick E. Ingram Greg Personality Research and Vulnerability Vulnerability to Depression: Depression: A History History ...... ...... 302 302 Personality Simulating Aspects Aspects of Depression Depression and Personality Personality on a Simulating Computer ....................................................................................... ....................................................................................... 304 304 Computer Simulating Personality Personality Factors Factors ........................................................ ........................................................ 320 320 Simulating Conclusion ......................................................................... ......................................................................... 348 348 A Brief Conclusion
Chapter 8. Reason" The Proximate Effects Effects and Chapter 8. Emotion Emotion and Reason: The Proximate Ultimate Functions of Emotions ........................................................... 355 Ultimate Functions of Emotions 355 .......................•...................................
Timothy Ketelaar GeraM L. Clore Timothy Ketelaar and and Gerald Why ............................................. 356 356 Why Does Does Emotion Emotion Affect Affect Cognition? Cognition? ............................................. Specific .......................................................... 358 358 Specific Aims Aims of this this Chapter Chapter .......................................................... Consequences of Mood ................................................................... 360 Consequences Mood ...................................................................360 Consequences .............................................................. 365 365 Consequences of Emotions Emotions .............................................................. Emotion-as-motivation and and Frank's Frank's (1988) (1988) Commitment Commitment Model Model ....... Emotion-as-motivation ....... 371 371 Affect-as-lnformation ................................................ 378 378 Affect-as-Information and and Behavior Behavior ................................................ The Processing ............................. ............................. 387 387 The Future Future of Affect Affect and and Information Information Processing Conclusion: ..................................... 388 388 Conclusion: Deficits, Deficits, Biases, Biases, and and Functions Functions .....................................
xiv XIV
Contents III. P PERSPECTIVES PPART A R T IIl. E R S P E C T I V E S FFROM R O M PPERSONALITY ERSONALITY RESEARCH TTRAIT RAIT R ESEARCH
Extraversion, Emotion Emotion and and Performance: Chapter 9. Extraversion, Chapter A Cognitive-Adaptive Cognitive-Adaptive Model Model................................................................ 399 399 A ................................................................
Gerald Matthews ..
Extravorsion .................................................................. 400 400 Extraversion and and Affect Affect .................................................................. Extraversion 405 Extraversion and and Performance Performance ......................................................... .. ... . .... . . ....... ..... . 405 Extraversion, 409 Extraversion, Arousal Arousal and and Attontion: Attention: Empirical Empirical Studies Studies ................... ... ....... . .409 An Adaptivr Adaptive Framowork Framework for for Cognitive Cognitive Correlates Correlates of of An Extraversion-Introversion ................................................................. .... .. .... . .... ... .. . ...... . .. . 426 426 Extraversion-lntroversion Conclusions .................................................................................... .. . .... . . ....... .. .. ... . . . ......... ... . . 434 Conclusions 434 .
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of Chapter 10. Motivational and Attentional Components of 443 Personality ............................................................................................ 443 ............................................................................................
Douglas Derryberry jorie A. Reed Derryberry and Mar Marjorie Biological .............................................. 444 Biological Approachos Approaches to to Personality Personality ..... .. . ... .... ........ ... .444 Assessing Attentional Processes in ......... . .. ...... ..... ...450 Assessing Attcntional Processes in Anxiety Anxiety ..................................... 450 Extensions to Complex . .. ... .......... ...... . .462 Extensions to Complex Cognitive Cognitive Processing Processing ................................... 462 Conclusions .. ............ . ........ .. .. . . ... ... . .. .... .. . ..... .466 Conclusions .................................................................................... 466 .
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Chapter 111. 1. Investigating Cognitive Processes in Schizotypal Personality and Schizophrenia
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Anthony Beech Beech and Leanne Williams Williams Mechanisms . ... .. ...... .. . .. . . ....... ....477 Mechanisms of of Selective Selective Attention Attention .................................................. 477 Experimental Investigations Investigations of of Inhibitory Inhibitory Processes Processes ........ ......................... 478 Experimental ........ . ...478 Inhibitory Inhibitory Processes Processes in in Schizophrenia Schizophrenia ............................................. .............................................. .485 485 Towards aa "Reduced "Roducexl Cognitive Cognitive Inhibition" Inhibition" Model Model of of Towards Schizophrenic Schizophrenic Symptomatology Symptomatology ...................................................... ...................................................... 490 490 Revising .. . ... .... .. ..... . . ........... ........ . . . . ... .. 494 Revising the the Model Model .......................................................................... 494 Conclusion . . .. .. . .. ..... . ... ...... .. .. . ... .. . 497 Conclusion ....................................................................................... 497 ... .
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Contents Chapter
Working Memory Memory and Arousal: 12. Attention, Working
Concepts Concepts Apt to Account Account for the "Process "Process of Intelligence"
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Edward Necka Theoretical Notions Notions ......................................................................... Theoretical Assumptions ................................................................................... Assumptions "The Process Process of o f Intelligence" Intelligence" ........................................................... "The Preliminary Empirical Data ............................................................. Preliminary Empirical Data Cognitive Science Science Perspectives Perspectives ........................................................ Cognitive
504 504 512 512 519 525 525 542 542
index ......................................................................................... Subject index
555
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PART P A R T II FRAMEWORKS FOR COGNITIVE FRAMEWORKS FOR COGNITIVE SCIENCE SCIENCE
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Perspectives on Personality Personality and Emotion Emotion-G. Matthews (Editor) (Editor) Cognitive Science Perspectives G. Matthews -
1997 V. 1997 Elsevier Science B. B.V.
CHAPTER 1 CHAPTER!
An Introduction Introduction to the Cognitive Cognitive Science of Personality Personality An Emotion and Emotion GeraM Matthews Gerald
The cognitive revolution has transformed the face of research on personality and emotion. Information-processing theories spring up like poppies in a cornfield, and often wither just as quickly, crowded out by more recent growth. With cognitive approaches so firmly established, it is timely to stand back a little from the intellectual ferment, and take stock of the achievements and limitations of the research area. This book represents the leading edge of research on the cognitive science of personality and emotion, contributions concern a variety of specific topics. But for and so the contributions personality and emotion research to mean anything at all, it must above all be integrative. Both constructs hang on a multi-layered web of data and hypothesis, spanning the gamut of psychological phenomena from neuronal firing to social interaction. The aim of this introductory chapter is to outline the overall framework provided by cognitive science, and its place in personality and emotion research. research. In this chapter, I will sketch the progress so far of the cognitive revolution in personality and emotion (PE) research. research. I will then describe the classical model of cognitive science, and its three levels of explanation: the biological, the symbol-processing and the knowledge levels. Cognitive science emphasises that information-processing models are necessary but not sufficient for understanding, understanding. lI will show that cognitive explanations provide new perspectives on some old problems, and science explanations demonstrate its integrative potential by outlining its application to anxiety. anxiety.
Landmarks Landmarks of the Cognitive Revolution Emotion and Emotion and cognition cognition
The cognitive science of emotion has disparate roots, roots, which demonstrate the diversity of "cognitive" approaches. The information-processing approach is based on empirical, empirical, performance-based studies of emotion, addressing problems such as the deleterious effects of anxiety on attention. It
4
Chapter 1
accommodates the the various various conccptualisations conceptualisations of emotion: as as aa universal universal but accommodates situationally-contingent human response, as as an individual individual difference factor, and as as aa property of stimuli (valence). (valence). Emotion may be conccptualiscd conceptualised as as aa and dependent variable influcnce~ influenced by processes such as as appraisal, or as as an independent variable which itself influences influences information-processing. The independent more sophisticated applications 1984) build in applications of the approach (e.g. Ingrain, Ingram, 1984) feedback from appraisals into emotion. In linking appraisals of performance back into emotion to bchaviour, behaviour, the basic research tactic is to demonstrate moderation of effects of emotion on performance standard technique performance by task factors, the standard of experimental experimental cognitive psychology. Emotion •x task parameter interactions inspire processing models which may then be subjected to further test. The approach scores highly on scientific rigour, but like much cognitive psychology, risks degenerating into an account of the minutiae of a specific experimental paradigm with little wider relevance (cf. Neisser, Neisscr, 1976). 1976). An alternative approach is design-oriented: design-oriented: what might be the purpose of emotion within the cognitive system as a whole? Simon (1967) linked emotion to an interrupt function, contributing to people's capacity to to adapt to unpredictable environments by switching back and forth between different goals. This analysis begs the question of why the interrupt function requires all the various concomitants of emotion such as physiological arousal, biases in thinking, action tendencies and the like. like. Research in the Artificial Intelligence (AI) tradition simulates complex, goal-directed systems to ple, what other features discover basic design principles, indicating, for exam example, are required for interrupts to arc to work properly. This approach generates rich and thought-provoking data, but its scientific rigour is open to question. Argument tends to proce~ proceed by analogy and comparison of features of artificial and human systems, and it is unclear that the parallels drawn are arc open to falsification or to formal test against alternative explanations. A third tradition derives from stress and clinical research, and the observation that negative emotions derive from the way people interpret and manage events, rather than from fixed properties of the events themselves. It 1984) on is exemplified by the work of Lazarus (1991; Lazarus & Folkman, 1984) the transactional transactional model of stress, and the roles of appraisal and coping within specific, potentially stressful encounters. As theory, it has some of the characteristics of both the design and information-processing approaches. Like the design approach, it is explicitly systems-based, with emotion conceptualised as a "core relational theme" characterising conceptualiseA charactcrising the person personenvironment system as a whole. However, like the information-processing tradition, transactional theory attempts to establish local cause-and-effect
G. Matthews
5
relationships open to direct empirical test, such as the effect of appraisals on emotion. Similarly, clinical accounts of anxiety and depression which emphasise the role of the person's self-knowledge and reasoning processes in generating negative emotion as an overall indicator of system functioning (e.g. Beck, 1967; 1967; Ellis, 1962). 1962). The advantages of such approaches are depth of insight obtained into the experiences of people in real environments, and practical applications to stress management and cognitive behaviour therapy (Matthews & Wells, 1996). 1996). Their shortcomings relate, first, to emphasis on self-report data, which may present a partial and distorted view of underlying processing, and, second, as with the design tradition, to difficulties in rigorous theory testing. Finally, the neuroscience of emotion has become increasing cognitive in orientation, as traditional arousal theory has fallen from favour (e.g. Robbins, 1986). 1986). Increasingly, it has becomes possible to align specific neural circuits with information-processing and behavioural function (e.g., Gray, 1982). 1982). Emotion is notoriously difficult diffmult to localise, but advances in brain scanning technology, and in simulation of neural function are a source of optimism for the future. Pessimists focus on the extent to which feelings are intertwined with thinking, and consequent difficulties in discriminating neural and influences. There remain fundamental disagreements over the extent cognitive influences. to which psychological phenomena are reducible to neural processes (see 1984, 1991, 1991, and Gazzaniga, 1992, 1992, for the end-points of the Lazarus, 1984, continuum of views). At the least, though, computational theories permit testable predictions concerning neural influences on behaviour, contributing to the development of cognitive neuroscience models of emotion.
and cognition Personality and Much of personality research is structure- rather than process-oriented, and so unaccommodating to cognitive perspectives. The current popularity of the Five Factor Model owes much to the prodigious empirical progr programmes ammes of researchers such as Costa and McCrae (1992) in deriving the Big Five as a structural description of various data sets. Personality trait theories have often been based on somewhat naive biological or conditioning models, J.B. Watson rather than by contemporary research. inspired by Pavlov and J.B. blessing. The concept Arousal theory, in particular, has proved to be a mixed blessing. undoubtedly has integrative value (K.A. Anderson, 1990), 1990), and the basic principle that personality reflects biology is becoming increasingly securely (Loehlm, 1992: 1992: Lesch supported by behaviour and molecular genetic studies (Loehlin,
6
Chapter 1 Chapter
ct 1996). Eyscnck et al., al., 1996). Eysenck and and Eyscnck's Eysenck's (1985) (1985) application application of of arousal arousal theory theory to to personality personality has has scored scored some some notable notable empirical empirical successes successes in in predicting predicting extraversion-introversion effects effects on on sensory sensory thresholds thresholds and and simple simple cxtraversion-introvcrsion conditioning conditioning tasks. tasks. Unfortunately, Unfortunately, psychophysiological psychophysiological data data on on personality personality are confusing confusing and and inconclusive, inconclusive, and and arousal arousal theory theory has has proved proved to to be be aa poor poor arc basis for for predicting predicting personality personality effects effects on on cognitive cognitive tasks tasks (e.g. (e.g. Matthews, Matthews, basis Matthews & & Deary, Deary, in in press). press). 1985; Matthews Despite Despite the the conservatism conservatism of of much much personality personality research, research, there there arc are increasing signs that that the the cognitive cognitive revolution is taking taking root root in in this this area area also. also. increasing signs revolution is of emotion, emotion, its its expressions expressions arc are diverse. diverse. Information-processing Information-processing As As in in the the case case of analyses analyses of of personality personality effects effects on on performance performance arc are becoming becoming increasingly increasingly common. common. The The trail trail has been been blazexl blazed by by research research on on anxiety anxiety traits, traits, driven driven by by that cognitive cognitive worry worry is is more more predictive predictive of of performance performance than than the observation observation that the emotional and and physiological physiological tension. tension. Detrimental Detrimental effects effects of of anxiety anxiety arc are now now emotional routinely routinely explained explained in in terms terms of of constructs constructs such such as as attentional attentional capacity capacity (Sarason, Sarason, & 1995) and (Eyscnck, 1992). 1992). (Sarason, Sarason, & Pierce, Pierce, 1995) and working working memory memory (Eysenck, Humphmys Rcvr162 (1984) have Humphreys and and Revelle have proposed proposed an an ambitious ambitious integration integration of of individual differences research which anxiety individual differences research which links links achievement achievement motivation, motivation, anxiety and to arousal and effort, effort, which which in availability of and impulsivity impulsivity to arousal and in tum turn influence influence availability of multiple and working multiple resources resources for for performing performing attcntional attentional and working memory memory tasks. tasks. There is also aa rather rather separate tradition with with aa basis basis in in social-cognitive There is also separate tradition social-cognitive psychology, concerned concerned with with the the knowledge knowledge structures which support psychology, structures which support personality, the self-schema personality, such such as as the self-schema (Cantor (Cantor & Zirkel, Zirkcl, 1990). 1990). This This approach approach supports work, such supports some some information-processing information-processing work, such as as studies studies of of self-referent self-referent processing (Klein (Klein & Loftus, Loftus, 1988) 1988) and and priming priming (Bargh, (Bargh, Chaiken, Chaikcn, Govender, Govcndcr, processing & Pratto, Pratto, 1992), 1992), but but also also leans leans heavily heavily on on qualitative qualitative and and self-report self-report data. data. Hence, Hence, itit resembles resembles the the transactional transactional approach approach to to emotion: emotion: its its allegiance allegiance is is to to cognition cognition but but not not necessarily necessarily to to cognitive cognitive science. science. On On the the other other hand, hand, itit is is sufficiently to both both nomothetic sufficiently flexible flexible to to be br applied applied to nomothctic and and idiographic idiographic aspects aspects of of personality, personality, and and engages engages with with individuals' individuals' actual actual life life experiences. experiences. Integration of ofpersonality and and emotion emotion research research
The distinction distinction made made between between personality personality and and emotion emotion is is artificial artificial to to the the The extent extent that that much much personality personality research research has has an an explicit explicit trait-state trait-state orientation, orientation, within within which which personality personality effects effects are arc mediated mediated by by emotional emotional states states (e.g. (e.g. Spielberger's, Spiclbcrgcr's, 1966, 1966, anxiety anxiety theory). theory). We We cannot cannot do do personality personality research research without without consideration consideration of of emotion, emotion, but but the the converse converse also also applies. applies. Some Some studies studies of mood mood make make aa strong strong equation equation between between positive positive and and negative negative affect affect on on the the of
G. Matthews G. one hand, and extraversion and neuroticism on the other.
77 Individual
differences in mood may substantially reflect individual differences differences in reward differences and punishment systems said to be the basis for extraversion and neuroticism (Watson
& Clark, 1992). Unfortunately, taken to the extreme, this approach
leads to a dreary tautology, such that some unfortunates have negative genes, negative brains, negative emotions and negative personalities, and little more can be be said.
More promising are interactionist approaches which emphasise that
differences in emotional response are not mechanically linked to individual differences personality, but depend on a more complex interplay between person and
environment. Within the transactional model, personality is seen as biasing environment. the appraisal and coping processes which are perhaps more direct influences on emotion (Matthews & Deary, in press). Interactionism can easily degenerate into an unfalsifiable everything-affects-everything position, but can potentially supply much needed precision to theory computational models can in this area. Information-processing analyses of performance frequently effects on different different processing attempt to discriminate trait and state effects trait components. Eysenck's (1992) review of the area suggests that simple traitstate models, within which trait effects are entirely mediated by gross state constructs, are not viable: trait anxiety may sometimes influence cognition and behaviour even with state anxiety controlled. Integration of trait and state research requires a more sophisticated view, such that traits affect stable parameters of processing systems which moderate their reactions to to stimuli. We might link traits traits to knowledge structures in long-term memory (LTM) (LTM) which feed into appraisal and coping (Wells & Matthews, 1994), 1994), or, from a connectionist perspective, to parameters of networks which govern the spread of activation (Matthews (Matthews & Harley, 1993). 1993). In either case, moderating effects of traits traits are apt to be subtle, and require careful modelling.
A Cognitive Framework Cognitive Science Framework The brief overview above demonstrates the vigour of the cognitive cogmtIve approach to P PE. approach E. It also shows that progress has been uneven, and the diversity of differing "cognitive" approaches. We require a general framework for examining where cognitive research has been most successful, and where its impact has so far been limited. "classical theory" of limited. Fortunately, the "classical cognitive science provides a ready made framework, discriminating different levels of explanation. Next, I will outline these levels, and discuss their application to PE research.
8
Chapter 1I
Pylyshyn (1984) presents a detailed analysis of knowledge, symbol symbolprocessing and biological levels of explanation, from which the following account is derived (see Figure 1). 1). The central point is that psychological events are open to qualitatively different explanations. Suppose we observe an extraverted man man at a party, engaging in cheerful social interaction. How do behaviour? One approach is to refer to we explain this bohaviour? to his motives and goals. Perhaps he is a newcomer, and wishes to to make new friendships from which he will benefit. This level of explanation is the knowledge-based or semantic level. It is concerned especially with the way the cognitive system is designed for adaptive interaction with the external environment, in pursuit of its goals. It has been developed in PE research through AI approaches approaches to understanding emotion, through work on the adaptive functions of PE, and through social knowledge approaches approaches to personality. Alternatively, we might present an account based on the formal cognitive architecture: a computational description of the processing structures and operations linking inputs to social behaviours. We may then identify spee~ of accessing individual differences in specific computations, such as speed items of social knowledge, which explain the individual's social behaviour at the processing level. Explanations of this kind are concerned with the formal characteristics characteristics of processing, rather than with the adaptive significance of processing routines. They provide the basis for much of the extensive research on information-processing information-processing models of emotion and personality previously described. Classical theory requires the architecture to be based on discrete symbols, expressing propositions. Pylyshyn distinguishes sub-levels of algorithm and functional architecture, which differentiate the logical operations performed on symbols form the cognitive structures implementing symbol processing. The centrality of symbols is a controversial area. Some authors place symbol-based accounts of processing centre stage, due to identifiability problems of modelling functional architecture (J.R. (J.R. Anderson, 1990). 1990). Conversely, connectionist models see network implementations as a more powerful method for modelling behavioural data than symbolic accounts, and may even reject symbolic representations as irrelevant to theory accounts, (Smolensky, 1988). 1988). I will take the view that, in the light of the successes of connectionism, an a priori commitment to to symbolic accounts may be too constraining for PE research. I will use the term "architectural explanation" to refer to explanation in terms of the formal properties of the processing machinery, irrespective of whether or not it is symbolic in nature.
G. Matthews Matthews G.
Knowledge = Knowledge
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Figure 10. Goal backpropagation: the model is used to learn transitions between stable states such as to go from A to B (AB) and next from B to C (BC)... CA1 neurons. CA3 neurons are used to merge the recognition of (BC) . . . on CAl the current state coming directly from the entorhinal cortex EC2 and delayed information about the previous state that that we suppose comes from the Dentate Gyrus and more precisely from the Granular Cells (the GC developing a time spectrum expression of of the information coming from EC2). The CA3 representation of of the the state transition is then learned on CAl CA1 neurons and copied on prefrontal cortical neurons which learn the "anti-causal" (backpropagated) links between pairs of of transition states. These prefrontal if they are neurons also learn associative links with motivation nodes if activated simultaneously with them. Assuming the activation of of a motivation coming from the limbic system (the will to eat for instance), the model of the goal to subsequent subgoals on the prefrontal explains the propagation of cortex. When a subgoal transition can be achieved because the robot state of the transition, the associated learned action is corresponds to the first part of the trigger and allows the robot to reach a new state which is the starting point for triggering the recognition of of a new transition. When several BD) the level of of transitions are possible from a current state (like BC or BO) activation of of the prefrontal neurons associated with the different possible transitions allows the choice of of taking the shorter or the most interesting pathway from the current state to the final goal.
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Chapter 4
11989). 989). These sharp waves present some of of the characteristics, in particular in amplitude amplitude and and frequency, of of the stimuli capable of of inducing LTP. They could therefore participate in the reactivation of of cortical patterns necessary for the TM storage at L LTM at cortical level. The linkage between successive events constituting transitional states would result in a playback not of of single events but of of sub-sequences of of events.
From hippocampus to pref rontal cortex prefrontal of states and transitions forming a sequence of of events is, in This memory of the model, further ~rther integrated at at CA CA11 level, with a possible partial partial restitution there of of the "cortical" topology thanks to the direct pathways from entorhinal cortex third layer to CAL CA1. From CAl CA1 there are direct as well as indirect connections to prefrontal cortex. At this prefrontal site the long-term registration of of a sequence can be considerd as a result of of the successive of nodes which can be assimilated to cortical columns. By the very activation of orderly nature of of a sequence sequence encoded by a spatial pattern of of activation, one could assume that the best neurophysiological support for such a storage would be a unidirectional facilitation of of the synaptic weights of of a specific path path in a network architecture, as it has been implemented in Bapi and Levine ((1994). 1994). It is plausible that such an oriented unidirectional facilitation takes place in primary or secondary cortical areas. Nevertheless, the prefrontal cortex is the most plausible site for the linkage between sensory and motor I). This sequences at least at a high level of of controlled processes (Figure I11). does not preclude the possibility of of sensory-motor links at at subcortical or even lower levels as schematized by Figure I11. I . At cortical level, the execution of of a sensory-motor sequence is necessarily linked, at at least implicitly, to the completion of of a goal selected by motivation. A goal in the model corresponds in fact to a secondary goal, ii.e. .e. a situation which allows the satisfaction of of a basic drive or of of a sublimation of of this basic drive. At the executive controlled level of of the prefrontal cortex there there is clear, even if only subjective, evidence that that the goal is usually present and therefore activated at the very onset of of the sequence. Thus it can can influence the choices of of subgoals and the hierarchical unfolding of of specific endeavors to reach them. The most parsimonious implementation of of this psychophysical reality requires the instantiation of of a bidirectional facilitation of of the different pathways leading from the starting point to the goal of of a sensory-motor sequence. In this way, the activation of of a goal induces a retropropagation of of activity, similar to a priming by top-down activation from the categorial
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Figure 111. 1 . Flowchart Flowchart of of multilevel multilevel information transfers: 1) between sensory and motor areas (horizontal (horizontal connections) connections) 2) between between sensory (or motor) and associative associative areas of of increasing complexity complexity (vertical connections) 3) between planification capabilities (prefrontal cortex). internal drives and planification
nodes 976a,b). nodes in an ART ART architecture (Grossberg, 11976a, b). Yet, Yet, here the priming process concerns an entire entire sequence sequence of of events, and accordingly, accordingly, is implemented implemented according according to a gradient. This subliminal backward backward priming of of a sequence sequence in conjunction with with a bottom-up activation from subcortical structures structures such as the hippocampus helps the selection of of the best sequence of of actions to reach a specific specific goal. This process of of goal retropropagation is not solely solely efficient efficient for selecting the optimal way way for goal attainment. It also operates in deciding deciding the order of of goal goal satisfaction, satisfaction, when when several goals are
1176 76
Chapter 4
simultaneously active or in competition. As such, it implements aspects of of
performed Similar disambiguation between several hierarchy setting perf ormed by Pc. Similar possible possible sequences takes place at Hs level during the playback of of the
if the prediction of of the future event is based on several previous sequence if of just the immediate preceding one. events instead of When such a neural network is used for the control control of of a mobile robot,
different of behavior in order to select and reach a goal are exhibited by diff erent types of the robot. These These choices are are dependent on three parameters of of the system: the
strength of of the diff different of the connections relative strength erent drives, the weights of implicated in the diff different erent paths, and the required match level between perceived and memorized steps towards the goal. Any node of of the cognitive map learns leams transitions between pairs of of learned places. The level of of activation activation of of these nodes results from the addition of of bottom-up (match-related) (match-related) and top toppath length-related) activations. These combined activations down (drive and path of of the nodes can lead to aa variety of of behaviors of of the system which have e. If counterparts in real lif life. If the top-down influences are too weak, the system or the attainment of is unable to follow aa specific path ffor of a specific goal. It is susceptible susceptible to distraction distraction by any new input previously associated associated with a if the the saliency of of the the top-down input is too different behavior. Conversely, if strong, the the recognition of of aa situation could be biased biased in the the direction of of a situation corresponding to the satisf action of its goal. The initiation of such the satisfaction of The of erroneous erroneous recognitions recognitions can can be be self-reinforcing. self-reinforcing. All All these these situations situations correspond correspond to pathologies of of frontal lobe. Fronto-Hippocampal Fronto-Hippocampal Function Function and Personality Personality in humans presents three key "primitives": "primitives": I1)) A temporal function which seems to to obey some principle of of symmetry of of past and future, memory and prospective, with respect to the present. This temporal memory function is mostly based on the the capacity to evaluate and record the order of of occurrence occurrence of of event sequences (a kind of of segmentation lost
eomplementarily the capacity capacity to recognize new from in frontal patients), and complementarily familiar events (a kind of of fusion of of events lost in hippocampal patients). We have seen the importance of of the Hs in the recording of of "one exposure" events. The consequence of of the suppression suppression of of this memory function is illustrated by anterograde amnesia, i.e. the incapacity starting at a period of of life, corresponding to some time prior to the lesion, to build up a continuing
history, just just as if if the factual factual lif lifee of of a person had stopped at this moment. Yet, the Pc is also involved in this historical function, as one of avoured of the ffavoured
J.P. Banquet Banquet et al.
1177 77
cortical cortical sites for the permanent recording of of these event memories. Symmetrically, the the prospective function supposes the capacity to project in the the future future an orderly orderly sequence of of planned planned events in order to either actually perform them or merely simulate them. This planning capacity is also an hallmark of of personality. This function is as important as the previous one, and in fact intimately linked to it. Our capacity to make plans, i.e. to project our actions in the future, is narrowly dependent on a library of of past behavioral schemes and of of their consequences. As our personal history goes back in time as far as our early childhood, our ability to project our life in the future concerns more or less remote time. The range of of this prospective capability is closely linked to the strength and integration of of our personality, and supports our motivation. Mostly from neuropsychological neuropsyehological studies, the role of of the Pc in this function is well documented. Pc is essential not only for the the strict and and logical ordering of of events or actions. Furthermore, it operates in the the determination of of an hierarchy of of subgoals and actions to reach a The incapacity to forecast the consequences of of actions predetermined goal. The could be responsible, along with the neutralisation of of affective life, for the incoherent and self-destructive behavior eventually encountered in prefrontal patients. of the temporal 2) Working memory can still be considered as a part of function. Nevertheless its unifying role, and its implication in practically other function related related to personality deserves a separate account. The every other historical and prospective function, in particular, could not exist without the support of of an "extended present", i.e. a working memory. The capacity to link successive, logically related events oriented towards the performance of of a task, or the accomplishment of of a goal, is essential to the development of of WM is not not present in early childhood and and this absence explains personality. WM the non-permanence of of hidden objects in the field of the of consciousness as internal representation, and therefore the incapacity to perform delayed tasks. This representation, capacity progressively develops during during infancy, and probably supports the unfolding of of logical reasoning. This logical function is a prototypical illustration of the characteristic of of WM WM defined as both both maintenance and of the of information over an extended period of manipulation of of time. Classically, Pc is endowed with WM are temporal and and plausibly other WM capacity, but but so also are structures. Our contention is that Hs also partakes of of cortical or subcortical structures. of WM, even though an automatic aspect of though delay neurons have not been recorded there, as in different cortices. We We have proposed at at least three recorded subsidiary mechanisms that could support this function at Hs level.
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3) Emotions and motivations are arc another important facet of of personality. One could hardly contend that a robot is a person even though by its previous experience experience it can have a semblance of of history. Emotions could be viewed as of basic drives resulting from sublimation, but certainly not a suppression, of including the instinct for survival and even the instinct of of death. Motivation could result from an integration and a trade-off trade-off between the need for drive satisfaction, satisfaction, emotions, and social constraints. Motivation is usually dependent on the degree of of satisfaction satisfaction of of these needs. Here Hero also limbic system and Pc act conjointly. Amygdala is as important for emotional life lifo as hippocampus act proper is important for correlational and WM ito WM functions. Similarly, orb orbitofrontal and meAial medial Pc are essential for the integration of of drives, emotions and motivations while more cognitive infonnation information processed in dorso-Iateral dorso-lateral Pc. The suppression of of any type of of affective affr162 colour, positive or negative, in the of severely damaged prefrontal patients, as after lobotomy, induces a life of disengagement from real real life. life. This underlies the the importance of of the integrative function of of Pc, in particular, particular, between cognition and emotion. These Those different functions are not compartmentalized. In particular particular emotional charge of of events, as previously mentioned, modulates the process of memory of consolidation in the hipp hippocampo-cortical of these consolidation ocampo-cortical system. The cooperation of different functions is perhaps best perceived in the mechanism of of attainment of of goals. 4) Attainment of of goals can be considered as the uttennost uttermost expression of of the cooperation between Pc and limbic system. This function presents sensory aspects which consist of of recognition of of goals and evaluation of of the outcomes of of action, and a motor aspect made up of of the setting and execution of of motor programs. In the classical learning theory, such as proposed by Skinner ((1953), 1 953), the necessary necessary chaining of of sequences of of sensory-motor events results from associative (or operant) conditioning of of a neutral stimulus by a reinforcer. Cascades of of secondary, and higher order, conditioning could account account for linking sequences of of events together. Obviously, this process can be and has been accounted for without without the extensive implication of of prefrontal cortex as in our model (Gray 99 1 ). The main structures concerned are (Gray et ct aI., al., 11991). hippocampus, amygdala and basal ganglia. They certainly correspond to a kind of of automatic operation mode for the attainment of of goals. Nevertheless, several problems arise arise if if the the basic components of of sequences, plans, or chained actions remain limited to stimulus-response conditional associations. In particular, 948) does not obey any clearly particular, latent learning (Tolman, 11948) defined drive satisfaction, motivation or goal attainment. The conditioning process seems to work correctly for simple sequences of of actions. But, taking
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into account simply the present states in the recognition or reproduction of into of actions leads to a combinatorial explosion explosion of possible long sequences of an active representation of more more than paths, which can only be avoided by an one pair of events. Furthermore, the strength of secondary or higher higher order reinforcers seems to sharply decrease with the distance to the unconditional Sigmficant progress has been achieved by the identification of of latent stimulus. Significant learning useful to build cognitive maps, even if these maps are used of any prespecified goal. We think that the definition of goals independently of based on the satisfaction of basic (or not so basic) needs conjointly with the of more or less complex maps is a further step required to account learning of for complex behaviors. The possibility for diffusion, and in particular of goals allows the discovery of of solutions that have never retropropagation of been experienced during learning, and thus are created from new by the of creativity. This functioning mode system. This is an actual illustration of of freedom in the system, independent from requires a supplementary degree of both sensory and motor processing, but still bridging the two systems. This extra degree of of freedom is provided by Pc. The efficacy of of an algorithmic extra version of of the model for the parsimonious solution of of several problems of of robotic learning and navigation either in free space or maze constraint does of biological plausibility for the system. not automatically deliver a certificate of Nevertheless, the fact that this efficacy has been obtained thanks to a of essential neurobiological constraints, makes stringent taking into account of us confident that that the model is oriented in aa relevant direction. Conclusion Conclusion
Two different forms of supported of memory, "active" and "dormant", supported respectively by post post synaptic potentials (PSPs) and synaptic potentiation are present everywhere in the brain. The interplay between the two forms of of memory and in particular the transition and/or and/or the modulation of of one form by the other are at at the bases bases of of the different processing modes and memory capacities capacities of of the the brain. brain. Variations in the the implementation modalities and and in the the ranges of of these two two types of of memory along with variation of of connectivity give functional functional specificities to to the the different systems. This This is specially true true for Hs Hs and Cortical processing processing depends essentially on two two memory registers, and Pc. Cortical and permanent permanent LTM. LTM. The transition from the long-term to to the short STM The transition the shortSTM and term term seems to to be be direct direct and and normally encounters encounters few problems. Plausibly, at at aa gross level of of analysis analysis the the anatomical anatomical substrates substrates are are topographically identical (STM at aa fine (STM representing active active forms of of LTM). LTM). Nevertheless, at
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grainexi grained level, level, the the neurophysiological supporting supporting mechanisms must must be necessarily different different as as previously mcntionexi, mentioned, involving respectively either electrical or or durable durable structural-chemical changes. Conversely, the transition transition from from STM STM to to LTM LTM store store follows follows aa more intricate path, probably probably for for the sake of optimizing the amount amount of of information infonnation stored, but but also for securing the of storage of unique events up the unique history of of each living storage of events which built up being. Between these two two extreme ranges (STM and LTM), LTM), only minor variations from primary to associative areas can be recorded recorded at the sole cortical level, with aa tendency temporal range range of tendency to to an increase in the temporal of memory of complexity in processing performed perfonned by these areas with the increasing level of (Lii (Lil ~ et al., aI., 1992). 1 992). Prefrontal and temporal cortices arc are endowed with delay neurons that that can can bridge a a gap gap between two sensory or sensori-motor events. temporal range in the usual experimental tests of of this Nevertheless, the the tg~nporal i.e. less than 30 property remains largely largely in the domain attributed to STM, STM, i.e. secs. SCCS.
The specificity and vantage point of of Hs concerns both topographical and temporal facets. The topographical aspect of of Hs specificity as a unique compact site of convergence and output output divergence has been extensively of input convergence of Hs which emphasized. It has been credited with the correlational function function of implies some loss of of the the cortical cortical topology. This functional characteristic is corrected and and complemented by aa loose topological correspondence between hippocampal system in the longitudinal direction. This loose cortical and hippoeampal correspondence could be transfonned transformed into a dynamic learning-dependent precise mapping between hippocampal and cortical neuronal populations in order to implement the topologically specific consolidation function. function. This function could be implemented thanks to the fast-transient learning capacities present both within the hippocampus itself, and also at the interfaces between cortex and hippocampus. hippoeampus. The emphasis placed on the spatial aspects of of Hs function was detrimental to the exploration of of the no less important temporal function. This function results from the capacity of of Hs to interact very flexibly with a whole spectrum of of registers from the short-tenn short-term to the long longtenn, nnanent L TM. The unique term, and also possibly to be detached from pe permanent LTM. characteristic of of Hs would be the conjunction of of this array of of registers with a wide wide variety of of loops of of various sizes providing for an easy transition between donnant-inactive onns of dormant-inactive and re-activated fforms of memory. differences Beyond these range diff erences between cortex and Hs memory registers, differences of some more subtle diff erences could exist in the implementation modalities of active memory. Extensive research has has been conducted on delay cells cells in Pc Pe or temporal cortex, as a support for WM. Indeed, this type of of activity can bridge
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the gap between two sensory or sensory-motor events. Up to now, delay cells have not been located at the level of of the Hs. Nevertheless, the equivalent function in Hs could be performed by different mechanisms subserving slightly different functions. First, loop iterative activation could operate the punctual reenactment of of recorded patterns of of activation either during information processing in WM, of L LTM TM consolidation. or during the more lengthy process of Second, spectral timing as performed in our model by DG could also operate the the function equivalent to that of of the cortical delay neurons. This of maintaining significant information in an active state, function consists of while waiting for correlation with a new significant event. This process creates the chaining chaining of of basic components of of the sequence. The Hs functional specificity would be in multimodal fusion and correlations. Finally, event locked and and modulated theta activity could constitute, at least for some species, a basic mechanism for the maintenance of a pattern in an active state, thus making possible a cross crosS correlation with forthcoming significant patterns. These types of of complementary "hardware" constraints in the implementation of of active memory and in the range of of "donnant" "dormant" registers determine the type of of cooperation established between the two structures Hs and cortex. Further complementarity results from the direct contact of of the cortex with environment, favoring externally triggered activation. Conversely, That property Hs is the only brain structure so easily prone to autoactivation. That leads, in the pathological domain, to seizure activity. The specific import of of Pc to this processing chain seems to result from its unique position at the top of the hierarchy of of sensory-motor and and motivational streams of of information of (Figure 11). 1 1 ). Both, its independence from and its close contact with multisensory and complex motor representations or codes provides the entire extra degree of of freedom. This feature gives to the brain the system with an extra capacity for: - Recording and simulating both sensory and motor sequences independently of of their actual implementation, in relation with planning and adaptation; of goals and subgoals, and goal - Motivated hierarchical selection of attainment; and creativity. - Finally, invention and These properties properties can be considered as the highest expression of of all these capacities. -
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Chapter 4 References References
Atkinson, R. C., & Shiffrin, R. M. ((1968). memory: A proposed 1 968). Human memory: system and its control 1. T. Spence control processes. In K. W. Spence & J. (Eds.), The psychology of of learning and motivation: motivation" Advances in 1 85). New York: Academic Press. research and theory (Vol. (Vol. 2, pp. 8989-185). 1 986). Workin Working Baddeley, A. D. ((1986). g memory. Oxford: Oxford University Press. Baddeley, A. D. ((1995). 1 995). Working memory. In M. S. Gazzaniga (Ed.), The cognitive neurosciences (pp. 755-764). Cambridge, MA: MIT Press. Baddeley, A. D., & Hitch, G. J. 1. ((1974). 1 974). Working memory. In G. A. Bower (Ed.), The psychology of of learning and motivation: motivation: Advances in research and theory (Vol. (Vol. 8, pp. 47-90). New York: Academic Press. Baddeley, A. D., & Warrington, E. K. ((1970). 1 970). Amnesia and the distinction between f Verbal Learning and between long-and short-term memory. Journal oof 176-189. Behavior, 9, 176Verbal Behavior, 1 89. Banquet, 1. 1 983). Inter and intra-hemispheric J. P. ((1983). intra-hemispheric relationships relationships of the EEG during sleep in man. m a n . Electroencephalography Electroencephalography and Clinical Neurophysiology, 55, .55, 551-59. 1-59. Banquet, 1. 1 987). Probing cognitive processes through J. P., & Grossberg, S. ((1987). the structure of of event-related event-related potentials during learning: learning: An experimental and theoretical analysis. Applied Optics, 26, 493 4931-4946. 1 -4946. J. P., Renault, B., & Lesevre, Les~vre, N. (1981). Effect of of task and stimulus Banquet, 1. probability on evoked potentials. 14. potentials. Biological Psychology, Psychology, 13, 203-2 203-214. Banquet, 1. J. P., Smith, M. 1., J., & Renault, B. ((1990). top1990). Bottom-up versus top down: down: An alternative to the automatic attended dilemma? Behavioral 3, 233-234. and Brain Sciences, Sciences, 113, 233-234. Banquet, 1. (1 992a). Temporal order, timing, J. P., & Contreras-Vidal, 1. J. L. (1992a). categorization. and probability context effects on pattern recognition and categorization. In I. Aleksander 1. Taylor (Eds.), ArtifiCial Aleksander & J. Artificial neural networks 2 (pp. 1 885-1 890). Amsterdam: Elsevier. 1885-1890). Banquet, J. 1. P., & Contreras-Vidal, J. 1. L. ((1992b). 1 992b). An integrated neural network-event network-event related potentials model of temporal and probability context effects on categorization. categorization. In Proceedings o f the International of Joint Con ference on Neural Networks (pp. 54 1 -546). Hillsdale, NJ: Conference 541-546). Lawrence Erlbaum. J. P., & Contreras-Vidal, J. Banquet, 1. 1. L. ((1993a). l993a). Learning temporal contexts and priming preparation modes for pattern recognition. recognition. In Proceedings o f the International World Conf erence on Neural Networks (pp. 26(pp. 1126of Conference NJ" Lawrence Erlbaum. 1131). 3 1). Hillsdale, NJ:
JP. Banquet et al.
1183 83
J. P., & Contreras-Vidal, 1.J. L. ((1993b). timing and Banquet, 1. l 993b). Spectral timing J. Taylor (Ed.), integration of multimodal systemic processes. In 1. Artificial neural networks (pp. 350-354). Amsterdam: Elsevier. P.,. , & Contreras-Vidal, JJ.. L L.. ((1994). Banquet, JJ.. P 1 994). Medium and long-term network model of of cortex-hippocampus memory in context processing: A network. f the International Conf erence on Neural of Conference relations. Proceedings o 647-654.. Networks, 4, 647-654 J. P., Contreras-Vidal, JL., Gaussier, P., Gissler, A., & Burnod, Bumod, Y Y.. Banquet, 1. cortico-hippocampal ((1997). 1 997). The corti co-hippocampal system as a multirange temporal processor: A neural model. In R. Park & D. Levin (Eds.), Fundamentals oof f neural network modelling f or neuropsychologists. Boston: MIT for Press. S.,. , & Levine, D. S. ((1990). of Bapi, R. S 1 990). Networks modelling the involvement of the frontal lobes in learning and performance of of flexible movement f the sequences. sequences. In Proceedings of of TWl!lth Twelth Annual Conference oof Cognitive Science Society (pp. 9915-922). 1 5-922). of the frontal lobes in Bapi, R. S., & Levine, D. S. ((1994). 1 994). Modelling the role of task performance. II:: Basic structure and primacy effect. sequential task effect. Neural Networks, 7, 11167-1180. 1 67-1 1 80 . Baylis, G G.. c C.,. , & Rolls, E. T T.. (1 (1987). of neurons in the inferior 987). Responses of temporal cortex in short-term and serial recognition memory tasks. 6.5, 6614-622. Experimental Brain Research, 65, 14-622. Berger, T. W., & Thompson, R. F. (1978). ( 1 978). Neuronal plasticity in the limbic system during classical conditioning of of the rabbit rabbit nictitating membrane response. I: The hippocampus. Brain Research, 114.5, 45, 323-346. Br6bion, Brebion, J. 1. (1994). ( 1 994). Memoire de travail, comprehension de texte et vieillissement. Unpublished doctoral dissertation, University Ren6 Rene Descarte, Paris. Brown, J. tests of 1 958). Some tests of the decay theory of of immediate memory. 1. ((1958). Quarterly Journal Journal of O, 112-21. ofExperimental Psychology, 110, 2-2 1 . Bullock, D., Fiala, 1J.. C., & Grossberg, SS.. ((1994). of timed 1 994). A neural model of response learning in the cerebellum. Neural Networks, 7, 1101-1114. 1 10 1 - 1 1 1 4 . cerebellum. Neural Burgess, N., Reece, Reece, M., & O'Keefe, O'Keefe, I. 1. (1994). ( 1 994). A model of of hippocampal hippocampal function. function. Neural Neural Networks, 7, 1065-1081. 1 065-1 08 1 . Buzsaki, G. (1988). ( 1988). Polysynaptic long-term potentiation: A physiological role of the Brain of the perforant perforant path path - CA3/CA1 CA3/CA I pyramidal cell synapse. Brain Research, 4.55, 455, 192-195. 1 92-195 . Buzsaki, G. G . (1989). ( 1989). Two-stage model of of memory trace formation: A role for 'noisy' brain states. Neuroscience, NeurOSCience, 31, 551-570. 5 5 1 -570.
1184 84
Chapter 4
Cave, C. B., & Squire, 1992). Intact and long-lasting visual object Squire, L. R. ((1992). f Experimental priming in amnesic patients. Journal o of Experimental Psychology: Psychology: Learning, Memory, and Cognition, Cognition, 18, 509-520. Cressant A., Muller R., & Poucet B. ((1997). 1 997). Failure of of centrally placed objects to control the firing fields of ocampal place cells. f of hipp hippocampal cells. Journal oof Neuroscience, 17. 1 7. Neuroscience, Darke, S. ((1988). 1 988). Anxiety and working memory capacity. Cognition Cognition and 145-154. 54. Emotion, 2, 145-1 Dehaene, S., Changeux, 1. 1 987). Neural networks that J. P., & Nadal, 1. J. P. ((1987). Proceedings oof f the National learn temporal sequences sequences by selection. selection. Proceedings Natwnal 1. Academy o fScience of 2727-2731. of of the USA, USA, 84, 2727-273 Denham, M 996) A model M.. 1., J., & Boitano, 1. J. (1 (1996)A model of of the interaction interaction between between
pref rontal cortex, prefrontal cortex, septum septum and the hippocampal hippocampal system system in the learning and recall oof f goal-directed sensory-motor sensory-motor behaviours. behaviours. Technical Report NRG-96-0 1 , University of NRG-96-01, of Plymouth School School of Computing. Drachman, D. A., & Arbib, M. ((1966). Drachrnan, 1 966). Memory and the hippocampal complex. Archives of 1. of Neurology, Neurology, 15, 52-6 52-61. Eichenbaum, H o, T., & Cohen, 1994). Two functional H.,, Ott Otto, Cohen, N N.. 1J.. ((1994). components of the hippocampal memory system. system. Behavioral Behavioral and Brain Science, 117, 449-518. 7, 449-5 18. Science, arousal: Cognition Cognition and per performance. M.. W W.. ((1982) Eysenck, M 1 982) Attention and arousal: formance. New York: Springer-Verlag. Funahashi, SS.,. , Bruce, C., & Goldrnan-Rakic, Goldman-Rakic, P. W. (1 (1989). Funahashi, 989). Mnemonic coding of of visual space by neurons in the monkey's dorsolateral dorsolateral prefrontal cortex revealed by an oculomotor delayed-response task. Journal o f of Neurophysiology, 61, 33 331-349. 1 -349. Neurophysiology, J. M., & Alexander, G. E. ((1971). relatext to short shortFuster, 1. 1 971). Neuron activity related term memory. 73, 652-654. memory. Science, Science, 1173, Fuster, 1J.. M. ((1980). 1 980). The pref rontal cortex: prefrontal cortex: Anatomy, Anatomy, physiology and neuropsychology o f the f rontal lobe. lobe . New York: Raven Press. of frontal J. M. ((1995). cerebral cortex. cortex. Cambridge, MA: MIT Fuster, 1. 1 995). Memory in the cerebral Press. Fuster, 1. J. M., & Jervey, J. 1. P. ((1981). 198 1). Inferotemporal neurons distinguish and Science, 2212, behaviorally relevant features of visual stimuli. stimuli. Science, retain behaviorally 1 2 52555. 5. architectures for autonomous Gaussier, P., & Zrehen, S. ((1994a). 1 994a). Complex architectures agents. In P. Gaussier & J. D.. Nicoud (Eds.), (Eds.), PerAc PerAc (pp. (pp. 278-290). 1. D Lausanne: IEEE Press. ,
J.P. Banquet et al. JP.
1185 85
S.. ((1994b). Gaussier, P., & Zrehen, S 1 994b). Navigating with an animal brain :: A neural network for landmark identification and navigation. In Proceedings of Vehicles (pp. 399-404), Paris. of Intelligent Vehicles Zmhen, S. ((1995). Gaussier, P., & Zrehen, 1 995). PerAc: A neural architecture to control Systems, 116, 291-320. artificial animals. Robotics and Autonomous Systems, 6, 29 1-320. A., & Banquet, 1. J. P. ((1996). Gaussier, P., Joulain, C., Revel, A, 1 996). Are shaping techniques the correct answer for the control of of an autonomous robot ? of UKACC UKACC International Conf Conference '96, erence on Control '96, In Proceedings of IEEE. C.,. , Revel, A A. Zrehen, S, & Banquet, 1. J. P. ((1997a). Gaussier, P., Joulain, c l 997a). Autonomous robot learning: What can we take for free? To appear in Proceedings of of IEEE conference on ISlE, ISIE, IEEE. C.,. , Zrehen, S. Banquet, 1. J. P, & Revel, A A. ((1997b). Gaussier, P., Joulain, c l 997b). Visual navigation in an open environment without map. To appear in Proceedings of erence. of IROS Conf Conference. Glanzer, M., & Amitz, A. A R. ((1966). 1 966). Two storage mechanisms in free recall. Behavior, 5, 35 351-360. Journal oof f Verbal Learning and Verbal Behavior, 1 -360. Goldman-Rakic, P. W. ((1988). 1 988). Topography of of cognition: Parallel distributed networks in primate association cortex. Annual Review Review oof fNeuroscience, 111, 1 , 1137-156. 37- 1 56. Goldman-Rakic, P. W. ((1994). 1 994). Working memory dysfunction in schizophrenia. Journal o f Neuropsychiatry of Neuropsychmtry and Clinical Neuroscience, 6, 348-357. J., & Lynch, G. ((1994). Granger, R., Whitson, J., Larson, 1., 1 994). Non-Hebbian of long-term potentiation enable high-capacity encoding of properties of fScience oof f temporal sequences. Proceedings of of the National Nanonal Academy oof the USA, USA, 91 91,, 110104-10108. 0 1 04- 1 0 1 08 . Gray, C 1 989). Oscillatory C.. M., Konig, KOnig, P., Engel, A A.. K K.,. , & Singer, W. ((1989). responses in cat visual cortex exhibit intercolumnar synchronization which reflect global stimulus properties. Nature, Nature, 338, 338, 334-337. A., Feldon, J., Rawlins, 1. J. N. P., Hemsley, D. R., & Smith, A A. D. Gray, 1J.. A, ((1991). 1 99 1 ). The neuropsychology of of schizophrenia. Behavioral and Brain. Sciences, 114, 4, 11-20. -20. Sciences, Grossberg, S. ((1976a). l976a). Adaptive pattern classification and universal recoding. I: Parallel development and coding of of neural feature detectors. detectors. receding. Cybernetics, 23, 12 121-134. Biological CybernetiCS, 1 - 1 34 . S.. ((1976b). Grossberg, S l976b). Adaptive pattern classification and universal receding. recoding. II: Feed-back, expectation, olfaction, and illusions. Biological Cybernetics, 23, 1187-202. 87-202. CybernetiCS,
1186 86
Chapter 4
Grossberg, S 1 978). A theory of S.. ((1978). of human memory: memory: Self-organization and performance of sensory-motor codes, codes, maps, and plans. In R. Rosen & F. Snell (Eds.), (Eds.), Progress in theoretical theoreacal biology (Vol. (Vol. 5, pp. 233-374). New York: Academic Press. Grossberg, S., & Merrill, 1 992). A neural network model MerriU, J. ((1992). model of of adaptively timed reinforcement ocampal dynamics. reinforcement learning and hipp hippocampal dynamics. Cognitive Cognitive Brain Research, 11,, 3-38. Guigon, E., Dorizzi, B., Bumod, Y., & Schultz, 1 995). Neural correlates Schultz, W. ((1995). of learning in the prefrontal cortex of the monkey: monkey: A predictive predictive model. model. Cerebral Cortex, 35-147. Cortex, 2, 1135-147. Halgren, E., Squires, Halgrcn, Squires, N. K., Wilson, C. L. Rohrbaugh, J. W., Babb, T. L., & CrandaU, P. H. (1980). Endogenous potentials generated in the human Crandall, ( 1980). Endogenous hippocampal formation and amygdala by infrequent infrequent events. events. SCience, Science, 210, 803-805 803-805.. Hasselmo, M. E., & Schnell, 1994). Laminar selectivity SchneU, E. ((1994). selectivity of the cholinergic suppression suppression of of synaptic transmission in rat hippocampal region region CA Il:: Computational modeling f modeling and brain slice slice physiology. physiology. Journal oof Neuroscience, 114, 4, 3898-3914. 1994). The localization of general memory Horel, J. A. ((1994). memory functions. functions. and Brain Sciences, 117, Behavioral and 7, 482. Howarth, E., & Eysenck, H. J. ((1968). paired1 968). Extraversion, arousal, and paired recall. Journal oof Research in Personality, 3, f Experimental Research associate recall. 1 14-1 1 6. ll4-116. Ivry, R 1 989). Timing functions R. B., & Keele, Keele, S. W. ((1989). functions of the cerebellum. Journal of 34- 1 50. of Cognitive Neurosciences, 11,, 1134-150. James, W. ((1890). 1 890). The prinCiples fpsychology. New York: principles oof York: Holt. R.,, Jr. ((1995). P300: Evidence Evidence from Johnson, R 1 995). On the neural generators of the P300: temporal lobeetomy lobectomy patients. Electroencephalography Electroencephalography and Clinical 10-129. Neurophysiology, 44 (Supplement), (Supplement), 1110-129. R., Jr., & Donchin E. ((1982). Sequential expectancies expectancies and decision Johnson, R, 1982). Sequential environment: An An electrophysiological approach, making in a changing environment: Psychophysiology, 19, 183-199. 1 83-199. S.. G. ((1993). connections: A speculative Jones, R. R S 1 993). Entorhinal-hippocampal connections: view of 6, 58-64. TINS, 116, of their function. function. TINS, Smith, E. E., Koeppe, Koeppe, R R. A., Awh, Awh, E., Minoshima, Minoshima, SS.,., & Mintun, Jonides, J., Smith, M. A. ((1993). revealed by PET. 1 993). Spatial working memory in humans as revealed Nature, 363, 363, 623-625 623-625..
J.P. JP. Banquet et al.
1187 87
D.. SS.,. , & Park, R. ((1992). Levine, D 1 992). Frontal lesion effects on verbal fluency in a of Conference network model. Proceedings o f the International Joint Conf erence on Neural Networks, 2, 39-44. J., & Kaufman, Lii, Z. L., Williamson, S. 1., Kaufinan, L. ((1992). 1 992). Human auditory primary and association cortex have differing lifetimes for activation 572, 236-241. traces. Brain Research, 5 72, 236-24 1. A. P. Smith & D D.. M. Jones (Eds.), Matthews, G. ((1992). 1 992). Extraversion. In A of human per performance. Vol. 3: State and trait (pp. 9595-126). Handbook of formance. Vol. 1 26). London: Academic Press. A. M., Puce, A, A., Nobre, A A. C. Bloch, G., Hyder, F., McCarthy, G., Blamire, A Goldman-Rakic, P. W., & Shulman, R. ((1994). 1 994). Functional magnetic imaging of of human prefrontal cortex activation during a spatial working memory task. Proceedings o of f the National Academy oof f Science of of the USA, 91, 8690-8694. Miller, E. K., Li, L., & Desimone, R. ((1993). of neurons in anterior 1 993). Activity of of inferior temporal cortex during a short-term memory task. Journal of 1460-1478. Neuroscience, 113, 3, 14601478 . Neuroscience, Desimone, R. ((1994). Miller, E. K., & Desimone, 1 994). Parallel neuronal mechanisms for Science, 263, 520-522. short-term memory. Science, Milner, B. ((1966). 1 966). Amnesia following operation on the temporal lobes. In C. W. M. Whitty & O. L. Zangwill (Eds.), Amnesia. London: Butterworths. S.,. , & Teuber, H.-L. ((1968). of the Milner, B., Corkin, S 1 968). Further analysis of of H H.. M. hippocampal amnesia syndrome: 14-year follow-up study of Neuropsychologia, 1 5-234. Neuropsychologia, 6, 2215-234. 1 982). Some cognitive effects of of frontal lobe lesions in man. Milner, B. ((1982). of the Royal SOCiety, Society, London, B, 298, 2211Philosophical Transactions of 1 1226. of pictorial short shortMiyashita, Y., & Chang, H. S. ((1988). 1 988). Neuronal correlate of 331,, 68-70. term memory in the primate temporal cortex. Nature, 331 Niki, of prefrontal units during right and left iki, H. ((1974). 1 974). Differential activity of N delayed response trials. Brain Research, Research, 70, 346-349. Naatanen, 1 982). Processing Negativity: An evoked-potential reflection of N~i/it~en, R. ((1982). of selective attention. Psychological Bulletin, 92, 605-640. J., & Nadel, L. ((1978). O'Keefe, 1., 1 978). The hippocampus as a cognitive map. Oxford: Oxford University Press. Olton, D. S., Becker, 1. 1 979). Hippocampus, J. T., & Handelmann, G. E. ((1979). Science, 2, 3313-365. and memory. Behavioral and Brain Science, space and 13-365 .
1188 88
Chapter 4
Owen, A. M., Morns, Morris, R. G., Sahakian, Sahakian, B.
1., J., Polkey, C. E., & Robbins,
1 996). Double T. W. ((1996). Double dissociations dissociations of of memory and executive functions ollowing lobe excisions, temporal lobe in working working memory tasks ffollowing 19, 11597597excisions or amygdalo-hippocampectomy in man. Brain, Brain, 1119, 11615. 615. Paulescu, E 1 993). The neural E.,. , Frith, C C.. D D.,. , & Frankoviak, R R.. SS.. 1J.. ((1993). Nature, correlates of the verbal component of working memory. of of Nature, 362, 362, 342-345. 342-345. Peterson, 1 959). Short-term retention of Peterson, L. R., & Peterson, Peterson, M. 1. J. ((1959). of individual /Experimental verbal items. Journal o of Experimental Psychology, Psychology, 58, 193-198. Petrides, 1 993). Dissociation Petrides, M., Alivisatos, B B.,. , Evans, A. C., & Meyer, E. ((1993). of human mid-dorsolateral from posterior dorsolateral frontal cortex in of /the National Academy / memory processing. Proceedings Proceedings 0of Academy 0/ of Science Science 0of USA, 90, 873-877. the USA, effect Rolls, E. T., Baylis, G. C., Hasselmo, M. E., & Nalwa, V. ((1989). 1 989). The eff ect of learning on the face selective responses responses of of neurons in the cortex in the of superior temporal sulcus in the monkey. monkey. Experimental Experimental Brain Brain Research, Research, 76, 153-164. Rolls, E. T., & O'Mara, S S.. M., (1995) View-responsive View-responsive neurons in the hippoeampal complex. Hippocampus, Hippoeampus, 5, 409-424. 409-424. primate hippocampal Ruchkin, D. S . , Sutton, S . , Mahaff ey, D., & Glaser, 1. ((1986). 1 986). Terminal Ruchkin, S., S., Mahaffey, J. CNV in the absence of of a motor response. Electroencephalography Electroencephalography and Clinical Neurophysiology, Neurophysiology, 63, 445-463 445-463.. Ruchkin, 1991). EventRuehkin, D. SS.,. , Johnson, R., Jr., Canoune, H., & Ritter, W. ((1991). related potentials during arithmetic and mental rotation. Electroencephalography Electroencephalography and Clinical Neurophysiology, Neurophysiology, 79, 79, 473-487. Ruehkin, D. S., Johnson, R., Jr., Grafinan, Grafman, 1., J., Canoune, H., & Ritter, W. Ruchkin, Distinctions and similarities among working memory processes: ((1992). 1 992). Distinctions An event-related event-related potentials study. Cognitive Cognitive Brain Brain Research, Research, 11,, 53-66. Schacter, D. L., Chu, C. -Y., & Ochsner, K. N. ( 1 993). Sehacter, Oehsner, (1993). Implicit memory: A /Neuroscience, 116, 6, 1159-82. 59-82. selective review. review. Annual Review oofNeuroscience, Scoville, 1 957). Loss of Seoville, W. B., & Milner, MiMer, B B.. ((1957). of recent memory after bilateral hippocampal hippoeampal lesions. Journal 0/ of Neurology, Neurology, Neurosurgery, Neurosurgery, and 1 -2 1 . Neuropsychiatry, Neuropsyehiatry, 20, 111-21. Shiffrin, R. M., & Schneider, W. ((1977). 1 977). Controlled and automatic inf ormation processing. information processing. II: Perceptual leaming, learning, automatic attending and a general theory. Psychological Psychological ReView, Review, 84, 1127-90. 27-90.
J.P. Banquet et al.
1189 89
Sidman, M 1. P. ((1968). 1 968). Some additional M.,. , Stoddard, L. T., & Mohr, J. quantitative observations of of immediate memory in a patient with bilateral hippocampal lesion. Neuropsychologia, 6, 245-54. Singer, W. ((1983). 1 983). Neuronal activity as a shaping factor in the self selforganization of of neuron assemblies. In E. Basar, H. Flohr, H. Haken, & Synergetics of the brain. brain. New York: Springer SpringerA. J. 1. Mandell (Eds.), S ynergetics of Verlag. Skinner, F. (1953). ( 1 953). Science and human behavior. behavior. New York: McMillan. Solomon, P 1 980). A time and a place for everything? Temporal P.. R R. ((1980). processing views of of hippocampal function with special reference to attention. PhYSiological 1. Physiological Psychology, 8, 254-6 254-61. Squire, L. R R.,, Ojemann, 1J.. G., Miezin, FF.. M., Petersen, SS.. E., Vdeen, T. 0 O.,. , of the hippocampus in normal & Raichle, M. E. ((1992). 1 992). Activation of humans: A functional anatomical study of f the of memory. Proceedings oof 837-4 1 . National Academy o fScience oof f the USA, of USA, 89, 11837-41. Tolman, E 1 948). Cognitive maps in rats and men. The Psychological E.. C C.. ((1948). ReView, 55, 189-208 1 89-208 Review, Zrehen., S. ((1995). 1 995). Elements o f brain design f or autonomous agents. of for agents. Unpublished PhD thesis, Swiss Federal Institute of of Technology, Lausanne. Zrehen, S., & Gaussier P 1 997). A neural architecture f or motivated P.. ((1997). for landmark-based landmark-based navigation. navigation. ETIS internal report (submitted for publication) publication).. Author Author Note Note
This research was supported by INSERM, NATO and DGAIDRET DGA/DRET 911470/A000/DRET/DS/DR. Grant # 9 1 1 470/AOOOIDRETIDSIDR
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P A R T II PART II PERSPECTIVES FROM FROM EMOTION EMOTION RESEARCH RESEARCH PERSPECTIVES
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Cognitive Science Science Perspectives Perspectives on Personality Personality and and Emotion Emotion Cognitive
- G. G. Matthews Matthews(Editor) (Editor)
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1997 V. 1997 Elsevier Elsevier Science Science B. B.V.
CHAPTER S5 CHAPTER Affective Influence in Perception:
Some Implications of the
Amplification Model Amplification Ki tayama Shinobu Kitayama Will affectively charged stimuli be perceived any differently from affectively neutral ones? Will affect inherent in a focal stimulus disrupt affectiveiy perceptual processing? Or will it facilitate the latter so that affective stimuli field? After years of waxing and waning (e.g., stand out in the perceptual field? Dixon, 11980; 980; Erdelyi, 11974, 974, 11985), 985), the influence of stimulus affect on immediate perception remains as a topic of considerable significance. Mechanisms underlying immediate conscious perception are both logically (e.g.,, Helmholtz, 11884) (e.g. 884) and empirically (e.g., Marcel, 11983a) 983a) preconscious. if it can be shown that that the immediate perception of of a stimulus stimulus is indeed indeext Thus, if influenced by affect inherent in the stimulus itself, we will have identified a window through which to observe what Kihlstrom ((1990) 1 990) has called the unconscious. psychological unconscious. . Championed by Freud and his successors (e.g., Freud, 11895/i966), 895/1 966), the functional structure of of the unconscious, especially the one involving affect, has turned out to be one of of the most formidable problems in psychology, often evading scientific scrutiny. However, with rigorous experimental experimental evading methodologies and theoretical tools now available at hand, recent investigations detectionless processing (e.g., Bargh, Bond, Lombardi, & investigations on detectionless Tota, 1986; 1 986; Carr & Dagenbach, 1990; 1 990; Greenwald, Klinger, & Lui, 11989; 989; Marcel, 1983a,b; Niedenthal, 1990; 1 983a,b; Niedenthal, 1 990; Shevrin, 11990), 990), automatic processing Schneider, 11977), (e.g., Uleman & Bargh, 1989; 1 989; Shiffrin & Schneider, 977), and implicit memory (e.g., Schacter, 1989) significant steps toward more 1 989) have taken significant comprehensive comprehensive and accurate understanding of of the unconscious. unconscious. And a new theoretical framework has begun to emerge (e.g., Erdelyi, 1985; 1985; Lewicki, 1986; 1 986; Kihlstrom, Kihlstrom, 1990; 1 990; Marcel, 1983b; 1 983b; Rumelhart, 1989; 1 989; Zajonc, 1980). 1 980). The present paper seeks to contribute to this literature. The literature. We will examine whether and and how the the perceptibility perceptibility of of a faintly shown stimulus can vary with the affective significance significance of of the stimulus stimulus itself. itself. The goal is to identify distinctly affective phenomena in a perceptual identification identification task, and integrate them with current current theories of of cognition, affect, and attention, understanding other forms of attention, thereby laying a solid foundation for understanding of
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"hot cognitions" (Abelson, 11963). 963). Should perceptibility depend on affective significance, significance, that would suggest that affect can be preconsciously elicited by an impinging stimulus and, moreover, that the elicited affect influences subsequent processing required to develop a conscious percept. Accordingly, of revealing the nature of of a preconscious the present work has the potential of interaction between affect and cognition. The current approach emphasizes a non-associative, energizing consequence consequence of of affect (cf. (of. Osgood, 1962) and analyzes how stimulus affect influences the perception of of the stimulus itself. Specifically, it will be proposed that affect evoked through preattentive processing amplifies attentive processing, thereby either enhancing or impairing the emerging conscious percept. This work therefore will supplement a presently dominant, 986; Bower, 11981; 98 1 ; largely associative approach to affect (e.g., Bargh et aI., al., 11986; 986; Greenwald et aI., Fazio, Sanbonmatsu, Powell, & Kardes, 11986; al., 1989; 1989; !sen, Isen, Shalker, Clark, & Karp, 11978; 978; Johnson & Tversky, 11984; 984; Lang, 11084; 084; 1 990; Zajonc, 989), which has proved Niedenthal, 1990; Zajone, Murphy, & Ingelhart, 11989), powerful in analyzing how affect of of one stimulus (prime) can bias the perception of of another (target). It is typically assumed in this literature that the activation of of affective affective information, caused by the prime, can can spread to related of associative memory, thus biasing the information within a network of of the target. perception of
historicalperspective: "New Look" and its a aftermath A historical perspective: The "New ftermath The general issue of of affect-cognition interaction in perception can can be back to the literature of traced back of "New Look" in perception in the 11950s 950s (Bruner, 11957). It was then proposed that perception depends not only on 957). exogenous factors, but also on endogenous factors including perceptual set, 1955, for a expectation, motivation, personality, and affect (see e.g., Allport, 1955, review). In a pioneering experiment on affect and perception, McGinnies MeGinnies of affectively affcctivdy charged words. He briefly ((1949) 1 949) examined the perception of flashed either a taboo word or a neutral word, and found recognition threshold to be considerably higher for the taboo word than for the neutral word. He maintained that this resulted from perceptual processes; affect ("anxiety") evoked by a taboo word recruited the process of psychological ("anxiety") defense, which blocked further perceptual processing, thus diminishing the that affect conscious percept (see also Blum, 11954). 954). Other studies observed that sometimes enhanced perception (e.g., Postman, Bronson, & Gropper, 11953). 953).
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then suggested the the operation of The proponents of perceptual defense then perceptual vigilance. Critics quickly pointed out an apparent paradox involved in McGinnies's assertion that one can feel "anxiety" without knowing the identity of the stimulus. They maintained that the finding could be explained most parsimoniously by post-perceptual response biases such as reluctance or 1958: see readiness to report a taboo word (Eriksen, 1963; Goldiamond, 1958: Erdelyi, 11974; 974; Dixon, 11980 980 for reviews). There are some methods, however, that allow one to examine perceptual accuracy independent of post-perceptual response bias. For instance, subjects may be asked to choose the item shown of equivalently valenced words. Research employing this and from a pair of other similar procedures has demonstrated that the affective tone of a (e.g.,, Bootzin & Natsoulas, stimulus does influence accuracy in perception (e.g. 11965; 965; Dorfman, 11967). 967). Thus, McGinnies was correct in this regard. Further, to be reviewed below, recent cognitive research has strongly suggested that of a number of of preconscious conscious perception is the end product of operations. Hence, McGinnies's notion that affect can be induced by an impinging stimulus before the stimulus is consciously identified is no longer considered paradoxical (Erdelyi, 1974). of defense/vigilance mediate the Nevertheless, his theory that processes of of affect in perception has faced serious challenges. Neither he nor his effects of of defense or vigilance. Hence, no successors articulated the mechanisms of prediction about of affect is possible. Further, about the direction of of the influence of of a stimulus evidence suggests that that affect can influence the perceptibility of whether its valence is positive or negative (Broadbent & Gregory, 1967; 1 967; Kitayama, 1990, 1 990, 1991). 1 99 1 ). In retrospect, then, it would seem that McGinnies was correct in that that the the effect he observed was, at at least in part, part, perceptual. However, his hypothesis of of defense/vigilance as an underlying mechanism is increasingly suspect.
The present approach current paper presents aa model of of affect-cognition interaction The current designed to to account account for perceptual perceptual influence of of affect. We We reconsider this old rubric of of defense and vigilance, from problem, traditionally studied under the rubric by aa number of of theoretical and and methodological aa new perspective afforded by innovations innovations accomplished accomplished in the the interim. Informed by by current theories of of cognition, affect, and and attention, the the model hypothesizes that that affect induced through through preattentive processing of of an impinging stimulus amplifies
1 96 196
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subsequent attentive processing. We We will review past past studies studies on preattentive subsequent processing, attention, and affect, which together form attention, and affect, fonn the empirical and and theoretical theoretical basis basis for the proposed model. It It will be shown shown that that the model coherent account account for for an an anomalous pattern pattern of of past past findings findings in the the provides aa coherent defense/vigilance model has guided guided more more recent defense/vigilance literature. Further, the model Evidence for the model will be reviewed, empirical investigations on the topic. Evidence and two new experiments will be reported. reported. Finally, broader implications of of for future research the proposed model will be discussed and directions for explored. explored. The present The present attempt to to test implications implications of of the model strategically just one form fonn of of perception: perception: word perception. perception. Studying focuses on just Studying this relatively simple case should make it possible to exert exert precise experimental control and, thus, to test the model in aa more rigorous fashion. Further, in the domain of of word perception, there is considerable overlap between research on affect of past research on aff affect affect and research on cognition. Much of ect and perception, dating back to McGinnies's original contribution, was done with words as stimuli, stimuli, and word perception has been extensively studied in current 989). cognitive psychology (see e.g., Posner, 11989).
The of Affect-Cognition Interaction The Amplification Model of
A model A model of ect-cognition interaction in early perceptual processing of aff affect-cognition (Kitayama,
11990, 990, 11991; 99 1 ; Kitayama & Howard, 11994) 994) is illustrated in Figure
11.. The basic tenet of ect induced of the model is that aff affect induceA through preattentive processing
of of
an
impinging stimulus amplifies amplifies subsequent attentive
processing, thereby either enhancing or impairing the conscious percept of of the stimulus. Unlike the def ense/vigilance hypothesis, this model assumes that an defense/vigilance influence ect in perception results from interaction among three influence of of aff affect component
processes
commonly implicated implicateA in ordinary processes of of
perception, i.e., preattentive processing, attentive processing, and aff ect. affect.
Preattentive processing. According to current cognitive theories of perceptual processing of of lexical lexieal materials such as words (e.g., McClelland & Rumelhart, 198 1 ; Posner, 11978) 978) and 1981; and certain graphic stimuli such as faces Damasio, Tranel & Damasio, (Bauer, 11984; 984; Damasio, D amas io, & Van Hoesen, 11982; 982; Tranel 11985), 985), an impinging stimulus is initially processed automatically without any involvement of of attention. Through preattentive processing, the graphic and emantic perceptual codes that that correspond to the stimulus can be possibly the ssemantic
1197 97
S. Kitayama S. ii
)"
Preattentive processing
,11111
i
i|1 ii iii
I Engagement of of attention in a relevant perceptual code
i
i
|l
Activation Activation of of alTective affective circuits and subsequent of amplification of attentive processing
Attentive
processing
Conscious
percept
Response out (i.e., reading out features, relevant reatures, selecting responses, etc.)
affectFigure 1. 1 . A schematic illustration of of the amplification model of of affect cognition interaction in early perceptual processing. The model is composed of, as its major components, preattentive processing, attentive processing, and of attentive processing, and activation of of affect and subsequent amplification of components are highlighted in bold squares. response. These components
activated before the conscious percept of of the stimulus is developed. A number of semantic priming paradigm have shown that that semantic of recent studies with aa semantic information (and, by implication, graphic information as well) can be activated by aa word that undcteetable in that is pattern masked and thus made undetectable consciousness consciousness (e.g., Allport, 1977; 1 977; Balota, 1983; Carr, McCaulcy, McCauley, Spcrber, Sperber, & Parmclee, ct aI., al., 11989; Parmelee, 1982; 1 982; Carr Carr & Dagcnbach, Dagenbach, 1990; 1 990; Grccnwald Greenwald et 989; Fowler, Wolford, Wolford, Sladc, Slade, Tassinary, Tassinary, 1981, 1 98 1 ; Marcel, 1983a, 1 983a, 1983b). 1 983b). This
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to the the hypothesis that attention, in the sense of of literature lends strong support to of processing mechanisms selectively and serially applied to a confined a set of spatial sp~/tial or semantic region, is not not necessary for the activation of of meanings of of an an impinging lexical lexieal stimulus, let alone the activation of of its shape. The The foregoing conclusion might seem at at odds with cognitive research on traditionally assumed that preattentive vision is very crude vision, which has traditionally (Egeth, 1977; Neisser, 1967). 1 967). For example, Sagi and colleagues (Braun & Sagi, 11990; 990; Sagi & Julesz, 11985) 985) have proposed that preattentive vision that a field contains a discrepancy, but does not enable one allows one to note that object. Similarly, for Treisman ((1988), to identify any object. 1988), preattentive vision is of a field (such as "green" or "square"), sufficient to identify separate features of but not any object defined by a conjunction of of more than two features (such as "green square"). However, the vision literature does not necessarily contradict contradict the above evidence for the preattentive activation of of shape and of a perceptual object. The two lines of of research research typically use meaning of conspicuously different stimulus materials. On the one hand, the vision literature literature has focused primarily on simple and to a large extent, arbitrary arbitrary graphic stimuli (e.g., colors, lines, simple geometric figures) that have no obvious, unique meanings. On the other hand, the studies attesting to the presence of of preattentive activation of of shape and meaning employ meaningful stimuli that are routinely encountered in everyday life, viz., mostly lexical materials such as words, but occasionally certain complex and realistic graphic graphic materials materials such such as as faces. faces. It goes without saying that some kind of of preexisting processing structures structures such as the ones exemplified in connectionist networks are required for preattentive activation of of shape or meaning to take place (McClelland & Rumelhart, 11981). 98 1). These structures will develop gradually from everyday These structures encounter with relevant stimuli (e.g., LaBerge & Samuels, 11973; 973; Shiffrin & Schneider, 11977) 977) although those those for certain phylogenically significant stimuli 985). Thus, the such as faces may be be hard-wired through through evolution (Field, 11985). extent of of preattentive processing can vary vary from very crude (as in the case of of arbitrary arbitrary and/or meaningless stimuli for which no ready-made processing structure structure is available) to very thorough and sophisticated (as in the case of of meaningfulllexical meaningful/lexical materials for which elaborate processing structures have been established and, thus are readily available). A series of of studies by Shevrin and his colleagues provided some evidence (Shevrin & Fritzler, 1968; 97 1). They found that evoked potential to a Shevrin, Smith, & Fritzler, 11971). subliminally shown picture is significantly more intense if if the the picture is than if if it is meaningless. Further, the the meaningfulness of of the meaningful than
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picture systematically influenced subsequent free associations associations as well, suggesting that semantic activation was actually caused by the subliminally shown picture if if it was meaningful. All in all, then, once a meaningful stimulus commonly encountered in daily life such as a word is presented, it will be processed automatically, and daily corresponding perceptual perceptual codes are activated. Although this activation is preconscious preconscious and quite weak especially if the stimulus is impoverished, it has been shown to be sufficient sufficient for affect associated with the stimulus to be O 985). Perhaps, the activated codes summon elicited covertly (Ohman, ( hman, 11985). affective circuits of of the brain located in the limbic or subcortical regions. LeDoux 1 987, 11989) 989) has reviewed neuroanatomical evidence suggesting LeDoux ((1987, numerous neuronal connections between between sensory processing areas of of the brain and the limbic regions. Furthermore, Furthermore, several studies (e.g., Corteen & Wood, Lazarus & McCleary, 11951; 11972; 972; Lazarus 95 1 ; Zajonc, 11962) 962) have shown a reliable autonomic response to a subliminal affective stimulus. Although this literature has been criticized on methodological grounds (e.g., Merikle, 11982; 982; literature Holender, 11986), 986), more recent research with a strict criterion for awareness has also shown that affect can can be elicited by undetectable stimuli (e.g., has Dawson & Schell, 11982; 982; Greenwald 989; Niedenthal, 11990; 990; Tassinary Greenwald et aI al.,., 11989; Tassinary et aI., 984; see also Kunst-Wilson 980). al., 11984; Kunst-Wilson & Zajonc, 11980). Attentive processing. It is reasonable, then, to postulate that affect turn influences subsequent attentive elicited via preattentive processing in tum of processing, which is generally believed necessary for conscious perception of the stimulus (Neely, 11977; 977; Posner & Snyder, 11975). 975). Unlike preattentive processing, attentive processing is selective, limited solely to a perceptual code to which attention has been directed. Thus, once a relevant perceptual activated by an impinging code has been automatically and preconsciously activated operations need be performed. First, attention is shifted and stimulus, two operations directed to the relevant code and, second, once so directed, attention furthers directed the code's processing (cf. Posner, 11980). 980). Through attentive processing, a more more elaborate elaborate perceptual perceptual and, perhaps, semantic image of of the stimulus is developed, which corresponds to the immediate conscious percept of of the stimulus. Finally, the conscious percept may be scanned and its more specific features may be read out out to control subsequent action (Allport, 11989). 989). to grasp the the proposed relationship between preattentive In order to of attention as a spotlight is processing and attentive processing, a metaphor of useful (Crick, 11984; LaBerge, 1983; Moser, 1988; 984; 1 983; 1 988; Posner, 11980). 980). According preattentive processing activates activates the relevant one of of to this metaphor, preattentive numerous perceptual perceptual codes in long term memory. This activation itself,
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to produce produce conscious conscious perception. For For the latter to to however, is not not enough to the latter occur, The spotlight must first first be occur, an an attentional attentional spotlight spotlight must must be deployed. The spotlight must shifted to the relevant to illuminate the the code. This to the relevant code and and then used to This illuminating of of the the relevant relevant information information amounts to to additional processing processing illuminating performed on on the latter latter and, as as such, is thought to to enable conscious conscious performed perception of perception of the stimulus. In this this formulation, attentive attentive processing is distinct preattentive processing processing in its selective nature. Whereas from preattentive Whereas preattentive preattentive activation can can occur simultaneously at at multiple loci (e.g., letter, graphic, activation semantic are valid as well as, especially when semantic codes that that are when the the stimulus is impoverished, those that that are invalid; see below), attentive processing can be focused on only one of Another implication of of the current current formulation of them. Another that attention and consciousness consciousness are distinct even though there is is that substantial overlap between them. Generally, preattentive substantial preattentive (nonselective) processing processing takes place without conscious awareness, whereas whereas attentive processing is mostly conscious. However, attentive (selective) (selective) processing processing required to produce conscious awareness is necessarily preconscIous. preconscious. Amplification by a ffect. One widely postulated property of affect. of affect is arousal, or its ability to amplify a variety of of psychological functions. In his pioneering work, Tomkins ((1962, 1 962, 11980) 980) has proposed that various basic can be described in terms of of differential emotions such as joy and anger can of amplification of of a nervous system. Although Tomkins's analysis patterns of of affect has may no longer seem feasible, arousal or an intensity dimension of of everyday vocabularies of of been shown to be essential in defining a variety of emotion and concepts in general, and suggested to be universal across of affect cultures (Osgood, 11962; 962; Russell, 11980). 980). Another major dimension of identified in this literature is pleasantness. From the very beginning, it has been widely recognized that an of affect can can have a variety of of consequences on amplifying property of drive, this assumption is central psychological processes. Under the guise of drive, to a behavioral theory of learning proposed by Hull, Spence, and Taylor in the 1950s (e.g., Spence, 11956). 956). It also is at the core of the Yerkes-Dodson modem extensions by H. law (Yerkes & Dodson, 11908), 908), as well as its modern to analysis of of personality dimensions of of extraversion! extraversion/ Eysenck ((1967) 1 967) to introversion and impulsivity. It has also proved applicable to social (Zajone, 11965). facilitation (Zajonc, 965). More recently, Revelle, Humphreys, and their colleagues (Humphreys & Revelle, 11984; 984; Revelle & Loftus, 1990; see also M. Eysenck, 11976) 976) have elaborated on some specific consequences of arousal on different stages of memory processes.
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As As has has been been pointed pointed out out by by aa number number of of researchers, researchers, the the notion notion of of generic, uni-dimensional uni-dimensional arousal arousal involving all aspects aspects of of the the sympathetic sympathetic nervous system system and and those those of of cortical processes processes seems too too simplistic simplistic (e.g., Lacey Lacey & & Lacey, Lacey, 1968). 1968) . Nevertheless, Nevertheless, the hypothesis that that affect affect amplifies amplifies aspects of of psychological psychological processes processes remains both both reasonable reasonable (Lindsley, some aspects 1 95 1 ) and and empirically empirically viable viable (Stembach, (Sternbach, 1968). 1 968). And, as such, it has the 1951) potential potential of of clarifying clarifying ways in which which affect affect influences influences cognition. Extrapolating Extrapolating from this this literature, literature, it may may be hypothesized that that affect affect elicited through through preattentive preattentive processing processing amplifies attentive attentive processing. This simple hypothesis which affect with an an hypothesis suggests both both (i) the the conditions conditions in which affect associated associated with impinging word perception of of the the word word itself itself and impinging word is most most likely to to enhance the perception (ii) those in which the the affect affect is most likely to impair the perception. perception. Enhancement and ofperception by affect. First First and and most Enhancement and impairment of by affect. if attention attention has accurately accurately been directed to a relevant perceptual obvious, if perceptual code (i.e., the one corresponding to an impinging word), affect and ensuing amplification of attention enhance the veridical perception of amplification of attention should enhance of the impinging stimulus. In this case, affective stimuli will be more accurately than neutral stimuli (affective enhancement). perceived than Suppose, that a stimulus is presented in an extremely Suppose, however, that impoverished manner, as is often the case in perceptual perceptual identification identification perceptual code will not experiments. Under these conditions, the relevant relevant perceptual receive strong activation. As we have reviewed earlier, this weak activation seems sufficient to produce a degree of of affect, thus amplifying subsequent attentive processing. Nevertheless, the weak activation will cause considerable difficulty in computing exactly which perceptual code corresponds to the impinging stimulus, especially because residual activations past experience are likely to remain for many other irrelevant codes caused by past of this difficulty in 983; Higgins & Bargh, 11987). 987). Because of (e.g., Jacoby, 11983; locating the relevant code, attention may be misdirected to an irrelevant code. locating Under Under these these conditions, affect produced through preattentive processing will amplify attentive processing processing that has been directed, accidentally, to invalid perceptual information and, as a consequence, it will impair an emerging conscious percept. In this case, affective stimuli will be less accurately perceived than neutral stimuli (affective impairment). In terms of of the spotlight metaphor introduced earlier, preattentive of an affective stimulus activates the corresponding code and, as a processing of consequence, evokes associated affect, which in tum turn increases the of the attentional spotlight. However, because the activation of illumination of the relevant code is weak, perhaps no stronger than residual activations
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of remaining in irrelevant codes, the spotlight is likely to be locked on to one of the irrelevant codes, accidentally illuminating the latter and, thus, causing an of valid perception: impairment of In sum, the present present model (the amplification model hereafter) predicts that that affective impairment should be most likely to occur when the presentation presentation of of a target target word is extremely impoverished. It further implies that the impairment effect should disappear disappear or even reverse itself once the difficulty in locating the relevant code is alleviated, that is, when the activation of of the relevant code is increased relative to the activation of of other irrelevant codes. Under these conditions, attention will be successfully directed to the relevant perceptual code and, as a consequence, affect and subsequent amplification of of attentive processing processing should enhance the emerging percept. The general prediction tested, therefore, can be be stated in terms of of a ffoctive enhancement (higher accuracy for affective than for neutral stimuli affective within a given experimental condition) or affe ctive impairment (lower affective accuracy for affective than for neutral neutral stimuli within a given experimental condition): Any variable that increases the activation of of a relevant perceptual of other, irrelevant codes will code relative to the activation of increase the likelihood o fa ffective enhancement and/or of affective and~or decrease the likelihood of ffective impairment. of a affective impairment. Evaluation Criteria of of the Amplification Model
Two points must be made explicit before setting out to test test implications Two of the amplification model. First, the model predicts that stimulus affect of of response bias either should influence perceptual accuracy independently of for or against reporting an affective stimulus. Earlier studies in the defense literature were criticized largely because they used recognition and vigilance literature threshold as a dependent variable. With this measure it is extremely difficult to separate perceptual accuracy from response bias (Eriksen, 11963; 963; Goldiamond, 11958). 958). As noted above, however, there are some methods, most that allow notably forced choice between two affectively equivalent stimuli, that one to control for response bias (Natsoulas, 11965). 965). In the following, we will draw primarily on those studies that have adequately controlled for response draw bias. of attentive processing in a preattentively Second, the engagement of perceptual code is only one of of several distinct operations that that can activated perceptual
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(see Figure 1). 1). The model contribute to overall perceptual identification (see therefore assumes that any variable that can enhance attentional engagement may also either improve or impair other operations, and thus either increase of stimulus or decrease the overall perceptual identification independently of
a ffect. affect. To illustrate, consider stimulus complexity, which is likely to have opposing effects on preattentive processing and response selection. To begin of features it with, the more complex a stimulus is, the greater the number of contains. Because each of these features will serve as an additional constraint in preattentive processing, as stimulus complexity increases, the corresponding perceptual code may be more unequivocally activated. According to the amplification model, under these conditions the percept will be more accurate for affective stimuli than for neutral stimuli (affective enhancement). In addition, however, once the percept has been developed, the of the respondent will subsequently have to make an overt response. Most of studies to be reviewed or reported in the current paper examine accuracy in a the respondent supposedly scans scans and and compares the forced choice, whereby the percept with available alternatives. Because complex stimuli contain more features to be compared and matched in the choice, stimulus complexity should make response selection more difficult, thereby leading to poorer overall performance. In short, stimulus complexity is likely to increase the likelihood of of affective enhancement, while while simultaneously decreasing choice performance. Once these two effects of of stimulus complexity are super-imposed on on each performance for affectively neutral neutral stimuli to decline other, one will observe performance with stimulus complexity. Relative Relative to this base base line defined by the the neutral stimuli, performance performance for comparable comparable affective stimuli should improve. Yet, this improvement due to stimulus affect may or may not compensate compensate for the decline of of overall performance due to choice difficulty. This means that performance for affective stimuli may or may not actually improve with The crucial prediction of of the amplification model in this stimulus complexity. The case then, then, is that decline of of performance performance as aa function function of of stimulus case that aa decline complexity is less for than for neutral stimuli. complexity for affective stimuli than In general, general, it is safe assume that any variable variable that can enhance safe to to assume that any that can attentional engagement (e.g., stimulus complexity) may attentional may also either improve or impair other operations impair other operations (e.g., response selection), and and thus thus either increase or or decrease decrease overall overall performance performance independently of of stimulus affect. Accordingly, the amplification model must the must be be evaluated evaluated in terms of of its ability to to predict either affective enhancement enhancement or or impairment, impairment, rather rather than than its ability to to predict either
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of perf performance affective an absolute increase or decrease of onnance for aff ective or neutral stimuli with the manipulated variable. With these evaluation criteria at hand, we now tum turn to a review of of extant extant studies pertinent to some predictions of of the amplification model.
Empirical evidence pnmmg has amply Expectation and word requency. Research on priming word f frequency. demonstrated that that when individuals are led to expect the identity of of a target,
& Posner & Snyder, 11975). 11987; 987; Neely, 11977; 977; Posner 975). It can be hypothesized,
the corresponding perceptual code receives extra activation (e.g., Higgins Bargh,
theref ore, that therefore, that in a perceptual perceptual identification task, the difficulty of of locating a
relevant perceptual code is relieved by a correct expectation about the target affective affective word. Thus, aff ective enhancement will be more likely and aff ective impainnent impairment less likely in the presence of of a valid expectation than in its absence (Kitayama,
11990). 990). Initial support for the prediction was uncovered in
a review of ense and vigilance. Because most of the literature of of perceptual def defense studies in this literature examined recognition threshold and f ailed to control failed f or response bias, their status as evidence f or the current analysis is uncertain for for (Eriksen,
11963; 963; Goldiamond, 11958; 958; see e.g., Dixon, 11980; 980; Erdelyi, 11974, 974, ffor or
two experiments which manipulated expectation reviews). Nevertheless, two 11954; 954; Lacey, Lewinger, & Adamson, 11953). 953). In these studies, when there was no expectation,
tended to support the amplification model (Freeman,
for affective than ffor recognition threshold was higher f or aff ective words than or neutral words (affective impairment); but when an expectation about the identity of of a target (aff ective impainnent); for affective that was provided, recognition threshold f or aff ective words was lower than that for (affective al.,, 11953, 953, ffor or a for neutral ones (aff ective enhancement; see also Postman et aI. similar result). Additional evidence f or the present analysis can be f ound in more recent, for found methodologically more sophisticated studies that assess perceptual accuracy of response bias (either readiness or reluctance to report independently of 1 990) located nine such affective rather than neutral stimuli). Kitayama ((1990) of these studies (Bootzin & Natsoulas, 11965; studies (see Table 1). In most of 965; Dorfman, 1967; 1967; Dorfinan, Dorfman, Grossberg, & Broadbent & Gregory, 11967; 967; Dorfinan, Kroeker, 11965), the dependent variable was correct response rate, with 965), the for appropriate adjustments made f or response bias. Two additional studies used different 1972) diff erent methods to minimize response bias. Chapman and Feather ((1972) examined the ability to detect (rather than identify) a novel graphic stimulus using a signal detection procedure. They assigned an affective tone to the using
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stimulus by classically conditioning an electric shock to it. Sales and Haber Haber ((1968) 1 968) minimized response bias by having subjects report ers of report individual lett letters of word rather than than the word word itself, and and analyzed the number number of of letters a flashed word correctly reported.
Table Table 11.. Comparison of of nine experiments experiments in which effects of of response bias were 990). were minimized (adapted (adapted from Kitayama, 11990). Experiment
Expectation Expectation
Outcome Outcome
Chapman 1 972) Chapman & & Feather Feather ((1972) Dorf man ((1967) 1 967) Dorfman Dorfman et al. ( 1965) 1 965) Dorfman Wertheimer ((1958) 1 958) Mathews Mathews & & Wertheimer Minard 1 965) Minard ((1965) Van Egeren ((1968) 1 968) Bootzin & 1 965) Bootzin & Natsoulas Natsoulas ((1965) Broadbent 1 967) . Broadbent & & Gregory Gregory((1967) Sales & 1 968) Sales & Harber Harber ((1968)
Clear Clear Clear Vague Vague Vague Vague Vague Absent Absent Absent
Enhancement Enhancement Enhancement Enhancement Enhancement Enhancement Inconsistent11 Inconsistent Inconsistent22 Inconsistent
effect No effect Impairment Impairment Impairment Impairment Impairment Impairment
11 Significant Significant impairment impairment effect effect was found found for "high-hysteria" "high-hysteria" subjects, subjects, but no effect effect was obtained for "high-psychasthenia" "high-psychasthenia"subjects. subjects. obtained 2 ound ffor or males, 2 Significant Significant impairment impairment effect effect was ffound males, whereas whereas significant significant enhancement enhancement effect effect was found found for females. females.
Among these these nine studies, three obtained affective enhancement Among (Chapman & Heather, 11972; Dorfman, 11967; Dorfman et aI., al., 11965). 972; Dorfinan, 967; Dorfinan 965). (Chapman Interestingly, all the three studies inadvertently used a procedure that assured that that the subjects had a a clear expectation expectation about about the target stimulus. In two experiments by Dorfinan Dorfman subjects were shown the target target word experiments word plus a nontarget word word immediately before the the target was actually flashed. They were nontarget that one of of the pre-target words would be flashed on that that trial. Chapman told that and 1 972) had and Feather Feather ((1972) had subjects keep in mind the target target stimulus while seeing a visual display. Thus, both both methods provided subjects with a clear a other experiments implanted subjects with vague expectation. Some other expectations by familiarizing them with experimental stimuli at at the beginning of the session. In these studies there was no systematic pattern. Mathews and of Mathews Minard ((1965) of affect to depend Wertheimer ((1958) 1 958) and Minard 1 965) found the influence of
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Van Egeren (1968) failed to on certain individual difference variables, and Van of affect on perceptual accuracy. The remaining did not find any influence of of the above procedures and reported affective impairment (Bootzin use any of & Natsoulas, 1965; Broadbent & Gregory, 1967; Sales & Haber, 1968). Kitayama (1990) subsequently conducted an experiment in which expectation expectation was systematically manipulated. In this experiment word frequency was also varied. It was hypothesized that as word frequency increased, the valid perceptual code would be more strongly activated and, as a consequence, affective impairment would become less likely and affective of a target enhancement more likely. Subjects were exposed to a 25 ms flash of word. They then chose the target word from a word pair. In half the trials, this word pair was given before the flash to create an expectation. Further, on some trials no target target was presented although subjects were led to believe that it was actually shown. Analysis of of the data from these trials revealed no response bias for or against reporting affective stimuli, so choice hit rate was used as a measure of of perceptual accuracy. Consistent with the amplification model, both expectation and word frequency increased the likelihood of of affective enhancement and decreased the likelihood of of affective impairment. As can 0-50 can be seen in Figure 2, when words were low in frequency (1 (10-50 occurrences per per million) and and an expectation was absent, affective words were identified significantly less accurately than neutral ones (affective impairment). This pattern, however, was reversed to show a reliable enhancement effect when high-frequency words (more than 100 occurrences per million) were examined and and an expectation was present. Finally, the of affect in the remammg remaining two conditions (high influence of frequency/unexpected and low frequency/expected) was no greater greater than than that (1990) 990) study thus generally in the former two conditions. The Kitayama (1 confirmed the predictions of of the amplification model. Nevertheless, it was not totally conclusive. First, it tested only a small number of of words (12 in total). Second, it found the predicted effect of of expectation only for high-frequency words. There was no such effect for low-frequency words: as can be seen in Figure 2, affective affeetive impairment of of evidently equal strength was observed regardless of of expectation. Stimulus contrast. The The amplification model states that affective impairment is most likely when the presentation of of a target is extremely impoverished. Another recent set of of experiments with a larger number of of stimulus words ((126 126 in total, ranging from 8 to 65 per million in frequency of of occurrence) has provided support (Kitayama, 1991). In Study 11,, a target target was
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of target affectivity, Figure 2. Perceptual accuracy (hit rate) as a function of expectation (adapted (adapted from Kitayama, 11990). word frequency, and expectation 990). = .72 ft-L) if-L) in a black background (.67 ft ilpresented in dark gray (luminance = L), so the contrast between the target and the background was extremely low. As predicted, a significant affective impairment effect was obtained - that is, of affective words was less accurate than the identification the identification of of neutral words. In Study 2, however, the contrast contrast was increased so that that the of if-L). Under the latter condition, there target was shown in lighter gray (.75 ft-L). was no influence of of affect. Exposure time. time. According to the amplification model, a relevant perceptual code needs to be located quite early in the processing bef before ore attention is directed. It then follows that effects of of exposure times should range in which they are manipulated. When relatively depend crucially on the range long exposure times are manipulated, it will be only late in the processing that of the relevant code. Thus, these variations begin to increase the activation of of extremely impoverished stimulus contrast, attention under the conditions of should be misdirected to an irrelevant code regardless of of the exposure times. of Kitayama ((1991) In Study 11 of 1 99 1 ) described above, three relatively long exposure times ((100, 1 00, 150, 1 50, and 200 ms) were tested. As predicted, affective of evidently equal magnitude was observed in all the three impairment of
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conditions. By contrast, when relatively short exposure times exposure time conditions. are tested, an increase in exposure times should increase the activation of of a relevant code early in processing, thus mitigating the difficulty in locating the code. Thus, an increase in relatively short exposure times should result in a lesser likelihood of of affective impainnent impairment and a greater likelihood of of affective enhancement. Kitayama ((1989) 1989) showed that affective impainnent impairment observed with a 25 ms exposure (Kitayama, · 11990) 990) could disappear with a 40 ms exposure. Word length. Virtually every past past study in this area area has examined examinexl only relatively short words (less than 6 letters long). However, current cognitive models of 9 8 1 ) suggest of word recognition (e.g., McClelland McCleUand & Rumelhart, 11981) that that word length may systematically change the likelihood of of affective affectivr enhancement and impainnent. impairment. According to these models, the initial, preattentive preattentivr processing of of a visual input proceeds process in parallel, leading to simultaneous activation of of parts of of the entire input. Currently, there is no what defines functional parts of of a word. Drawing on consensus about exactly what some prominent models of of word recognition (e.g., McClelland McCleUand & Rumelhart, 11981), 98 1 ), we assume here that "word-parts" correspond fairly closely to individual letters, although, for the purposes of of the present argument, however, it makes little difference whether the units are letters or something else. turn impose Once individual letters have been activated, they in tum of the input, pennitting permitting only a significant constraints on the likely identity of limited number of of English words as reasonable candidates for the input. All else being equal, as word length increases, a greater number number of of letters should be activated and the letter-level infonnation information should more strongly constrain of a four fourthe word-level identity. To illustrate, imagine that the processing of half of of the constituent letters, say, "LxxE." letter word successfully activated half There are several 4-letter candidate words that meet these constraints, say, if half of of the "LIVE," "LIKE," "LOVE," "LAKE," and so on. In contrast, if constituent letters are activated in a word that is 110 0 letters long, say, "AxTRAxxlxx," there will be very few 110-letter "AxTRAxxIxx," O-letter words other than "ATTRACTIVE" "ATTRACTIVE" that that fully meet the constraints. Thus, as word length increases, the perceptual code corresponding to an impinging word will be more unequivocally and uniquely activated and attention will be more likely to be directed to the valid perceptual code. As word length increases, there of affective enhancement as opposed to affective should be a greater chance of impainnent. impairment.
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In a recent experiment, both word affect and word length were systematically manipulated (Study 11 in Kitayama, 11991). 991). Words comparable to Kitayama's ((1990) 1990) low-frequency words were presented with an extremely contrast and no expectation expectation was provided - a condition diminished stimulus contrast the amplification model predicts to be highly conducive to affective impairment. A reliable affective impairment effect was observed. However, this impairment effect was also observed for longer words, thus failing to confirm the model's prediction. Perhaps, with the extremely diminished stimulus contrast contrast examined examined in this study, there was only marginal activation of a relevant perceptual code regardless of of word length. It would seem of reasonable that that an increase increase in word length could contribute to the unique and of a relevant perceptual code only when there was unequivocal activation of enough stimulus input. In the experiments to be reported below, therefore, presented with greater stimulus contrast. The perceptibility of of targets were presented the target target was then reduced by presenting a masking stimulus immediately after the disappearance disappearance of of the target. Under these conditions of of backward pattern masking, an increase in word length was predicted to decrease the likelihood of of affective impairment and to increase the likelihood of of affective enhancement. Valence o f aff ect. One potential divergence between the of affect. defense/vigilance hypothesis and the amplification model concerns the effect of of the valence (positive or negative) of of affect. Unlike the amplification model, the defense/vigilance hypothesis has never been explicit enough to advance clear-cut predictions for affective enhancement and impairment. Yet, it would seem to predict that that the processing is either prohibited (the defense) or enhanced (the vigilance) if if and only if if "anxiety" (or, equivalently, enhanced "psychodynamic conflict") is evoked. Since "anxiety" is more closely linked with negative than positive affect, the perceptual influence of of affect should be obtained primarily with negative affective words. In contrast, the obtained amplification model is non-committal in this regard. It is possible that of an attention is amplified once the significance or the interest value of perceptual impinging stimulus has been detected. If this is the case, the perceptual not depend on the valence (positive or negative) of influence of of affect need not of the affect; for the significance or interest value can be signalled by any any affect either positive or negative, that examined accuracy accuracy in perception In virtually all the past studies that of response bias for or against affective stimuli, only taboo independently of Kitayama, 11990, (mostly affectively negative) words were used (see Kitayama, 990, for a The exclusive use of of taboo taboo words words was justified justified on the supposition review). The
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that Freudian Freudian defense defense should should mediate mediate the the perceptual perceptual influence influence of of affect affect (e.g., (e.g., that Blum, 1 954; Erdelyi, Erdelyi, 1974; 1 974; McGinnies, McGinnies, 1949), 1 949), but but ironically made made it Blum, 1954, to test test the the supposition supposition itself. itself. A A few few studies, studies, however, however, examined examined impossible to impossible both positive positive and and negative negative affective affective words words while while controlling controlling for for response response bias. both It was was found found that that the the perceptual perceptual influence of of affect affect was was mostly identical identical It whether affect affect was was positive or or negative negative (Broadbent (Broadbent & & Gregory, 1968; 1 968; whether Kitayama, 1990, 1991). This evidence is consistent with the amplification Kitayama, 1 990, 1 991). This with but raises raises some doubt doubt on on the the defense/vigilance hypothesis. model, but
The present experiments attempt to to further of the model, In an attempt further test test the implications of the amplification model, for the two experiments were two were conducted. As noted above, initial support for of past studies that model was obtained obtained in a review of that differed in the extent to to which aa valid expectation was available available to to subjects. It was hypothesized that a valid expectation should activate the relevant code prior to the presentation presentation of a target target stimulus, thus alleviating the difficulty in locating of locating the code in identification. The expectation, therefore, should increase the perceptual identification. likelihood of of affective enhancement and decrease the likelihood likelihood of of affective manipulated impairment. So far, however, only a few studies have actually manipulated expectation (Fr (Freeman, ct al., 1953; Kitayama, 11990; ct expectation eeman, 11954; 954; Laccy Lacey et 990; Postman et of the 953). Although these studies supported the predictions of al., 11953). Freeman Laccy et ct al. amplification model, they were not conclusive. Fr eeman ((1954), 1954), Lacey (1953), and Postman et al. ((1953) 1953) measured recognition threshold, so for their findings. fmdings. Although response response bias response bias may in part account f or their of was controlled in the Kitayama ((1990) 1990) experiment, only a small number of of the ffmdings. words ((12 1 2 in total) were tested, leaving open the generality of mdings. of expectation was further examined in the present Thus, the effects of experiments. to current models of of Another variable tested was word length. According to (e.g.,, McClelland & Rumelhart, Rumclhart, 198 1981), an increase in word word processing (e.g. 1), an length should impose impose more constraints on the the identity identity of of the the word word and, and, thus, thus, length unequivocal activation activation of of the the relevant relevant perceptual perceptual code. code. Thus, Thus, conduce to unequivocal affective affcctive enhancement should should be be more likely likely and and impairment impairment less less likely likely with an increase of 1991) studied of word word length. Only Kitayama ((1991) studied the the effect effect of of this variable, and failed to to find find any evidence. To To test test the the conjecture conjecture that that this variable, failure was was due due to to the the highly highly degraded degraded input, input, the the current current series series of of experiments experiments failure employed aa pattern-masking pattern-masking procedure, procedure, whereby whereby aa target target stimulus stimulus was was employed presented with aa relatively relatively high high stimulus stimulus contrast, contrast, but but was was immediately immediately presented
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word frequency was held followed by a pattern mask. In these experiments word constant at the level comparable to the low-frequency condition of the 1 990) experiment (the level also examined in the Kitayama ((1991) 1 99 1 ) Kitayama ((1990) study) to maximize the comparability across different studies. Finally, both positive and negative affective words were tested to determine whether the of affect depends on its valence. perceptual influence of Predictions. We predicted that both expectation and word length would of affective enhancement and decrease the likelihood of increase the likelihood of affective impairment. Thus, our first two predictions were: ((1) 1 ) Affective impairment will be most likely when short words are used and no expectation is provided. (2) Affective enhancement will be most likely when long words are tested and an expectation is provided.
It was not certain exactly how expectation and word length would jointly operate. According to the amplification model, in order for these variables to of affective enhancement or have additive impacts on the likelihood of impairment, two conditions must be met. First, expectation and word length must additively increase the activation of of a target perceptual code relative to of other irrelevant codes. Second, the relative increase of of the the activation of activation of of the target code must linearly increase the likelihood of of affective enhancement (or decrease the likelihood of of affective impairment). Neither enhancement assumption has been explicitly tested in the literature. Thus, no a priori priori prediction could be made made regarding whether the two variables would interact or have additive effects. Thus, our third prediction was:
The influence of two conditions (i.e., short (3) The of affect in the remaining two words/expected, long words/unexpected) will fall somewhere between the above two extremes (short words/unexpected, and long words/expected); in other of affect in the former conditions greater other words, the influence of conditions will be no greater than than that that in the latter. In addition to to improve attentional engagement to their hypothesized role to and thereby to to increase the likelihood of of affective enhancement and to reduce and that of of affective impairment, there are some suggestions in the literature that that that and word length may have some extraneous effects on forced both expectation and choice performance. To demonstrated that To begin with, it has been demonstrated that explicit
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formulation formulation of of aa "hypothesis" "hypothesis" or or expectation expectation can can impair impair perceptual perceptual identification identification (e.g., Bruner Bruner & & Potter, Potter, 1964; 1 964; Lawrence Lawrence & & Coles, 1954). 1 954). Perhaps, Perhaps, aa clear clear expectation expectation may may direct direct one's attention attention to to only one one type type of of information that that is potentially potentially available available (e.g., orthographic, orthographic, phonemic, information perceptual identification). identification). Information on the ignored semantic, etc., in perceptual ignored may then then be be unavailable unavailable in response selection, leading poorer dimensions may leading to poorer performance Note that performance in the the presence presence of of an expectation than than in its absence. Note that this restrictive restrictive effect effect of of expectation expectation should occur occur equally regardless regardless of of this stimulus stimulus affect. affect. Similarly, word word length is also likely to to depreciate depreciate overall performance independently of of stimulus stimulus affect. In aa forced choice task performance task tested in present research, research, the the respondent respondent scans the percept and compares the present the percept compares it with alternatives. The The longer the word, the greater greater the number of of features features available alternatives. (e.g., individual letters) letters) that that must must be be matched matched and, therefore, the more difficult response selection should be. Furthermore, as we shall show below difficult 2 1 9), this difficulty in response selection for longer (p. 219), longer words words may be exacerbated by the fact that of long words exacerbated by that any any given pair of words tend tend to share aa greater a pair pair of greater number of of common letters than a of short words. All in all, as word length increases, response word response selection will be more difficult and, further, effect of of word length on response response selection will occur of word this effect occur regardless regardless of word affect. In sum, we hypothesized that affect. that both both expectation and word word length length would would performance in perceptual depreciate overall overall performance perceptual identification, while simultaneously of affective simultaneously increasing the the likelihood of affeetive enhancement and decrease that ective impairment. Taken together, we predicted a general that of of aff affeetive decline of of perceptual perceptual identification with expectation and word length, and further expected this decline of of performance to be significantly less ffor or aff ective words than affective than for neutral words. Notice that that this this latter prediction prediction amounts amounts to the three predictions stated stated above. Experiment Experiment 11
Method Overview and subjects. There were 128 trials, divided into two blocks, diff ering in the length of differing of the words words (long (long versus short). The order of of the two blocks was counter-balanced over subjects. On each trial subjects were ms flash of of either an affectively positive, negative, or neutral exposed to a 33 ms target word, immediately followed by a pattern mask (a string of "&"s of of the target word and same length as the word). They were then presented with the target of the same length, and asked to choose the an equivalently valenced word of
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one presented. Whereas word length was a within-subject variable, expectation was a between-subject variable. Thus, for half the subjects the two choices were presented immediately before the target was flashed to create an expectation, but for the other half there was no such expectation. undergraduates at at the University of of Oregon (both males and and females) Seventy undergraduates participated in the experiment to partially fulfill their introductory psychology course requirements. All the subjects claimed to be a native English speaker. Materials. The one-hundred twenty-eight words used in the present experiment are listed in Appendix A. There were an approximately equal of affectively positive, negative, and neutral words. Thirty three number of undergraduates who did not participate in the present experiment were asked of each word ((11 = = unpleasant, 5 = = pleasant). The to judge the affective quality of = 4.3, s = = .23) than the neutral positive words were rated as more positive (M = . 1 , s = .2 1 ), which in tum words (M = 33.1, .21), turn were rated to be more positive than half of of the words of of each affect the negative words (M = 11.8, . 8, s = ..30). 30). About half type were long (more than nine letters long) and half half were short (fewer than of occurrence ranged from 8 to 65 appearances appearances six letters long). Frequency of per million words, as determined by Kucera and Francis's ((1967) 1 967) norms. The of occurrence for the six word categories (3 affective types mean frequencies of • 2 length types) were practically identical (varying from 27 to 37 x occurrences per million). This frequency range roughly corresponded to to the of the Kitayama ((1990) low-frequency condition of 1 990) experiment. Sixty-four pairs were formed between with equivalent valences and lengths, as shown were between words words with nontarget once, Each word served as target target once and as nontarget in Appendix A. Each resulting in 128 experimental trials. The order of of these these trials were randomized randomized upperwithin each block for each each subject. All stimulus words words were shown in upper case letters. The experiment was Equipment. The was controlled by an AMDEK-286 AMDEK-286 personal computer presented on an an computer with an an AMDEK-132 AMDEK-1 32 VGA VGA adapter. Stimuli were presented AMDEK-732 and contrast AMDEK-732 color color graphic graphic monitor. Both the brightness and contrast of of the screen were kept maximal. To To the monitor was attached a translucent translucent tube. The inner the tube 23.5 cm, and and the the length, 60 60 cm. The inner contour contour of of the tube was was 17 1 7 cm •x 23.5 One the tube tube was the monitor, and subjects One end end of of the was fitted fitted to to the monitor, and subjects watched watched the the screen screen through the other end. Target presented at through the other Target words words were were presented at the the center center of of the the monitor. monitor. The The height of of the the words was was approximately approximately 4 mm. The The length of of aa five-letter word word was was 12 1 2 mm, and and that that of of aa nine-letter word word was was 23 mm, mm, resulting angle of the short resulting in the the visual visual angle of approximately approximately 1.15 1 . 15°~ and and 2.06 2.06°~ for the short and the and the long words, words, respectively. The The experiment experiment was was controlled controlled by by the the MEL MEL (Micro Experimental Experimental Laboratory) Laboratory) system developed by by Schneider (1988). ( 1 988). =
=
=
=
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This system synchronizes the the presentation of of stimuli with the refresh cycle of of This the monitor, enabling accurate accurate control control over the exposure durations. The experiment experiment was conducted under under normal room illumination. With the VGA facility, it is possible possible to create 62 shades of of gray in addition to white and background (luminance = .67 ft-L [foot-Lambert]), a target black. In a black background was shown in the 23rd shade"of 1 .02 ft-L). This level of shade"of gray ((1.02 of stimulus contrast was considerably higher than the level employed in the Kitayama ((1991) 1 99 1) study ((15th 1 5th shade of of gray; .72 ft-L). It-L). A fixation point, a mask, an expectation, and response response choices were shown in the 32nd shade of of gray i~-L). (2.65 ft-L). Procedure. Subjects were tested individually. Upon arrival, they were randomly assigned to one of of the four conditions representing representing the presence or the absence of of an expectation expectation and the order of of the short-word and the long longword blocks. They were instructed instructed to look into the tube, and to place their left and right fight index fingers respectively respectively on the Z and the M keys of of the computer keyboard. The subjects were told that that the experiment was concerned with perception of of briefly shown words. After the procedure was described described (see perception below), they were given the following instruction: liAs "As I mentioned to you, words are are presented very briefly. We want to know how accurately accurately people can recognize a word under such impoverished r ~ u r e is set up so that you cannot perfectly viewing conditions. So, the pprocedure of the word. see the word, yet you can still recognize some fragments or parts of may be able able to recognize a letter or two, or even a a small For instance, you may part of of some letter. Or you may may be able to recognize recognize the contour of of the word. part partial information has has proved very useful in performing this task. I will Such partial explain to you exactly what can be learned le~meA from this sort of of experiments later. explain can For the time being, even though though you you might occasionally feel that that you are For merely guessing, don't be discouraged discouraged or disturbed by this. Instead, try to pick up as many physical cues from the flash as possible. In this way your responses will be most accurate. Even when you don't think that that you have enough information to make a choice, give us your very best guess. Please never use any intuition or gut-feeling in making judgment; once you do this, never performance better than chance. From past research research we know rmance cannot be better your perfo that that it is essential that that you try to pick up physical features such as letter if you are to perform this task at a better-than better-thansegments and overall contour if chance level. level."II
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In the expectation-present condition, each trial started with the fight of the center of the screen presentation of a pair of words with one to the right see, the pair was replaced by a fixation point and the other to the left. After 2 sec, center of of the screen. The subjects in this condition condition had been told that at the center of the two words would be a target in the upcoming trial and that it was Was one of important to keep the pair in mind in order to perform well in the task. In the expectation-absent condition the trial began with the presentation of of a fixation expectation-absent expectation conditions were otherwise identical. Thus, in both point. The two expectation conditions, when the subject simultaneously pressed the two response keys, point disappeared disappeared and, 200 ms later, a target word was presented the fixation point for 33 ms, immediately followed by a pattern mask. A sequence of "&"s of served as a mask. The mask was presented the same length as the target word serven -dr-. -- NonDepressed-Valm:e NonDcprcssed-Valence Identificatim Idenfifr.ation -- ....
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4 . Simulated lexical decision and valence identification identification tasks" tasks: always Figure 4. ruminating.
which did not feedback network which not engage in the the excessive affective-semantic feedback Specifically, the network which engaged in fccdback feedback was delayed at loop. Specifically, at both positive positive and and negative negative words words on the valence identification identification recognizing both occurred because the network network which engaged in an an analog of of task. This delay occurred throughout its its training effectively effectively used used its ruminative ruminative periods to to rumination throughout its representation representation of of incoming incoming stimuli to to be be close close to to representations representations it it modify its had already already learned. learned. Thus, Thus, it it did did not not learn learn the the valence valence of of new new incoming incoming had stimuli as as strongly as as the the original original nctwork. network. Inspection Inspection of of the the network's network's stimuli weights weights revealed revealed that that nearly nearly all all weights weights throughout throughout the the semantic semantic and and affcctive affective loop were were lower lower in in the the network network which which did did cngage engage in in feedback feedback than than in in the the loop network which which did did not. not. Potentially, Potentially, this this result result could could be be used used to to suggest suggest that that nctwork individuals who who are are particularly particularly slow slow at at recognizing recognizing the the valence valence of of stimuli stimuli individuals might might be be ruminating ruminating on on their their perceptions. perceptions. Hence, Hence, they they may may bc be vulnerable vulnerable to to
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Were future research to validate this speculation, simple depression. Were information processing tests such as a valence identification task might be infonnation used to assess for vulnerability to depression. by ruminating - a protective f factor. of Coping by actor. To simulate the effects of ruminative coping, brought on by a loss experience, the network was made to engage in 10 cycles of of feedback between the affective and semantic representations only during the overtraining ovortraining on a negative stimulus. This of the lexical decision network's performance on the computational analogs of and valence identification tasks is illustrated in Figure 5. When the network was overtrained on a negative stimulus, with 110 0 of feedback feexlbaek between the affective and semantic layers, its performance cycles of on the valence identification task was less biased than the network which had been overtrained on a negative stimulus but incurred no extra feedback between the affective and semantic representations (Figure 3). The reason that the overtraining did not affect the network's valence identification a great deal is that feedback feeAbaek between the network's affective affeetive and semantic minimizeA the effects of of noise, and thus, the network components effectively minimized did not need to adjust its weights a great deal upon overtraining. In this way, the computational analog of of rumination prevented the network from learning the negative stimulus in a way which would distort its information processing great deal. Thus, feedback analogous to rumination protected the network a great from infonnation information processing biases characteristic of of depressed individuals. Practically, this result suggests that rumination might be an effective of coping with the possibly distorted affect common after a loss way of experience! if you think about experience! Simply put, if about how to reasonably interpret your life experiences immediately after a loss with respect to what you have learned in the past, rather than with respect to just just the current loss, you may be prevented from acquiring the negative infonnation information processing biases characteristic of of depression. While there is little empirical support support for rumination ever being a helpful coping style, potentially its benefits have not been investigated for individuals who restrict rumination to the moments directly after a traumatic event. Anecdotally, many individuals speak of of the of "seeing the larger picture" or "not lett letting benefits of ing an event bother me" as of dealing with negative incidents. Potentially, these coping a way of mechanisms, which appear to involve allowing associations with the affective content to be subsumed by less negative associations from an individual's knowledge base, might correspond to this type of of rumination.
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during depression - the prevention of of healing. The person Ruminating during The person who with negative ruminating, and.thus warded off who has has often often coped coped with negative events by ruminating, and .thus warded off cognitive correlates correlates of of aa possible possible depression, depression, might believe that rumination rumination is cognitive believe that always always aa beneficial beneficial way way of of dealing dealing with with loss. Suppose, Suppose, that that this this same same person person experiences experiences aa loss, is so so overcome overcome by by the the loss that that he he or or she she does does not not processes it intellectually intellectually immediately, immediately, and and only only begins begins to to ruminate ruminate later. later. processes it Now, because because the the rumination rumination tends tends to to preserve preserve learned learned knowledge knowledge (including (including Now, learned learned biased biased information information processing), processing), the the depressed depressed person person is is expected expected to to have have exceptional exceptional difficulty difficulty learning learning new new positive positive information! information! As As aa consequence, the the depressed depressed person person may may have have difficulty difficuH:y recovering recovering from from consequence, depression. depression. This This phenomenon phenomenon can can be be shown shown in in the the network network by by increasing increasing feedback feedback between between the the affective affective and and semantic semantic layers layers after after overtraining overtraining the the network network on on aa negative negative stimulus. stimulus . In In this this case, case, the the network network performs performs no no
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depressive rumination. Indeed modifying "what individuals say to of time-honored themselves" is a common theme running through a number of cognitive intervention procedures (e.g., cognitive relabeling: Goldfried Goldfried & Davison, 1976; stress inoculation training: Meichenbaum, 11985). Davison, 1 976; stress 985). Coping by by ruminating ruminating - aa vulnerability vulnerability factor. factor. Individuals who cope by Coping ruminating were suggested above above to be protected from some of of the most detrimental cognitive correlates of The argument for this of depression. The conclusion assumes that their cognitive that individuals individuals who ruminate change their structure (i.e., learn) only aider after they ruminate structure ruminate on aa stimulus. Another Another possibility is that that individuals who ruminate ruminate learn during the rumination rumination process. That That is, while an individual engages in rumination he or she actually reinforces the the ideas which which are are being ruminated upon. This phenomenon is simulated in the the network to the network model, by allowing the to learn during the feedback between the semantic nodes. When When this the network's network's affective and semantic
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of rumination no longer acts as a technique is used, the computational analog of protective factor, and and in fact, increases the network's negative information OCessing biases a great deal. processing pr Figure Figure 7 shows the relative increases in the network's reaction time on the lexical decision task to a negative stimulus on which the network is not the overtrained, as it begins to overlearn overleam a negative stimulus. The nonruminating network showed no appreciable change in reaction times over the first 8 appear around 110 The network in which epochs (delays begin to appear 0 epochs). The learning occurs during a cycle of of feedback feeAback between the affective and semantic layers 110 0 times for each stimulus presentation is delayed after even one epoch of overtraining. By 8 epochs of of overtraining, the ruminating network is of virtually unable to distinguish the nondepressotypic nondepressotypie negative word from the negative word on which it is being trained. This happens because the of overtraining for ruminating network has effectively received 110 0 epochs of 2206 06 - -
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each single single epoch epoch at at which which the the negative negative stimulus stimulus was was presented. presented. Clinically, Clinically, each this phenomenon phenomenon might might reflect reflect the the idea idea that that individuals individuals who who use use rumination rumination to to this teach themselves themselves negative negative information information are are extremely extremely vulnerable vulnerable to to the the teach cognitive correlates correlates of of depression. depression. After After even even aa very very brief brief exposure exposure to to some some cognitive loss event, event, learning learning through through rumination rumination could could engender engender large large information information loss processing biases. biases. processing Distractive coping. Nolen-Hoeksema Nolen-Hoeksema (Nolen-Hoeksema (Nolen-Hoeksema & Morrow, Morrow, also discusses discusses distractive distractive coping. coping. She She demonstrates demonstrates that that people people who who 11993) 993) also cope by by distracting distracting themselves themselves from from the the issues issues which which are are troubling troubling them them seem seem cope to be be less vulnerable to to features features of of depression depression than than individuals individuals who who ruminate. ruminate. to less vulnerable Nolen-Hoeksema does does not not provide provide aa theoretical theoretical model model for for why why this this Nolen-Hoeksema phenomenon should should occur. occur. Simulating Simulating aspects aspects of of distraction distraction in in the the current current phenomenon neural network network model model will will tie tie rumination rumination and and distraction distraction into into the the same same neural theoretical model, and thus thus the the two two types types of of coping can be be compared compared in in aa theoretical model, and coping can theoretically meaningful meaningful mann manner. theoretically er. Nolen-Hoeksema and and Morrow Morrow ((1993) conceive of of distraction distraction as as aa Nolen-Hoeksema 1 993) conceive process by by which which individuals individuals think think of of potentially potentially random random information information other other process than their symptoms of of depression. depression. This This phenomenon phenomenon was was modeled modeled in in the the than their symptoms network by by varying varying the the amount amount of of random random noise noise which which entered entered into into the the network processing of of stimuli stimuli during during overtraining overtraining on on negative negative information. information. More noise processing More noise is assumed assumed to to correspond correspond to to more more distraction distraction when when information information is is processed, processed, is because noise noise leads leads the the network network to to randomly randomly associate associate incoming incoming information information because with information other than than that that which which it it has has learned. learned. Figure 8 shows shows the the with network's performance on the lexical decision decision task task and and valence network's performance on the affective affective lexical valence identification task 0.12. task when noise is increased from 0.05 to 0. 12. As shown in Figure 8, when the network network was was overtrained on on one one negative stimulus stimulus for for 70 epochs, noise not appear appear to greatly affect affect negative 70 epochs, noise did did not to greatly performance on on the the lexical lexical decision decision task task with with respect respect to to its its original original performance performance (Figure contrast, affective affective interference interference on on the the valence valence performance (Figure 3). 3). In In contrast, identification task task was in the the network network in in which which noise noise identification was substantially substantially decreased decreased in was result suggests suggests that that individuals individuals who who engage engage was increased. increased. Potentially, Potentially, this this result in in distractive distractive coping coping may may not not be be subject subject to to the the same same sorts sorts of of affective affective interference which which plague plague individuals individuals who who do do not not distract distract themselves themselves from from associations associations with memories which depress them. A how people who who distract similar question question regards regards how distract themselves from A similar thinking about affect throughout their lives, rather than just thinking about throughout rather just in response to aa particularly cope with with aa negative These people people particularly negative negative event, event, will will cope negative event. event. These might the classic idea of who avoid might correspond correspond to to the classic idea of "repressors" "repressors" who avoid thinking thinking about about the the emotional about his his or or her her emotions, emotions, and and about emotional significance significance of of events, events, via via
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3). This finding reflects the the clinical idea idea that that aa person who
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tasks which which require semantic processing (e.g., traditional tasks tasks which might tasks be found in the work place) but might have exaggerated difficulty
assimilating emotional emotional information. This description description reflects reflects many theorists' theorists' assimilating intuitions regarding the nature nature of of repression. intuitions and distractive coping. The The preceding Conclusions about ruminative and or trait simulations have suggested aa number of of possible roles ffor trait variables variables aspects of of rumination and and distraction. distraction. The simulations simulations suggest representing aspects that that based based on individuals' individuals' life experiences, when they begins to use aa coping strategy, and whether or not they learn from that that coping strategy while they they strategy, of coping may either increase or decrease the are using it, the same ways of that they experience experience pervasive information information processing biases chances that characteristic of of depression. Similarly these same factors may may govern how characteristic an individual individual who who becomes becomes dysphoric dysphoric or depressed can recover from easily an
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Chapter 7
this this state. state. By By carefully carefully attending attending to to the the interaction interaction of of trait trait variables variables such such as as coping style style with with life life experiences, experiences, researchers researchers may be able able to to explain explain aa great great coping may be deal deal of of variation variation in in vulnerability vulnerability to, to, and and recovery recovery from from depression. depression.
cognitive structure structure Factors associated with cognitive The The vast vast majority majority of of the the literature literature regarding regarding vulnerability vulnerability to to depression depression concerns how how an an individual's individual's previous previous life life experiences experiences impact impact his his or or her her concerns current life experiences. experiences. This This literature literature is is based based on on theories theories of of cognitive cognitive current life psychology psychology which which suggest suggest that that an an individual's individual's "cognitive "cognitive structure" structure" or or cognitive schema schema which which the the individual individual has has derived derived from from previous previous experiences, experiences, cognitive helps helps to to govern govern how how he he or or she she interprets interprets and and assimilates assimilates new new information information (e.g., Winfrey Winfrey & & Goldfried, For example, example, literature literature in in cognitive cognitive (e.g., Goldfried, 1986). For shows that that individuals individuals who who have have learned learned aa great about music psychology shows great deal deal about music psychology tend to perceive songs songs very individuals who who have not learned learned tend to perceive very differently differently from from individuals have not aa great great deal about music Presumably this this difference Simon, 1972). Presumably difference deal about music (Newell (Newell & Simon, occurs because because people people who who have have learned learned a great deal about music music have have a occurs a great deal about a much different different internal such as much internal representation representation of of stimuli stimuli such as notes notes than than those those who who have not. structure has has frequently frequently been been suggested suggested to to govern govern an have not. Cognitive Cognitive structure an individual's personality (e.g., and interpretation interpretation of of everyday everyday individual's personality (e.g., Cantor, Cantor, 1990) and life experiences experiences (Sehank (Schank & Abelson, life Abelson, 1977). Depression researchers researchers such as Beck have extended extended the the Depression such as Beck ((1967; 1967; 1976) have idea of of cognitive cognitive structure structure to to suggest suggest that that individuals individuals who who have have experienced experienced idea loss events create create detailed detailed representations representations of of loss experiences for for themselves, themselves, loss events loss experiences which become become the the foundation foundation of of their their depression. depression. Their Their perception perception of of negative negative which events may may therefore therefore be be very very different different from from people people who who have have not not experienced experienced events a loss. loss. As As for for cognitive cognitive psychologists psychologists who who study study normal normal functioning, functioning, Beck's Beck's a notion of of distorted distorted cognitive cognitive schemas schemas in in depression depression is is based based on on the the learning learning of of notion negative negative information information from from one's one's environment. environment. Potentially, the the cognitive cognitive ,.structures that are are derived derived from from different different types types Potentially, structures that of previous previous experiences experiences contribute contribute to to different different reactions reactions to to qualitatively qualitatively of similar similar negative negative events. events. Yet, Yet, it it is is not not clear clear exactly exactly how how previous previous experiences experiences will will affect affect an an individual's individual's reaction reaction to to an an event. event. For For example, example, an an individual individual who has has experienced experienced death death in in the the past past may may be be more more disturbed disturbed by by the the death death of of who a a relative relative than than the the individual individual who who has has not, not, precisely precisely because because he he or or she she has has aa more well well developed developed notion notion death. death. That That is, is, his his or or her her conception conception of of death death more might be be strongly strongly associated associated with with to to his his or or her her mental mental representation representation of of might sadness sadness and and other other aspects aspects of of the the cognitive cognitive network. network. Alternately, Alternately, an an individual individual who has has experienced experienced the the death death of of many many individuals individuals may may be be able able to assimilate assimilate who
G.J. G.J. Siegle and R.E. Ingram
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of a relative because he he or or she has a well information from the recent death of developed developed sense of of loss. An An individual individual who has never never experienced experienced a loss may may have more difficulty dealing with the same event. To better understand the role which cognitive structure, as governed by previous life experiences,
the onset and maintenance of of depression, we have chosen to simulate plays in the of previous one factor associated with previous life experience; the role of negative experiences.
New negative experiences are more damaging. The first question relevant to cognitive structure structure which we addressed through simulation was relevant whether an individual's previous experience with a negative stimulus would be expected to affect his or her reaction reaction to a loss involving that experience.
The question was operationalized by overtraining the network on a novel The negative stimulus (one to which it had not been exposed in the past) rather
than a stimulus it had previously learned. This procedure was meant to than first simulate a loss involving something new to a person, (e.g., the fi rst time a person experiences the death of of aa loved-one) loved-one).. Figure 110 0 shows the network's person performance on the simulated lexical decision and valence identification tasks
overtrained on a novel negative stimulus for just 110 after being overtrained 0 epochs. As may be seen from the the figure, information processing biases due to the new may far more apparent than than they were for the network which had stimulus are far received 110 of overtraining on a previously learned negative stimulus 0 epochs of 3). Similarly, when the network is trained ffor or 59 epochs on the novel negative stimulus, its information processing biases are greatly exaggerated with respect to to the network network which was trained ffor a previously or 70 epochs on a learned negative stimulus. When the network is trained trained for any more than 59 epochs on the novel negative stimulus, it attempts to match match the valence of of any incoming stimulus to that that of of the the novel stimulus, and thus thus displays extremely exaggerated simulated reaction times. times . It labels many positive stimuli as negative on the valence identification task. Effectively, the network "forgets" how to identify stimulus.. Inspection revealed that that during anything but but the novel negative stimulus overtraining, all of relevant to the new of the network's weights except those relevant stimulus decayed, corresponding corresponding to an actual loss of of previously learned knowledge not not relevant to to the stimulus representing the loss event. The idea that network is overtrained on new that old information is lost when aa neural network information has has been been explored explored extensively by by Ratcliff Ratcliff (1990) ( 1 990) in aa discussion of neural networks. This sort of of phenomena phenomena related related to to "forgetting" "forgetting" in neural sort of forgetting new meaning meaning in relation to the current forgetting takes on new current model. In effect the network forgets the positive information it has has learned when it experiences a a (Figure
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computational computational analog analog of of depression. depression.
The network's nctwork's behavior behavior suggests suggests that that individuals individuals who who experience experience aa loss loss The which is is very very new new to to them them may may be be more more profoundly profoundly affected affected than than individuals individuals which who who experience experience aa more more easily easily interpretable interpretable loss. loss. This This finding finding might might suggest suggest
that sometimes sometimes individuals individuals who who are arc dealing dealing for for the the first first time time with with concepts concepts that such as as death, death, divorce, divorce, or or losing losing aa job job are are more more strongly strongly affected affected by by these these such events than than individuals individuals who who have have lost lost multiple multiple jobs, jobs, been been previously previously divorced, divorced, events etc. etc. Empirical Empirical studies studies could could address address this this hypothesis hypothesis in in the the future. future.
The overtrained overtrained network's nctwork's inability inability to to identify identify the the affective affcctive valence valence of of The positive information information resembles resembles the the finding finding that that people people who who are are depressed depressed have have positive difficulty recalling recalling positive positive inf information (Blancy, 11986). The current current model model difficulty ormation (Blaney, 986). The suggests that that only only individuals individuals whose whose depression depression is is due due to to aa loss loss experience experience suggests with which which they they have have not not had had previous previous experience experience would would have have such such aa with
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difficulty. Individuals who have learned about loss similar to the one which has sparked their depression in the past might be able to recall more positive information in the context of their depression than those who have not, an idea that merits further research. role of of previous negative negative experiences. experiences. From the idea that previous The role experiences with loss might help an individual to remember with positive researcher might be information when they are depressed, the creative researcher tempted to speculate that previous depressions help to prevent future depression. Empirical evidence does not support this idea. Instead, previous depression appears to be associated with vulnerability to future depression (Weissman et ~ al., 11991), depressogemc loss occurs at a 99 1), especially if the depressogenic more closely developmentally critical time. It is therefore interesting to more examine the idea that some familiarity with a negative stimulus prevents the incumng extreme information processing biases associated network from incurring of previous overtraining on a negative with depression, but a great deal of stimulus might leave the network more vulnerable to information processing biases than a non-overtrained network. Empirically, this situation might be "optimal" range of of familiarity with loss. Individuals who represented by an "optimal" have experienced some minimal losses and developed adaptive reactions to these losses might be better prepared for new losses than individuals who have never experienced loss, or who have experienced a large number of of losses. this situation in the computational model, the model was was first To explore this of 9 positive, negative, and and neutral neutral stimuli to an made to learn the full set of error threshold of of 0.01, 0.0 1 , representing a time approximately half half way through the network's original training. Then, the model was overtrained for 100 1 00 epochs on one negative stimulus. Finally, the network was retrained on all 9 epochs stimuli to the error error threshold of the value which was used for all other to the of 0.004, the simulations. This retraining might be thought of of as having many new experiences after an initial episode of of depression, or possibly as having "gotten past" the depressive incident. incident. The retrained network's performance on the the tasks is shown in Figure 11. 1 1. Many researchers find Many find that that it is difficult to detect depressive attentional biases in individuals who without who have have recovered from depression, without manipulations 1 995). manipulations such such as negative negative mood inductions (Segal & Ingram, 1995). Some researchers have thus thus concluded that that many cognitive correlates of of depression do not not persist persist after after the the depressive episode (Persons & Miranda, Miranda, 1992). 1 992). Consistent Consistent with with this idea, the retrained network shows almost no biases on the valence identification task the valence task or lexical decision task for for negative
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was not stimuli on which it was not overtrained. Yet, the retrained network's performance is still facilitated facilitated on particular negative stimulus on performance on the particular on which it was originally overtrainedf that individuals who overtrained! This This finding might suggest that have not be biased in the way they have recovered from from depression may not they process most negative information but might still be biased in the way they process but might negative stimuli which were related related to the the onset of negative of their depression. that the weights within the This finding finding can be explained explained by observing that network leading from the semantic content of of the node on which the network was overtrained to negativity are stronger than from the other nodes semantic content (3.06 (3 .06 as opposed to 2.76 and 2.74) representing negative semantic and are are stronger than than the connections from the the semantic nodes representing and positive stimuli to positivity (2.83, 2.87, 2.88). Similarly, connections from the negativity node to the node representing the semantic content on which it was overtrained are more positive (-.063) than f or all other negative stimuli for -. 1 9) and (-.24 and -.19) and for the positivity node node to positive semantic stimuli (-. 17, that the network is less 1 7, -. 116, 6, -. 17). 1 7). The network's biases also suggest that from this information (-1.952) information biased away from information (-1 .952) than from other inf ormation (biases ranging from --1.987 1 .987 to -1.989). - 1 .989). Were the network to change the bias term term representing its propensity to activate negativity, as happened during during its initial overtraining, the weights suggesting facilitation on the stimulus on thus still be in place. Potentially, these which it was overtrained would thus results suggest that structural correlates of of depression may be observable even when inf ormation processing is not biased in formerly depressed information individuals. individuals. on the same negative stimulus Moreover, when the network is retrained on for its perf performance, ormance, shown in on which it was initially overtrained f or 70 epochs, its lexieal decision task than the Figure 111, 1 , was much more biased on the lexical network which had not received previous overtraining, shown in Figure 33.. Moreover, on some confirmatory runs of of the same simulation, this network was unable to identify a negative stimulus on which it had not been overtramed. The clinical analog of of these simulations would be that overtrained. from overleaming individuals who experience a prolonged dysphoria resulting f rom overlearning some negative experience once may be become even more depressed at a could correspond to previously similar stimulus later. Such a behavior could depressed individuals individuals being more vulnerable to future future depressions than other individuals, as discussed by researchers such as Weissman et al. (1991). Having a good understanding f positive in formation helps. understanding oof information helps. The with negative preceding simulations suggest that previous experience with information information processing processing inf ormation may help to govern the magnitude of information
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biases in aa depressed individual. individual. Other Other empirical empirical research research suggests suggests that that individuals' individuals' previous experiences with positive positive stimuli stimuli may may affect affect how how they deal with loss. loss. For For example, example, Lcwinsohn Lewinsohn and and Hobcrman's Hoberman's (1982) ( 1 982) behavioral theory of of depression suggests that depression is is at least least as much much a function of of aa lack of of positive positive stimuli stimuli as it it is ovcrlcaming overlearning negative stimuli. stimuli. Similarly, Similarly, Schwartz and Schwartz and Garamoni Garamoni (1989) ( 1 989) show show that clinically clinically depressed depressed individuals individuals tend tend to have have fewer fewer positive positive cognitions cognitions as wcU well as more more negative cognitions than than nondcprcsscd nondepressed individuals. individuals. To To simulate aa cognitive cognitive structure structure less less attuned to positive positive than negative information information before aa loss the network network was was initially initially trained one one fourth as much much on positive stimuli stimuli as it it was was on on the negative and and neutral neutral stimuli. stimuli. Its Its on the three positive reaction times on on the simulated simulated Icxical lexical decision decision and and valence identification identification
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tasks, before and after being overtrained ovcrtraincd for 7700 epochs on a negative stimulus are shown in Figure 12. As may be seen from the figure, figure, the network which received less initial training training on positive stimuli was initially delayed delayed in responding to a stimulus with a positive valence on the valence identification ormance on the network perf performance task. Information processing biases on the network simulated simulated valence valence identification identification task after after overtraining ovcrtraining on on negative information information are arc greatly greatly exaggerated exaggerated with respect respect to the the network which had had previously experienced as as much much positive positive training training as as negative negative and and neutral Yet, the network shows little interference interference on on the the simulated lexical lcxical training. Yet, decision decision task. This behavior behavior suggests that that individuals individuals who who do do not not have have aa great great deal deal of of initial initial positive positive experiences experiences may may be be especially especially vulnerable vulnerable to to some some cognitive correlates correlates of of depression depression but but not not others. others. Potentially, Potentially, this this cognitive cognitive cognitive profile profile is is indicative indicative of of aa particular particular cognitive cognitive subtype subtype of of depression. depression.
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can be found for a network which does not receive a A similar behavior can great deal of of initial training on any stimulus. For example, when the the network is initially trained to an error threshold of of 0.01 rather than 0.004 as in the original simulations (that is, it is given less initial training), its performance on the simulated affective lexieal lexical decision and valence identification tasks after having been overtrained on negative information, shown in Figure 13, is biased than that of of the original network shown in Figure 33.. This much more biased the idea that individuals without much experience to behavior might reflect the back on are are greatly affected by loss events. The observation that less fall back experience might be a vulnerability factor for negative information processing biases might suggest that children, who have fewer experiences to guide the of their cognitive network than adults, might be especially structure of vulnerable vulnerable to loss. This hypothesis might be tested by determining whether children are more vulnerable to depression than adults when confronted with similar losses. -+- NonDepressed-Lexical NonDepressed-Lexi:al
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from simulations simulations of of cognitive structure. Our simulations Conclusions from of of cognitive structure structure suggest suggest that that individuals individuals who have either learned an extraordinary amount of of negative information information or learned little positive information in the the past past might be vulnerable vulnerable to to experiencing negative information information processing biases when confronted with a loss. Less intuitively, information the results also suggest that that when a loss event is new for for an individual, the individual has little experience with loss or little because the little experience with life in general, it may be particularly detrimental for the individual. individual. Each of of life factors could contribute contribute to individual differences in expressed these factors information and information processing biases on measures such as the lexical decision and valence identification tasks. To better account account for variation variation in performance performance for researchers investigating due to previous experience, it may thus be useful for information processing biases to account for for an individual's negative information previous life events schedules and previous depression depression life history. Life Life events inventories may be useful in this this regard. intellect - the case of Factors associated with intellectof openness to experience
Historically, differences Historically, one of of the best recognized sources of of individual diff erences in information effects of intellect and mood, information processing is mtelle~. intellect. The joint eff ects of well studied nor well though, are neither well well understood. Potentially, computational models can help to integrate these areas by providing providing theoretically motivated predictions regarding regarding the relationship between aspects of of intellect intelle~ and mood. Recent research suggests that people with aff ective disorders often affective experience inf information ormation processing deficits traditionally associated with low intelligence. intelligence. For example, a hallmark of of depression is psychomotor retardation (American Psychiatric Association, 1995); 1995); processing speed is one of of the primary variables thought to contribute contribute to intelligence intelligence (Sattler, 1993, p. 77). Similarly, people who are depressed often display impaired 77). depressed 99 1), difficulty in learning rules problem solving (MacLeod ( M a c ~ & Mathews, 11991), ( M a c ~ & Mathews, 1991), 1991), and diminished diminished attentional capacity capacity (Gotlib & (MacLeod 1984), all of of which are often associated with low low intelligence. intelligence. Yet, McCann, 1984), many inf ormation processing biases present in depressed people appear to go information away when they are not depressed (Persons & Miranda, 1992) 1992) suggesting the impairments are a function of the disordered mood state rather than the "trait" intelligence. Potentially, observing how ffactors " trait" termed low intelligence. actors associated information with intellect help to mediate the inf ormation processing biases expressed in
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the model which is overtrained on negativity can help to shed light on this relationship. factor. Openness to Openness to experience as a risk and protective f actor. Openness new experiences is an aspect of personality which appears to be related to intellect (McCrae & Costa, 11985). 985). One of the ""Big Big Five" factors repeatedly identified on personality inventories, openness to experience is traditionally characterised by traits such as curiosity and creativity (Goldberg, 11993) 993) or willingness to explore new ideas. Its origin stems from a series of items on mteUect, and in fact, many personality inventories originally associated with intellect, personality theorists equate these items directly with intellect (e.g., Digman & 1981). Takemoto-Chock, 198 1). Individuals who possess more of this trait are said to learn faster and be more willing to change their beliefs in the face of new information than those who do not. The neural network framework proposed that openness to learning new experiences may also be here suggests that especially important in determining depressive information processing biases. overleaming of of negative Because depression is operationalized as the overlearning information, individuals who are more open to learning new information would be expected to incur the types of of information processing processingbiases biases of depression depression more readily than than those those who do not. Similarly, characteristic of these same individuals might be expected to be able to ""unlearn" unlearn" their than individuals who do not information processing biases more easily than possess the same openness to new experiences. It is not clear whether being open to to experience means that a person readily changes changes any and and all of based on new experience, or of his or her beliefs based whether aa person changes only certain, more mutable beliefs. The former operationalized in a neural network by modifying a definition may be operationalized parameter to many neural network models called the the ""learning parameter common to learning rate" (rl). The The latter definition may be operationalized by modifying a related, but (11). (~t). To different common parameter parameter termed the network's ""momentum" momentum" (a). understand of the backunderstand the function of of these parameters, some knowledge of back propagation algorithm algorithm which is used to allow neural networks to learn propagation information weights of information is important. important. During During training, the network updates updates the the weights of connections the amount error incurred in the connections between nodes nodes proportional proportional to the amount of of error network's output, according to to the formula: 6 i = r l , ( l a y e r l)T,errorlayer2 + t~,6 i
where/5 the change in the the weight of given connection which connects where OJi is the of aa given layerl The formula formula states that that the change in weights of of layer layeq1 is aa layer} to to layer2. layer2 . The
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function function of of both both the the learning learning rate rate (11) (11) times times the the difference difference between between the the desired desired
and actual outputs and actual outputs of of layer layer2, and and the the momentum momentum (ex) ((z) times times the the previous previous 2 change to the change to the connection's connection's weight weight after aiter previous previous stimuli stimuli have have been been presented. presented.
Thus, Thus, the the learning learning rate rate governs governs how how much much aa connection connection will will change change in in response response to the the presentation presentation of of aa single single stimulus. stimulus. When When 11 TI is is small, small, even even if if the the
network incurs a great great deal deal of of error error in in processing processing aa stimulus, stimulus, the the network network network incurs a may weights a deal with may not not change change its its weights a great great deal with respect respect to to the the stimulus. stimulus.
Alternately, Alternately, if if 11 vI is is large large aa single single stimulus stimulus could could greatly greatly affect affect the the network's n~work's
responses. responses. The The momentum momentum governs governs how how much much previous previous changes changes in in the the
network ect its is high, is more network aff affect its current current responses. responses. When When ex tz is high, aa connection connection is more
likely change if it has changed changed in in the the past. Thus, recently recently learned learned likely to to change if it past. Thus, information has has an an aspect of mutability mutability which which is is not not attributed attributed to to previously previously information aspect of learned ormation. learned inf information. The The effects effects of of changes changes in in the the learning learning rate rate and and momentum momentum in in the the network network were illustrated illustrated by by training training the the network network on on all all stimuli, stimuli, and and then then on on aa were characteristically characteristically negative negative stimulus, stimulus, in in aa set set of of 324 simulations simulations in in which which 11 11 and ex (z varied varied continuously continuously between between O.OS 0.05 (very (very low) low) and and I1 (very (very high) high) by by steps steps and of O.OS 0.05.. For For previous simulations, 11 11 was was 0.2 0.2 and and ex ct was was 0.4. 0.4. The The network's network's of previous simulations, simulated or low simulated reaction reaction times times to the the tasks tasks ffor low values values of of ex ot (O.OS) (0.05) and and 11 r I (O.OS) (0.05) are are shown shown in in Figure Figure 14. 14. To To depict depict the the magnitude magnitude of of the the network's network's information information processing processing biases biases 11, Figure S shows as as a a continuous continuous function function of of ex ot and and 11, Figure I15 shows ex (z on on the the X X axis axis and and 11 rl on the Y on the Y axis. axis. The The Z axis axis on on the the upper upper figure figure represents represents the the difference difference in in the the overtrained reaction time time to overtrained and and nonovertrained nonovertrained network's network's simulated simulated reaction to a a negative network was negative stimulus, stimulus, on on which which the the network was not not overtrained. overtrained. The The Z axis axis on on the lower lower figure figure represents represents the the diff difference in the the overtrained overtrained and and the erence in nonovertrained reaction time time to nonovertrained network's network's simulated simulated reaction to aa positive positive stimulus. stimulus. Reaction are superimposed Reaction times times are superimposed upon upon the the best best fit fit interaction interaction surface, surface, found found through linear regression. On the through linear regression. On the lexical lexieal decision decision task, task, the the overtrained overtrained network unable to correctly stimuli when network was was unable correctly identify identify negative negative stimuli when ex cz or or 11 11 were were increased above increased above about about O.S 0.5 and and thus thus these these data data were were not not plotted. plotted. As As in in previous previous simulations, simulations, the the overtrained overtrained network network was, was, in in general, general, delayed stimuli on decision task delayed in in responding responding to negative negative stimuli on the the lexical lexical decision task and and positive the valence positive stimuli stimuli on on the valence identification identification task. task. As the the learning learning parameters parameters increased, increased, the the magnitude magnitude of of the the network's network's information information processing processing biases biases increased or both the increased ffor the simulated simulated lexical lexical decision decision task task (R2=.S3, (R2=.53, F{2,8S)=49.3, F(2,85)=49.3, p.
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amount of attentional attcntional resources but but lesser lesser capacity of working memory, or vice versa, are arc not taken taken into account account here. According to the model, tasks also differ, namely, namely, in in the the amount amount of of attentional attcntional resources and and working memory capacity capacity they they require require for correct performance. For instance, instance, a hypothetical task task A A requires more resources than task B; therefore, the first one may be bc regarded regarded more more difficult. difficult. For the sake sake of clarity, clarity, the the intermediate intermediate instances instances were wcrc omitted, omitted, i.e., i.e., the the task that that is is challenging challenging for for attention attention but but less less demanding demanding for for memory, memory, or or vice vice versa. versa. Anyway, Anyway, the the theoretical theoretical model model suggests suggests two two consequences consequences of of the the differences differences
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task's requirements. First, task A may require more more restricted restricted boundaries boundaries of in task's arousal that ormance (Figure that are acceptable for successful perf performance
I). 1). Second, Second,
of attentional and and working working memory task A may require higher absolute levels of performed are two parameters in order to be successfully perf ormed (Figure 2). These are ways in which a person can tackle task A, and the choice may be determined
of this person, i.e., by the absolute levels of of by the structural prerequisites of his/her attention and memory functioning, or by hislher his/her cognitive styles or hislher strategies.
of the game. In this way way we ref refer Situation is the third party of er to many different of arousal. There are probably diff erent factors that influence transitory states of of high or low arousal; however, the majority of of factors constitutional sources of influencing our being "high" or "low" ref refer of the day, intensity of of er to time of external stimulation or substance intake. Even the motivational arousal, effort best, may may be treated as rooted in caused by increased eff ort to do one's best, because it is transitory in nature and and results mainly from situational factors, because external pressure pressure or requirements, in addition to intrinsic motivation. Thus, we can consider the situation situation in which a person tackles the tasks - and specifically, the level of of arousal caused by situational factors - as the third of the level of of performance. important determinant of Let us consider two particular particular problems involved in the the model of of The first problem ref refers the precise meaning of of intelligence sketched above. The ers to the the inverted U-shaped V-shaped relationships, symbolized in Figure I1 and Figure 2 by the caption of the bold lines. It has been been already suggested (see the caption of the Figure 11)) that of performance of the cognitive task. that these lines represent the level of performance of However, at at least least two two possibilities seem to to exist as to to the actual actual dependence of horizontal of performance performance on arousal. arousal . For For both tasks depicted in Figure 2, the horizontal lines define the quantity of to classical resource of resources required. According to theory (Norman & Bobrow, 1975), the availability of of 1 975), further increases in the theory resources should have have no further effect effect on performance, since the task becomes or, say, Task becomes data-limited. So, between the the two two vertical vertical lines ffor, Task A, variation in arousal arousal should should have no effect the perf performance of person person X, effect on the ormance of X, so this specific fragment of of the bold line should rather than than this the bold should be entirely flat rather Gaussian-like. Gaussian-like. But the measures task performance are continuous in nature nature (like But if if the measures of of task performance are reaction time, time, for instance), still change with the instance), performance performance will still the arousalarousal fluctuations of of resource the vertical lines. dependent fluctuations resource availability, defined by the this case, case, the horizontal lines define the minimum oof resources required, so In this the horizontal the minimum f resources additional to some additional supply of of resources resources seems likely to to improve performance performance to extent. There natural bamers There are, are, of of course, natural barriers to to performance performance (e.g.,
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anatomical, physiological) but, until they are met, performance should still arousal even above above the mim'mal of supply. This issue cannot depend on arousal minimal level of of the general theory of of resource be solved properly without modifications of if our line of of reasoning reasoning makes sense, it applies only to availability. However, if person X X (i.e., the more "endowed" one) doing the task A (i.e., the more Y must be regarded as structurally unable to solve demanding one). Person Y the Task A, because he/she does not reach the minimal level of of resource supply even in the most favorable circumstances. The second problem amounts to to the question of of automaticity of of intelligence, processes involved in intelligent behavior. Some measures of intelligence, including the typical IQ tests, definitely engage "higher-level" aspects of of cognition, e.g., thinking, concentration and controlled rather than automatic processing. Other measures of of intelligence, intelligence, on the other hand, may not require higher-order cognitive processes. For instance, vocabulary tests require "only" the retrieval of of information from semantic memory; retrieval, however complex, is mostly an automatic process. To what extent, one could ask, does of intelligence? intelligence? Is the proposed model apply to the more "automatic" aspects of it possible to apply its basic notions and assumptions to tasks that do not rely of cognition? Searching for tenable answers to such on the controlled aspects of questions, one should bear in mind that that certain valid measures of of intelligence do not necessarily require complex thinking and problem solving. For instance, reaction time (Jensen, 11987b) 987b) or nerve conduction velocity (Reed & Jensen, 11991, 99 1 , 11992) 992) proved to correlate with the general mental ability, while being entirely nonintellectual in themselves. It would be risky to claim that intelligence amounts to reaction time or nerve conduction velocity. Such simple measures measures may correlate with with general mental ability ability for reasons reasons which are more or less accidental. Vocabulary span span is a somewhat special case, ease, because it is probably a result 983; Sternberg, result of of past past intellectual processes (Sternberg (Steinberg & Powell, 11983; Stemberg, 11985, 985, 11990). 990). According to Sternberg's Stemberg's hypothesis, high IQ people have larger vocabulary span - not because retrieval of of the word meaning form semantic memory is a difficult, complex, and "controlled" "controlled" mental process, but because f the word meaning is a very difficult and complex task. We the acquisition oof learn vocabulary mainly from context, i.e., we infer about the word meaning on the basis of of its repeated usage in various real-life situations. The more "intelligent" "intelligent" we are, the more efficiently and quickly we acquire our vocabulary; in effect, the vocabulary span correlates with IQ, although it is "intelligence." So, our model seems far from being synonymous with "intelligence." applicable to the "nonintellectual measures of of intelligence" intelligence" too, if if we look at
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as the the results of past intellectual processes. To To be precise, the such measures as model applies to these past processes rather than to the current use of its results. one particular implication of the the model Let us now concentrate on one moderate levels of of arousal, people who depicted in Figure 2. It seems that, at moderate of attentional resources and working are endowed with high absolute values of state and to arousal memory capacity should be less sensitive to emotional state from the environment. We could simply call such people "intelligent," if we of the term to the structural limitations of of one's agreed to reduce the meaning of processing apparatus. apparatus. I am trying to argue, though, that intelligence is a processing at least least three elements take part: the person person with with hislher his/her process, in which at limitations, the task with its processing demands, and the situation with many of arousal. Anyway, "intelligent" people factors influencing the current level of regarded as less arousal-dependent arousal-dependent - but but only in moderate moderate states of of should be regarded of arousal, arousal, "intelligence" becomes less important, excitation. At the extremes of because performance performance primarily primarily reflects arousal level. Thus, "intelligence" understood in terms of of the processing limitations appears appears useless when understood arousal arousal becomes extremely high or low; however, "intelligence" decides which levels of of the state state of of arousal arousal are still "moderate," i.e., acceptable acceptable from the point of of view of of task requirements. requirements. To sum up, "the process process of of intelligence" can just just be be defined as a process of oscillation between the the limits of of arousal arousal that are are acceptable acceptable for task task of requirements current circumstances. the process of requirements under under the the current circumstances. It is also the process of choosing that can account both a a choosing tasks that can be performed performed successfully, taking into account person's structural and the situational situational factors that that determine determine the person's structural limitations limitations and current of arousal. of intelligence" intelligence" amounts amounts current state of arousal. In other words, "the process process of of either to manipulation manipulation of either arousal level or the task's difficulty - depending on what because one cannot change what may may be controlled controlled under under the the circumstances circumstances - because structural limitations limitations on attention attention and the structural and working memory capacity. Thus, Thus, the model model predicts predicts that amount of of the that aa person person X, X, endowed with a great great amount resources, may act act below the the level level that structurally available to him/her. It resources, may that is structurally available to also with lesser amount also predicts predicts that that aa person person Y, with amount of of resources, resources, may may surpass surpass person X X in some some circumstances. circumstances. All depends on one's competence competence in person depends on controlling the the arousal arousal level, as as well as on one's ability to to choose choose the the proper proper controlling well as one's ability task task at at aa proper proper moment. Efficient manipulation manipulation of of the the current current level of of arousal, arousal, as well as as the the of aa task task whose whose complexity is adequate adequate in the given circumstances, circumstances, choice of probably engages engages strategic strategic and and metacognitive metacognitive factors. factors. For instance, people people probably For instance, can deliberately deliberately regulate regulate their their mood, mood, and, and, consequently, consequently, their their level level of of arousal arousal can
Chapter 12
524 (Thayer
Thayer, Peters, Takahashi & Birkhead-Flight, 11993). et al., 11994; 994; Thayer, 993).
of this kind, we can can speculate that the mood Although there is no evidence of be adjusted to the level of of constitutional constitutional arousal, regulation strategies have to be· because ectiveness of because the eff effectiveness of various various modes of of regulation is likely to depend on the arousal-related personality traits traits (e.g., extraversion, neuroticism). In other
words, people can regulate their mood and arousal to some extent, providing that they have learned the regulation regulation techniques that that work in their case. The that process of -knowledge, as of regulation therefore therefore demands a high level of of self self-knowledge, well as the ability to control one's cognitive processes 1 984) processes.. Mischel Misehel ((1984) suggests that that impulse control and the ability to delay gratification may be critical in child child social social and emotional development. It seems that the analogical mechanism, when applied in the cognitive domain, might be responsible f or for intellectual development. Skills and areas of of expertise probably play a role in these processes, too too.. It seems to be so because expertise usually allows us to reduce the the complexity
of the task, either through its redefinition or through taking a new perspective of in looking at 99 1 ; Kossowska, Matthaus at it (cf. Hany, 11991; Matth~ius
& Necka, 11996; 996;
Ohlsson, 11984a, 984a, 11984b). 984b). When we we gain experience in a domain, we start start to or novices. Herbert perceive regularities and similarities that that are invisible ffor of "f "familiarization" Simon calls this the process of amiliarization" and thinks it may be 988). Due to the responsible f or the act of for of insight (after Langley & Jones, 11988). reduction of of complexity, tasks that that were fonnerly formerly too complex to tackle ective solutions suddenly become less demanding and allow eff effective solutions.. And, emanding it becomes according to our model, when when the task becomes less ddemanding automatically ectively tackled automatically less dependent on arousal, that is, it may be eff effectively in states of of activation activation that that are far far from optimal. So, "the process of of intelligence" intelligence" depends on whether a person understands understands hislher his/her constitutional constitutional arousal, whether he/she knows how to regulate transient transient states of of arousal, and whether he/she is able to reduce the complexity of of the task task due to redefinition, redefinition, "familiarization," or acquisition of of expertise. Mechanisms of of this sort are probably rooted in the processes of of metacognition and strategic choice, which are not covered by the proposed model. It means that that the model does not cover the whole area of of intelligence research. In fact, it pertains only to the f onnal level of 199 1l)) formal of analysis. Necka ((199 suggested that, since the concept of of intelligence intelligence iiss extremely heterogeneous, it has to be analyzed at f our distinct levels: biopsychological, ormal, strategic, four biopsychologieal, fformal, and and value-related. The The proposed model refers only to the second level, at which the basic formal characteristics characteristics of of the cognitive apparatus apparatus are taken
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consequence, it it is a model of of the formal aspects of of into account. In consequence, rather than than a complete model of of intelligence. intelligence rather Although the the model does not specify some important aspects of of Although probably accounts accounts ffor intelligence, it probably or the human intellectual functioning at Three important facets of of this model seem worth least to some extent. Three pointing out. First, it tries tries to join join the processing aspects of of intelligence with the structural structural ones. In other words, it suggests that that intelligence is a matter of of transitory processing processing factors and stable structural structural traits. Second, the both transitory model tries to seek for the intelligence-personality and intelligence-emotion interface. In this way, it views intelligent behavior behavior as resulting from the joint joint interface. operation of of cognition, cognition, personality, personality, and and emotions. Such a stance stance is not not quite operation frequent among the diff differential usually regard regard intelligence frequent erential psychologists, who usually to be separated separated from emotions, temperament and personality; at the most, try to investigate the mutual mutual relationships relationships (Saklof (Saklofske 995). they try ske & Zeidner, 11995). Third, the model is able to to account account for the the fact that that apparently intelligent Third, people may behave under their natural natural level of of perf performance, ormance, and vice versa. to present some empirical data data gathered as aa preliminary Now, it is time to attempt to verify the model. attempt
Preliminary Empirical Empirical Data Preliminary A series series of of experiments was was carried out in order to check the the model of of
predictions. We We chose one single study for this this chapter chapter to intelligence and its predictions. illustrate illustrate the methodological approach approach that that was was applied in these experiments.
Method Method 9-22, took part Subjects. Subjects. Eighty one college candidates, aged 119-22, part in the
experiment as volunteers. experiment Materials. our paper Materials. We We used used two two computerized procedures and and ffour paper and ((1969) 1969) STM our, six, or eight STM scanning task. Subjects were presented with series of of ffour, digits, which appeared of the computer screen one by one. The appeared in the center of presentation presentation of of the first first digit was preceded by a mask, which also followed of the series. After two two seconds, a probe letter letter appeared on the the last digit of screen, and subjects were supposed supposed to say YES if if they thought thought it belonged to if they though though it did not. In order order to prevent subjects subjects from the series, or NO, if utilizing specific specific strategies of of encoding (e.g., "chunking"), the presentation presentation of of utilizing (therefore, task was called Steinberg ore, the task Sternberg digits was as short as 250 ms (theref
instruments.. First, we employed the modified Saul Sternberg Steinberg pencil instruments
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"turbo"). Sternbcrg's Sternberg's task task has has been been already already applied applied in in various various experiments on on STM and and intelligence (e.g., Necka, 1992; 1 992; Vernon, 1983, 1 983, 1985). 1 985). However, However, it STM appeared appeared that that the the increased increased speed speed of of presentation presentation made made the the task task rather rather difficult. The The computer registered registered accuracy accuracy and and reaction time of of subjects' responses. responses. Second, the DIVA DIVA ("DIVided Attention") task task was employed in order to assess subjects' attcntional attentional parameters parameters (Nccka, (Necka, 1996). 1 996). The The task task consisted of of presentation presentation of of an uppercase uppercase target target letter in the center of of the computer computer screen, together with three, four, or other letters which appeared appeared and together or five other and vanished in locations around the central target at the pace pace of one letter per second. around the target at of one supposed to to press press the mouse key Subjects were supposed the left-hand mouse key whenever they could that was semantically identical the target but differed in see aa letter letter that identical to the target letter but case case (e.g., lowercase "c" "e" when uppercase uppercase "E" servexl served as target). All other letters were to be ignored as noise. Letters Letters identical with the target target both in meaning and in case (e.g., "E" versus "E") were not utilized in this version of of the DIVA task. Usually, their appearance serves to introduce distraction of the task (Necka, conditions, which normally increases the difficulty level of task (Nccka, 1996). of distractors of of this kind was 1 996). In this study, the presence or absence of not manipulated as an independent variable, since we wished to simplify the experimental design. Instead, every single trial was repeated twice, so as to guarantee the necessary number of of trials over the whole task. guarantee Apart from the primary detection task, task, subjects simultaneously had to Apart from perform a simple psychomotor task, defined as a secondary one. This task of two bars located left and right fight of of the demanded the control of of the position of of these bars would central panel containing the letters. Unexpectedly, one of start start to drop down, and subjects had to prevent from further descent by of the mouse. If they pressed the button too pressing the right-hand button of bar would ascend above the central point, which was frequently, though, the bar also prohibited. In other words, subjects were investigated in a typical dual comparison of of their perfo performance rmance in single versus dual task paradigm. The comparison task conditions allowed an assessment of of how much the individual subject "suffered" from the necessity to control two simultaneous tasks. In this way, we were able to assess how much attentional attcntional resources the person possesses. of accurate responses; it also counted The computer registered reaction time of the number of of hits, misses, and false alarms as accuracy measures of performance. Two measures of of intelligence were administered: Raven's Advanced Two 983) and the verbal Analogy Progressive Matrices (Raven, Court & Raven, 11983) Test constructed in our laboratory. The second tool has not been subjected to
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proveA its validity as as an standard psychometric investigation yet, but it has proved (Nccka, Gruszka & experimental measure of the general mental capacity (Necka, Orzechowski, 11996). 996). We decided to include it into this study as a test contrasting with the nonverbal spatial material on which the progressive matrices are based. Arousal was assessed with Thayer's Activation-Deactivation Adjective Check List (ADACL, Thayer, 11989), 989), in the Polish adaptation prepared by Klonowicz ((1984). 1 984). As we have already mentioned, Thayer distinguished four dimensions of arousal: 11.. energetic (which he calls "high activation"), 2. tense (called "high activation"), 33.. vigilant (antagonistic to the state of drowsiness, "deactivation"), and 4. relaxed (called (called "general deactivation"). deactivation"). which he calls "deactivation"), The Activation-Deactivation Adjective Check List consists of twenty items (adjectives), five for each dimension of of arousal. It allows quick assessment of (adjectives), these dimensions, understood as momentary states rather than stable traits. In order to assess arousal which is believed to be rooted in stable, determined traits, we decided to apply the constitutional, physiologically determined Eysenck Personality Questionnaire-Revisexl Questionnaire-Revised (EPQ-R; Eysenck & Eysenck, 1975), 1 975), in the Polish adaptation made by Brzozowski and Drwal ((1995). 1 995). The of which are relevant to arousal. EPQ-R consists of of three scales, two of According to Eysenck's theory, introversion is rooted in permanently increased cortical arousal, while neuroticism relates to the ease of of instigation of visceral activation. Thus, the scores obtained on the E and N scales of of of information about our EPQ-R were expected to provide some additional reformation subjects' level of of arousal. Procedure. The The experiment was conducted in the following order: ADACL, attention task (DIVA), ADACL, short term memory task (Steinberg), (Sternberg), ADACL, intelligence intelligence tests (Raven's matrices and the Analogy Test), EPQ-Q, ADACL. In this way, we obtained four consecutive measures of arousal referred to subsequently as ADACLl of ADACL1,, ADACL2, ADACL3 and respectively, so that performance in every cognitive task task could be ADACL4, respectively, related to the ADACL results obtained just just before or after aider this task. Results Results
The results for the attention attention test (DIVA) showed that that the manipulation with independent variables was very effective. Response latcncies latencies were longer in the dual task condition than in the single task condition condition (p