Handbook of Cognition
Publication Year: 2005
The Handbook of Cognition provides a definitive synthesis of the most up-to-date and advanced work in cognitive psychology in a single volume. The editors have gathered together a team of world-leading researchers in specialist areas of the field, both traditional and `hot' new areas, to present a benchmark - in terms of theoretical insight and advances in methodology - of the discipline. This book contains a thorough overview of the most significant and current research in cognitive psychology that will serve this academic community like no other volume.
- Front Matter
- Subject Index
Part One: Perception, Attention and Action
- Chapter 1: Visual Perception I: Basic Principles
- Chapter 2: Visual Perception II: High-Level Vision
- Chapter 3: Auditory Perception
- Chapter 4: Attention
- Chapter 5: Action and Motor Skills: Adaptive Behaviour for Intended Goals
Part Two: Learning and Memory
- Chapter 6: Theories of Learning
- Chapter 7: Category Learning
- Chapter 8: Implicit Learning
- Chapter 9: Mechanisms of Memory
Part Three: Language
Part Four: Reasoning and Decision Making
Part Five: Cognitive Neuropsychology
- Chapter 15: The Cognitive Neuropsychology of Object Recognition and Action
- Chapter 16: Cognitive Neuropsychology of Learning and Memory
- Chapter 17: The Cognitive Neuropsychology of Language
Part Six: Modelling Cognition
Editorial arrangement and introduction © Koen Lamberts and Robert L. Goldstone, 2005
Chapter 1 © Johan Wagemans, Felix A. Wichmann and Hans Op de Beeck, 2005
Chapter 2 © William G. Hayward and Michael J. Tarr, 2005
Chapter 3 © Christopher J. Plack, 2005
Chapter 4 © Claus Bundesen and Thomas Habekost, 2005
Chapter 5 © Yvonne Delevoye-Turrell and Alan M. Wing, 2005
Chapter 6 © Michael E. Young and Edward A. Wasserman, 2005
Chapter 7 © John K. Kruschke, 2005
Chapter 8 © David R. Shanks, 2005
Chapter 9 © Ian Neath and Aimée M. Surprenant, 2005
Chapter 10 © Alan Garnham, 2005
Chapter 11 © James M. McQueen, 2005
Chapter 12 © Alexander Pollatsek and Keith Rayner, 2005
Chapter 13 © Nick Chater, Evan Heit and Mike Oaksford, 2005
Chapter 14 © Craig R. M. McKenzie, 2005
Chapter 15 © Glyn W. Humphreys and M. Jane Riddoch, 2005
Chapter 16 © Barbara J. Knowlton, 2005
Chapter 17 © Randi C. Martin and Denise H. Wu, 2005
Chapter 18 © Koen Lamberts, 2005
Chapter 19 © Jae I. Myung, Mark A. Pitt and Woojae Kim, 2005
First published 2005
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List of Contributors[Page vii]
Claus Bundesen is Professor of Cognitive Psychology at the University of Copenhagen, Director of the Centre for Visual Cognition in Copenhagen, and Director of the Danish Graduate School of Psychology. He is a member of the executive committees of the International Association for the Study of Attention and Performance and the European Society for Cognitive Psychology, Editor in Chief of the European Journal of Cognitive Psychology, and member of the editorial boards of Psychological Review, Psychological Research and Visual Cognition. His achievements include measurement of effects of visual size in pattern recognition and apparent movement and development of mathematical models of selective attention in vision.
Nick Chater is Professor of Psychology and Director of the Institute for Applied Cognitive Science at the University of Warwick. His research focuses on building mathematical and computational models of cognitive processes, including reasoning, decision making, language processing and acquisition, and perception and categorization. He is particularly interested in ‘rational’ models of cognition. He is also interested in the application of cognitive science to the private and public sectors.
Yvonne Delevoye-Turrell is a postdoctorate fellow in the Neuroscience Laboratory (CNRS) located within the psychiatric unit of the University Hospitals of Lille, France. After completing a PhD on the predictive adjustments of motor parameters in collisions (University of Birmingham, UK, September 2000), she initiated a research project on the systematic investigation of the motor deficits characterizing the psychiatric illness of schizophrenia. Overall, the topic of her research centres on the problem of motor prediction: how does the brain adapt motor actions to the continuously changing dynamics of the environment? Using schizophrenia as a pathological model, her research now aims at the development of a cognitive model of the motor systems that incorporates three types of predictive mechanisms: automatic, controlled and voluntary. The fine integration of these different functions would achieve efficient and optimized adjustments of motor behaviour.
Alan Garnham is Professor of Experimental Psychology at the University of Sussex, Brighton, UK. He has been a member of faculty at Sussex since 1985. Before that he spent two years at the University of Reading. His main research interests are in psycholinguistics, in particular the comprehension of anaphoric expressions, the role of inference in comprehension, and the role of non-syntactic information in parsing. His work in psycholinguistics is carried out in the mental [Page viii]models framework. He is also interested in the application of mental models theory to reasoning, and in particular in the role of prior beliefs on reasoning.
Thomas Habekost is a PhD student at the Centre for Visual Cognition, University of Copenhagen. He has also been visiting scholar at the Cognition and Brain Sciences Unit in Cambridge. His research focuses on the neural basis of visual attention, especially through studies of brain damage. His work includes mathematical modelling of attentional deficits and development of bootstrap methods in neuropsychological testing. He has also contributed to the NTVA model of attentional effects in single cells.
William G. Hayward is an Associate Professor in the Department of Psychology at the Chinese University of Hong Kong. He received a BA and MA from the University of Canterbury, New Zealand, and a PhD from Yale University. After spending four years as a lecturer at the University of Wollongong in Australia, he has been at CUHK since 1999. His research focuses on the information that subserves object recognition processes, examining such issues as the debate between view-based and structural description theories, the role of outline shape information in recognition judgements, and the relationship between mental rotation and object recognition. In addition, he currently has research projects investigating visual attention (particularly visual search) and human factors of the World Wide Web.
Evan Heit is on the faculty of the Psychology Department at the University of Warwick. Since obtaining his PhD from Stanford University in 1990, he has worked in three related areas of cognitive psychology: categorization, inductive reasoning and recognition memory. He is especially interested in issues that are relevant to two or more of these areas, such as the effects of prior knowledge, and psychological accounts that can be applied to two or more of these, such as Bayesian models.
Glyn W. Humphreys is Professor of Cognitive Psychology at the University of Birmingham. He has long-standing interests in high-level visual cognition, using converging data from experimental psychology, neuropsychology, computational modelling and functional brain imaging. He is the editor of the journal Visual Cognition and has received the British Psychological Society's Spearman and President Awards for research, along with the Cognitive Psychology Prize.
Woojae Kim is a graduate student in the Department of Psychology at the Ohio State University, Columbus, Ohio. His research interests include connectionist modelling of language learning, model selection methods, and Bayesian statistics.
Barbara J. Knowlton is an Associate Professor of Psychology at UCLA. Her research focuses on the neural substrates of memory and executive function. One of her main interests is the study of multiple forms of implicit learning, both in terms of psychological properties and supporting brain structures. Another interest is the role of the medial temporal lobe in the formation and retrieval of episodic memory.[Page ix]
John K. Kruschke is Professor of Psychology at Indiana University, Bloomington, where he has been employed since earning his PhD from the University of California at Berkeley in 1990. He studies how people allocate attention during simple learning tasks, and he creates mathematical models and computer simulations to rigorously test theories of attention in learning. He was a recipient of the Troland Research Award from the United States National Academy of Sciences in 2002, and has received teaching excellence awards from Indiana University.
Koen Lamberts is Professor of Psychology at the University of Warwick. Following his PhD at the University of Leuven (Belgium) in 1992, he was a postdoctoral research associate at the University of Chicago, and then moved to a lectureship at the University of Birmingham. He moved to Warwick in 1998, where he has been head of the Psychology Department since 2000. He has won the British Psychological Society's Cognitive Award (1996) and the Experimental Psychology Society Prize (1997). His research interests include mathematical models of cognitive processes in perceptual categorization and recognition memory.
Randi C. Martin is the Elma Schneider Professor of Psychology and Department Chair at Rice University where she has been a faculty member since 1982. Her research interests are in cognition and cognitive neuroscience, with a particular interest in language processing. Much of her research has been concerned with the nature of verbal short-term memory and its role in the comprehension, production and learning of language. She has also carried out studies on reading and spelling, semantic representation and executive function. In addition to behavioural studies with normal and brain-damaged populations, her recent work has included functional neuroimaging studies of language processing.
Craig R. M. McKenzie is Associate Professor of Psychology at the University of California, San Diego, where he has been since receiving his PhD from the University of Chicago in 1994. His research interests include inference, uncertainty and choice. Most of his recent research centres on how higher-order cognition is influenced by the predictable structure of our natural environment.
James M. McQueen is a member of the scientific staff at the Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands, where he has been since 1993. Prior to that appointment, he held a postdoctoral position at the MRC Applied Psychology Unit, Cambridge, UK. He studies spoken language processing, especially spoken word recognition. His research focuses on the way in which the information in the speech signal makes contact with stored lexical knowledge as we process spoken language, on how we perceive speech sounds, and on how we segment the acoustically continuous speech signal into discrete words during speech comprehension.
Jae I. Myung is Professor of Psychology at the Ohio State University, Columbus, Ohio. After completing his graduate study at Purdue University in 1990 and one-year postdoctoral work at the University of Virginia, he moved to Ohio State [Page x]in 1991 and has been there since. The focus of his recent research efforts has been on the development of statistical methods for testing and selecting among mathematical models of cognition, especially Bayesian inference methods and minimum description length.
Ian Neath is Professor of Psychology at Purdue University in West Lafayette, Indiana, where he has been on the faculty since receiving his PhD in 1991. His research interests focus on human memory as a discrimination problem, with remembering and forgetting reflecting the outcome of the discrimination decision. He is especially interested in distinctiveness models of memory as well as models of immediate memory. Both types of models account for memory performance without the concept of decay and both emphasize the functional importance of the type of processing.
Mike Oaksford is Professor of Experimental Psychology at Cardiff University, Wales, UK. He was a postdoctoral research fellow at the Centre for Cognitive Science, University of Edinburgh, and was then lecturer at the University of Wales, Bangor, and senior lecturer at the University of Warwick, before moving to Cardiff University in 1996. His research interests are in the area of human reasoning and decision making. In particular, with his colleague Nick Chater, he has been developing a Bayesian probabilistic approach to deductive reasoning tasks. According to this approach, reasoning ‘biases’ are the result of applying the wrong normative model and failing to take account of people's normal environment. He also studies the way the emotions affect and interact with reasoning and decision making processes.
Hans Op de Beeck is a postdoctoral associate in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology. He obtained his PhD at the University of Leuven (Belgium) in April 2003. His research focuses on the cognitive neuroscience of object recognition and categorization. Research topics include the effect of visual learning on object representations and the relation between object similarity and categorization. His work involves human and monkey subjects, and a range of methodologies (psychophysics, single-cell recordings and fMRI).
Mark A. Pitt is Professor of Psychology at Ohio State University. He began his academic career at OSU studying the age-old question of how memory influences perception. In particular, he sought to understand how knowledge of one's language (e.g. its words and linguistic structure) affects its perception. In 1995 this work led him to become interested in how to compare computational models of these and other psychological processes. Done in collaboration with his buddy down the hall, In Jae Myung, the early work has a Bayesian flavour and focused on quantifying the complexity of statistical models. Subsequent research probes the concept of complexity more deeply to obtain a richer understanding of model behaviour, the goal being to clarify the relationship between a model, the theory from which it was derived, and the experimental data being modelled. He cannot seem to make up his mind which topics he likes more, maths modelling or psycholinguistics, so he continues to study both.[Page xi]
Christopher J. Plack is Professor of Psychology at the University of Essex, Colchester, UK. He studied at the University of Cambridge before taking postdoctoral positions at the University of Minnesota in 1990 and at the University of Sussex in 1992. In 1994 he was awarded a Royal Society University Research Fellowship. He has been at Essex since 1998. In his research he uses psychophysical techniques to measure basic auditory processes, particularly those underlying the sensations of pitch and loudness, and the integration of information over time. He has also helped develop techniques for measuring the response of the basilar membrane in the human cochlea, the structure responsible for separating out the different frequency components of sounds.
Alexander Pollatsek is Professor of Psychology at the University of Massachusetts. His research interests are varied, including mathematical and statistical reasoning, visual perception and cognition, and applied areas such as driving safety. However, his major research interest is in language, and specifically, the process of reading. Most of this work is in collaboration with Keith Rayner and examines the process of reading using the pattern of eye movements while people read text, and many studies also involve making changes in the text when the reader's eyes are moving. This research has established that the area of text from which readers extract information is quite small, and also that phonological processing is routinely used–even by skilled readers. His recent research has explored the role of morphemes in word identification in English, Finnish and Hebrew.
Keith Rayner is Distinguished University Professor in the Psychology Department at the University of Massachusetts, Amherst. He was on the faculty at the University of Rochester from 1973 to 1978 prior to moving to the University of Massachusetts. He was Visiting Professor at the University of Oxford (1984-1985), an Invited Fellow at the Netherlands Institute for Advanced Study (1987-1988) and Leverhulme Visiting Professor at the University of Durham (2001-2002). His research interests are primarily in the area of skilled reading and language processing. With Alexander Pollatsek and other colleagues, he has used the eyemovement methodology to study various issues related to moment-to-moment processing. He was editor of the Journal of Experimental Psychology: Learning, Memory, and Cognition from 1990 to 1995, and is currently editor of Psychological Review.
M. Jane Riddoch is a Professor in Cognitive Neuropsychology at the University of Birmingham. She has been a member of the faculty in the School of Psychology, University of Birmingham, since 1989. Her research interests focus on visual attention (grouping processes in perceptual organization and their interaction with visual attention), space processing (investigation of the neural mechanisms involved in space perception and cognition), mental imagery (investigations into the equivalence of mental imagery and visual perception), shape and object recognition (investigations into the nature of processing underlying object recognition) and vision and action (investigations into how visual information is used in the selection of actions to objects).[Page xii]
David R. Shanks is Professor of Experimental Psychology and Head of the Psychology Department at University College London, and is also Scientific Director of the ESRC Centre for Economic Learning and Social Evolution, UCL. His research interests cover human learning, memory and decision making. He is particularly interested in the use of broad computational models that deploy a small set of fundamental principles such as error correction to elucidate a range of mental processes. An example is the use of connectionist models to simulate category learning, amnesia, probability judgement and choice behaviour. He is the author of The Psychology of Associative Learning (Cambridge University Press, 1995).
Aimée M. Surprenant is an Associate Professor in the Department of Psychological Sciences at Purdue University, in West Lafayette, Indiana. She received a BA in psychology from New York University in 1988 and a PhD in cognitive psychology from Yale University in 1992. She received a National Research Service Award from the National Institutes of Health for postdoctoral work at Indiana University in the Department of Speech and Hearing Sciences. Her research focuses on the effects of noise on the perception of and memory for auditorily presented information.
Michael J. Tarr is the Fox Professor of Ophthalmology and Visual Sciences in the Department of Cognitive and Linguistic Sciences at Brown University (Providence, Rhode Island). Prior to that he was a professor at Yale University. His research focuses on mid- and high-level visual processing in the primate brain. The basic question he would like to answer is ‘How does vision make sense of the world around us?’ Current interests aimed at answering this question include the types of visual inferences made about lighting in the environment, the role of surface properties in object recognition, and the nature of processing in domains of perceptual expertise (including face recognition). When not pondering such problems, he is often riding his bike or playing in his wood shop.
Johan Wagemans is Professor in Psychology at the University of Leuven, Belgium. He has been visiting professor at the University of Nijmegen, The Netherlands, and at the University of Virginia. His research interests are all in visual perception, mainly in perceptual organization (e.g. grouping, symmetry, subjective contours), shape perception (e.g. picture identification, categorization, 3-D objects) and depth perception (e.g. texture, motion, stereo). He has interdisciplinary research projects with neuroscientists and computer vision engineers. He has published about 70 papers in international research journals and is currently editor of Acta Psychologica.
Edward A. Wasserman is the Stuit Professor of Experimental Psychology at the University of Iowa. He received his PhD from Indiana University in 1972 and was a postdoctoral associate at the University of Sussex. His research programme includes the comparative analysis of learning, memory and cognition, with special interests in causation, conceptualization and visual perception. His most recent [Page xiii]work has studied the recognition of objects by pigeons, and the discrimination of variability by pigeons, baboons and humans.
Felix A. Wichmann is a research scientist and head of the Computational Vision Laboratory in the Empirical Inference Department of the Max Planck Institute for Biological Cybernetics in Tübingen, Germany. He did his undergraduate studies and received his doctorate from the University of Oxford, UK, and was a Junior Research Fellow at Magdalen College. Prior to moving to the MPI in Tübingen he was a postdoctoral visiting fellow at the University of Leuven, Belgium. His main interests are quantitative models of spatial vision and the implications of natural image statistics for models of human vision. Recently, he has begun to explore the application of machine learning methods to problems of human categorization.
Alan M. Wing is Professor of Human Movement in the School of Psychology at the University of Birmingham. He heads the Sensory Motor Neuroscience group in the interdisciplinary Brain Behavioural Science Centre. Previously he was Assistant Director at the MRC Applied Psychology Unit in Cambridge. He has published widely on motor psychophysics of normal and impaired control of movement and balance, including three edited volumes. His current research includes reactive and predictive control of movement of the upper and lower limbs, active touch, rhythm and timing.
Denise H. Wu is a postdoctoral research fellow at the Center for Cognitive Neuroscience, University of Pennsylvania. She studied in the Psychology Department at Rice University and received her PhD in January 2003. Her research mainly concentrates on long-term linguistic representation, verbal short-term memory and the interaction between the two. She has studied reading mechanisms with brain-damaged patients. She has also employed the functional neuroimaging technique to examine the neural substrates of semantic and phonological short-term memory. Her current research focuses on processing of action and verbs.
Michael E. Young is an Assistant Professor of Psychology and Director of the Brain and Cognitive Sciences programme at Southern Illinois University at Carbondale. He received his PhD from the University of Minnesota and was a postdoctoral associate at the University of Iowa. His research interests include the perception of stimulus variability and the psychology of causal learning and perception. His most recent work incorporates models of visual search into models of variability discrimination and explores the impact of temporal predictability on causal judgements.
The author and publishers wish to thank the following for permission to use copyright material:
Wandell, 1995, Foundations of Vision, Fig 7.16, p. 222. Sunderland MA: Sinauer
Adelson, E. H., & Bergen, J. R. (1991). ‘The plenoptic function and the elements of early vision’, Fig 1.8, in, Landy, M. S., & Movshon A. (Eds.), Computational Models of Visual Processing. Cambridge MA: MIT Press
Adelson, E. H., & Bergen, J. R. (1991). ‘The plenoptic function and the elements of early vision’, Fig 1.14, in, Landy, M. S., & Movshon A. (Eds.), Computational Models of Visual Processing. Cambridge MA: MIT Press
Adelson, E. H., & Bergen, J. R. (1991). ‘The plenoptic function and the elements of early vision’, Fig 1.15, in, Landy, M. S., & Movshon A. (Eds.), Computational Models of Visual Processing. Cambridge MA: MIT Press
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Reprinted from Cognitive Psychology, Vol 21(2). Tarr, M. J., & Pinker ‘Mental Rotation and Orientation-Depdence in Shape’, Fig 1, p. 243, and Fig 6, p. 255, 1989, with permission from Elsevier.[Page xv]
Biederman, I., & Cooper (1991), ‘Priming Counter-Deleted Images: Evidence for Intermediate Representations in Visual Object Recognition’, Fig 1, Cognitive Psychology, 23(3). Elsevier
Every effort has been made to trace all the copyright holders, but if any have been overlooked or if any additional information can be given the publishers will make the necessary amendments at the first opportunity.
This book aims to provide an overview of current theory and research in cognitive psychology. Of course, it is quite a challenge to capture the essence of such a large and active research area in a single volume. There is so much to be said about cognition and cognitive psychology that any overview must be selective. Nevertheless, we have tried to produce a text that is as comprehensive as possible, and yet provides sufficient depth to satisfy a more specialist audience.
This Handbook is not an introduction to cognitive psychology. We presume that the reader already has a background in cognitive psychology or cognitive science. The chapters are intended to introduce specialist areas of the field to advanced students and researchers. The advanced level of the text also implies that difficult or controversial topics have not been avoided, as is so often the case in introductory textbooks. In addition, the authors have often presented a personal view on what they see as the most important issues in their field. We hope that this approach will benefit the reader who wants to get a thorough update on the true state-of-the-art in perhaps less familiar areas of cognitive psychology.
Although the following nineteen chapters cover a wide range of topics, they are unified in teaching us not to take ourselves for granted. Each one of us is cognitively more impressive than it would seem when we are struggling to recollect our best friend's sister's name. Even in an age of unprecedented technological advances, most of us would be sceptical if we were told of a single machine that was able to speak English fluently, learn to understand a new language within three years, efficiently store any number of different data structures (e.g. images, songs, facial expressions, words, odours, etc.), recognize familiar faces within a half a second, play a reasonable game of chess, learn how to play new games, fix a bicycle, and answer various posed questions in mathematics and poetry interpretation. Yet we are all existent proofs of the possibility of such machines. We do it all, and in most cases do it better than special-purpose machines designed to perform only one of the above tasks. People tend to focus on individual differences. We may wonder why we are so poor at spatial navigation compared to others, and be impressed at an acquaintance's memory span. Upon further reflection, the sophisticated cognitive equipment shared by all people is even more striking. Understanding the nature of this shared equipment is a worthy enterprise, and one that is adroitly undertaken by the chapters here.
The Handbook is divided into six parts. The division is thematic and methodological. The first four parts each cover a broad aspect of cognition, whereas the final two sections group together chapters that have a common methodological focus.
Part I (Perception, Attention and Action) contains five chapters. Wagemans, Wichmann and Op de Beeck give a broad introduction to visual perception. They [Page xvii]review a number of classic studies that fit within the ‘measurement approach’ to low-level vision, which is concerned with finding systematic laws that relate objective stimulus characteristics to subjective impressions. They also discuss the natural image statistics approach, and indicate how this complements the measurement approach. Their overview then proceeds to mid-level vision, focusing on how vision creates psychologically meaningful internal representations. Finally, they examine the offerings of two radically different viewpoints on perception, Gestalt psychology and Gibson's ecological approach.
The chapter by Hayward and Tarr focuses on high-level vision, addressing the question of how we see objects. The low- and mid-level processes discussed by Wagemans et al. ultimately serve the main purpose of vision, which is to create an adequate representation of the environment and the objects it contains. Hayward and Tarr discuss the processes that underlie our ability to recognize objects, despite variations in viewing conditions (such as luminance, viewpoint, etc.) or object features. They discuss the merits of multiple-view theories of object recognition (in which it is assumed that recognition is achieved through combination of information from specific object views stored in memory) and structural description theories (which assume that recognition proceeds on the basis of viewpoint-independent structural object models in memory). Together, the first two chapters provide a comprehensive overview of some of the most important and challenging issues in current research on visual perception.
In the third chapter, Plack takes us on an extensive tour of auditory perception. He introduces the physiology of the auditory system, followed by a detailed discussion of the processes involved in loudness perception, pitch perception, temporal resolution (which is the ability to follow changes in a sound over time), sound localization, auditory scene analysis and auditory object identification. The chapter highlights the challenges posed by each of these tasks, and thereby conveys just how sophisticated and complex auditory perception really is.
Bundesen and Habekost's chapter on attention deals with the selectivity of perception. At any time, the perceiver focuses only on certain aspects of the environment, thereby excluding other aspects. The question is how such selectivity can be achieved. Bundesen and Habekost explore a wide range of theories that aim to address this problem, from the early filter models of the 1950s to recent mathematical and computational theories of attention. They also review the experimental results that have supported different theoretical proposals. Attention research is an area of cognitive psychology that has witnessed remarkable cumulative theory development in a relatively short time. The chapter gives an insight into the empirical and conceptual underpinnings of this development.
In the fifth chapter in Part I, Delevoye-Turrell and Wing present an overview of the mechanisms that control actions and motor behaviour. They demonstrate how motor actions depend on goals, environmental constraints and knowledge of effector limits. Motor control involves the integration of these different sources of information. Delevoye-Turrell and Wing discuss in great depth how the notions of control and feedback are essential for understanding motor actions. For example, they analyse reactions to unpredictable events, showing that the central nervous system can rapidly use incoming sensorimotor and visual information to adjust [Page xviii]ongoing movements. Perceptual information constantly feeds into motor processes, providing information about the context for movement, about errors in attaining movement targets, and about the effects of movements on the environment.
Part II (Learning and Memory) contains four chapters. The distinction between learning and memory as areas of research is somewhat artificial (learning clearly involves memory, and all memory tasks require initial learning), but because they have each generated distinctive research programmes, it seemed appropriate to maintain the division in the Handbook. At the same time, the four chapters in this section show the close links that exist between research on learning and memory. In their chapter on theories of learning, Young and Wasserman start with an overview of the major empirical findings that must be explained by theories of learning. They discuss the role of time (including the notions of contiguity and contingency), competition among predictors (which occurs in blocking and the relative validity effect), configural learning (which involves acquisition of information about entire sets of features, events or cues), generalization and similarity, and unlearning. In the second part of their chapter, Young and Wasserman introduce a number of theories of learning. They make a distinction between theories of supervised learning (in which feedback leads to a reduction of the discrepancy between actual and ideal responses) and unsupervised learning (in which statistical regularities in the environment are detected and represented, without being driven by the aim to reach some explicit performance target). They end with a plea for greater integration between different fields of cognitive psychology that all address issues related to learning.
Kruschke's chapter on category learning addresses the question of how we learn to group things together in categories. Categorization lends structure, simplicity and predictability to the mental representation of our environment. Kruschke shows that contemporary theories of categorization vary on how categories are assumed to be represented, on how abstract the representations of categories are supposed to be, and on how they assume that stored category information is used to categorize new stimuli. He reviews instances of each type of theory, discusses the roles of rules and similarity, investigates the relation between categorization and induction, and emphasizes the importance of attention for a comprehensive theory of category learning.
In the chapter on implicit learning, Shanks reviews empirical and theoretical research into learning that proceeds both unintentionally and unconsciously. He investigates the empirical and conceptual basis of claims for implicit learning, and asks whether implicit learning should be seen as independent from explicit learning. He also presents a critical review of a common technique for the study of implicit learning (the dissociation technique). Shanks concludes that it has not yet been proved that truly unintentional and unconscious learning exists, although the empirical studies that have given rise to claims about implicit learning have raised many important questions.
In their chapter on the mechanisms of memory, Neath and Surprenant discuss a number of general principles that apply to all memory tasks. They discuss the importance of interactions between encoding and retrieval, task purity, forgetting and interference, retrieval cues, constructive and reconstructive processes, and [Page xix]false memory. They outline and review the principles of three basic conceptions of memory: the systems view, the processing view and the functional view.
Part III (Language) contains three chapters on different aspects of language processing. Garnham reviews language comprehension. Language comprehension can be studied at different levels. The chapter starts with a discussion of (written) word recognition, showing that word recognition is sensitive to a large number of variables (such as frequency, regularity, etc.). Garnham then moves on to how we understand groups of words (syntactic processing), discussing various issues related to the derivation of meaning from sentences. Finally, he provides an extensive discussion of how we understand discourse and text, presenting mental models theory and its alternatives.
Speech perception is the focus of the chapter by McQueen. He explains how spoken word recognition involves a complex decoding problem, and argues that spoken word perception involves the simultaneous evaluation of multiple, competing lexical hypotheses. He also presents evidence for phonetic analysis of speech prior to lexical processing, and he discusses several models of speech perception.
Pollatsek and Rayner's chapter is devoted to reading, focusing primarily on the processes involved in word identification. They present an overview of the methods that are used to study reading, including brief presentation of stimuli, speeded naming and examination of eye movements. Pollatsek and Rayner further discuss the relation between encoding of letters and encoding of words, the role of auditory coding in word identification, and the speed and automaticity of identifying words. A large part of the chapter addresses eye movements in reading, with discussion of topics such as perceptual span, parafoveal preview and computational modelling of eye movements.
Part IV (Reasoning and Decision Making) contains two chapters on reasoning and decision making. Chater, Heit and Oaksford review the reasoning literature. Reasoning refers to inferential processing that derives verbally stated conclusions from premises. The chapter first introduces a number of issues related to form and content of arguments. The authors then describe Wason's classical studies with the selection task, which were among the first to cast doubt on the assumption that humans are generally rational. They present four approaches to explaining deductive reasoning, and provide an overview of data and theories of inductive reasoning.
McKenzie gives an overview of research on decision making. In the 1960s, it was widely assumed that normative statistical models provided a good basis for understanding human choice. This view was challenged in the 1970s, mainly under the impulse of Kahneman and Tversky's groundbreaking work on heuristics and biases in decision making. Since the 1990s, it has become increasingly clear that studying decision making independent of environmental considerations can lead to misleading conclusions. Much of the chapter is devoted to the context or environment in which decisions are made. McKenzie shows that seemingly irrational decisions turn out to be adaptive when their environmental context is taken into account.
The three chapters in Part V (Cognitive Neuropsychology) have a common methodological focus. Each chapter in this section gives an overview of an area of cognitive neuropsychology. The chapters revisit many issues that have also been addressed in the previous sections, but they do so from a different perspective. The [Page xx]chapters demonstrate just how much can be learned from the study of patients with selective disturbances of a cognitive ability, and how data from such patients can lead to surprising new insights about normal cognition. The three chapters complement the first three parts of the Handbook (focusing on perception, memory and language, respectively–the neuropsychology of reasoning and decision making is far less established than these three areas).
Humphreys and Riddoch review the cognitive neuropsychology of object recognition and action. They discuss the implications of impairments in object recognition for our understanding of high-level vision. Patient data have challenged traditional views of object recognition, and opened up new avenues of investigation. Humphreys and Riddoch also discuss differences between recognition of objects, faces and words, the links between objects and actions, and computational models of object recognition and action.
Knowlton discusses the cognitive neuropsychology of learning and memory. She reviews how studies of patients with amnesia supports a distinction between implicit and explicit memory, and touches upon a number of issues related to this fundamental distinction. She also discusses the logic of double dissociations, Alzheimer's disease and dementia, frontotemporal dementia, the role of the frontal lobes in memory, memory and ageing, and the relation between neuropsychology and functional neuroimaging.
Martin and Wu review the cognitive neuropsychology of language. They discuss neuropsychological data and theoretical issues with regard to the comprehension and production of single words and sentences. They also review the neuropsychology of reading and spelling and the interaction between syntactic and semantic processing.
Part VI (Modelling Cognition) contains two chapters that discuss various aspects of formal modelling of cognitive processes. Formal modelling has become firmly established as a standard technique in cognitive psychology. Lamberts provides a basic introduction to mathematical models of cognition. He discusses the different types of models that can be constructed, and explains what model parameters are and how their values can be estimated using goodness-of-fit criteria. The chapter ends with a discussion of formal modelling as a tool for data analysis. Myung, Pitt and Kim's chapter offers a more advanced discussion of several central issues in formal modelling of cognition. They review model specification and parameter estimation, and focus extensively on model evaluation and model testing. They introduce the concepts of model complexity and model generalizability. Model selection is also treated in considerable depth. Together, the two chapters on modelling cognition offer an accessible and yet advanced overview of the principles of formal modelling.
As will be clear from this overview, this Handbook is the result of the joint efforts of a large number of people. We thank all of the contributors to the volume, as well as the referees who provided invaluable feedback and advice. We are deeply grateful for the enthusiasm and dedication of everyone who was involved in the project.
Robert L. Goldstone