This volume provides an overview of a relatively neglected branch of connectionism known as localist connectionism. The singling out of localist connectionism is motivated by the fact that some critical modeling strategies have been more readily applied in the development and testing of localist as opposed to distributed connectionist models (models using distributed hidden-unit representations and trained with a particular learning algorithm, typically back-propagation). One major theme emerging from this book is that localist connectionism currently provides an interesting means of evolving from verbal-boxological models of human cognition to computer-implemented algorithmic models. The other central messages conveyed are that the highly delicate issue of model testing, evaluation, and selection must be taken seriously, and that model-builders of the localist connectionist family have already shown exemplary steps in this direction.

This volume provides an overview of a relatively neglected branch of connectionism known as localist connectionism. The singling out of localist connectionism is motivated by the fact that some critical modeling strategies have been more readily applied in the development and testing of localist as opposed to distributed connectionist models (models using distributed hidden-unit representations and trained with a particular learning algorithm, typically back-propagation). One major theme emerging from this book is that localist connectionism currently provides an interesting means of evolving from verbal-boxological models of human cognition to computer-implemented algorithmic models. The other central messages conveyed are that the highly delicate issue of model testing, evaluation, and selection must be taken seriously, and that model-builders of the localist connectionist family have already shown exemplary steps in this direction.

This book is a condensation of a large body of work concerning human learning carried out over a period of more than five years by Dr. Sun and his collaborators. In a nutshell, this work is concerned with a broad framework for studying human cognition based on a new approach that is characterized by its focus on the dichotomy of, and the interaction between, explicit and implicit cognition and a computational model that implements this framework. In this work, a broad, generic computational model was developed that instantiates Dr. Sun's framework and enables the testing of his theoretical approach in a variety of ways. With this model, simulation results were matched with data of human cognition in a variety of different domains. Formal (mathematical and computational) analyses were also carried out to further explore the model and its numerous implementational details. Furthermore, this book addresses some of the most significant theoretical issues, such as symbol grounding, intentionality, social cognition, consciousness, and other theoretical issues in relation to the framework. The general framework and the model developed generate interesting insights into these theoretical issues.

Many of our thoughts and decisions occur without us being conscious of them taking place; connectionism attempts to reveal the internal hidden dynamics that drive the thoughts and actions of both individuals and groups. Connectionist modeling is a radically innovative approach to theorising in psychology, and more recently in the field of social psychology. The connectionist perspective interprets human cognition as a dynamic and adaptive system that learns from its own direct experiences or through indirect communication from others. Social Connectionism offers an overview of the most recent theoretical developments of connectionist models in social psychology. The volume is divided into four sections, beginning with an introduction and overview of social connectionism. This is followed by chapters on causal attribution, person and group impression formation, and attitudes. Each chapter is followed by simulation exercises that can be carried out using the FIT simulation program; these guided exercises allow the reader to reproduce published results. Social Connectionism will be invaluable to graduate students and researchers primarily in the field of social psychology, but also in cognitive psychology and connectionist modeling.

Implicit memory refers to a change in task performance due to an earlier experience that is not consciously remembered. The topic of implicit memory has been studied from two quite different perspectives for the past 20 years. On the one hand, researchers interested in memory have set out to characterize the memory system (or systems) underlying implicit memory, and see how they relate to those underlying other forms of memory. The alternative framework has considered implicit memory as a by-product of perceptual, conceptual, or motor systems that learn. That is, on this view the systems that support implicit memory are heavily constrained by pressures other than memory per se. Both approaches have yielded results that have been valuable in helping us to understand the nature of implicit memory, but studied somewhat in isolation and with little collaboration. This volume is unique in explicitly contrasting these approaches, bringing together world class scientists from both camps in an attempt to forge a new approach to understanding one of the most exciting and important issues in psychology and neuroscience. Written for postgraduate students and researchers in cognitive psychology and cognitive neuroscience, this is a book that will have an important influence on the direction that future research in this field takes.

This book brings together current research findings on the involvement of word-internal structure for the purpose of word reading (especially morphological structure). The central theme of reading complex words is approached from several angles, such that the chapters span a wide variety of topics where this issue is important. It is a valuable resource for all researchers studying the mental lexicon and to those who teach advanced courses in the psychology of language.

This book is divided into five sections dealing with various fundamental issues in current research: attention, information processing and eye movement control; the role of phonology in reading; syntax and discourse processing and computational models and simulations. Control and measurement of eye movements form a prominent theme in the book. A full understanding of the where and when of eye movement control is a prerequisite of any complete theory of reading, since it is precisely at this point that perceptual and cognitive processes interact. Amongst the 'hot topics' included are the relation between parafoveal and foveal visual processing of linguistic information, the role of phonology in fluent reading and the emergence of statistical 'tuning' approaches to sentence parsing. Also discussed in the book are three attempts to develop quantitative models of reading which represent a significant departure in theory-building and a quantum step in the maturation of reading research. Much of the work reported in the book was first presented at the 5th European Workshop on Language Comprehension organised in April 1998 which was held at the CNRS Luminy Campus, near Marseilles. All contributions summarise the state-of-the-art in the relevant areas of reading research.