The most important distinction derived from the computational view of thought is between structures and processes. So proclaimed Farah and Kosslyn in 1982, arguing that structures and processes cannot be examined in isolation and concluding that converging operations are required to isolate the structure-process pair that can explain a particular finding. The distinction between structure and process within the study of percepts, concepts and categories is considered in depth in this volume, with penetrating commentaries by fellow authors concluding each chapter. This interesting format achieves a broad coverage of the various aspects and implications of the structure-process distinction. It affords a salient indication of the diversity of positions as to the description and utility of distinguishing structures and processors. At the same time, it reveals that researchers specializing in areas of study ranging from simple structure and process involved in perceptual organization and texture to complex structure and process associated with reading graphs and chess expertise, do utilize such a distinction in similar ways. The analysis is organized into four major parts within the book: Early Visual Representation and Processing; Percepts, Concepts, Categories and Development; Categories, Concepts and Learning; and Higher-Order Representation and Processing.

This text brings together an overview of recent research on concepts and knowledge that abstracts across a variety of specific fields of cognitive psychology. Readers will find data from many different areas, including developmental psychology, formal modelling, neuropsychology and connectionism.

Whether or not infants' earliest perception of the world is a "blooming, buzzing, confusion," it is not long before they come to perceive structure and order among the objects and events around them. At the core of this process, and cognitive development in general, is the ability to categorize--to group events, objects, or properties together--and to form mental representations, or concepts, that encapsulate the commonalities and structure of these categories. Categorization is the primary means of coding experience, underlying not only perceptual and reasoning processes, but also inductive inference and language. The aim of this book is to bring together the most recent findings and theories about the origins and early development of categorization and conceptual abilities. Despite recent advances in our understanding of this area, a number of hotly debated issues remain at the center of the controversy over categorization. Researchers continue to ask questions such as: Which mechanisms for categorization are available at birth and which emerge later? What are the relative roles of perceptual similarity and nonobservable properties in early classification? What is the role of contextual variation in categorization by infants and children? Do different experimental procedures reveal the same kind of knowledge? Can computational models simulate infant and child categorization? How do computational models inform behavioral research? What is the impact of language on category development? How does language partition the world? This book is the first to address these and other key questions within a single volume. The authors present a diverse set of views representing cutting-edge empirical and theoretical advances in the field. The result is a thorough review of empirical contributions to the literature, and a wealth of fresh theoretical perspectives on early categorization.

Connectionist Models of Cognition and Perception collects together refereed versions of twenty-three papers presented at the Seventh Neural Computation and Psychology Workshop (NCPW7). This workshop series is a well-established and unique forum that brings together researchers from such diverse disciplines as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their latest work on connectionist modelling in psychology.The articles have the main theme of connectionist modelling of cognition and perception, and are organised into six sections, on: cell assemblies, representation, memory, perception, vision and language. This book is an invaluable resource for researchers interested in neural models of psychological phenomena.

Within cognitive science, two approaches currently dominate the problem of modeling representations. The symbolic approach views cognition as computation involving symbolic manipulation. Connectionism, a special case of associationism, models associations using artificial neuron networks. Peter Gärdenfors offers his theory of conceptual representations as a bridge between the symbolic and connectionist approaches. Symbolic representation is particularly weak at modeling concept learning, which is paramount for understanding many cognitive phenomena. Concept learning is closely tied to the notion of similarity, which is also poorly served by the symbolic approach. Gärdenfors's theory of conceptual spaces presents a framework for representing information on the conceptual level. A conceptual space is built up from geometrical structures based on a number of quality dimensions. The main applications of the theory are on the constructive side of cognitive science: as a constructive model the theory can be applied to the development of artificial systems capable of solving cognitive tasks. Gärdenfors also shows how conceptual spaces can serve as an explanatory framework for a number of empirical theories, in particular those concerning concept formation, induction, and semantics. His aim is to present a coherent research program that can be used as a basis for more detailed investigations.

This book examines a key issue in current cognitive theories - the nature of representation. Each chapter is characterized by attempts to frame hot topics in cognitive development within the landscape of current developmental theorizing and the past legacy of genetic epistemology. The chapters address four questions that are fundamental to any developmental line of inquiry: How should we represent the workings and contents of the mind? How does the child construct mental models during the course of development? What are the origins of these models? and What accounts for the novelties that are the products and producers of developmental change? These questions are situated in a historical context, Piagetian theory, and contemporary researchers attempt to trace how they draw upon, depart from, and transform the Piagetian legacy to revisit classic issues such as the child's awareness of the workings of mental life, the child's ability to represent the world, and the child's growing ability to process and learn from experience. The theoretical perspectives covered include constructivism, connectionism, theory-theory, information processing, dynamical systems, and social constructivist approaches. The research areas span imitation, mathematical reasoning, biological knowledge, language development, and theory of mind. Written by major contributors to the field, this work will be of interest to students and researchers wanting a brief but in-depth overview of the contemporary field of cognitive development.

Leading scholars examine the relationship between child language acquisition and cognitive development.

A comprehensive overview of what psychologists now know about the nature of cognition Principles of Cognition provides students with an invaluable introduction to the modern science of cognition, blending invaluable insights from behavioral and neuroscientific studies of humans and other animals with unique examples, cutting-edge research summaries, and real-world applications. This accessible textbook builds on the legacy of psychologist William James by emphasizing not only the form cognition takes in laboratory research but also the functional dynamics of cognitive processes in everyday life and the ways they vary across individuals and species. Using an integrative approach that highlights the relevance of cognition across psychological disciplines, it engages students by showing how cognition emerges over time, how cognitive abilities can be improved, and how thinking can be upended by something as simple as falling in love. Discusses topics in cognition rarely covered by other textbooks, including perception of time and space, consciousness, animal cognition, mathematical and reading skills, emotions, intelligence, generalization, and social cognition Emphasizes learning and its interactions with memory and cognition Features practical applications from cognitive research in every chapter Connects topics across chapters to promote retention and critical thinking Draws on the latest experimental, naturalistic, and applied research Integrates findings about animals and children with traditional studies of adults to develop a more neurally grounded framework for thinking about the mechanisms of cognition An ideal textbook for undergraduate and graduate classrooms

Now available in paperback. This revised and updated edition of the definitive resource for experimental psychology offers comprehensive coverage of the latest findings in the field, as well as the most recent contributions in methodology and the explosion of research in neuroscience. Volume Two: Memory and Cognitive Processes, focuses on the neurological and cognitive processes on topics such as memory, decision-making, spatial cognition, linguistics, reasoning, and concepts.

The purpose of the book is to advance in the understanding of brain function by defining a general framework for representation based on category theory. The idea is to bring this mathematical formalism into the domain of neural representation of physical spaces, setting the basis for a theory of mental representation, able to relate empirical findings, uniting them into a sound theoretical corpus. The innovative approach presented in the book provides a horizon of interdisciplinary collaboration that aims to set up a common agenda that synthesizes mathematical formalization and empirical procedures in a systemic way. Category theory has been successfully applied to qualitative analysis, mainly in theoretical computer science to deal with programming language semantics. Nevertheless, the potential of category theoretic tools for quantitative analysis of networks has not been tackled so far. Statistical methods to investigate graph structure typically rely on network parameters. Category theory can be seen as an abstraction of graph theory. Thus, new categorical properties can be added into network analysis and graph theoretic constructs can be accordingly extended in more fundamental basis. By generalizing networks using category theory we can address questions and elaborate answers in a more fundamental way without waiving graph theoretic tools. The vital issue is to establish a new framework for quantitative analysis of networks using the theory of categories, in which computational neuroscientists and network theorists may tackle in more efficient ways the dynamics of brain cognitive networks. The intended audience of the book is researchers who wish to explore the validity of mathematical principles in the understanding of cognitive systems. All the actors in cognitive science: philosophers, engineers, neurobiologists, cognitive psychologists, computer scientists etc. are akin to discover along its pages new unforeseen connections through the development of concepts and formal theories described in the book. Practitioners of both pure and applied mathematics e.g., network theorists, will be delighted with the mapping of abstract mathematical concepts in the terra incognita of cognition.