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A collection of leading models of how the human brain encodes for the memory of the items that surround us.
A mechanistic theory of the representation and use of semantic knowledge that uses distributed connectionist networks as a starting point for a psychological theory of semantic cognition.
Humans have a unique ability to understand the beliefs, emotions, and intentions of others—a capacity often referred to as mentalizing. Much research in psychology and neuroscience has focused on delineating the mechanisms of mentalizing, and examining the role of mentalizing processes in other domains of cognitive and affective functioning. The purpose of the book is to provide a comprehensive overview of the current research on the mechanisms of mentalizing at the neural, algorithmic, and computational levels of analysis. The book includes contributions from prominent researchers in the field of social-cognitive and affective neuroscience, as well as from related disciplines (e.g., cognitive, social, developmental and clinical psychology, psychiatry, philosophy, primatology). The contributors review their latest research in order to compile an authoritative source of knowledge on the psychological and brain bases of the unique human capacity to think about the mental states of others. The intended audience is researchers and students in the fields of social-cognitive and affective neuroscience and related disciplines such as neuroeconomics, cognitive neuroscience, developmental neuroscience, social cognition, social psychology, developmental psychology, cognitive psychology, and affective science. Secondary audiences include researchers in decision science (economics, judgment and decision-making), philosophy of mind, and psychiatry.
The advent of modern investigative techniques to explore brain function has led to major advances in understanding the neural organization and mechanisms associated with semantic memory. This book presents current theories by leading experts in the field on how the human nervous system stores and recalls memory of objects, actions, words and events. Chapters range from models of a specific domain or memory system (e.g., lexical-semantic, sensorimotor, emotion) to multiple modality accounts; from encompassing memory representations, to processing modules, to network structures, focusing on studies of both normal individuals and those with brain disease. Recent advances in neuro-exploratory techniques allow for investigation of semantic memory mechanisms noninvasively in both normal healthy individuals and patients with diffuse or focal brain damage. This has resulted in a significant increase in findings relevant to the localization and mechanistic function of brain regions engaged in semantic memory, leading to the neural models included here.
An authoritative, up-to-date survey of the state of the art in cognitive science, written for non-specialists.
Handbook of Categorization in Cognitive Science, Second Edition presents the study of categories and the process of categorization as viewed through the lens of the founding disciplines of the cognitive sciences, and how the study of categorization has long been at the core of each of these disciplines. The literature on categorization reveals there is a plethora of definitions, theories, models and methods to apprehend this central object of study. The contributions in this handbook reflect this diversity. For example, the notion of category is not uniform across these contributions, and there are multiple definitions of the notion of concept. Furthermore, the study of category and categorization is approached differently within each discipline. For some authors, the categories themselves constitute the object of study, whereas for others, it is the process of categorization, and for others still, it is the technical manipulation of large chunks of information. Finally, yet another contrast has to do with the biological versus artificial nature of agents or categorizers. - Defines notions of category and categorization - Discusses the nature of categories: discrete, vague, or other - Explores the modality effects on categories - Bridges the category divide - calling attention to the bridges that have already been built, and avenues for further cross-fertilization between disciplines
It is only relatively recently that it has been possible to study the neural processes that might underlie working memory, leading to a proliferation of research in this domain. This volume brings together leading researchers from around the world to summarise current knowledge of this field.
‘Behavioral Neuroscience of Learning and Memory’ brings together the opinions and expertise of some of the world’s foremost neuroscientists in the field of learning and memory research. The volume provides a broad coverage of contemporary research and thinking in this field, focusing both on well established topics such as the medial temporal lobe memory system, as well as emerging areas of research such as the role of memory in decision making and the mechanisms of perceptual learning. Key intersecting themes include the molecular and cellular mechanisms of memory formation, the multiplicity of memory systems in the brain, and the way in which technological innovation is driving discovery. Unusually for a volume of this kind, this volume brings together research from both humans and animals—often relatively separate areas of discourse—to give a more comprehensive and integrated view of the field. The book will be of interest to both established researchers who wish to broaden their knowledge of topics outside of their specific areas of expertise, and for students who need a resource to help them make sense of the vast scientific literature on this subject.
This handbook is an essential, comprehensive resource for students and academics interested in topics in cognitive psychology, including perceptual issues, attention, memory, knowledge representation, language, emotional influences, judgment, problem solving, and the study of individual differences in cognition.
How is information stored and retrieved from long-term memory? It is argued that any systematic attempt to answer this question should be based on a particular set of specific representational assumptions that have led to the development of a new memory theory -- the connectivity model. One of the crucial predictions of this model is that, in sharp contrast to traditional theories, the speed of processing information increases as the amount and complexity of integrated knowledge increases. In this volume, the predictions of the model are examined by analyzing the results of a variety of different experiments and by studying the outcome of the simulation program CONN1, which illustrates the representation of complex semantic structures. In the final chapter, the representational assumptions of the connectivity model are evaluated on the basis of neuroanatomical and physiological evidence -- suggesting that neuroscience provides valuable knowledge which should guide the development of memory theories.