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Gateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology)

Posted on 2010-04-28




Name:Gateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology)
ASIN/ISBN:0262571528
Author:Mark A. Gluck, Catherine E. Myers
Publisher:The MIT Press (2001)
Pages:Paperback, 464 pages
File size:69.69 Mb
   Gateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology)


Author: Mark A. Gluck, Catherine E. Myers


Publisher: The MIT Press (2001)


Binding: Paperback, 464 pages


pricer: $27.00


ISBN-10: 0262571528


editorialreviews

"Gateway to Memory is an exciting and badly needed text that integrates computational and neurobiological approaches to memory. Authoritative and clearly written, this book will be valuable for students and researchers alike." -- Daniel L. Schacter, Professor and Chair of Psychology, Harvard University, and author of Searching for Memory This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning. It emphasizes the function of brain structures as they give rise to behavior, rather than the molecular or neuronal details. It also emphasizes the process of modeling, rather than the mathematical details of the models themselves. The book is divided into two parts. The first part provides a tutorial introduction to topics in neuroscience, the psychology of learning and memory, and the theory of neural network models. The second part, the core of the book, reviews computational models of how the hippocampus cooperates with other brain structures--including the entorhinal cortex, basal forebrain, cerebellum, and primary sensory and motor cortices--to support learning and memory in both animals and humans. The book assumes no prior knowledge of computational modeling or mathematics. For those who wish to delve more deeply into the formal details of the models, there are optional "mathboxes" and appendices. The book also includes extensive references and suggestions for further readings.




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