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" Introduction to neural and cognitive modeling / "
Daniel S. Levine.
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BL
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| Record Number
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857041
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| Main Entry
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Levine, Daniel S.
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| Title & Author
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Introduction to neural and cognitive modeling /\ Daniel S. Levine.
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| Edition Statement
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Third edition.
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| Publication Statement
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London :: Routledge,, 2018.
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| Page. NO
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1 online resource :: illustrations (black and white)
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| ISBN
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0429448805
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: 0429828780
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: 0429828799
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: 0429828802
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: 9780429448805
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: 9780429828782
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: 9780429828799
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: 9780429828805
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1848726481
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9781848726475
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9781848726482
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Contents -- Part I: Foundations of Neural Network Theory -- Chapter 1: Neural Networks for Modeling Behavior -- Chapter 2: Historical Outline -- Chapter 3: Associative Learning and Synaptic Plasticity -- Chapter 4: Competition, Lateral Inhibition, and Short-Term Memory -- Part II: Computational Cognitive Neuroscience -- Chapter 5: Progress in Cognitive Neuroscience -- Chapter 6: Models of Conditioning and Reinforcement Learning -- Chapter 7: Models of Coding, Categorization, and Unsupervised Learning -- Chapter 8: Models of Supervised Pattern and Category Learning -- Chapter 9: Models of Complex Mental Functions -- Appendices -- Appendix 1: Mathematical Techniques for Neural Networks -- Appendix 2: Basic Facts of Neurobiology -- References.
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| Abstract
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This textbook provides a general introduction to the field of neural networks. Thoroughly revised and updated from the previous editions of 1991 and 2000, the current edition concentrates on networks for modeling brain processes involved in cognitive and behavioral functions. Part one explores the philosophy of modeling and the field's history starting from the mid-1940s, and then discusses past models of associative learning and of short-term memory that provide building blocks for more complex recent models. Part two of the book reviews recent experimental findings in cognitive neuroscience and discusses models of conditioning, categorization, category learning, vision, visual attention, sequence learning, behavioral control, decision making, reasoning, and creativity. The book presents these models both as abstract ideas and through examples and concrete data for specific brain regions. The book includes two appendices to help ground the reader: one reviewing the mathematics used in network modeling, and a second reviewing basic neuroscience at both the neuron and brain region level. The book also includes equations, practice exercises, and thought experiments.
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| Subject
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Neural networks (Computer science)
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Neural networks (Neurobiology)
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Neural networks (Computer science)
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Neural networks (Neurobiology)
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PSYCHOLOGY-- Cognitive Psychology.
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| Dewey Classification
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612.82
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| LC Classification
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QA76.87
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