Neuroscience and Connectionist Theory

Author:   Mark A. Gluck ,  David E. Rumelhart ,  Mark A. Gluck
Publisher:   Taylor & Francis Inc
ISBN:  

9780805806199


Pages:   424
Publication Date:   01 February 1990
Format:   Paperback
Availability:   In Print   Availability explained
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Neuroscience and Connectionist Theory


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Overview

Written for cognitive scientists, psychologists, computer scientists, engineers, and neuroscientists, this book provides an accessible overview of how computational network models are being used to model neurobiological phenomena. Each chapter presents a representative example of how biological data and network models interact with the authors' research. The biological phenomena cover network- or circuit-level phenomena in humans and other higher-order vertebrates.

Full Product Details

Author:   Mark A. Gluck ,  David E. Rumelhart ,  Mark A. Gluck
Publisher:   Taylor & Francis Inc
Imprint:   Psychology Press
Dimensions:   Width: 15.20cm , Height: 2.80cm , Length: 22.90cm
Weight:   0.680kg
ISBN:  

9780805806199


ISBN 10:   0805806199
Pages:   424
Publication Date:   01 February 1990
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Contents: B.L. McNaughton, L. Nadel, Hebb-Marr Networks and the Neurobiological Representation of Action in Space. M.F. Bear, L.N. Cooper, Molecular Mechanisms for Synaptic Modification in the Visual Cortex: Interaction Between Theory and Experiment. R. Granger, J. Ambros-Ingerson, U. Staubli, G. Lynch, Memorial Operation of Multiple, Interacting Simulated Brain Structures. M.A. Gluck, E.S. Reifsnider, R.F. Thompson, Adaptive Signal Processing and the Cerebellum: Models of Classical Conditioning and VOR Adaptation. W.B. Levy, C.M. Colbert, N.L. Desmond, Elemental Adaptive Processes of Neurons and Synapses: A Statistical/Computational Perspective. H.T. Wang, B. Mathur, C. Koch, I Thought I Saw It Move: Computing Optical Flow in the Primate Visual System. K.D. Miller, Correlation-Based Models of Neural Development. D. Zipser, Modeling Cortical Computation With Backpropagation.

Reviews

...provides good evidence that neuroscience continues to provide new inspiration for computational modelers. -Artificial Intelligence There are important messages that can be gleaned by contemplating the collection as a whole....The future of computational neuroscience over the long-term must involve psychologists if it is to maintatin relevance and intellectual rigor. Neuroscience and Connectionist Theory points the way. -Contemporary Psychology


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Mark A. Gluck, David E. Rumelhart

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