Neuroscience and Connectionist Theory

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.

Mark A. Gluck, David E. Rumelhart

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.