Parallel distributed processing : implications for psychology and neurobiology

Bibliographic Information

Parallel distributed processing : implications for psychology and neurobiology

edited by R.G.M. Morris

Clarendon Press , Oxford University Press, 1989

  • U.K. : est.

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Note

Based on a conference organized by the Experimental Psychology Society and held at the University of Oxford on July 1, 1987

Includes bibliographies and indexes

Description and Table of Contents

Description

In recent years there has been a substantial growth of interest in parallel distributed processing among experimental psychologists and neurobiologists. Many neurobiologists hope that current developments in the formal analysis of neural networks will provide a bridge between psychological accounts of cognitive function and accounts couched at the neural level. This book examines the implications of these new developments and their influence on experimental psychology and neurobiology. Part 1 looks at formal PDP models, introducing the approach and discussing the all-important assumptions and algorithms. Part 2 discusses the implications of these models for psychology, covering both human and animal research. Part 3 is concerned with the implications for neurobiology. Each of the parts is introduced by a short chapter outlining some of the issues discussed and alluded to in the main chapters that follow.

Table of Contents

  • Network models of the mind, H.C.Longuet-Higgins
  • parallel distributed processing - implications for cognition and development, Jay L.McClelland
  • learning distributed representations of concepts, Geoffrey E.Hinton
  • parallel distributed processing and psychology, Glyn W.Humphreys
  • selective attention, variable processing and distributed representation of stimuli - applications to perceptual learning and latent inhibition, Ian P.McLaren et al
  • connections and disconnections - acquired dyslexia in a computational model of reading processes
  • rules and connections in human language, Steven Pinker and Alan Prince
  • computational neuroscience - modelling the brain, Richard G.M.Morris
  • a biologically realistic neural network model for higher-order features of classical conditioning, Robert D.Hawkins
  • does synaptic plasticity play a role in information storage in the vertebrate brain?, Richard G.M.Morris
  • parallel distributed processing in the brain - implications of the functional architecture of neuronal networks in the hippocampus, Edmund T.Rolls
  • rapid incremental learning of hierarchically organized stimuli by layer II sensory (olfactory) cortex.

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