Neural Networks and Psychopathology: Connectionist Models in Practice and Research

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More About This Textbook

Overview

Research on connectionist models is one of the most exciting areas in cognitive science, and neural network models of psychopathology have immediate theoretical and empirical appeal. The contributors to this pioneering book review theoretical, historical and clinical issues, including the contribution of neural network models to diagnosis, pharmacotherapy, and psychotherapy. The text presents models for a range of disorders, including schizophrenia, obsessive-compulsive disorder, disassociative phenomena, autism, and Alzheimer's disease. This volume will be read with interest by psychiatrists, psychologists and other clinicians and researchers in psychopathology. Additionally, it will appeal to those working in the fields of cognitive science and artificial intelligence, and particularly those interested in neural network or connectionist models.

The book contains black-and-white illustrations.

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Product Details

  • ISBN-13: 9780521036061
  • Publisher: Cambridge University Press
  • Publication date: 5/28/2007
  • Pages: 388
  • Product dimensions: 5.98 (w) x 8.98 (h) x 0.87 (d)

Table of Contents

List of contributors; Preface; Part I. General Concepts: 1. Neural networks and psychopathology: an introduction Dan J. Stein and Jacques Ludik; 2. The history of neural network research in psychopathology Manfred Spitzer; 3. Neural network models in psychiatric diagnosis and symptom recognition Eric Y. H. Chen and German E. Berrios; 4. Neural networks and psychopharmacology S. B. G. Park; 5. A connectionist view of psychotherapy Franz Caspar; 6. Modulatory mechanisms in mental disorders David Hestenes; Part II. Clinical Disorders: 7. The nature of delusions: a hierarchical neural network approach Eric Y. H. Chen and German E. Berrios; 8. 'Produced by either God or Satan': neural network approaches to delusional thinking Sophia Vinogradov, John H. Poole and Jason Willis-Shore; 9. Neural network modelling of cognitive disinhibition and neurotransmitter dysfunction in obsessive-compulsive disorder Jacques Ludik and Dan J. Stein; 10. The fables of Lucy R.: association and disassociation in neural networks Dan Lloyd; 11. Neural network analysis of learning in autism Ira L. Cohen; 12. Are there common neural mechanisms for learning, epilepsy and Alzheimer's disease? Gene V. Wallenstein and Michael E. Hasselmo; Epilogue: the patient in the machine: challenges for neurocomputing David V. Forrest; Index.

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