Dan J. M. D. Stein, Jacques Ludik

Neural Networks and Psychopathology

Connectionist Models in Practice and Research
Herausgeber: Stein, Dan J. M. D.

• Broschiertes Buch

Produktbeschreibung

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 study review theoretical, historical and clinical issues, including the contribution of neural network models to diagnosis, pharmacotherapy and psychotherapy. Models are presented for a range of disorders, including schizophrenia, obsessive-compulsive disorder, dissociative phenomena, autism and Alzheimer's disease. This book will appeal to a broad audience. On the one hand, it will be read with interest by psychiatrists, psychologists and other clinicians and researchers in psychopathology. On the other, it will appeal to those working in cognitive science and artificial intelligence, and particularly those interested in neural network or connectionist models.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 388
• Erscheinungstermin: 31. Januar 2007
• Englisch
• Abmessung: 229mm x 152mm x 23mm
• Gewicht: 628g
• ISBN-13: 9780521036061
• ISBN-10: 0521036062
• Artikelnr.: 22729208

Inhaltsangabe

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.