Neural Modeling Of Brain And Cognitive Disorders
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Neural Modeling of Brain and Cognitive Disorders
During the last few years there has been a rapidly increasing interest in neural modeling of brain and cognitive disorders. This multidisciplinary book presents a variety of such models in neurology, neuropsychology and psychiatry. A review of work in this area is given first. Computational models are then presented of memory impairment in Alzheimer's disease, functional brain reorganization following a stroke, patterns of neural activity in epilepsy, disruption of language processes in aphasia and acquired dyslexia, altered cognitive processes in schizophrenia and depression, and related disorders. This is the first book on this topic, with contributions from many of the leading researchers in this field.
Neural Modeling Of Brain And Cognitive Disorders
Author: Rita Sloan Berndt
language: en
Publisher: World Scientific
Release Date: 1996-11-09
During the last few years there has been a rapidly increasing interest in neural modeling of brain and cognitive disorders. This multidisciplinary book presents a variety of such models in neurology, neuropsychology and psychiatry. A review of work in this area is given first. Computational models are then presented of memory impairment in Alzheimer's disease, functional brain reorganization following a stroke, patterns of neural activity in epilepsy, disruption of language processes in aphasia and acquired dyslexia, altered cognitive processes in schizophrenia and depression, and related disorders. This is the first book on this topic, with contributions from many of the leading researchers in this field.
Fundamentals of Neural Network Modeling
Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble