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.

Fundamentals of Neural Network Modeling: Neuropsychology and Cognitive Neuroscience (Computational Neuroscience) PDF

The list of books you might like