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Synopsis
Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.
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About the Author
William W. Lytton is an associate professor of physiology and neurology and a practicing neurologist at the State University of New York, Downstate.
Review
From the Foreword:
"In From Computer to Brain: Foundations of Computational Neuroscience, William W. Lytton provides a gentle but rigorous introduction to the art of modeling neurons and neural systems. It is an accessible entry to the methods and approaches used to model the brain at many different levels, ranging from synapses and dendrites to neurons and neural circuits. This book gives a balanced view of the wide range of modeling techniques that are available in a way that is accessible to a wide audience. This is a book that will bring a smile to your face as well as inspire your imagination."
-- Terrence J. Sejnowski
Howard Hughes Medical Institute, Salk Institute, University of California at San Diego
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2002
- ISBN 10 0387955283
- ISBN 13 9780387955285
- BindingHardcover
- LanguageEnglish
- Number of pages384
- Rating
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From Computer to Brain: Foundations of Computational Neuroscience
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From Computer to Brain : Foundations of Computational Neuroscience
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Buch. Condition: Neu. Neuware - Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system. Seller Inventory # 9780387955285
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