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Mathematical Foundations of Neuroscience / by G. Bard Ermentrout, David H. Terman
(Interdisciplinary Applied Mathematics. ISSN:21969973 ; 35)
版 | 1st ed. 2010. |
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出版者 | New York, NY : Springer New York : Imprint: Springer |
出版年 | 2010 |
大きさ | XV, 422 p. 38 illus. in color : online resource |
著者標目 | *Ermentrout, G. Bard author Terman, David H author SpringerLink (Online service) |
件 名 | LCSH:Biomathematics LCSH:Neurosciences FREE:Mathematical and Computational Biology FREE:Neuroscience |
一般注記 | The Hodgkin–Huxley Equations -- Dendrites -- Dynamics -- The Variety of Channels -- Bursting Oscillations -- Propagating Action Potentials -- Synaptic Channels -- Neural Oscillators: Weak Coupling -- Neuronal Networks: Fast/Slow Analysis -- Noise -- Firing Rate Models -- Spatially Distributed Networks This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University HTTP:URL=https://doi.org/10.1007/978-0-387-87708-2 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9780387877082 |
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EB00197103 |
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データ種別 | 電子ブック |
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分 類 | LCC:QH323.5 LCC:QH324.2-324.25 DC23:570.285 |
書誌ID | 4000120061 |
ISBN | 9780387877082 |
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※2017年9月4日以降