| 书目名称 | Mathematical Foundations of Neuroscience |
| 编辑 | G. Bard Ermentrout,David H. Terman |
| 视频video | |
| 概述 | Links both neuroscience and applied mathematics.Extensive illustrations, examples and exercises using real data.Includes supplementary material: |
| 丛书名称 | Interdisciplinary Applied Mathematics |
| 图书封面 |  |
| 描述 | This book applies methods from nonlinear dynamics to problems inneuroscience. It uses modern mathematical approaches to understandpatterns of neuronal activity seen in experiments and models of neuronalbehavior. The intended audience is researchers interested in applyingmathematics to important problems in neuroscience, and neuroscientistswho would like to understand how to create models, as well as themathematical and computational methods for analyzing them. The authorstake a very broad approach and use many different methods to solve andunderstand complex models of neurons and circuits. They explain andcombine numerical, analytical, dynamical systems and perturbationmethods to produce a modern approach to the types of model equationsthat arise in neuroscience. There are extensive chapters on the role ofnoise, multiple time scales and spatial interactions in generatingcomplex activity patterns found in experiments. The early chaptersrequire little more than basic calculus and some elementary differentialequations and can form the core of a computational neuroscience course.Later chapters can be used as a basis for a graduate class and as asource for current research in mathematic |
| 出版日期 | Textbook 2010 |
| 关键词 | Radiologieinformationssystem; behavior; computational neuroscience; dynamical systems; neurons; neuroscie |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-0-387-87708-2 |
| isbn_softcover | 978-1-4614-2621-9 |
| isbn_ebook | 978-0-387-87708-2Series ISSN 0939-6047 Series E-ISSN 2196-9973 |
| issn_series | 0939-6047 |
| copyright | Springer Science+Business Media, LLC 2010 |
发表于 2025-3-21 19:24:23
