Item description for Modeling in the Neurosciences: From Ionic Channels to Neural Networks by R.R. Poznanski...
Computational models of neural networks have proven insufficient to accurately model brain function, mainly as a result of simplifications that ignore the physical reality of neuronal structure in favor of mathematically tractable algorithms and rules. Even the more biologically based "integrate and fire" and "compartmental" styles of modeling suffer from oversimplification in the former case and excessive discretization in the second. This book introduces an integrative approach to modeling neurons and neuronal circuits that retains the integrity of the biological units at all hierarchical levels.
With contributions from more than 40 renowned experts, Modeling in the Neurosciences, Second Edition is essential for those interested in constructing more structured and integrative models with greater biological insight. Focusing on new mathematical and computer models, techniques, and methods, this book represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the molecular to the network level. Many state-of-the-art examples illustrate how mathematical and computer modeling can contribute to the understanding of mechanisms and systems in the neurosciences. Each chapter also includes suggestions of possible refinements for future modeling in this rapidly changing and expanding field.
This book will benefit and inspire the advanced modeler, and will give the beginner sufficient confidence to model a wide selection of neuronal systems at the molecular, cellular, and network levels.
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Studio: CRC Press
Est. Packaging Dimensions: Length: 10.34" Width: 6.7" Height: 1.51" Weight: 2.66 lbs.
Release Date Feb 19, 1999
ISBN 9057022842 ISBN13 9789057022845
Reviews - What do customers think about Modeling in the Neurosciences: From Ionic Channels to Neural Networks?
QUANTITATIVE MODELING WITH VIGOR! Jan 10, 2001
What distinguishes this book from other neuronal modeling books? Firstly, it contains a solid quantitative flavor necessary for real advances in neural networks. Secondly, it places an emphasis on neuronal models not encountered in computational neuroscience. Thirdly, it is written with authority by some well known names in the field. Each chapter is self-contained and written in a didactic fashion with a future perspectives section and a problem set. The contents range from stochastic fluctuations of ionic channels to morphologically realistic neural networks. Some features include: Lanczos matrices to construct fully equivalent cables, application of Maxwell equations to derive the cable equation, and a chapter devoted to nonlinear cable theory co-authored by one of the founders of theoretical biophysics. This book is thoroughly recommended to anyone who is serious about neuronal modeling.