Modeling in the Neurosciences: From Ionic Channels to Neural Networks [Hardcover]

R.R. Poznanski (Editor)

Book Description

ISBN-10: 9057022842 | ISBN-13: 978-9057022845 | Publication Date: February 19, 1999 | Edition: 1

With contributions from more than 40 renowned experts, Modeling in the Neurosciences: From Ionic Channels to Neural Networks is essential for those interested in neuronal modeling and quantitative neiroscience. Focusing on new mathematical and computer models, techniques and methods, this monograph represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the biophysical, cellular and netwrok levels. Many state-of-the-art examples are presented as to 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 give the beginner sufficient confidence to model a wide selection of neuronal systems at the biophysical, cellular and network levels.

Product Details

• Hardcover: 528 pages
• Publisher: CRC Press; 1 edition (February 19, 1999)
• Language: English
• ISBN-10: 9057022842
• ISBN-13: 978-9057022845
• Product Dimensions: 10.3 x 6.7 x 1.5 inches
• Shipping Weight: 2.7 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #4,393,450 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

2 of 3 people found the following review helpful:

5.0 out of 5 stars QUANTITATIVE MODELING WITH VIGOR!, January 9, 2001

By A Customer

This review is from: Modeling in the Neurosciences: From Ionic Channels to Neural Networks (Hardcover)

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.