Dynamical Systems in Neuroscience

November 2006
7 x 10, 457 pp., 409 illus.
$62.00/£45.95 (CLOTH)
Short

ISBN-10:
0-262-09043-0
ISBN-13:
978-0-262-09043-8

Paper (2010)

Computational Neuroscience

Related Links

Author's Website

Scholarpedia

Welcome, Technology Review Subscriber!
The MIT Press is pleased to offer you a 20% discount on our books. To claim your discount, simply click the "add to cart" button and proceed to the checkout.

Dynamical Systems in Neuroscience
The Geometry of Excitability and Bursting
Eugene M. Izhikevich

Table of Contents and Sample Chapters

In order to model neuronal behavior or to interpret the results of modeling studies, neuroscientists must call upon methods of nonlinear dynamics. This book offers an introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience. It also provides an overview of neuroscience for mathematicians who want to learn the basic facts of electrophysiology.

Dynamical Systems in Neuroscience presents a systematic study of the relationship of electrophysiology, nonlinear dynamics, and computational properties of neurons. It emphasizes that information processing in the brain depends not only on the electrophysiological properties of neurons but also on their dynamical properties.

The book introduces dynamical systems, starting with one- and two-dimensional Hodgkin-Huxley-type models and continuing to a description of bursting systems. Each chapter proceeds from the simple to the complex, and provides sample problems at the end. The book explains all necessary mathematical concepts using geometrical intuition; it includes many figures and few equations, making it especially suitable for non-mathematicians. Each concept is presented in terms of both neuroscience and mathematics, providing a link between the two disciplines.

Nonlinear dynamical systems theory is at the core of computational neuroscience research, but it is not a standard part of the graduate neuroscience curriculum—or taught by math or physics department in a way that is suitable for students of biology. This book offers neuroscience students and researchers a comprehensive account of concepts and methods increasingly used in computational neuroscience.

An additional chapter on synchronization, with more advanced material, can be found at the author's website, www.izhikevich.com.

About the Author

Eugene M. Izhikevich is Senior Fellow in Theoretical Neurobiology at the Neurosciences Institute, San Diego, coauthor of Weakly Conducted Neural Networks, and editor-in-chief of Scholarpedia, the free peer-reviewed encyclopedia.

"This book will be a great contribution to the subject of mathematical neurophysiology."
—Richard Fitzhugh, former researcher, Laboratory of Biophysics, National Institutes of Health

"Eugene Izhikevich has written an excellent introduction to the application of nonlinear dynamics to the spiking patterns of neurons. There are dozens of clear illustrations and hundreds of exercises ranging from the very easy to Ph.D.-level questions. The book will be suitable for mathematicians and physicists who want to jump into this exciting field as well as for neuroscientists who desire a deeper understanding of the utility of nonlinear dynamics applied to biology."
—Bard Ermentrout, Department of Mathematics, University of Pittsburgh

"A stimulating, entertaining, and scenic tour of neuronal modeling from a nonlinear dynamics viewpoint."
—John Rinzel, Center for Neural Science and Courant Institute, New York University

See Other Titles In:


>	Cognition, Brain, & Behavior

	- Neuroscience

>	Neuroscience

	- Neural Computation

	Join an E-mail Alert List

TECHNOLOGY PARTNER: Azility, Inc.