- Series: Computational Neuroscience Series
- Paperback: 464 pages
- Publisher: The MIT Press (January 22, 2010)
- Language: English
- ISBN-10: 0262514206
- ISBN-13: 978-0262514200
- Product Dimensions: 7 x 0.9 x 10 inches
- Shipping Weight: 1.8 pounds (View shipping rates and policies)
- Average Customer Review: 4.6 out of 5 stars See all reviews (11 customer reviews)
- Amazon Best Sellers Rank: #161,265 in Books (See Top 100 in Books)
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Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience Series)
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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)
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 unique contribution to the theoretical neuroscience literature that can serve as a useful reference for audiences ranging from quantitatively skilled undergraduates interested in mathematical modeling, to neuroscientists at all levels, to graduate students and even researchers in the field of theoretical neuroscience.(Jonathan E. Rubin Mathematical Review)
This book will be a great contribution to the subject of mathematical neurophysiology.(Richard Fitzhugh, former researcher, Laboratory of Biophysics, National Institutes of Health)
About the Author
Eugene M. Izhikevich is Chairman and CEO of Brain Corporation in San Diego and was formerly Senior Fellow in Theoretical Neurobiology at the Neurosciences Institute, San Diego. He is editor-in-chief of Scholarpedia, the free peer-reviewedencyclopedia.
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Top Customer Reviews
I read this book cover to cover (including ch10 which is online on the author's website) and it never got boring. This book gives you "the big picture" about neuron dynamics.
The author also does an exquisite job at classifying different neuron models and showing "what really matters" about them. And at every step, information is provided about how to reproduce the figures (which is easy with MATLAB, Mathematica, or similar tools) so that you can verify your understanding and play around. There are tons of examples of specific neuron recordings and explanations in terms of the models being discussed.
The preface and ch1 are available on the author's website
As a point of reference, Dayan & Abbott "Theoretical Neuroscience" has broader and deeper coverage of "computational neuroscience" than Izhikevich, but does not have the same kind of deep qualitative geometrical insight into neuron dynamics. I would consider it as a next step after reading this book.
As a rule of thumb, if you are uncomfortable with the idea of using MATLAB, Mathematica, or a similar tool to plot a vector field or integrate a system of ODE, you will probably not benefit from the quantitative side of this book. But the book may still be useful for developing qualitative understanding.
Prior exposure to dynamical systems and neuroscience is helpful.