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Dynamical Systems in Neuroscience (Computational Neuroscience) Paperback – 15 Feb 2010

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Product details

  • Paperback: 528 pages
  • Publisher: MIT Press (15 Feb. 2010)
  • Language: English
  • ISBN-10: 0262514206
  • ISBN-13: 978-0262514200
  • Product Dimensions: 17.8 x 2.2 x 25.4 cm
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Bestsellers Rank: 394,760 in Books (See Top 100 in Books)

Product Description


"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 "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

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-reviewed encyclopedia.

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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 4.7 out of 5 stars 10 reviews
29 of 29 people found the following review helpful
5.0 out of 5 stars An Interesting Book on Spiking Mechanism and Nonlinear Dynamical System 10 Aug. 2007
By Man Kam Tam - Published on Amazon.com
Format: Hardcover Verified Purchase
The goal of Izhikevich's book is to study "the relationship between electrophysiology, bifurcations, and computational properties of neurons." The book also introduces the fundamental concepts of nonlinear dynamical system such as (1) equilibrium, (2) stability, (3) limit cycle attractor, and (4) bifurcations. Actually, it is a good introductory book on applying nonlinear dynamical system on scientific research. The primary subject of the book is the spiking (excitability and bursting) of neurons. By utilizing graphs or phase portraits to demonstrate the mechanism of the spiking generation of neurons, the author makes the readers understand both the spiking mechanism and the concepts of nonlinear dynamical system with ease.
27 of 27 people found the following review helpful
5.0 out of 5 stars So you think you are afraid of some math? 24 Oct. 2007
By Robert Butera - Published on Amazon.com
Format: Hardcover
This book encapsulates in a single text a large body of knowledge by the author and others over the past two decades on the use of geometrical techniques to both classify and study a large range of single neuron models. While much of this material is known to "experts" in the field, the value of this text is i1) teaching this dynamical systems perspective on single neuron dynamics to generations of new students and 2) educating non-mathematicians into both the utility and use of these theories. Many other texts and papers on this topic leave non-mathematicians "in the dust" shortly after the introduction, but Eugene's excellent use of figures to explain concepts geometrically as well as mathematically enables a PhD student in engineering or quantitative biology to fully appreciate what is going on, not to mention seasoned experimentalists.
8 of 8 people found the following review helpful
5.0 out of 5 stars Amazing Book 9 May 2011
By Ghassan Ayesh - Published on Amazon.com
Format: Paperback Verified Purchase
This book will teach you the dynamics of neurons, how to model the dynamics of neurons, complex systems modeling and how our understanding of the spiking neural systems came. This is a prize in every way. The book is engaging and easy to follow - well to some extent given the advanced topic the author is engaging the readers with. I am impressed of the ease the author applies non linear dynamical systems theory modeling techniques at ease in order to come up with a neural model that the author Izhikevich evolves throughout the chapters of the book, with clear schematics in every chapter which visually explain the modeling as well. Superb indeed. The subject overall is not an easy topic to attack or explain but Izhikevich is up for the challenge.
5 of 5 people found the following review helpful
5.0 out of 5 stars Beautiful book of dynamical system of neurons 22 Feb. 2009
By Il Park - Published on Amazon.com
Format: Hardcover Verified Purchase
This is an excellent book on application of 2-D dynamical system theory to (minimal) spiking neuron models. I highly recommend it for electrophysiologist who wants to learn more about what they observe, and to computational neuroscientists in general.
Prior exposure to dynamical systems and neuroscience is helpful.
3 of 3 people found the following review helpful
5.0 out of 5 stars Excellent, but not for the beginner. 3 May 2014
By Occasional Reviewer - Published on Amazon.com
Format: Paperback Verified Purchase
This qualifies as a "bible" of compuational neuroscience, but it is not a beginner's book. I had the good fortune to have lunch with the author and he is one of the best in the field. The book is well written and does a great job of providing an overview of applying non-linear dynamics to neuroscience. The mathematical concepts are explained well and in sufficient detail for the punctilious. I bought a second copy to keep at work and it will become a go-to manual for me of sorts.
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