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ddfptcskfsiegvdw – Read and download Eugene M. Izhikevich’s book Dynamical Systems in Neuroscience : The Geometry of Excitability and Bursting in PDF, EPub, Mobi, Kindle online. Book Dynamical Systems in Neuroscience : The Geometry of Excitability and Bursting by Eugene M. Izhikevich

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

Summary: Explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition. 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. show more

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Theoretical Neuroscience, An Introductory Course in Computational Neuroscience, Biophysics of Computation, Principles of Neural Design, Fundamentals of Computational Neuroscience, Nonlinear Dynamics and Chaos, Principles of Neural Information Theory, Principles of Neural Science, Neuronal Dynamics, Mathematical Foundations of Neuroscience, Reinforcement Learning, Principles of Computational Modelling in Neuroscience, Sync, Pattern Recognition and Machine Learning, Student Solutions Manual for Nonlinear Dynamics and Chaos, 2nd edition, How to Build a Brain, Spiking Neuron Models, Cognitive Neuroscience, Data-Driven Science and Engineering, Deep Learning

Product details Format Paperback | 464 pages Dimensions 178 x 254 x 22.86mm | 816g Publication date 06 Apr 2010 Publisher MIT Press Ltd Imprint MIT Press Publication City/Country Cambridge, United States Language English Illustrations note 409 illus.; 409 Illustrations, unspecified ISBN10 0262514206 ISBN13 9780262514200 Bestsellers rank 238,703

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