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Dynamical Systems in Neuroscience - The Geometry of Excitability and Bursting (Paperback)
Loot Price: R1,593
Discovery Miles 15 930
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Dynamical Systems in Neuroscience - The Geometry of Excitability and Bursting (Paperback)
Series: Computational Neuroscience Series
Expected to ship within 10 - 15 working days
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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.
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