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Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience Series) download epub

by Terrence J. Sejnowski,Tomaso A. Poggio,Eugene M. Izhikevich


Epub Book: 1953 kb. | Fb2 Book: 1427 kb.

Izhikevich, Eugene . 1967– Dynamical systems in neuroscience: the . This book introduces dynamical systems starting with simple one- and two-dimen-sional spiking models and continuing all the way to bursting systems

Izhikevich, Eugene . 1967– Dynamical systems in neuroscience: the geometry of excitability and bursting, Eugene M. Izhikevich. p. cm. - (Computational neuroscience) Includes bibliographical references and index. ISBN 978-0-262-09043-8 (hc. : alk. paper) 1. Neural networks (Neurobiology) 2. Neurons - computer simulation This book introduces dynamical systems starting with simple one- and two-dimen-sional spiking models and continuing all the way to bursting systems. Each chapter is organized from simple to complex, so everybody can start reading the book; only the reader’s background will determine where he or she stops.

Dynamical Systems in Neuroscience. Computational Neuroscience Izhikevich, Eugene . 1967– Dynamical systems in neuroscience: th. . The Geometry of Excitability and Bursting. Eugene M. Dynamical Systems in Neuroscience. Computational Neuroscience. Neural Nets in Electric Fish, Walter Heiligenberg, 1991. The Computational Brain, Patricia S. Churchland and Terrence J. Sejnowski, 1992. Izhikevich, Eugene .

Series: Computational Neuroscience Series. Paperback: 458 pages. This is an excellent book on application of 2-D dynamical system theory to (minimal) spiking neuron models. Publisher: MIT Press (January 22, 2010). 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.

Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational . Series: Computational Neuroscience Series.

Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience Series). MATLAB for Brain and Cognitive Scientists (The MIT Press).

Request PDF On Jan 1, 2008, Jeff Moehlis and others published Dynamical Systems in Neuroscience: The .

We use a model of spiking neurons that was developed to satisfy two requirements: It is computational simple and efficient to implement in large-scale simulations, and it exhibits most of the types of the firing patterns recorded in animals in vitro and in vivo. where v v and u are the membrane potential and recovery variables, respectively; a,b,c

Computational neuroscience is an approach to understanding the development and function of nervous systems at many different . Izhikevich 2006.

Computational neuroscience is an approach to understanding the development and function of nervous systems at many different structural scales, including the biophysical, the circuit, and the systems levels. Methods include theoretical analysis and modeling of neurons, networks, and brain systems and are complementary to empirical techniques in neuroscience. The Computational Neurobiology of Reaching and Pointing. A Foundation for Motor Learning. Reza Shadmehr and Steven P. Wise 2004.

IV takes up issues for the coherent phenomena in stochastic dynamical systems, described by ordinary.

The Limits of Organic Life in Planetary Systems. 29 MB·28,172 Downloads·New!. Stem Cells and the Future of Regenerative Medicine. IV takes up issues for the coherent phenomena in stochastic dynamical systems, described by ordinary. Rising Above the Gathering Storm: Energizing and Employing America for a Brighter Economic Future.

Eugene M. Being a biomathematician and neuroscientist, I found that Izhikevich's book "Dynamical Systems in Neuroscience" is a great reference to broaden my understanding of mathematical neuroscience and neurophysiology, and in particular, neural modeling, nonlinear dynamics and the mathematics involved between the brief bursts of neural activity. I recommend it to every neuroscientist in the field.

3 Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting Eugene M. Izhikevich The MIT Press Cambridge, Massachusetts London, England. 4 c 27 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.

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.

Comments: (7)

Questanthr
The author's incessant focus on providing geometrical insight into the mathematics is the most astonishing feature of this book. I cannot imagine a better introduction to quantitative and qualitative understanding of the dynamics of individual neurons.
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.
Froststalker
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.
Cordann
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.
Nalmezar
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.
Vertokini
The author's method (of looking for chaotic attractors first in neurons, and then in oscillators of neurons) may be the key to understanding real brains.
SoSok
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.
saafari
Being a biomathematician and neuroscientist, I found that Izhikevich's book "Dynamical Systems in Neuroscience" is a great reference to broaden my understanding of mathematical neuroscience and neurophysiology, and in particular, neural modeling, nonlinear dynamics and the mathematics involved between the brief bursts of neural activity. I recommend it to every neuroscientist in the field.
The book claims to be an 'introduction to nonlinear dynamical systems theory for researchers and graduate students in neuroscience'. Potential purchasers need to be warned that it provides a highly mathematical account of neuroscience that those coming from psychology or biology might find challenging. The challenge is not eased by the approach taken by the author, who clearly has little sympathy for any reader who finds mathematical equations a pain. The cartoon on page 7 says it all. One character dressed in a tee shirt (presumably a researcher) is telling his senior 'I developed the most realistic neural networks'. His senior, dressed in suit and tie, replies 'I do not see any neurons here, only equations'. This book will be a joy to all who do not want to see neurons, only mathematical equations.
Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience Series) download epub
Medicine
Author: Terrence J. Sejnowski,Tomaso A. Poggio,Eugene M. Izhikevich
ISBN: 0262514206
Category: Medical Books
Subcategory: Medicine
Language: English
Publisher: The MIT Press (January 22, 2010)
Pages: 464 pages