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Spiking Neuron Models: Single Neurons, Populations, Plasticity [Paperback]

Wulfram Gerstner (Author), Werner M. Kistler (Author)
5.0 out of 5 stars  See all reviews (4 customer reviews)

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Book Description

August 26, 2002 0521890799 978-0521890793 1
This introduction to spiking neurons can be used in advanced-level courses in computational neuroscience, theoretical biology, neural modeling, biophysics, or neural networks. It focuses on phenomenological approaches rather than detailed models in order to provide the reader with a conceptual framework. The authors formulate the theoretical concepts clearly without many mathematical details. While the book contains standard material for courses in computational neuroscience, neural modeling, or neural networks, it also provides an entry to current research. No prior knowledge beyond undergraduate mathematics is required.

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Spiking Neuron Models: Single Neurons, Populations, Plasticity + Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience) + Spikes: Exploring the Neural Code (Computational Neuroscience)
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Editorial Reviews

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'The treatment undoubtedly holds pointers to future developments that will allow robots to come closer to their biological prototypes.' Journal of Robotica

Book Description

This is an introduction to spiking neurons for advanced undergraduate or graduate students. It can be used with courses in computational neuroscience, theoretical biology, neural modeling, biophysics, or neural networks. It focuses on phenomenological approaches rather than detailed models in order to provide the reader with a conceptual framework. No prior knowledge beyond undergraduate mathematics is necessary to follow the book. Thus it should appeal to students or researchers in physics, mathematics, or computer science interested in biology; moreover it will also be useful for biologists working in mathematical modeling.

Product Details

  • Paperback: 496 pages
  • Publisher: Cambridge University Press; 1 edition (August 26, 2002)
  • Language: English
  • ISBN-10: 0521890799
  • ISBN-13: 978-0521890793
  • Product Dimensions: 9.6 x 7 x 0.9 inches
  • Shipping Weight: 2.2 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Best Sellers Rank: #674,825 in Books (See Top 100 in Books)

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17 of 17 people found the following review helpful:
5.0 out of 5 stars All you ever wanted to know about spiking neuron models, August 19, 2004
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This review is from: Spiking Neuron Models: Single Neurons, Populations, Plasticity (Paperback)
I have used this book as an introduction and reference book for modeling neurons since I started my thesis work in computational neuroscience two years ago. It covers various types of spiking neuron models (e.g. Hodgkin-Huxley, Morris-Lecar, Integrate&Fire, Spike-Response-Model), noise in neuron models, population models, and plasticity/learning.
It is a very useful book, clearly written and comprehensive, providing sufficient detail and background information. Derivations of the equations are clearly presented and understandable to anyone with a decent knowledge of mathematics. A degree in physics is not required in order to read this book ;-) With this book and some programming skills, one has a solid foundation for modeling neurons on various levels.
I also like the literature recommendations at the end of each chapter, they give a good overview over important original papers and further reviews.
I would strongly recommend this book to undergraduate and PhD-students in computational neuroscience, as well as to anyone interested in modeling neurons.
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9 of 9 people found the following review helpful:
5.0 out of 5 stars Impressive book, August 30, 2004
This review is from: Spiking Neuron Models: Single Neurons, Populations, Plasticity (Paperback)
This is a very impressive book. It covers in a systematic manner a broad portion of the field of theoretical neuroscience. It covers topics from models of single spiking neurons, through networks of interconnected neurons and up to neuronal plasticity. This book is also written very well. The style of this book reflects the background of the authors as Physicists; it therefore strives for simplicity wherever possible.

I used chapters from this book as a basis for some of my lectures in a course I teach: Introduction to Theoretical/Computational Neuroscience, a graduate level course. I especially liked the systematic approach they have adopted for describing various simplifications of the Hodgkin-Huxley equations.
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3 of 3 people found the following review helpful:
5.0 out of 5 stars excellent book, November 30, 2007
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bob (Boston, MA United States) - See all my reviews
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This review is from: Spiking Neuron Models: Single Neurons, Populations, Plasticity (Paperback)
very well written, easy to understand, walks you through the logic of each part of each equation. builds up more and more complex models based upon the previous models. You'll learn a lot of practical neurobiology stuff other than just modeling too.
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Inside This Book (learn more)
First Sentence:
From a biophysical point of view, action potentials are the result of currents that pass through ion channels in the cell membrane. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
presynaptic spike arrival, noisy reset, cortical neuron model, diffusive noise, detailed neuron models, refractory kernel, last firing time, last output spike, irregular spike trains, firing time difference, formal spiking neurons, neuronal firing times, spike packet, total postsynaptic potential, spike evokes, spiking neuron models, refractory densities, reverse correlation function, postsynaptic firing rate, postsynaptic spike train, signal transmission properties, input current pulse, last postsynaptic spike, next firing time, precisely timed spikes
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Spike Response Model, Locking Theorem
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