Spiking Neuron Models

Single Neurons, Populations, Plasticity

Wulfram Gerstner, Werner Kistler

494 pages, parution le 06/11/2002

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Résumé

Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.

Contents

Introduction

Part 1 Single neuron models

Detailed neuron models
Two-dimensional neuron models
Formal spiking neuron models
Noise in spiking neuron models

Part 2 Population models

Population equations
Signal transmission and neuronal coding
Oscillations and synchrony
Spatially structured networks

Part 3 Models of synaptic plasticity

Hebbian models
Learning equations
Plasticity and coding

Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	Wulfram Gerstner, Werner Kistler
Parution	06/11/2002
Nb. de pages	494
Format	17,5 x 24,5
Couverture	Broché
Poids	1026g
Intérieur	Noir et Blanc
EAN13	9780521890793
ISBN13	978-0-521-89079-3