Spiking Neuron Models: Single Neurons, Populations, Plasticity / Edition 1

by Wulfram Gerstner, Werner M. Kistler

Overview

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.

Product Details

ISBN-13:	9780521890793
Publisher:	Cambridge University Press
Publication date:	08/15/2002
Edition description:	New Edition
Pages:	496
Product dimensions:	6.97(w) x 9.61(h) x 0.91(d)

Table of Contents

1. Introduction; Part I. Single Neuron Models: 2. Detailed neuron models; 3. Two-dimensional neuron models; 4. Formal spiking neuron models; 5. Noise in spiking neuron models; Part II. Population Models: 6. Population equations; 7. Signal transmission and neuronal coding; 8. Oscillations and synchrony; 9. Spatially structured networks; Part III. Models of Synaptic Plasticity: 10. Hebbian models; 11. Learning equations; 12. Plasticity and coding; Bibliography; Index.

Editorial Reviews

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

From the Publisher

A core textbook for a one-semester graduate or advanced undergraduate course on neuronal dynamics, or an auxiliary text for a larger course on computational neuroscience, theoretical biology, and related topics. Students might be majors in physics, mathematics, or computer science with an interest in biology or majors in biology interested in mathematical modeling. No knowledge beyond undergraduate mathematics is assumed except for marked sections. Annotation c. Book News, Inc., Portland, OR