Introduction to Theoretical Neurobiology: Volume 1, Linear Cable Theory and Dendritic Structure

by Henry C. Tuckwell

Overview

The human brain contains billions of nerve cells whose activity plays a critical role in the way we behave, feel, perceive, and think. This two-volume set explains the basic properties of a neuron—an electrically active nerve cell—and develops mathematical theories for the way neurons respond to the various stimuli they receive. Volume 1 contains descriptions and analyses of the principle mathematical models that have been developed for neurons in the past thirty years. It provides a brief review of the basic neuroanatomical and neurophysiological facts that will form the focus of the mathematical treatment. Tuckwell discusses the mathematical theories, beginning with the theory of membrane potentials. He then goes on to treat the Lapicque model, linear cable theory, and time-dependent solutions of the cable equations. He concludes with a description of Rall's model nerve cell. Because the level of mathematics increases steadily upward from Chapter Two some familiarity with differential equations and linear algebra is desirable.

Product Details

ISBN-13:	9780521022224
Publisher:	Cambridge University Press
Publication date:	04/20/2006
Series:	Cambridge Studies in Mathematical Biology , #8
Pages:	304
Product dimensions:	5.98(w) x 9.02(h) x 0.71(d)

Table of Contents

Preface; 1. Introductory neuroanatomy and neurophysiology: the properties of motoneurons; 2. The classical theory of membrane potentials; 3. The Lapicque model of the nerve cell; 4. Linear cable theory for nerve cylinders and dendritic trees: steady-state solutions; 5. Time-dependent cable theory for nerve cylinders and dendritic trees; 6. Rall's model neuron; References.

Editorial Reviews

"It will undoubtably prove to be very useful for experimentalists...Its application will clearly help experimentalists and modelers to better understand thte behavior of their research system...an up-to-date comprehensive effort that encompasses the major analytical approaches to neuronal modeling at the cellular level." —Physics Today

From the Publisher