From Computer to Brain: Foundations of Computational Neuroscience

ISBN-13: 9780387955261 / Angielski / Miękka / 2002 / 364 str.

William W. Lytton; W. W. Lytton

Opis

Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.

Recenzje

From the Foreword:
"In From Computer to Brain: Foundations of Computational Neuroscience, William W. Lytton provides a gentle but rigorous introduction to the art of modeling neurons and neural systems. It is an accessible entry to the methods and approaches used to model the brain at many different levels, ranging from synapses and dendrites to neurons and neural circuits. This book gives a balanced view of the wide range of modeling techniques that are available in a way that is accessible to a wide audience. This is a book that will bring a smile to your face as well as inspire your imagination."
-- Terrence J. Sejnowski
Howard Hughes Medical Institute, Salk Institute, University of California at San Diego

Spis treści

Introduction * I. Perspectives * Computational Neuroscience and You * Basic Neuroscience * II. Computers * Computer Representations * The Soul of an Old Machine * III. Cybernetics * Concept Neurons * Neural Coding * Our Friend the Limulus * Supervised Learning: The Delta Rule and Back-Propagation * Associative Memory Networks * IV. From Artificial to Real * From Soap to Volts * Hodgkin-Huxley Model * Compartment Modeling * From Artificial Neural Network to Realistic Neural Network * Neural Circuits * The Basics * Glossary * Index