9780262511001-0262511002-Neural Codes and Distributed Representations: Foundations of Neural Computation (Computational Neuroscience)

Neural Codes and Distributed Representations: Foundations of Neural Computation (Computational Neuroscience)

ISBN-13: 9780262511001
ISBN-10: 0262511002
Edition: First Edition
Author: Terrence J. Sejnowski, Laurence F Abbott
Publication date: 1999
Publisher: MIT Press
Format: Paperback 351 pages
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Book details

ISBN-13: 9780262511001
ISBN-10: 0262511002
Edition: First Edition
Author: Terrence J. Sejnowski, Laurence F Abbott
Publication date: 1999
Publisher: MIT Press
Format: Paperback 351 pages

Summary

Neural Codes and Distributed Representations: Foundations of Neural Computation (Computational Neuroscience) (ISBN-13: 9780262511001 and ISBN-10: 0262511002), written by authors Terrence J. Sejnowski, Laurence F Abbott, was published by MIT Press in 1999. With an overall rating of 4.3 stars, it's a notable title among other AI & Machine Learning (Neuropsychology, Psychology & Counseling, Cognitive Psychology, Behavioral Sciences, Cognitive, Psychology, Neuropsychology, Computer Science) books. You can easily purchase or rent Neural Codes and Distributed Representations: Foundations of Neural Computation (Computational Neuroscience) (Paperback) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years.The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.
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