Stochastic Neuron Models

✍ Scribed by Priscilla E. Greenwood, Lawrence M. Ward (auth.)

Publisher: Springer International Publishing
Year: 2016
Tongue: English
Leaves: 82
Series: Mathematical Biosciences Institute Lecture Series 1.5
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise.
This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included.

Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain Research Centre at the University of British Columbia.

✦ Table of Contents

Front Matter....Pages i-x
Introduction....Pages 1-7
Single Neuron Models....Pages 9-31
Population and Subpopulation Models....Pages 33-47
Spatially Structured Neural Systems....Pages 49-62
The Bigger Picture....Pages 63-67
Back Matter....Pages 69-75

✦ Subjects

Physiological, Cellular and Medical Topics; Probability Theory and Stochastic Processes; Neurosciences; Statistics for Life Sciences, Medicine, Health Sciences

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