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Stochastic Methods in Neuroscience

Carlo Laing and Gabriel J Lord

Abstract

We give a brief introduction to modelling in mathematical neuroscience, to stochastic processes, and stochastic differential equations as well as an overview of the book.

Keywords: stochastic processes

Bibliographic Information

Print publication date: 2009	Print ISBN-13: 9780199235070
Published to Oxford Scholarship Online: February 2010	DOI:10.1093/acprof:oso/9780199235070.001.0001

Authors

Affiliations are at time of print publication.

Carlo Laing, Editor
Institute of Information and Mathematical Sciences, Massey University, New Zealand

Gabriel J Lord, Editor
Heriot-Watt University, Edinburgh

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Front Matter

1 A Brief Introduction to Some Simple Stochastic Processes

2 Markov Chain Models of Ion Channels and Calcium Release Sites

3 Stochastic Dynamic Bifurcations and Excitability

4 Neural Coherence and Stochastic Resonance

6 The Role of Variability in Populations of Spiking Neurons

7 Population Density Methods in Large-Scale Neural Network Modelling

8 A Population Density Model of the Driven LGN/PGN

9 Synaptic ‘Noise’: Experiments, Computational Consequences and Methods to Analyse Experimental Data

10 Statistical Models of Spike Trains

11 Stochastic Simulation of Neurons, Axons, and Action Potentials

12 Numerical Simulations of SDEs and SPDEs From Neural Systems Using SDELab

End Matter

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (www.oxfordscholarship.com). (c) Copyright Oxford University Press, 2013. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a monograph in OSO for personal use (for details see http://www.oxfordscholarship.com/page/privacy-policy).date: 18 June 2013

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Stochastic Methods in Neuroscience

Carlo Laing and Gabriel J Lord

Abstract

Bibliographic Information

Authors

Affiliations are at time of print publication.

Reviews

Contents

Front Matter

Title Pages

Introduction

Nomenclature

List of Contributors

1 A Brief Introduction to Some Simple Stochastic Processes

2 Markov Chain Models of Ion Channels and Calcium Release Sites

3 Stochastic Dynamic Bifurcations and Excitability

4 Neural Coherence and Stochastic Resonance

5 Noisy Oscillators

6 The Role of Variability in Populations of Spiking Neurons

7 Population Density Methods in Large-Scale Neural Network Modelling

8 A Population Density Model of the Driven LGN/PGN

9 Synaptic ‘Noise’: Experiments, Computational Consequences and Methods to Analyse Experimental Data

10 Statistical Models of Spike Trains

11 Stochastic Simulation of Neurons, Axons, and Action Potentials

12 Numerical Simulations of SDEs and SPDEs From Neural Systems Using SDELab

End Matter

Index

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Stochastic Methods in Neuroscience

Carlo Laing and Gabriel J Lord

Abstract

Bibliographic Information

Authors

Affiliations are at time of print publication.

Subject(s) in Oxford Scholarship Online

Reviews

Contents

Front Matter

End Matter