Stochastic methods in neuroscience / edited by Carlo Laing and Gabriel J. Lord.

Format:

Book

Contributor:

Laing, Carlo.

Lord, Gabriel J.

Hazel M. Hussong Fund.

Language:

English

Subjects (All):

Computational neuroscience.

Stochastic processes.

Neurosciences--Mathematics.

Neurosciences.

Physical Description:

xxiii, 370 pages, 4 unnumbered pages of plates : illustrations ; 24 cm

Place of Publication:

Oxford : New York : Oxford University Press, 2010.

Summary:

Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large amounts of neurophysiological data, and advances in stochastic analysis. These techniques are leading to biophysically more realistic models. It has also become clear that both neuroscientists and mathematicians profit from collaborations in this exciting research area.

Graduates and researchers in computational neuroscience and stochastic systems, and neuroscientists seeking to learn more about recent advances in the modelling and analysis of noisy neural systems, will benefit from this comprehensive overview. The series of self-contained chapters, each written by experts in their field, covers key topics such as: Markov chain models forion channel release, stochastically forced single neurons and populations of neurons, statistical methods for parameter estimation; and the numerical approximation of these stochastic models.

Each chapter gives an overview of a particular topic, including its history, important results in the area, and future challenges, and the text comes complete with a jargon-busting index of acronyms to allow readers to familiarize themselves with the language used.

Contents:

1 A brief introduction to some simple stochastic processes / Benjamin Lindner 1

2 Markov chain models of ion channels and calcium release sites / Jeffrey R. Groff, Hilary DeRemigio, Gregory D. Smith 29

3 Stochastic dynamic bifurcations and excitability / Nils Berglund, Barbara Gentz 65

4 Neural coherence and stochastic resonance / Andrè Longtin 94

5 Noisy oscillators / Bard Ermentrout 124

6 The role of variability in populations of spiking neurons / Brent Doiron 153

7 Population density methods in large-scale neural network modelling / Daniel Tranchina 181

8 A population density model of the driven LGN/PGN / Marco A. Huertas, Gregory D. Smith 217

9 Synaptic 'noise': Experiments, computational consequences and methods to analyse experimental data / Alain Destexhe, Michelle Rudolph-Lilith 242

10 Statistical models of spike trains / Liam Paninski, Emery N. Brown, Satish Iyengar, Robert E. Kass 272

11 Stochastic simulation of neurons, axons, and action potentials / A. Aldo Faisal 297

12 Numerical simulations of SDEs and SPDEs from neural systems using SDELab / Hasan Alzubaidi, Hagen Gilsing, Tony Shardlow 344.

Notes:

Includes bibliographical references and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Hazel M. Hussong Fund.

ISBN:

9780199235070

0199235074

OCLC:

401164343

Publisher Number:

99937319689