Table of Contents

PrefaceCarlo Laing and Gabriel J Lord:
Nomenclature
1: Benjamin Lindner: A brief introduction to some basic stochastic processes
2: Jeffrey R Groff, Hilary DeRemigio, and Gregory D Smith: Markov chain models of ion channels and calcium release sites
3: Nils Berglund and Barbara Gentz: Stochastic dynamic bifurcations and excitability
4: André Longtin: Neural coherence and stochastic resonance
5: Bard Ermentrout: Noisy oscillators
6: Brent Doiron: The role of variablity in populations of spiking neuons
7: Daniel Tranchina: Population density methods in large-scale neural network modelling
8: Marco A Huertas and Gregory D Smith: A population density model of the driven LGN/PGN
9: Alin Destexhe and Michelle Rudolph-Lilith: Syanptic "noise": experiments, computatioal consequences and methods to analyze experimental data
10: Liam Paninski, Emery N Brown, Satish Iyengar, and Robert E Kass: Statistical models of spike trains
11: A Aldo Faisal: Stochastic simulations of neurons, axons, and action potentials
12: Hasan Alzubaidi, Hagen Gilsing, Tony Shardlow: Numerical simulations of SDEs and SPDEs from neural systems using SDELAB

About the Author

Carlo Laing obtained his PhD in applied mathematics from the University of Cambridge. After post-doctoral positions in the UK, USA and Canada, he joined Massey University in Auckland, New Zealand, where he is currently a senior lecturer. His interests include nonlinear dynamical systems, particularly as applied in computational neuroscience. Gabriel Lord obtained his PhD from the University of Bath, UK. After a post-doctoral position at the University of Bristol
and working for a time in industry he joined Heriot-Watt University in Edinburgh, UK. His research interests are in applied computational analysis, stochastic numerics and applications from
computational neuroscience.