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Oxford2010Stochastic Methods in Neuroscience
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CONTENTS Introduction vii Nomenclature xx List of Contributors xxii 1 A brief introduction to some simple stochastic processes 1 Benjamin Lindner 2 Markov chain models of ion channels and calcium release sites 29 Jeffrey R. Groff, Hilary DeRemigio, and Gregory D. Smith 3 Stochastic dynamic bifurcations and excitability 65 Nils Berglund and Barbara Gentz 4 Neural coherence and stochastic resonance 94 Andr′e Longtin 5 Noisy oscillators 124 Bard Ermentrout 6 The role of variability in populations of spiking neurons 153 Brent Doiron 7 Population density methods in large-scale neural network modelling 181 Daniel Tranchina 8 A population density model of the driven LGN/PGN 217 Marco A. Huertas and Gregory D. Smith 9 Synaptic ‘noise’: Experiments, computational consequences and methods to analyse experimental data 242 Alain Destexhe and Michelle Rudolph-Lilith 10 Statistical models of spike trains 272 Liam Paninski, Emery N. Brown, Satish Iyengar, and Robert E. Kass 11 Stochastic simulation of neurons, axons, and action potentials 297 A. Aldo Faisal vi Contents 12 Numerical simulations of SDEs and SPDEs from neural systems using SDELab 344 Hasan Alzubaidi, Hagen Gilsing, and Tony Shardlow Index |
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