Informationen zum Autor 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. Klappentext A text for graduates and researchers in computational neuroscience and stochastic systems, concentrating on the intersection between stochastic dynamics and neuroscience, through the presentation of a series of self-contained chapters on major aspects of noise and neuroscience, each written by an expert in their particular field. Zusammenfassung A text for graduates and researchers in computational neuroscience and stochastic systems, concentrating on the intersection between stochastic dynamics and neuroscience, through the presentation of a series of self-contained chapters on major aspects of noise and neuroscience, each written by an expert in their particular field.

Autorentext
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.

Klappentext

A text for graduates and researchers in computational neuroscience and stochastic systems, concentrating on the intersection between stochastic dynamics and neuroscience, through the presentation of a series of self-contained chapters on major aspects of noise and neuroscience, each written by an expert in their particular field.

Inhalt

PREFACE; NOMENCLATURE; 1. A brief introduction to some basic 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 variablity in populations of spiking neuons; 7. Population density methods in large-scale neural network modelling; 8. A population density model of the driven LGN/PGN; 9. Syanptic "noise": experiments, computatioal consequences and methods to analyze experimental data; 10. Statistical models of spike trains; 11. Stochastic simulations of neurons, axons, and action potentials; 12. Numerical simulations of SDEs and SPDEs from neural systems using SDELAB