Neuronal Noise.
Alain Destexhe and Michelle Rudolph

Springer, New York, 2012 (Preface by Christof Koch ISBN 978-0-387-79019-0).

neuronal noise
“Neuronal Noise” combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity, and how noise can be important for neuronal computations. The book covers many aspects of noise in neurons, with an emphasis on the largest source of noise: synaptic noise. It provides students and young researchers with an overview of the important methods and concepts that have emerged from research in this area. It also provides the specialist with a summary of the large body of sometimes contrasting experimental data, and different theories proposed to explore the computational power that various forms of “noise” can confer to neurons.

The book was published online and in paper format in February 2012.

Table of Contents:
  • Foreword (by Christof Koch)
  • Preface
  • Acknowledgments
  • Chapter I – Introduction
  • Chapter II – Basics
  • Chapter III – Synaptic noise
  • Chapter IV – Models of synaptic noise
  • Chapter V – Integrative properties in the presence of noise
  • Chapter VI – Recreating synaptic noise in dynamic-clamp
  • Chapter VII – The mathematics of synaptic noise
  • Chapter VIII – Analyzing synaptic noise
  • Chapter IX – Case studies
  • Chapter X – Conclusions and perspectives
  • Appendix A – Numerical integration of stochastic differential equations
  • Appendix B – Distributed generator algorithm
  • Appendix C – The Fokker-Planck formalism
  • Appendix D – The RT-Neuron interface for dynamic-clamp
  • References
  • Index

See the Springer “Neuronal Noise” web page