Advertisement

Neuronal Noise pp 243-290 | Cite as

The Mathematics of Synaptic Noise

  • Alain Destexhe
  • Michelle Rudolph-Lilith
Chapter
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 8)

Abstract

The previous chapters of this book have focused mostly on studies assessing and characterizing synaptic noise under a variety of experimental conditions, and on evaluating its role in shaping neural dynamics through computational models. Although detailed biophysical models of neurons in vivo (see Sect. 4.2) remain, so far, out of reach for a mathematically more rigorous approach, the introduced simplified models (see Sects. 4.3 and 4.4), at least partially, allow for an analytical treatment. The latter can be used to complement experimental and computational studies and, therefore, provide a deeper understanding of neuronal dynamics under noisy conditions. Moreover, a mathematical treatment can also be used to provide unprecedented characterization of synaptic noise and how it affects spiking activity. This will be the subject of this and the forthcoming chapters.

Keywords

Synaptic Input Planck Equation Synaptic Conductance Membrane Time Constant Membrane Equation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Unité de Neuroscience, Information et ComplexitéCNRS, UPR-2191Gif-sur-YvetteFrance

Personalised recommendations