Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Stochastic Neural Field Theory

  • Paul Bressloff
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_77-3

Definition

One of the major challenges in neuroscience is to determine how noise that is present at the molecular and cellular levels affects dynamics and information processing at the macroscopic level of synaptically coupled neuronal populations. Often noise is incorporated into deterministic neural network models using extrinsic noise sources. An alternative approach is to assume that noise arises intrinsically as a collective population effect, which has led to a master equation formulation of stochastic neural networks. Stochastic neural fields are obtained by taking a continuum limit of a stochastic neural network with spatially structured synaptic weights.

Detailed Description

The spike trains of individual cortical neurons in vivo tend to be very noisy, having interspike interval (ISI) distributions that are close to Poisson (Softky and Koch 1993). The main source of intrinsic fluctuations at the single-cell level is channel noise, which arises from the variability in the...

Keywords

Master Equation Neural Field Chemical Master Equation Jump Markov Process Stochastic Neural Network 
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.
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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of UtahSalt Lake CityUSA