Temporally correlated fluctuations drive epileptiform dynamics.

ABSTRACT: Macroscopic models of brain networks typically incorporate assumptions regarding the characteristics of afferent noise, which is used to represent input from distal brain regions or ongoing fluctuations in non-modelled parts of the brain. Such inputs are often modelled by Gaussian white noise which has a flat power spectrum. In contrast, macroscopic fluctuations in the brain typically follow a 1/f^b spectrum. It is therefore important to understand the effect on brain dynamics of deviations from the assumption of white noise. In particular, we wish to understand the role that noise might play in eliciting aberrant rhythms in the epileptic brain. To address this question we study the response of a neural mass model to driving by stochastic, temporally correlated input. We characte

SUBMITTER: Jedynak M 

PROVIDER: S-EPMC5353705 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature