A critical role for network structure in seizure onset: A computational modeling approach

Research output: Contribution to journalArticle

Authors

Colleges, School and Institutes

Abstract

Recent clinical work has implicated network structure as critically important in the initiation of seizures in people with idiopathic generalized epilepsies. In line with this idea, functional networks derived from the electroencephalogram (EEG) at rest have been shown to be significantly different in people with generalized epilepsy compared to controls. In particular, the mean node degree of networks from the epilepsy cohort was found to be statistically significantly higher than those of controls. However, the mechanisms by which these network differences can support recurrent transitions into seizures remain unclear. In this study, we use a computational model of the transition into seizure dynamics to explore the dynamic consequences of these differences in functional networks. We demonstrate that networks with higher mean node degree are more prone to generating seizure dynamics in the model and therefore suggest a mechanism by which increased mean node degree of brain networks can cause heightened ictogenicity.

Details

Original languageEnglish
Article number261
Pages (from-to)1-7
Number of pages7
JournalFrontiers in neurology
Volume5
Publication statusPublished - 8 Dec 2014

Keywords

  • network dynamics, epilepsy, dynamical systems, graph theory, EEG