Causal Analysis Of Epileptogenic Networks In Patients With Lesional Epilepsy

Patients with refractory epilepsy are usually admitted for invasive video electroencephalography monitoring(IVEM) which is utilized to guide surgical intervention by identifying the location and extent of the ictal-onset zones. Previous studies have shown that causal analysis of intracranial EEG(IEEG) signals contributes to the location of the ictal-onset zone by comparing the hypothesized epileptogenic focus with surgical outcome or region visually defined by the epileptologist, neither of which is the definite localization of the epileptogenic zone. The purpose of this study is to investigate the reliability of causal analysis in a more precise way by applying it to patients with magnetic resonance image(MRI) lesions neocortical epilepsyWe employed a time-varying causality measure, the adaptive directed transfer function(ADTF) to identify the epileptogenic cortical network in three patients with lesional refractory neocortical epilepsy. Then graph theory methods were applied as a mean to identify critical network nodes in epileptic networks. Both out-degree and betweenness-centrality(BC) were obtained from each patient’s epileptic network during ictal state.In all three patients, electrode contacts with highest total out-degree or betweenness-centrality among all contacts lie within or nearby the focal and betweenness-centrality outperforms out-degree. Furthermore, both out-degree and betweenness-centrality were found to be frequency dependent, with high frequency Gamma band most closely correlated with focal, as has been reported in previous studies.This study showed that causal connectivity patterns derived from IEEG recordings could lead to improved understandings about seizure propagation and may improve the accuracy of the pre-surgical evaluation in patients with refractory epilepsy. It also suggests betweenness-centrality may be a better network characteristic to locate the ictal-onset zone.