O155 Pre-seizure brain networks architecture as index of prediction in epileptic seizure

Abstract

Objective Epilepsy is a neurological disorder characterized by sudden and unpredictable occurrence of paroxysmal neuronal firing and sometimes evolving in clinically evident seizure. To predict seizure event, small-world characteristic in nine minutes before seizure, divided in three 3-min periods (T0, T1, T2) were investigated. Methods Intracerebral recordings were obtained from 10 patients with drug resistant focal epilepsy examined by means of stereotactically implanted electrodes; analysis was focused in a period of low spiking (Baseline) and during two seizures for each subject. Weighted and undirected networks were built. Network vertices are electrodes’ contacts close to epileptic focus, edges are weighted by mscohere (magnitude squared coherence). Results Differences were observed between Baseline and T1 and between Baseline and T2 in Theta band; and between Baseline and T1, Baseline and T2, and near-significant difference between T0 and T2 in Alpha 2 band. Moreover, an intra-band index was computed for small worldness as difference between Theta and Alpha 2. It was found a growing index trend from Baseline to T2. Discussion Results of this study suggest that cortical network features significantly modify their configuration up to about 10 min before seizure onset. Significance Identifying connectivity alterations could provide valuable informations at individual level on transient factors that influence the clinical manifestations of the disease. Conclusions Cortical network shows a specific pre-seizure architecture which could predict the incoming epileptic seizure. This study opens interesting avenues for future researches investigating brain connectivity modifications approximating a clinical seizure also in order to address a preventive therapy.