Synchronization Analysis of EEG Epilepsy by Visibility Network Graph and Cross-correlation

Epilepsy is a chronic neurological disorder affects people of all ages; this paper presents cross-correlation and state transfer network method to analyze synchronization between EEG data-channels from subjects with epilepsy seizures. The datasets are in two phases, preictal and ictal phase. All EEG segments are mapped into a corresponding state network graph to obtain the corresponding motifs and then the cross-correlation is applied to exhibit the synchronization changing during epilepsy seizures. The results showed that ictal phase presented high synchronization between channels, where low synchronization level is observed within preictal phase.