Temporal evolution analysis of functional connectivity in epilepsy based on weighted complex networks

摘要

It's proposed that weights of links play critical role in complex system. In this study, we adopted nine network characteristics to verify their performance in the brain of temporal lobe epilepsy (TLE). Weighted networks were derived from phase locking values on multichannel intracranial electroencephalography (EEG) recordings when the patient is undergoing seizure attack. It's illustrated that network efficiency, vertex strength, transitivity and characteristic path were sensitive to the occurrence of seizures compared to other measurements. What's more, networks derived from gamma band neural oscillations performs more remarkable than other sub band signals while networks in delta band manifests trivial alterations during seizure process. Further research would focus on investigating characteristic network features in weighted networks and frequency dependency in epileptic brain of TLE.