Semi-automatic Extraction of Functional Dynamic Networks Describing Patient's Epileptic Seizures.

ABSTRACT: Intracranial electroencephalography (EEG) studies using stereotactic EEG (SEEG) have shown that during seizures, epileptic activity spreads across several anatomical regions from the seizure onset zone toward remote brain areas. A full and objective characterization of this patient-specific time-varying network is crucial for optimal surgical treatment. Functional connectivity (FC) analysis of SEEG signals recorded during seizures enables to describe the statistical relations between all pairs of recorded signals. However, extracting meaningful information from those large datasets is time consuming and requires high expertise. In the present study, we first propose a novel method named Brain-wide Time-varying Network Decomposition (BTND) to characterize the dynamic epileptogenic networks

SUBMITTER: Frusque G 

PROVIDER: S-EPMC7759641 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature