Graph-Based Brain Network Analysis in Epilepsy: An EEG Study

Yuejing Hu1, Qizhong Zhang1, Rihui Li2, Tom Potter, Yingchun Zhang

  • 1Hangzhou Dianzi University
  • 2University of Houston

Details

16:30 - 18:30 | Thu 21 Mar | Grand Ballroom B | ThPO.33

Session: Poster Session I

Abstract

In order to investigate the alterations of brain network in children with epilepsy during the interictal and ictal periods, partial directed coherence (PDC) was employed as a measure of causality to analyze 22 electroencephalography (EEG) datasets recorded from 10 focal seizure children in this study. Functional brain network during interictal and ictal periods were constructed based on the computed PDC values, from which two graph-based measures, including the degree and clustering coefficient were extracted to assess the functional connectivity in seizure-linked network. Results showed that, compared to interictal period, the regional degree at the center lobe in delta band during the ictal period was significantly reduced. On the contrary, the clustering coefficients in delta band during the ictal period were significantly increased in the frontal, parietal, and temporal lobes. Our findings therefore suggest that ictal state may affect the visual, physical, mental, auditory, and other functions in epileptic children, providing a new perspective to explore the brain network alterations in children with epilepsy.