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

Yuejing Hu, Qizhong Zhang, Rihui Li, Thomas Potter, Yingchun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages130-133
Number of pages4
ISBN (Electronic)9781538679210
DOIs
StatePublished - May 16 2019
Event9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States
Duration: Mar 20 2019Mar 23 2019

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2019-March
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other9th International IEEE EMBS Conference on Neural Engineering, NER 2019
CountryUnited States
CitySan Francisco
Period3/20/193/23/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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