Literature DB >> 33501642

Interictal electroencephalographic functional network topology in drug-resistant and well-controlled idiopathic generalized epilepsy.

Emily J Pegg1,2, Jason R Taylor2,3, Petroula Laiou4, Mark Richardson5, Rajiv Mohanraj1,2.   

Abstract

OBJECTIVE: The study aim was to compare interictal encephalographic (EEG) functional network topology between people with well-controlled idiopathic generalized epilepsy (WC-IGE) and drug-resistant IGE (DR-IGE).
METHODS: Nineteen participants with WC-IGE, 18 with DR-IGE, and 20 controls underwent a resting state, 64-channel EEG. An artifact-free epoch was bandpass filtered into the frequency range of high and low extended alpha. Weighted functional connectivity matrices were calculated. Mean degree, degree distribution variance, characteristic path length (L), clustering coefficient, small world index (SWI), and betweenness centrality were measured. A Kruskal-Wallis H-test assessed effects across groups. Where significant differences were found, Bonferroni-corrected Mann-Whitney pairwise comparisons were calculated.
RESULTS: In the low alpha band (6-9 Hz), there was a significant difference in L at the three-group level (p < .0001). This was lower in controls than both WC-IGE and DR-IGE (p < .0001 for both), with no difference in L between WC-IGE and DR-IGE. Mean degree (p = .031), degree distribution variance (p = .032), and SWI (p = .023) differed across the three groups in the high alpha band (10-12 Hz). Mean degree and degree distribution variance were lower in WC-IGE than controls (p = .029 for both), and SWI was higher in WC-IGE compared with controls (p = .038), with no differences in other pairwise comparisons. SIGNIFICANCE: IGE network topology is more regular in the low alpha frequency band, potentially reflecting a more vulnerable structure. WC-IGE network topology is different from controls in the high alpha band. This may reflect drug-induced network changes that have stabilized the WC-IGE network by rendering it less likely to synchronize. These results are of potential importance in advancing the understanding of mechanisms of epilepsy drug resistance and as a possible basis for a biomarker of DR-IGE.
© 2021 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.

Entities:  

Keywords:  EEG; IGE; connectomics; drug resistance; graph theory; network analysis

Mesh:

Substances:

Year:  2021        PMID: 33501642     DOI: 10.1111/epi.16811

Source DB:  PubMed          Journal:  Epilepsia        ISSN: 0013-9580            Impact factor:   5.864


  5 in total

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2.  Feature Extraction of the Brain's Dynamic Complex Network Based on EEG and a Framework for Discrimination of Pediatric Epilepsy.

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4.  Heterogeneity of resting-state EEG features in juvenile myoclonic epilepsy and controls.

Authors:  Amy Shakeshaft; Petroula Laiou; Eugenio Abela; Ioannis Stavropoulos; Mark P Richardson; Deb K Pal
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5.  Characterizing the electrophysiological abnormalities in visually reviewed normal EEGs of drug-resistant focal epilepsy patients.

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  5 in total

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