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Pre-ictal fluctuation of EEG functional connectivity discriminates seizure phenotypes in mesial temporal lobe epilepsy.

Authors :
Ye, Hongyi
He, Chenmin
Hu, Wenhan
Xiong, Kai
Hu, Lingli
Chen, Cong
Xu, Sha
Xu, Cenglin
Wang, Yi
Ding, Yao
Wu, Yingcai
Zhang, Kai
Wang, Shan
Wang, Shuang
Source :
Clinical Neurophysiology. Jul2023, Vol. 151, p107-115. 9p.
Publication Year :
2023

Abstract

• Clinical and subclinical seizures have quantifiable pre-ictal EEG differences in mesial temporal lobe epilepsy. • Variability of pre-ictal functional connectivity is able to distinguish seizure phenotypes. • Pre-ictal brain network stability within or between epileptic zones is pertinent to the expression of seizure behavior. We explored whether quantifiable differences between clinical seizures (CSs) and subclinical seizures (SCSs) occur in the pre-ictal state. We analyzed pre-ictal stereo-electroencephalography (SEEG) retrospectively across mesial temporal lobe epilepsy patients with recorded CSs and SCSs. Power spectral density and functional connectivity (FC) were quantified within and between the seizure onset zone (SOZ) and the early propagation zone (PZ), respectively. To evaluate the fluctuation of neural connectivity, FC variability was computed. Measures were further verified by a logistic regression model to evaluate their classification potentiality through the area under the receiver-operating-characteristics curve (AUC). Fifty-four pre-ictal SEEG epochs (27 CSs and 27 SCSs) were selected among 14 patients. Within the SOZ, pre-ictal FC variability of CSs was larger than SCSs in 1–45 Hz during 30 seconds before seizure onset. Pre-ictal FC variability between the SOZ and PZ was larger in SCSs than CSs in 55–80 Hz within 1 minute before onset. Using these two variables, the logistic regression model achieved an AUC of 0.79 when classifying CSs and SCSs. Pre-ictal FC variability within/between epileptic zones, not signal power or FC value, distinguished SCSs from CSs. Pre-ictal epileptic network stability possibly marks seizure phenotypes, contributing insights into ictogenesis and potentially helping seizure prediction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13882457
Volume :
151
Database :
Academic Search Index
Journal :
Clinical Neurophysiology
Publication Type :
Academic Journal
Accession number :
164259924
Full Text :
https://doi.org/10.1016/j.clinph.2023.05.004