Brain network excitatory/inhibitory imbalance is a biomarker for drug-naive Rolandic epilepsy: A radiomics strategy.
Rolandic epilepsy
benign epilepsy of childhood with centro-temporal spikes
classification
cognitive network
dynamic causal modeling
excitation and inhibition imbalance
machine learning
support vector machine
Journal
Epilepsia
ISSN: 1528-1167
Titre abrégé: Epilepsia
Pays: United States
ID NLM: 2983306R
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
revised:
06
07
2021
received:
14
04
2021
accepted:
08
07
2021
pubmed:
5
8
2021
medline:
19
4
2022
entrez:
4
8
2021
Statut:
ppublish
Résumé
Seizure occurs when the balance between excitatory and inhibitory (E/I) inputs to neurons is perturbed, resulting in abnormal electrical activity. This study investigated whether an existing E/I imbalance in neural networks is a useful diagnostic biomarker for Rolandic epilepsy by a resting-state dynamic causal modeling-based support vector machine (rs-DCM-SVM) algorithm. This multicenter study enrolled a discovery cohort (76 children with Rolandic epilepsy and 76 normal controls [NCs]) and a replication cohort (59 children with Rolandic epilepsy and 60 NCs). Spatial independent component analysis was used to seven canonical neural networks, and a total of 25 regions of interest were selected from these networks. The rs-DCM-SVM classifier was used for individual classification, consensus feature selection, and feature ranking. The rs-DCM-SVM classifier showed that the E/I imbalance in brain networks is a useful neuroimaging biomarker for Rolandic epilepsy, with an accuracy of 88.2% and 81.5% and an area under curve of .92 and .83 in the discovery and the replication cohorts, respectively. Consensus brain regions with the highest contributions to the classification were located within the epilepsy-related networks, indicating that this classifier was suitable. Consensus functional connection pairs with the highest contributions to the classification were associated with an excitation network loop and an inhibition network loop. The excitation loop mediated the integration of advanced cognitive networks (subcortex, dorsal attention, default mode, executive control, and salience networks), whereas the inhibition loop was involved in the segregation of sensorimotor and language networks. The two loops showed functional segregation. Brain E/I imbalance has potential to serve as a biomarker for individual classification in children with Rolandic epilepsy, and might be an important mechanism for causing seizures and cognitive impairment in children with Rolandic epilepsy.
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2426-2438Commentaires et corrections
Type : ErratumIn
Informations de copyright
© 2021 International League Against Epilepsy.
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