Interictal structural and functional connectivity in idiopathic generalized epilepsy: A systematic review of graph theoretical studies.
Connectome
EEG
Graph theory
IGE
Network analysis
fMRI
Journal
Epilepsy & behavior : E&B
ISSN: 1525-5069
Titre abrégé: Epilepsy Behav
Pays: United States
ID NLM: 100892858
Informations de publication
Date de publication:
05 2020
05 2020
Historique:
received:
29
11
2019
revised:
22
02
2020
accepted:
28
02
2020
pubmed:
21
3
2020
medline:
20
1
2021
entrez:
21
3
2020
Statut:
ppublish
Résumé
The evaluation of the role of anomalous neuronal networks in epilepsy using a graph theoretical approach is of growing research interest. There is currently no consensus on optimal methods for performing network analysis, and it is possible that variations in study methodology account for diverging findings. This review focuses on global functional and structural interictal network characteristics in people with idiopathic generalized epilepsy (IGE) with the aim of appraising the methodological approaches used and assessing for meaningful consensus. Thirteen studies were included in the review. Data were heterogenous and not suitable for meta-analysis. Overall, there is a suggestion that the cerebral neuronal networks of people with IGE have different global structural and functional characteristics to people without epilepsy. However, the nature of the aberrations is inconsistent with some studies demonstrating a more regular network configuration in IGE, and some, a more random topology. There is greater consistency when different data modalities and connectivity subtypes are compared separately, with a tendency towards increased small-worldness of networks in functional electroencephalography/magnetoencephalography (EEG/MEG) studies and decreased small-worldness of networks in structural studies. Prominent variation in study design at all stages is likely to have contributed to differences in study outcomes. Despite increasing literature surrounding neuronal network analysis, systematic methodological studies are lacking. Absence of consensus in this area significantly limits comparison of results from different studies, and the ability to draw firm conclusions about network characteristics in IGE.
Identifiants
pubmed: 32193094
pii: S1525-5050(20)30192-X
doi: 10.1016/j.yebeh.2020.107013
pii:
doi:
Types de publication
Journal Article
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
107013Informations de copyright
Copyright © 2020 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest None of the authors has any conflict of interest to disclose.