Network-motif delay differential analysis of brain activity during seizures.
Journal
Chaos (Woodbury, N.Y.)
ISSN: 1089-7682
Titre abrégé: Chaos
Pays: United States
ID NLM: 100971574
Informations de publication
Date de publication:
01 Dec 2023
01 Dec 2023
Historique:
received:
01
07
2023
accepted:
28
11
2023
medline:
2
1
2024
pubmed:
2
1
2024
entrez:
29
12
2023
Statut:
ppublish
Résumé
Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions.
Identifiants
pubmed: 38156987
pii: 2932137
doi: 10.1063/5.0165904
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2023 Author(s). Published under an exclusive license by AIP Publishing.