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Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
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SYSNO ASEP 0546900 Druh ASEP J - Článek v odborném periodiku Zařazení RIV Záznam nebyl označen do RIV Poddruh J Článek ve WOS Název Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised Tvůrce(i) Woldman, W. (GB)
Schmidt, Helmut (UIVT-O) ORCID, RID, SAI
Abela, E. (GB)
Chowdhury, F.A. (GB)
Pawley, A.D. (GB)
Jewell, S. (GB)
Richardson, M.P. (GB)
Terry, J.R.Celkový počet autorů 8 Číslo článku 7043 Zdroj.dok. Scientific Reports. - : Nature Publishing Group - ISSN 2045-2322
Roč. 10, č. 1 (2020)Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova ilae commission ; functional connectivity ; position paper ; epilepsy ; eeg ; classification ; misdiagnosis ; oscillations ; management ; diagnosis UT WOS 000530731300017 EID SCOPUS 85083982123 DOI 10.1038/s41598-020-63430-9 Anotace Current explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast light on seizure-generating mechanisms and allow to quantify to which extent a seizure is focal or generalised. Functional brain networks were estimated in segments of scalp-EEG without interictal discharges (68 people with epilepsy, 38 controls). Simplified brain dynamics were simulated using a computer model. We introduce: Critical Coupling (C-c), the ability of a network to generate seizures; Onset Index (OI), the tendency of a region to generate seizures; and Participation Index (PI), the tendency of a region to become involved in seizures. C-c was lower in both patient groups compared with controls. OI and PI were more variable in focal-onset than generalised-onset cases. In focal cases, the regions with highest OI and PI corresponded to the side of seizure onset. Properties of interictal functional networks from scalp EEG can be estimated using a computer model and used to predict seizure likelihood and onset patterns. This may offer potential to enhance diagnosis through quantification of seizure type using inter-ictal recordings. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2022
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