Dynamic network properties of the interictal brain determine whether seizures appear focal or generalised
| Autor: | Eugenio Abela, Adam D. Pawley, Sharon L. Jewell, John R. Terry, Mark P. Richardson, Fahmida A Chowdhury, Helmut Schmidt, Wessel Woldman |
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| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Dynamic network analysis lcsh:Medicine Electroencephalography Article Functional networks 03 medical and health sciences Functional brain Epilepsy 0302 clinical medicine Seizures medicine Humans Ictal lcsh:Science 030304 developmental biology Brain network 0303 health sciences Multidisciplinary medicine.diagnostic_test business.industry lcsh:R Brain Generalised seizure Diagnostic markers medicine.disease 030104 developmental biology Case-Control Studies lcsh:Q business Neuroscience 030217 neurology & neurosurgery |
| Zdroj: | Scientific Reports Scientific Reports, Vol 10, Iss 1, Pp 1-11 (2020) |
| DOI: | 10.1101/576785 |
| Popis: | ObjectiveCurrent 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 in the clinic the extent to which a seizure is focal or generalised.Methods68 people with epilepsy and 38 healthy controls underwent 19 channel scalp EEG recording. Functional brain networks were estimated in each subject using phase-locking between EEG channels in the 6-9Hz band from segments of 20s without interictal discharges. Simplified brain dynamics were simulated using a computer model. We introduce three concepts: Critical Coupling (Cc), 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.ResultsCc was lower in both patient groups compared with controls. OI and PI were more variable in focal-onset than generalised-onset cases. No regions showed higher OI and PI in generalised-onset cases than in healthy controls; in focal cases, the regions with highest OI and PI corresponded to the side of seizure onset.ConclusionsProperties of interictal functional networks from scalp EEG can be estimated using a computer model and used to predict seizure likelihood and onset patterns. Our framework, consisting of three clinically-meaningful measures, could be implemented in the clinic to quantify the diagnosis and seizure onset pattern. |
| Databáze: | OpenAIRE |
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