期刊
SCIENTIFIC REPORTS
卷 9, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41598-019-46633-7
关键词
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资金
- Medical Research Council [MR/N026063/1, MR/K013998/1]
- EPSRC [EP/P021417/1, EP/N014391/1]
- Epilepsy Research UK [P1505]
- Wellcome Trust Institutional Strategic Support Award [WT105618MA]
- National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust
- Epilepsy Research UK
- EPSRC [EP/N014391/1, EP/P021417/1] Funding Source: UKRI
- MRC [MC_PC_15047, MR/K013998/1, MR/N026063/1] Funding Source: UKRI
Seizure onset in epilepsy can usually be classified as focal or generalized, based on a combination of clinical phenomenology of the seizures, EEG recordings and MRI. This classification may be challenging when seizures and interictal epileptiform discharges are infrequent or discordant, and MRI does not reveal any apparent abnormalities. To address this challenge, we introduce the concept of Ictogenic Spread (IS) as a prediction of how pathological electrical activity associated with seizures will propagate throughout a brain network. This measure is defined using a person-specific computer representation of the functional network of the brain, constructed from interictal EEG, combined with a computer model of the transition from background to seizure-like activity within nodes of a distributed network. Applying this method to a dataset comprising scalp EEG from 38 people with epilepsy (17 with genetic generalized epilepsy (GGE), 21 with mesial temporal lobe epilepsy (mTLE)), we find that people with GGE display a higher IS in comparison to those with mTLE. We propose IS as a candidate computational biomarker to classify focal and generalized epilepsy using interictal EEG.
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