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A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG

Marinho A. Lopes Orcid Logo, Sanchita Bhatia, Glen Brimble, Jiaxiang Zhang Orcid Logo, Khalid Hamandi

eneuro, Volume: 9, Issue: 3, Pages: ENEURO.0486 - 21.2022

Swansea University Author: Jiaxiang Zhang Orcid Logo

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Abstract

People with photosensitive epilepsy (PSE) are prone to seizures elicited by visual stimuli. The possibility of inducing epileptiform activity in a reliable way makes PSE a useful model to understand epilepsy, with potential applications for the development of new diagnostic methods and new treatment...

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Published in: eneuro
ISSN: 2373-2822
Published: Society for Neuroscience 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa61203
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Abstract: People with photosensitive epilepsy (PSE) are prone to seizures elicited by visual stimuli. The possibility of inducing epileptiform activity in a reliable way makes PSE a useful model to understand epilepsy, with potential applications for the development of new diagnostic methods and new treatments for epilepsy. A relationship has been demonstrated between PSE and both occipital and more widespread cortical hyperexcitability using various types of stimulation. Here we aimed to test whether hyperexcitability could be inferred from resting interictal electroencephalographic (EEG) data without stimulation. We considered a cohort of 46 individuals with idiopathic generalized epilepsy who underwent EEG during intermittent photic stimulation: 26 had a photoparoxysmal response (PPR), the PPR group, and 20 did not, the non-PPR group. For each individual, we computed functional networks from the resting EEG data before stimulation. We then placed a computer model of ictogenicity into the networks and simulated the propensity of the network to generate seizures in silico [the brain network ictogenicity (BNI)]. Furthermore, we computed the node ictogenicity (NI), a measure of how much each brain region contributes to the overall ictogenic propensity. We used the BNI and NI as proxies for testing widespread and occipital hyperexcitability, respectively. We found that the BNI was not higher in the PPR group relative to the non-PPR group. However, we observed that the (right) occipital NI was significantly higher in the PPR group relative to the non-PPR group. Other regions did not have significant differences in NI values between groups.
Item Description: Data availability:MATLAB scripts implementing the methods described in the article are freely available online at https://github.com/ml0pe5/Photostimulation_BNI_NI.
Keywords: functional network; hyperexcitability; interictal EEG; mathematical model; photosensitive epilepsy
College: Faculty of Science and Engineering
Funders: M.A.L. was supported by Grant 204824/Z/16/Z the Cardiff University Wellcome Trust Institutional Strategic Support Fund (ISSF). J.Z. was supported by European Research Council Grant 716321. K.H. was supported by UK MEG Medical Research Council (MRC) Partnership Grant MRC/ Engineering and Physical Sciences Research Council MR/K005464/1, and Wellcome Trust Strategic Award 104943/Z/14/Z. K.H. also was supported by BRAIN Unit Infrastructure Grant UA05, which is funded by the Welsh Government through Health and Care Research Wales.
Issue: 3
Start Page: ENEURO.0486
End Page: 21.2022