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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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DOI (Published version): 10.1523/eneuro.0486-21.2022

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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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.</abstract><type>Journal Article</type><journal>eneuro</journal><volume>9</volume><journalNumber>3</journalNumber><paginationStart>ENEURO.0486</paginationStart><paginationEnd>21.2022</paginationEnd><publisher>Society for Neuroscience</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2373-2822</issnElectronic><keywords>functional network; hyperexcitability; interictal EEG; mathematical model; photosensitive epilepsy</keywords><publishedDay>31</publishedDay><publishedMonth>5</publishedMonth><publishedYear>2022</publishedYear><publishedDate>2022-05-31</publishedDate><doi>10.1523/eneuro.0486-21.2022</doi><url/><notes>Data availability:MATLAB scripts implementing the methods described in the article are freely available online at https://github.com/ml0pe5/Photostimulation_BNI_NI.</notes><college>COLLEGE NANME</college><department>Computer Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SCS</DepartmentCode><institution>Swansea University</institution><apcterm/><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. 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spelling 2022-10-06T10:48:34.3386689 v2 61203 2022-09-13 A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG 555e06e0ed9a87608f2d035b3bde3a87 0000-0002-4758-0394 Jiaxiang Zhang Jiaxiang Zhang true false 2022-09-13 SCS 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. Journal Article eneuro 9 3 ENEURO.0486 21.2022 Society for Neuroscience 2373-2822 functional network; hyperexcitability; interictal EEG; mathematical model; photosensitive epilepsy 31 5 2022 2022-05-31 10.1523/eneuro.0486-21.2022 Data availability:MATLAB scripts implementing the methods described in the article are freely available online at https://github.com/ml0pe5/Photostimulation_BNI_NI. COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 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. 2022-10-06T10:48:34.3386689 2022-09-13T13:52:04.1768834 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Marinho A. Lopes 0000-0002-5764-2261 1 Sanchita Bhatia 2 Glen Brimble 3 Jiaxiang Zhang 0000-0002-4758-0394 4 Khalid Hamandi 5 61203__25312__50ce80b1b23a42f296592f5928f0acaf.pdf 61203_VoR.pdf 2022-10-06T10:47:22.4980078 Output 1619637 application/pdf Version of Record true Copyright © 2022 Lopes et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license true eng http://creativecommons.org/licenses/by/4.0/
title A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG
spellingShingle A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG
Jiaxiang Zhang
title_short A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG
title_full A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG
title_fullStr A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG
title_full_unstemmed A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG
title_sort A Computational Biomarker of Photosensitive Epilepsy from Interictal EEG
author_id_str_mv 555e06e0ed9a87608f2d035b3bde3a87
author_id_fullname_str_mv 555e06e0ed9a87608f2d035b3bde3a87_***_Jiaxiang Zhang
author Jiaxiang Zhang
author2 Marinho A. Lopes
Sanchita Bhatia
Glen Brimble
Jiaxiang Zhang
Khalid Hamandi
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container_issue 3
container_start_page ENEURO.0486
publishDate 2022
institution Swansea University
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publisher Society for Neuroscience
college_str Faculty of Science and Engineering
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hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
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department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
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description 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.
published_date 2022-05-31T04:19:52Z
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