{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/86846"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/86846","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Source Localization of Simulated Electroencephalogram of Virtual Epileptic Patient to Investigate Clinically Feasible Montages","abstract":"M.S.","abstract_html":"M.S.","abstract_has_math":false,"creators":["Herrick, Zoe; 0000-0001-9907-6950"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Dutta, Anirban","Biomedical Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-02-25T23:23:23Z","date_published":"2025-02-25T23:23:23Z","updated_at":"2026-07-27T19:05:37Z","subjects":["neurosciences","applied mathematics","medical imaging"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/86846","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dutta, Anirban","Biomedical Engineering"]},{"key":"dc:creator","label":"Author","values":["Herrick, Zoe; 0000-0001-9907-6950"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-02-25T23:23:23Z","2020","2020-08-07 14:27:44"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["neurosciences","applied mathematics","medical imaging"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/86846"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["M.S.","Source localization of electroencephalogram (EEG) data is commonly used to estimate regions of ictal onset in epilepsy patients with temporal lobe epilepsy. Results are used to inform further investigations and treatment options such as surgical resection. Localization of EEG data still struggles to achieve high spatial resolution, especially in deep regions of brain tissue, and is difficult to validate because the ground truth is unknown. In this paper we utilize a spatiotemporally realistic generative brain network model based on patient structural and functional data, created in The Virtual Brain (TVB) platform, to generate simulated EEG data for assessment of head model approaches, distributed source inverse methods and clinically feasible electrode montages. We find that dSPM is less sensitive to head model errors introduced when warping an anatomical template in localization; sparse montages with increased density over regions of interest provide a clinically feasible way to increase localization accuracy of a sparse montage; and TVB platform can be utilized to model patient anatomy and physiology virtually, incorporating individualized estimates of disease mechanisms through parameter choices reflecting clinical assessment, which may be implemented to determine an optimized electrode montage for the purpose of providing personalized neurological care.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Source Localization of Simulated Electroencephalogram of Virtual Epileptic Patient to Investigate Clinically Feasible Montages"]}]}],"canonical_facts":{"dc:contributor":["Dutta, Anirban","Biomedical Engineering"],"dc:creator":["Herrick, Zoe; 0000-0001-9907-6950"],"dc:date":["2025-02-25T23:23:23Z","2020","2020-08-07 14:27:44"],"dc:description":["M.S.","Source localization of electroencephalogram (EEG) data is commonly used to estimate regions of ictal onset in epilepsy patients with temporal lobe epilepsy. Results are used to inform further investigations and treatment options such as surgical resection. Localization of EEG data still struggles to achieve high spatial resolution, especially in deep regions of brain tissue, and is difficult to validate because the ground truth is unknown. In this paper we utilize a spatiotemporally realistic generative brain network model based on patient structural and functional data, created in The Virtual Brain (TVB) platform, to generate simulated EEG data for assessment of head model approaches, distributed source inverse methods and clinically feasible electrode montages. We find that dSPM is less sensitive to head model errors introduced when warping an anatomical template in localization; sparse montages with increased density over regions of interest provide a clinically feasible way to increase localization accuracy of a sparse montage; and TVB platform can be utilized to model patient anatomy and physiology virtually, incorporating individualized estimates of disease mechanisms through parameter choices reflecting clinical assessment, which may be implemented to determine an optimized electrode montage for the purpose of providing personalized neurological care.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/86846"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["neurosciences","applied mathematics","medical imaging"],"dc:title":["Source Localization of Simulated Electroencephalogram of Virtual Epileptic Patient to Investigate Clinically Feasible Montages"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:05:37Z"}