{"id":{"repo_id":"gatech","oai_identifier":"oai:repository.gatech.edu:1853/72636"},"canonical_url":"https://search.dev.ndltd.org/etd/gatech/oai:repository.gatech.edu:1853/72636","repository":{"repo_id":"gatech","name":"Georgia Tech","base_url":"https://repository.gatech.edu/server/oai/request"},"display":{"title":"Functional Brain Connectivity Estimators: Understanding and Developing New Methodologies","abstract":"The objective of the proposed research is to develop a framework to unify the different methodologies that are used for constructing a specific part of the brain functional networks (i.e., functional connectivity or the relationship between different parts of the functional networks). In addition, we will develop new methodologies for estimating functional connectivity and propose modifications for other methods already available in the field to improve them. Finally, we implement the proposed methods on real brain functional data to showcase these methods' applications for extracting biomarkers for both healthy (i.e., development of the human brain from early childhood to adolescence) and abnormal conditions of the human brain (e.g., Schizophrenia).","abstract_html":"The objective of the proposed research is to develop a framework to unify the different methodologies that are used for constructing a specific part of the brain functional networks (i.e., functional connectivity or the relationship between different parts of the functional networks). In addition, we will develop new methodologies for estimating functional connectivity and propose modifications for other methods already available in the field to improve them. Finally, we implement the proposed methods on real brain functional data to showcase these methods' applications for extracting biomarkers for both healthy (i.e., development of the human brain from early childhood to adolescence) and abnormal conditions of the human brain (e.g., Schizophrenia).","abstract_has_math":false,"creators":["Faghiri, Ashkan"],"institution":"Georgia Institute of Technology","degree_name":null,"degree_level":"Doctoral","degree_discipline":null,"degree_department":"Electrical and Computer Engineering","school":null,"contributors":[],"advisors":["Calhoun, Vince D."],"committee_chairs":[],"committee_members":["Anderson, David V.","Dovrolis, Constantine","Miller, Robyn Leigh","Rahnev, Dobromir"],"year":2022,"date_issued":"2022-07-30","date_published":"2022-07-30","updated_at":"2026-07-27T19:49:09Z","subjects":["dynamic functional connectivity","resting state fmri"],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1853/72636","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Calhoun, Vince D."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Anderson, David V.","Dovrolis, Constantine","Miller, Robyn Leigh","Rahnev, Dobromir"]},{"key":"dc:contributor.department","label":"Department","values":["Electrical and Computer Engineering"]},{"key":"dc:creator","label":"Author","values":["Faghiri, Ashkan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-09-06T19:45:00Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-09-06T19:45:00Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-07-30"]},{"key":"dc:publisher","label":"Institution","values":["Georgia Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["dynamic functional connectivity","resting state fmri"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1853/72636"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The objective of the proposed research is to develop a framework to unify the different methodologies that are used for constructing a specific part of the brain functional networks (i.e., functional connectivity or the relationship between different parts of the functional networks). In addition, we will develop new methodologies for estimating functional connectivity and propose modifications for other methods already available in the field to improve them. Finally, we implement the proposed methods on real brain functional data to showcase these methods' applications for extracting biomarkers for both healthy (i.e., development of the human brain from early childhood to adolescence) and abnormal conditions of the human brain (e.g., Schizophrenia)."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Functional Brain Connectivity Estimators: Understanding and Developing New Methodologies"]}]}],"canonical_facts":{"dc:contributor.advisor":["Calhoun, Vince D."],"dc:contributor.committeemember":["Anderson, David V.","Dovrolis, Constantine","Miller, Robyn Leigh","Rahnev, Dobromir"],"dc:contributor.department":["Electrical and Computer Engineering"],"dc:creator":["Faghiri, Ashkan"],"dc:date.accessioned":["2023-09-06T19:45:00Z"],"dc:date.available":["2023-09-06T19:45:00Z"],"dc:date.issued":["2022-07-30"],"dc:description.abstract":["The objective of the proposed research is to develop a framework to unify the different methodologies that are used for constructing a specific part of the brain functional networks (i.e., functional connectivity or the relationship between different parts of the functional networks). In addition, we will develop new methodologies for estimating functional connectivity and propose modifications for other methods already available in the field to improve them. Finally, we implement the proposed methods on real brain functional data to showcase these methods' applications for extracting biomarkers for both healthy (i.e., development of the human brain from early childhood to adolescence) and abnormal conditions of the human brain (e.g., Schizophrenia)."],"dc:description.degree":["Ph.D."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/1853/72636"],"dc:language.iso":["en_US"],"dc:publisher":["Georgia Institute of Technology"],"dc:subject":["dynamic functional connectivity","resting state fmri"],"dc:title":["Functional Brain Connectivity Estimators: Understanding and Developing New Methodologies"],"dc:type":["Text"],"thesis:degree_level":["Doctoral"]},"updated_at":"2026-07-27T19:49:09Z"}