{"id":"https://openalex.org/W4410295711","doi":"https://doi.org/10.1109/isbi60581.2025.10980976","title":"Masked Momentum Contrastive Dynamic Transformer for Self-Supervised Functional Connectivity Representation Learning","display_name":"Masked Momentum Contrastive Dynamic Transformer for Self-Supervised Functional Connectivity Representation Learning","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4410295711","doi":"https://doi.org/10.1109/isbi60581.2025.10980976","pmid":"https://pubmed.ncbi.nlm.nih.gov/41050554"},"language":"en","primary_location":{"id":"doi:10.1109/isbi60581.2025.10980976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10980976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12490092/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002409683","display_name":"Jiale Cheng","orcid":"https://orcid.org/0000-0002-0032-7455"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]},{"id":"https://openalex.org/I4210166946","display_name":"Imaging Center","ror":"https://ror.org/05hsqsk33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210166946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jiale Cheng","raw_affiliation_strings":["University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA","institution_ids":["https://openalex.org/I114027177","https://openalex.org/I4210166946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101517880","display_name":"Dan Hu","orcid":"https://orcid.org/0000-0002-4437-6339"},"institutions":[{"id":"https://openalex.org/I4210166946","display_name":"Imaging Center","ror":"https://ror.org/05hsqsk33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210166946"]},{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dan Hu","raw_affiliation_strings":["University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA","institution_ids":["https://openalex.org/I114027177","https://openalex.org/I4210166946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070300188","display_name":"Zhengwang Wu","orcid":"https://orcid.org/0000-0003-4436-9005"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]},{"id":"https://openalex.org/I4210166946","display_name":"Imaging Center","ror":"https://ror.org/05hsqsk33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210166946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengwang Wu","raw_affiliation_strings":["University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA","institution_ids":["https://openalex.org/I114027177","https://openalex.org/I4210166946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074280565","display_name":"Xinrui Yuan","orcid":"https://orcid.org/0009-0006-2032-0126"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]},{"id":"https://openalex.org/I4210166946","display_name":"Imaging Center","ror":"https://ror.org/05hsqsk33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210166946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinrui Yuan","raw_affiliation_strings":["University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA","institution_ids":["https://openalex.org/I114027177","https://openalex.org/I4210166946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100438653","display_name":"Gang Li","orcid":"https://orcid.org/0000-0001-9585-1382"},"institutions":[{"id":"https://openalex.org/I114027177","display_name":"University of North Carolina at Chapel Hill","ror":"https://ror.org/0130frc33","country_code":"US","type":"education","lineage":["https://openalex.org/I114027177"]},{"id":"https://openalex.org/I4210166946","display_name":"Imaging Center","ror":"https://ror.org/05hsqsk33","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210166946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Li","raw_affiliation_strings":["University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Chapel Hill,Department of Radiology and Biomedical Research Imaging Center,Chapel Hill,NC,USA","institution_ids":["https://openalex.org/I114027177","https://openalex.org/I4210166946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5002409683"],"corresponding_institution_ids":["https://openalex.org/I114027177","https://openalex.org/I4210166946"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04514535,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2025","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9419999718666077,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9419999718666077,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9154000282287598,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.661928653717041},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.6063423156738281},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45681723952293396},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4325258731842041},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3319072127342224},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.17329737544059753},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1309441328048706},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.09516876935958862}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.661928653717041},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6063423156738281},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45681723952293396},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4325258731842041},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3319072127342224},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.17329737544059753},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1309441328048706},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.09516876935958862},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/isbi60581.2025.10980976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10980976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmid:41050554","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41050554","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":null},{"id":"pmh:oai:europepmc.org:11300638","is_oa":false,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12490092","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:12490092","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12490092/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:12490092","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12490092/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7404779680","display_name":null,"funder_award_id":"MH123202,ES033518,AG075582,NS128534,NS135574","funder_id":"https://openalex.org/F1631871679","funder_display_name":"National Institute of Health Sciences"}],"funders":[{"id":"https://openalex.org/F1631871679","display_name":"National Institute of Health Sciences","ror":"https://ror.org/04s629c33"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Functional":[0],"connectivity":[1],"(FC)":[2],"derived":[3],"from":[4,106,129],"functional":[5],"MRI":[6],"(fMRI)":[7],"shows":[8],"significant":[9],"promise":[10],"in":[11],"predicting":[12],"behavior":[13],"and":[14,46,79,115,119,137],"demographics":[15],"using":[16],"deep":[17],"learning":[18,128],"techniques.":[19],"Incorporating":[20],"vertex-wise":[21,104,123],"FC":[22],"maps,":[23],"which":[24,69],"capture":[25],"fine-grained":[26],"spatial":[27],"details":[28],"of":[29,88,109],"neural":[30,49],"activity,":[31],"offers":[32],"the":[33,85,145],"potential":[34],"to":[35,51,75,126],"enhance":[36],"FC-based":[37],"prediction":[38,81,139],"accuracy.":[39],"However,":[40],"fMRI":[41],"data":[42],"is":[43],"inherently":[44],"limited":[45,130],"noisy,":[47],"challenging":[48],"networks":[50],"reliably":[52],"identify":[53],"patterns":[54],"within":[55],"high-dimensional":[56],"cortical":[57],"vertices.":[58],"Therefore,":[59],"we":[60],"design":[61],"a":[62,91,122],"novel":[63],"Masked":[64],"Momentum":[65],"Contrastive":[66],"Dynamic":[67],"Transformer,":[68],"utilizes":[70],"masked":[71],"momentum":[72],"contrastive":[73],"pre-training":[74],"explore":[76],"subject-specific":[77,100],"features":[78],"enhances":[80],"accuracy":[82],"by":[83,102],"leveraging":[84],"temporal":[86],"dynamics":[87],"FCs":[89,105],"with":[90],"dynamic":[92],"transformer.":[93],"Specifically,":[94],"our":[95],"framework":[96],"1)":[97],"learns":[98],"effective":[99],"representations":[101],"treating":[103],"different":[107],"runs":[108],"an":[110],"individual":[111],"as":[112],"distinct":[113],"views":[114],"maximizing":[116],"their":[117],"affinity,":[118],"2)":[120],"employs":[121],"masking":[124],"strategy":[125],"promote":[127],"data.":[131],"Extensive":[132],"experiments":[133],"on":[134,144],"gender":[135],"classification":[136],"cognition":[138],"validate":[140],"its":[141],"superior":[142],"performance":[143],"Human":[146],"Connectome":[147],"Project":[148],"dataset.":[149]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
