{"id":"https://openalex.org/W7128434857","doi":"https://doi.org/10.1109/access.2026.3662260","title":"Multidimensional Comparisons Between Constrained ICA/IVA Algorithms for Multi-Subject fMRI Data Analysis","display_name":"Multidimensional Comparisons Between Constrained ICA/IVA Algorithms for Multi-Subject fMRI Data Analysis","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7128434857","doi":"https://doi.org/10.1109/access.2026.3662260","pmid":"https://pubmed.ncbi.nlm.nih.gov/41868269"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3662260","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3662260","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3662260","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047502215","display_name":"Lucas Gois","orcid":"https://orcid.org/0000-0002-1735-0811"},"institutions":[{"id":"https://openalex.org/I71715416","display_name":"Universidade Federal do ABC","ror":"https://ror.org/028kg9j04","country_code":"BR","type":"education","lineage":["https://openalex.org/I71715416"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Lucas Gois","raw_affiliation_strings":["Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil"],"affiliations":[{"raw_affiliation_string":"Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil","institution_ids":["https://openalex.org/I71715416"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125467781","display_name":"Hanlu Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanlu Yang","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125456108","display_name":"Trung Vu","orcid":null},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trung Vu","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121630189","display_name":"Weixin Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weixin Wang","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063873307","display_name":"Denis G. Fantinato","orcid":"https://orcid.org/0000-0002-5009-3431"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Denis Fantinato","raw_affiliation_strings":["Department of Computer Engineering and Automation, Universidade Estadual de Campinas, Campinas, Brazil"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering and Automation, Universidade Estadual de Campinas, Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123473156","display_name":"Aline Neves","orcid":null},"institutions":[{"id":"https://openalex.org/I71715416","display_name":"Universidade Federal do ABC","ror":"https://ror.org/028kg9j04","country_code":"BR","type":"education","lineage":["https://openalex.org/I71715416"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Aline Neves","raw_affiliation_strings":["Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil"],"affiliations":[{"raw_affiliation_string":"Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo Andr&#x00E9;, Brazil","institution_ids":["https://openalex.org/I71715416"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125451287","display_name":"Vince D. Calhoun","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]},{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]},{"id":"https://openalex.org/I4210133909","display_name":"Center for Translational Research in Neuroimaging and Data Science","ror":"https://ror.org/02qx6zf82","country_code":"US","type":"facility","lineage":["https://openalex.org/I130701444","https://openalex.org/I150468666","https://openalex.org/I181565077","https://openalex.org/I4210133909"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vince D. Calhoun","raw_affiliation_strings":["Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I4210133909","https://openalex.org/I130701444","https://openalex.org/I181565077","https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":null,"display_name":"T\u00fclay Adali","orcid":"https://orcid.org/0000-0003-0594-2796"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T\u00fclay Adali","raw_affiliation_strings":["Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5047502215"],"corresponding_institution_ids":["https://openalex.org/I71715416"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35252822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"23467","last_page":"23482"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11094","display_name":"Face Recognition and Perception","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.7401000261306763},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6255999803543091},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.48969998955726624},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.4878999888896942},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4875999987125397},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.4869999885559082},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.48489999771118164},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4431000053882599}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.777400016784668},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.7401000261306763},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6255999803543091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5406000018119812},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.48969998955726624},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.4878999888896942},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4875999987125397},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.4869999885559082},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.48489999771118164},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.42340001463890076},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42010000348091125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3896999955177307},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.3781999945640564},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27639999985694885},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/access.2026.3662260","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3662260","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmid:41868269","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41868269","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":"IEEE access : practical innovations, open solutions","raw_type":null},{"id":"pmh:doi:10.13016/m23fry-i5hc","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ACCESS.2026.3662260.","pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:mdsoar.org:11603/42194","is_oa":true,"landing_page_url":"http://hdl.handle.net/11603/42194","pdf_url":null,"source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:13003940","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13003940/","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3662260","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3662260","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1822143055","https://openalex.org/W1845880232","https://openalex.org/W1973741448","https://openalex.org/W1985327120","https://openalex.org/W1991840148","https://openalex.org/W2016444985","https://openalex.org/W2040985763","https://openalex.org/W2054714441","https://openalex.org/W2055637322","https://openalex.org/W2067955720","https://openalex.org/W2080987602","https://openalex.org/W2082207932","https://openalex.org/W2094345233","https://openalex.org/W2097271689","https://openalex.org/W2098787985","https://openalex.org/W2105461944","https://openalex.org/W2115971978","https://openalex.org/W2127499921","https://openalex.org/W2131681506","https://openalex.org/W2136284422","https://openalex.org/W2151936673","https://openalex.org/W2156779951","https://openalex.org/W2167822639","https://openalex.org/W2172045185","https://openalex.org/W2663135018","https://openalex.org/W2891097454","https://openalex.org/W2893298789","https://openalex.org/W2913406796","https://openalex.org/W2953079170","https://openalex.org/W3021352772","https://openalex.org/W3048396787","https://openalex.org/W3199526410","https://openalex.org/W4220838968","https://openalex.org/W4283696279","https://openalex.org/W4295561065","https://openalex.org/W4321002370","https://openalex.org/W4372260193","https://openalex.org/W4377043842","https://openalex.org/W4392909311","https://openalex.org/W4394838525","https://openalex.org/W4400942727","https://openalex.org/W4405360511","https://openalex.org/W4408962836"],"related_works":[],"abstract_inverted_index":{"Large-scale":[0],"functional":[1,41,210],"magnetic":[2],"resonance":[3],"imaging":[4],"(fMRI)":[5],"datasets":[6],"provide":[7],"exciting":[8],"opportunities":[9],"for":[10,33,219,239,253,280],"understanding":[11],"and":[12,24,55,61,67,100,127,164,189,205],"improving":[13],"brain":[14],"health.":[15],"Data-driven":[16],"techniques":[17],"such":[18,156],"as":[19,37,157,193,195],"independent":[20,25],"component":[21],"analysis":[22,27],"(ICA)":[23],"vector":[26],"(IVA)":[28],"have":[29],"been":[30],"attractive":[31],"solutions":[32],"multi-subject":[34],"fMRI":[35,169],"analysis,":[36],"the":[38,45,68,113,121,132,135,179,187,227,284,294,301,307],"extraction":[39],"of":[40,53,71,87,118,124,131,171,191],"connectivity":[42,212],"networks":[43],"is":[44],"key":[46],"step":[47],"in":[48,109,128,198,203,233],"many":[49],"studies.":[50],"Constrained":[51],"versions":[52],"ICA":[54,103],"IVA":[56,94,98,119],"help":[57],"significantly":[58,108],"improve":[59],"performance":[60],"interpretability,":[62],"but":[63],"their":[64,72,129,183],"comparative":[65],"advantages":[66],"practical":[69,297],"impact":[70],"different":[73],"formulations":[74],"remain":[75],"unclear.":[76],"This":[77],"work":[78,295],"addresses":[79],"this":[80],"gap":[81],"by":[82],"conducting":[83],"a":[84,141,147,167,216,291],"comprehensive":[85],"comparison":[86,149],"three":[88,180],"state-of-the-art":[89],"constrained":[90,93,97,102,125],"algorithms:":[91],"threshold-free":[92,142],"(tf-cIVA),":[95],"adaptive-reverse":[96,101],"(ar-cIVA),":[99],"(ar-cEBM).":[104],"These":[105],"methods":[106,152,181],"differ":[107],"how":[110],"they":[111],"leverage":[112],"cross-subject":[114,261],"information":[115],"(joint":[116],"processing":[117],"versus":[120,140],"subject-wise":[122,247],"approach":[123],"ICA)":[126],"definitions":[130],"closeness":[133],"with":[134,161,186],"references":[136,188],"(Lagrangian-based":[137],"adaptive":[138],"thresholding":[139],"regularization":[143],"term).":[144],"We":[145],"perform":[146],"multidimensional":[148],"among":[150],"these":[151],"using":[153],"multiple":[154],"metrics":[155],"reproducibility,":[158],"scalability,":[159],"alignment":[160],"references,":[162],"connectivity,":[163],"consistency":[165,282],"on":[166,306],"multi-site":[168],"dataset":[170],"429":[172],"subjects.":[173],"Our":[174],"results":[175],"reveal":[176],"replicability":[177],"across":[178,269],"regarding":[182],"spatial":[184,234,241,267],"correlation":[185],"identification":[190],"biomarkers,":[192],"well":[194],"distinct":[196],"trade-offs":[197],"other":[199],"aspects:":[200],"tf-cIVA":[201],"excels":[202],"reproducibility":[204],"produces":[206,264],"highly":[207],"structured":[208],"temporal":[209],"network":[211],"(FNC),":[213],"making":[214],"it":[215],"strong":[217],"candidate":[218],"dynamic":[220],"or":[221],"connectivity-based":[222],"analyses.":[223],"Meanwhile,":[224],"ar-cIVA":[225],"demonstrates":[226],"greatest":[228],"sensitivity":[229],"to":[230],"group":[231,281],"differences":[232],"FNC,":[235],"suggesting":[236,271],"its":[237,246,272],"utility":[238],"identifying":[240],"biomarkers.":[242],"Finally,":[243],"ar-cEBM,":[244],"via":[245],"approach,":[248],"offers":[249],"superior":[250],"computational":[251],"scalability":[252],"large":[254],"datasets.":[255],"Surprisingly,":[256],"despite":[257],"not":[258],"jointly":[259],"modeling":[260],"information,":[262],"ar-cEBM":[263],"more":[265,278],"stable":[266],"maps":[268],"subjects,":[270],"flexible":[273],"density":[274],"matching":[275],"may":[276],"be":[277],"critical":[279],"than":[283],"joint-processing":[285],"framework":[286],"itself.":[287],"Therefore,":[288],"besides":[289],"providing":[290],"complete":[292],"picture,":[293],"provides":[296],"guidance,":[298],"indicating":[299],"that":[300],"algorithm":[302],"choice":[303],"might":[304],"depend":[305],"specific":[308],"research":[309],"question.":[310]},"counts_by_year":[],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2026-02-10T00:00:00"}
