{"id":"https://openalex.org/W7133326515","doi":"https://doi.org/10.48550/arxiv.2603.01135","title":"FCN-LLM: Empower LLM for Brain Functional Connectivity Network Understanding via Graph-level Multi-task Instruction Tuning","display_name":"FCN-LLM: Empower LLM for Brain Functional Connectivity Network Understanding via Graph-level Multi-task Instruction Tuning","publication_year":2026,"publication_date":"2026-03-01","ids":{"openalex":"https://openalex.org/W7133326515","doi":"https://doi.org/10.48550/arxiv.2603.01135"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01135","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01135","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01135","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113012234","display_name":"Xingcan Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Xingcan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127914829","display_name":"Wei Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127986215","display_name":"Li Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.3538999855518341,"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":0.3538999855518341,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.16869999468326569,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.11760000139474869,"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/comprehension","display_name":"Comprehension","score":0.6438000202178955},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5896000266075134},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5694000124931335},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.45509999990463257},{"id":"https://openalex.org/keywords/functional-connectivity","display_name":"Functional connectivity","score":0.421099990606308},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4124999940395355},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3774000108242035}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7581999897956848},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.6438000202178955},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5896000266075134},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5694000124931335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5529000163078308},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.421099990606308},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3774000108242035},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35010001063346863},{"id":"https://openalex.org/C74672266","wikidata":"https://www.wikidata.org/wiki/Q815859","display_name":"Language acquisition","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2964000105857849},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.29429998993873596},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28999999165534973},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01135","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01135","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01135","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01135","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.780853807926178,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"have":[3,37],"achieved":[4],"remarkable":[5],"success":[6],"in":[7,40],"language":[8],"understanding":[9],"and":[10,12,21,93,116,130,162,181],"reasoning,":[11],"their":[13],"multimodal":[14],"extensions":[15],"enable":[16],"comprehension":[17],"of":[18,57,102],"images,":[19],"video,":[20],"audio.":[22],"Inspired":[23],"by":[24],"this,":[25,65],"foundation":[26,163],"models":[27],"for":[28,171,184],"brain":[29,173],"functional":[30,91,174],"connectivity":[31],"networks":[32,175],"derived":[33],"from":[34],"resting-state":[35],"fMRI":[36],"shown":[38],"promise":[39],"clinical":[41],"tasks.":[42],"However,":[43],"existing":[44],"methods":[45],"do":[46],"not":[47],"align":[48],"FCNs":[49,76],"with":[50,127,176],"the":[51,55,99,128,134],"text":[52],"modality,":[53],"limiting":[54],"ability":[56],"LLMs":[58,73],"to":[59,74,137],"directly":[60],"understand":[61,75],"FCNs.":[62],"To":[63],"address":[64],"we":[66],"propose":[67],"FCN-LLM,":[68],"a":[69,85,144,168,179],"framework":[70,183],"that":[71,150],"enables":[72],"through":[77],"graph-level,":[78],"multi-task":[79],"instruction":[80,107],"tuning.":[81],"Our":[82],"approach":[83],"employs":[84],"multi-scale":[86],"FCN":[87,125,147],"encoder":[88],"capturing":[89],"brain-region,":[90],"subnetwork,":[92],"whole-brain":[94],"features,":[95],"projecting":[96],"them":[97],"into":[98],"semantic":[100,140],"space":[101],"LLM.":[103],"We":[104],"design":[105],"multi-paradigm":[106],"tasks":[108],"covering":[109],"19":[110],"subject-specific":[111],"attributes":[112],"across":[113],"demographics,":[114],"phenotypes,":[115],"psychiatric":[117],"conditions.":[118],"A":[119],"multi-stage":[120],"learning":[121],"strategy":[122],"first":[123],"aligns":[124],"embeddings":[126],"LLM":[129],"then":[131],"jointly":[132],"fine-tunes":[133],"entire":[135],"model":[136],"capture":[138],"high-level":[139],"information.":[141],"Experiments":[142],"on":[143,156],"large-scale,":[145],"multi-site":[146],"database":[148],"show":[149],"FCN-LLM":[151],"achieves":[152],"strong":[153],"zero-shot":[154],"generalization":[155],"unseen":[157],"datasets,":[158],"outperforming":[159],"conventional":[160],"supervised":[161],"models.":[164],"This":[165],"work":[166],"introduces":[167],"new":[169],"paradigm":[170],"integrating":[172],"LLMs,":[177],"offering":[178],"flexible":[180],"interpretable":[182],"neuroscience.":[185]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}
