{"id":"https://openalex.org/W7129497883","doi":"https://doi.org/10.48550/arxiv.2602.13770","title":"NeuroMambaLLM: Dynamic Graph Learning of fMRI Functional Connectivity in Autistic Brains Using Mamba and Language Model Reasoning","display_name":"NeuroMambaLLM: Dynamic Graph Learning of fMRI Functional Connectivity in Autistic Brains Using Mamba and Language Model Reasoning","publication_year":2026,"publication_date":"2026-02-14","ids":{"openalex":"https://openalex.org/W7129497883","doi":"https://doi.org/10.48550/arxiv.2602.13770"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.13770","is_oa":true,"landing_page_url":null,"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":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126236089","display_name":"Yasaman Torabi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Torabi, Yasaman","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126228943","display_name":"Parsa Razmara","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Razmara, Parsa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5096912326","display_name":"Hamed Ajorlou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ajorlou, Hamed","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5024945433","display_name":"Bardia Baraeinejad","orcid":"https://orcid.org/0000-0003-1554-9883"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baraeinejad, Bardia","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5126236089"],"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":0.3393999934196472,"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":0.3393999934196472,"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":0.12370000034570694,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.06909999996423721,"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/embedding","display_name":"Embedding","score":0.5701000094413757},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4763000011444092},{"id":"https://openalex.org/keywords/dynamic-functional-connectivity","display_name":"Dynamic functional connectivity","score":0.46160000562667847},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4117000102996826},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.39469999074935913},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.374099999666214},{"id":"https://openalex.org/keywords/connectome","display_name":"Connectome","score":0.3379000127315521},{"id":"https://openalex.org/keywords/functional-connectivity","display_name":"Functional connectivity","score":0.3237000107765198}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7605000138282776},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5819000005722046},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5701000094413757},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C2781312939","wikidata":"https://www.wikidata.org/wiki/Q17088721","display_name":"Dynamic functional connectivity","level":3,"score":0.46160000562667847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4334000051021576},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4117000102996826},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.39469999074935913},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.374099999666214},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35179999470710754},{"id":"https://openalex.org/C45715564","wikidata":"https://www.wikidata.org/wiki/Q1292103","display_name":"Connectome","level":3,"score":0.3379000127315521},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.3019999861717224},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C2778538070","wikidata":"https://www.wikidata.org/wiki/Q1436063","display_name":"Autism spectrum disorder","level":3,"score":0.2847999930381775},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C205778803","wikidata":"https://www.wikidata.org/wiki/Q38404","display_name":"Autism","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.27140000462532043}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.13770","is_oa":true,"landing_page_url":null,"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":"Article"},{"id":"doi:10.48550/arxiv.2602.13770","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.13770","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.13770","is_oa":true,"landing_page_url":null,"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":"Article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6904269456863403,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"demonstrated":[5],"strong":[6],"semantic":[7],"reasoning":[8],"across":[9],"multimodal":[10],"domains.":[11],"However,":[12],"their":[13],"integration":[14],"with":[15,87,107],"graph-based":[16],"models":[17],"of":[18,131],"brain":[19,123],"connectivity":[20,95,110],"remains":[21,140],"limited.":[22],"In":[23],"addition,":[24],"most":[25],"existing":[26],"fMRI":[27,171],"analysis":[28],"methods":[29],"rely":[30],"on":[31],"static":[32],"Functional":[33],"Connectivity":[34],"(FC)":[35],"representations,":[36],"which":[37],"obscure":[38],"transient":[39],"neural":[40],"dynamics":[41],"critical":[42],"for":[43,150],"neurodevelopmental":[44],"disorders":[45],"such":[46],"as":[47,62],"autism.":[48],"Recent":[49],"state-space":[50,84],"approaches,":[51],"including":[52],"Mamba,":[53],"model":[54,139],"temporal":[55,85,118],"structure":[56],"efficiently,":[57],"but":[58],"are":[59,125,148],"typically":[60],"used":[61],"standalone":[63],"feature":[64],"extractors":[65],"without":[66],"explicit":[67],"high-level":[68],"reasoning.":[69],"We":[70],"propose":[71],"NeuroMambaLLM,":[72],"an":[73,132],"end-to-end":[74],"framework":[75],"that":[76],"integrates":[77],"dynamic":[78,122,170],"latent":[79,109],"graph":[80],"learning":[81],"and":[82,115,142,163,173],"selective":[83],"modelling":[86],"LLMs.":[88],"The":[89,120],"proposed":[90],"method":[91],"learns":[92],"the":[93,128,136,156],"functional":[94],"dynamically":[96],"from":[97],"raw":[98],"Blood-Oxygen-Level-Dependent":[99],"(BOLD)":[100],"time":[101],"series,":[102],"replacing":[103],"fixed":[104],"correlation":[105],"graphs":[106],"adaptive":[108],"while":[111],"suppressing":[112],"motion-related":[113],"artifacts":[114],"capturing":[116],"long-range":[117],"dependencies.":[119],"resulting":[121],"representations":[124],"projected":[126],"into":[127],"embedding":[129],"space":[130],"LLM":[133,157],"model,":[134],"where":[135],"base":[137],"language":[138],"frozen":[141],"lightweight":[143],"low-rank":[144],"adaptation":[145],"(LoRA)":[146],"modules":[147],"trained":[149],"parameter-efficient":[151],"alignment.":[152],"This":[153],"design":[154],"enables":[155],"to":[158,168],"perform":[159],"both":[160],"diagnostic":[161],"classification":[162],"language-based":[164],"reasoning,":[165],"allowing":[166],"it":[167],"analyze":[169],"patterns":[172],"generate":[174],"clinically":[175],"meaningful":[176],"textual":[177],"reports.":[178]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-18T00:00:00"}
