{"id":"https://openalex.org/W4416373618","doi":"https://doi.org/10.1016/j.patcog.2025.112738","title":"Prompt-guided dual-channel attention model predicts brain activation from functional and structural profiles","display_name":"Prompt-guided dual-channel attention model predicts brain activation from functional and structural profiles","publication_year":2025,"publication_date":"2025-11-19","ids":{"openalex":"https://openalex.org/W4416373618","doi":"https://doi.org/10.1016/j.patcog.2025.112738"},"language":"en","primary_location":{"id":"doi:10.1016/j.patcog.2025.112738","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.patcog.2025.112738","pdf_url":null,"source":{"id":"https://openalex.org/S414566","display_name":"Pattern Recognition","issn_l":"0031-3203","issn":["0031-3203","1873-5142"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Recognition","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.patcog.2025.112738","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101842083","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0001-7854-4006"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wei Huang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-7854-4006","affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Pengfei Yang","orcid":"https://orcid.org/0009-0002-8623-6585"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pengfei Yang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0002-8623-6585","affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Fan Qin","orcid":"https://orcid.org/0009-0001-7379-197X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan Qin","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0001-7379-197X","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029745450","display_name":"Hengjiang Li","orcid":"https://orcid.org/0009-0003-7944-8990"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hengjiang Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0003-7944-8990","affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Jingpeng Li","orcid":"https://orcid.org/0009-0009-4325-8849"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingpeng Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0009-4325-8849","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070519212","display_name":"Sizhuo Wang","orcid":"https://orcid.org/0009-0007-0722-6335"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sizhuo Wang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0007-0722-6335","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051978172","display_name":"Changde Du","orcid":"https://orcid.org/0000-0002-0084-433X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Changde Du","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-0084-433X","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007568636","display_name":"K. P. Cheng","orcid":"https://orcid.org/0000-0002-1160-1296"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaiwen Cheng","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-1160-1296","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100786255","display_name":"Huafu Chen","orcid":"https://orcid.org/0000-0002-4062-4753"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huafu Chen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4062-4753","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5101842083"],"corresponding_institution_ids":[],"apc_list":{"value":2710,"currency":"USD","value_usd":2710},"apc_paid":{"value":2710,"currency":"USD","value_usd":2710},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3355314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"172","issue":null,"first_page":"112738","last_page":"112738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.8115000128746033,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.8115000128746033,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.13379999995231628,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.0066999997943639755,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.336899995803833},{"id":"https://openalex.org/keywords/brain-mapping","display_name":"Brain mapping","score":0.29330000281333923},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.27549999952316284},{"id":"https://openalex.org/keywords/neural-activity","display_name":"Neural activity","score":0.2703000009059906},{"id":"https://openalex.org/keywords/neurophysiology","display_name":"Neurophysiology","score":0.263700008392334}],"concepts":[{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.5012000203132629},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47870001196861267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3937000036239624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C50231774","wikidata":"https://www.wikidata.org/wiki/Q639842","display_name":"Brain mapping","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.29010000824928284},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2984127161","wikidata":"https://www.wikidata.org/wiki/Q969316","display_name":"Neural activity","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.26899999380111694},{"id":"https://openalex.org/C152478114","wikidata":"https://www.wikidata.org/wiki/Q660910","display_name":"Neurophysiology","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.26159998774528503},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2590999901294708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.patcog.2025.112738","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.patcog.2025.112738","pdf_url":null,"source":{"id":"https://openalex.org/S414566","display_name":"Pattern Recognition","issn_l":"0031-3203","issn":["0031-3203","1873-5142"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Recognition","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.patcog.2025.112738","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.patcog.2025.112738","pdf_url":null,"source":{"id":"https://openalex.org/S414566","display_name":"Pattern Recognition","issn_l":"0031-3203","issn":["0031-3203","1873-5142"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Recognition","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2340591891","display_name":null,"funder_award_id":"62036003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2486214109","display_name":null,"funder_award_id":"2023NSFSC0640","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"},{"id":"https://openalex.org/G2873907712","display_name":null,"funder_award_id":"62333003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2947399595","display_name":null,"funder_award_id":"2024M750360","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G339557173","display_name":null,"funder_award_id":"ZYGX2021YGLH201","funder_id":"https://openalex.org/F4320323292","funder_display_name":"University of Electronic Science and Technology of China"},{"id":"https://openalex.org/G4035041290","display_name":null,"funder_award_id":"ZYGX2024XJ051","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G728059352","display_name":null,"funder_award_id":"82121003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8066668468","display_name":null,"funder_award_id":"62406058","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8873694433","display_name":null,"funder_award_id":"62276051","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320323292","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1983208069","https://openalex.org/W2157106546","https://openalex.org/W2319534434","https://openalex.org/W2499800833","https://openalex.org/W2741941708","https://openalex.org/W2949767599","https://openalex.org/W2981734935","https://openalex.org/W3093116876","https://openalex.org/W3124267158","https://openalex.org/W3162699398","https://openalex.org/W4220901244","https://openalex.org/W4225957971","https://openalex.org/W4241074797","https://openalex.org/W4283708321","https://openalex.org/W4289946024","https://openalex.org/W4306319049","https://openalex.org/W4308459649","https://openalex.org/W4360806252","https://openalex.org/W4364302332","https://openalex.org/W4367672868","https://openalex.org/W4379053726","https://openalex.org/W4385880767","https://openalex.org/W4388234101","https://openalex.org/W4393241094","https://openalex.org/W4400342385","https://openalex.org/W4401270728","https://openalex.org/W4409196435","https://openalex.org/W4410360752"],"related_works":[],"abstract_inverted_index":{"\u2022":[0,15,30,44],"A":[1,31],"prompt-guided":[2,144],"dual-channel":[3,126],"attention":[4,127],"effectively":[5],"fuses":[6],"brain":[7,37,66,75,87,118,134,154,210],"structural":[8,25,65,86,109,133],"and":[9,26,52,64,85,108,132,139,156,242],"functional":[10,27,63,84,95,107,131],"information":[11,22,155],"using":[12],"target":[13],"priors.":[14],"An":[16],"attention-based":[17],"framework":[18],"dynamically":[19],"leverages":[20],"task-specific":[21,94],"to":[23,111,129,148,162,178,237,244],"optimize":[24],"modality":[28],"complementarity.":[29],"categorized-contrastive":[32],"learning":[33,176],"strategy":[34,177,189],"addresses":[35],"multi-task":[36,186],"activation":[38,76,119,211],"prediction":[39,193],"while":[40],"preserving":[41],"individual":[42,116,208,239],"specificity.":[43],"The":[45],"proposed":[46],"method":[47],"significantly":[48],"outperforms":[49],"existing":[50],"single-":[51],"multi-modal":[53],"approaches":[54],"across":[55],"seven":[56],"tasks":[57],"on":[58,164],"the":[59,70,122,150,160,180,214,222],"HCP":[60,215],"dataset.":[61],"Resting-state":[62],"imaging":[67],"are":[68],"considered":[69],"foundation":[71],"for":[72,92],"understanding":[73,247],"task-related":[74,117,209],"patterns.":[77,120],"However,":[78],"few":[79],"studies":[80],"have":[81],"integrated":[82],"multidimensional":[83],"features":[88,110,166],"into":[89],"predictive":[90],"models":[91],"predicting":[93,168,238],"activation.":[96],"To":[97],"address":[98,179],"this,":[99],"we":[100,172],"propose":[101],"PG-DCAM,":[102],"which":[103],"simultaneously":[104],"integrates":[105],"resting-state":[106],"achieve":[112],"precise":[113],"predictions":[114],"of":[115,182,248],"First,":[121],"model":[123,161,205,231],"employs":[124],"a":[125,143,174,227,234,245],"network":[128],"merge":[130],"features,":[135],"extracting":[136],"both":[137],"global":[138],"local":[140],"information.":[141],"Second,":[142],"mechanism":[145],"is":[146],"introduced":[147],"enhance":[149],"deep":[151],"interaction":[152],"between":[153],"task":[157,183],"information,":[158],"allowing":[159],"focus":[163],"key":[165],"when":[167],"different":[169],"tasks.":[170],"Finally,":[171],"adopt":[173],"Categorized-Contrastive":[175],"challenge":[181],"differentiation":[184],"in":[185,221],"learning.":[187],"This":[188,224],"not":[190],"only":[191],"improves":[192],"accuracy":[194],"but":[195],"also":[196],"substantially":[197],"enhances":[198],"training":[199],"efficiency.":[200],"Experiments":[201],"confirm":[202],"that":[203,232],"our":[204],"accurately":[206],"predicts":[207],"patterns":[212],"from":[213],"dataset,":[216],"achieving":[217],"state-of-the-art":[218],"(SOTA)":[219],"performance":[220],"field.":[223],"study":[225],"presents":[226],"comprehensive":[228],"feature":[229],"integration":[230],"offers":[233],"novel":[235],"approach":[236],"cognitive":[240],"traits":[241],"contributing":[243],"deeper":[246],"human":[249],"cognition":[250],"mechanisms.":[251]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-20T00:00:00"}
