{"id":"https://openalex.org/W4417069931","doi":"https://doi.org/10.1142/s0129065726500048","title":"An Interpretable Hybrid Neural Network Integrating Sinc-Convolution and Transformer for EEG-Based Depression Detection","display_name":"An Interpretable Hybrid Neural Network Integrating Sinc-Convolution and Transformer for EEG-Based Depression Detection","publication_year":2025,"publication_date":"2025-12-06","ids":{"openalex":"https://openalex.org/W4417069931","doi":"https://doi.org/10.1142/s0129065726500048","pmid":"https://pubmed.ncbi.nlm.nih.gov/41508896"},"language":"en","primary_location":{"id":"doi:10.1142/s0129065726500048","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065726500048","pdf_url":null,"source":{"id":"https://openalex.org/S197665576","display_name":"International Journal of Neural Systems","issn_l":"0129-0657","issn":["0129-0657","1793-6462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Neural Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061217738","display_name":"Minmin Miao","orcid":"https://orcid.org/0000-0002-8437-2412"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Minmin Miao","raw_affiliation_strings":["School of Information Engineering, Huzhou University Huzhou 313000, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-8437-2412","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University Huzhou 313000, P. R. China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qianqian Tan","orcid":"https://orcid.org/0009-0007-2267-7329"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianqian Tan","raw_affiliation_strings":["School of Information Engineering, Huzhou University Huzhou 313000, P. R. China"],"raw_orcid":"https://orcid.org/0009-0007-2267-7329","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University Huzhou 313000, P. R. China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ke Zhang","orcid":"https://orcid.org/0000-0002-5543-3116"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Zhang","raw_affiliation_strings":["School of Information Engineering, Huzhou University Huzhou 313000, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-5543-3116","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University Huzhou 313000, P. R. China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010250378","display_name":"Zhenzhen Sheng","orcid":"https://orcid.org/0000-0002-5853-6882"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenzhen Sheng","raw_affiliation_strings":["School of Information Engineering, Huzhou University Huzhou 313000, P. R. China"],"raw_orcid":"https://orcid.org/0000-0002-5853-6882","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University Huzhou 313000, P. R. China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiayi Hu","orcid":"https://orcid.org/0009-0006-3039-4639"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayi Hu","raw_affiliation_strings":["School of Information Engineering, China University of Geosciences Beijing 100083, P. R. China"],"raw_orcid":"https://orcid.org/0009-0006-3039-4639","affiliations":[{"raw_affiliation_string":"School of Information Engineering, China University of Geosciences Beijing 100083, P. R. China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"last","author":{"id":null,"display_name":"Baoguo Xu","orcid":"https://orcid.org/0000-0003-0735-1498"},"institutions":[{"id":"https://openalex.org/I4210090971","display_name":"Southeast University","ror":"https://ror.org/00cf0ab87","country_code":"BD","type":"education","lineage":["https://openalex.org/I4210090971"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["BD","CN"],"is_corresponding":false,"raw_author_name":"Baoguo Xu","raw_affiliation_strings":["School of Instrument Science and Engineering, Southeast University Nanjing 210096, P. R. China"],"raw_orcid":"https://orcid.org/0000-0003-0735-1498","affiliations":[{"raw_affiliation_string":"School of Instrument Science and Engineering, Southeast University Nanjing 210096, P. R. China","institution_ids":["https://openalex.org/I76569877","https://openalex.org/I4210090971"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5061217738"],"corresponding_institution_ids":["https://openalex.org/I3018263800"],"apc_list":null,"apc_paid":null,"fwci":1.1597,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83888066,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"36","issue":"04","first_page":"2650004","last_page":"2650004"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.8235999941825867,"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":0.8235999941825867,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.1331000030040741,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.01720000058412552,"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/interpretability","display_name":"Interpretability","score":0.8871999979019165},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5981000065803528},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5896000266075134},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5519000291824341},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.446399986743927},{"id":"https://openalex.org/keywords/hybrid-neural-network","display_name":"Hybrid neural network","score":0.40790000557899475},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4016000032424927},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.39489999413490295}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8871999979019165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7853999733924866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7089999914169312},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5981000065803528},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5896000266075134},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5519000291824341},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.446399986743927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43389999866485596},{"id":"https://openalex.org/C2779990667","wikidata":"https://www.wikidata.org/wiki/Q5953266","display_name":"Hybrid neural network","level":3,"score":0.40790000557899475},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3553999960422516},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.35280001163482666},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.32600000500679016},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2502000033855438}],"mesh":[{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000503","qualifier_name":"physiopathology","is_major_topic":true},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1142/s0129065726500048","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065726500048","pdf_url":null,"source":{"id":"https://openalex.org/S197665576","display_name":"International Journal of Neural Systems","issn_l":"0129-0657","issn":["0129-0657","1793-6462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Neural Systems","raw_type":"journal-article"},{"id":"pmid:41508896","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41508896","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":"International journal of neural systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W1481458145","https://openalex.org/W1488104929","https://openalex.org/W1589606770","https://openalex.org/W1879995557","https://openalex.org/W1974028377","https://openalex.org/W2053099699","https://openalex.org/W2061018891","https://openalex.org/W2116888785","https://openalex.org/W2126719297","https://openalex.org/W2128495200","https://openalex.org/W2153635508","https://openalex.org/W2157282844","https://openalex.org/W2159516675","https://openalex.org/W2168901492","https://openalex.org/W2479263883","https://openalex.org/W2493869336","https://openalex.org/W2559463885","https://openalex.org/W2584523198","https://openalex.org/W2741907166","https://openalex.org/W2790644103","https://openalex.org/W2800428573","https://openalex.org/W2890088166","https://openalex.org/W2915893085","https://openalex.org/W2964052309","https://openalex.org/W2968094935","https://openalex.org/W3003417734","https://openalex.org/W3030420691","https://openalex.org/W3034315405","https://openalex.org/W3113102112","https://openalex.org/W3126085817","https://openalex.org/W3153880451","https://openalex.org/W4200483594","https://openalex.org/W4220805741","https://openalex.org/W4220904564","https://openalex.org/W4224247713","https://openalex.org/W4225788814","https://openalex.org/W4225917240","https://openalex.org/W4249989394","https://openalex.org/W4256049924","https://openalex.org/W4283524612","https://openalex.org/W4285307926","https://openalex.org/W4289538860","https://openalex.org/W4309166667","https://openalex.org/W4311686796","https://openalex.org/W4312222040","https://openalex.org/W4323568506","https://openalex.org/W4324290675","https://openalex.org/W4360871668","https://openalex.org/W4365506071","https://openalex.org/W4366778275","https://openalex.org/W4368356416","https://openalex.org/W4381739313","https://openalex.org/W4383112473","https://openalex.org/W4386027405","https://openalex.org/W4386222461","https://openalex.org/W4388304090","https://openalex.org/W4388572429","https://openalex.org/W4388703849","https://openalex.org/W4392148621","https://openalex.org/W4393088546","https://openalex.org/W4402976380","https://openalex.org/W4403089752","https://openalex.org/W4403352318","https://openalex.org/W4404907259","https://openalex.org/W4405521251","https://openalex.org/W4406389370","https://openalex.org/W4407900404","https://openalex.org/W4408092225","https://openalex.org/W4410108411","https://openalex.org/W4410712207","https://openalex.org/W4411161051","https://openalex.org/W4411192411","https://openalex.org/W4411219423","https://openalex.org/W4412693657","https://openalex.org/W4412887670","https://openalex.org/W6959705997"],"related_works":[],"abstract_inverted_index":{"EEG":[0,19],"recordings":[1],"obtained":[2],"before":[3],"medication":[4],"are":[5,37,62],"regarded":[6],"as":[7],"valuable":[8],"biological":[9],"indicators":[10],"for":[11,267],"depression":[12,15],"detection.":[13],"Currently,":[14],"diagnosis":[16],"based":[17],"on":[18,179,192,219],"using":[20,188],"convolutional":[21],"neural":[22,83],"networks":[23],"(CNNs)":[24],"has":[25],"achieved":[26],"relatively":[27],"high":[28],"detection":[29],"performance,":[30,253],"but":[31,254],"some":[32],"issues":[33],"remain":[34],"unresolved.":[35],"CNNs":[36,61],"constrained":[38],"by":[39,60,169],"their":[40],"limited":[41],"receptive":[42],"fields,":[43],"which":[44],"restrict":[45],"them":[46],"to":[47,65,126,151,160,228],"capturing":[48],"local":[49],"rather":[50],"than":[51],"global":[52,153],"dependencies.":[53,155],"In":[54],"addition,":[55],"the":[56,95,124,136,143,165,170,180,193,209,230,233,243,261,271],"complex":[57],"features":[58,167],"learned":[59,168],"often":[63],"hard":[64],"interpret":[66],"and":[67,97,205,213,223,276],"typically":[68],"require":[69],"a":[70,108,115,183,257],"substantial":[71],"number":[72],"of":[73,195,232,263],"trainable":[74],"parameters.":[75],"To":[76,175],"tackle":[77],"these":[78],"issues,":[79],"an":[80],"interpretable":[81,264],"hybrid":[82,109],"network":[84],"named":[85],"SINCFORMER-SHAP":[86,89],"is":[87,118,158,186],"proposed.":[88],"comprises":[90],"two":[91],"main":[92],"components,":[93],"namely":[94],"spatial-frequency":[96,103,171],"temporal":[98,112,144],"feature":[99,104,146,172],"extraction":[100,105,147,173],"modules.":[101],"The":[102,131,236],"module":[106,148],"leverages":[107],"design,":[110],"where":[111],"filtering":[113],"through":[114],"sinc-based":[116],"convolution":[117],"coupled":[119],"with":[120],"spatial":[121,181],"convolution,":[122],"enabling":[123],"model":[125,140],"learn":[127],"fine-grained":[128],"spatial-spectral":[129],"patterns.":[130],"sinc-convolutional":[132],"layer":[133],"helps":[134],"constrain":[135],"parameter":[137],"count,":[138],"enhancing":[139],"efficiency.":[141],"Subsequently,":[142],"domain":[145],"utilizes":[149],"Transformer":[150],"capture":[152],"time-domain":[154],"Kernel":[156],"visualization":[157],"used":[159,227],"provide":[161,239],"direct":[162],"insights":[163],"into":[164],"spectral":[166],"module.":[174],"further":[176],"enhance":[177],"interpretability":[178,196],"domain,":[182],"post-hoc":[184],"analysis":[185],"conducted":[187,218],"SHAP":[189],"method.":[190],"Based":[191],"results":[194],"analysis,":[197],"potential":[198],"biomarkers":[199],"have":[200],"been":[201],"observed":[202],"within":[203],"alpha":[204],"gamma":[206],"rhythms":[207],"across":[208],"frontal,":[210],"parietal,":[211],"temporal,":[212],"occipital":[214],"areas.":[215],"Comprehensive":[216],"experiments":[217],"public":[220],"MODMA,":[221],"EDRA":[222],"Mumtaz":[224],"datasets":[225],"were":[226],"assess":[229],"performance":[231],"proposed":[234,244],"approach.":[235],"experimental":[237],"outcomes":[238],"compelling":[240],"evidence":[241],"that":[242],"method":[245],"not":[246],"only":[247],"surpasses":[248],"multiple":[249],"state-of-the-art":[250],"approaches":[251],"in":[252],"also":[255],"contributes":[256],"significant":[258],"advancement":[259],"toward":[260],"development":[262],"diagnostic":[265],"technique":[266],"depression,":[268],"thereby":[269],"bridging":[270],"gap":[272],"between":[273],"computational":[274],"methodologies":[275],"practical":[277],"psychiatric":[278],"applications.":[279]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-12-06T00:00:00"}
