{"id":"https://openalex.org/W4417483168","doi":"https://doi.org/10.1007/s44443-025-00411-w","title":"EmoDNCL+: Dual-stream negative-sample-free contrastive learning with neurophysiological augmentation for EEG emotion recognition","display_name":"EmoDNCL+: Dual-stream negative-sample-free contrastive learning with neurophysiological augmentation for EEG emotion recognition","publication_year":2025,"publication_date":"2025-12-19","ids":{"openalex":"https://openalex.org/W4417483168","doi":"https://doi.org/10.1007/s44443-025-00411-w"},"language":"en","primary_location":{"id":"doi:10.1007/s44443-025-00411-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44443-025-00411-w","pdf_url":null,"source":{"id":"https://openalex.org/S2764955546","display_name":"Journal of King Saud University - Computer and Information Sciences","issn_l":"1319-1578","issn":["1319-1578","2213-1248"],"is_oa":true,"is_in_doaj":true,"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":"Journal of King Saud University Computer and Information Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44443-025-00411-w","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104364933","display_name":"Feiyu Jiang","orcid":"https://orcid.org/0009-0005-5233-5499"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feiyu Jiang","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032573414","display_name":"Nisuo Du","orcid":"https://orcid.org/0000-0002-3026-1741"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]},{"id":"https://openalex.org/I4210160692","display_name":"Guizhou Academy of Sciences","ror":"https://ror.org/05ty2n298","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210160692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nisuo Du","raw_affiliation_strings":["Guizhou Big Data Academy, Guizhou University, Guiyang, 550025, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"Guizhou Big Data Academy, Guizhou University, Guiyang, 550025, Guizhou, China","institution_ids":["https://openalex.org/I4210160692","https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056684759","display_name":"MingHao Yu","orcid":"https://orcid.org/0009-0004-8485-7382"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghao Yu","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012814888","display_name":"Qing He","orcid":"https://orcid.org/0000-0002-1801-9901"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing He","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China","institution_ids":["https://openalex.org/I178232147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5104364933"],"corresponding_institution_ids":["https://openalex.org/I178232147"],"apc_list":{"value":1350,"currency":"USD","value_usd":1350},"apc_paid":{"value":1350,"currency":"USD","value_usd":1350},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44865266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9771000146865845,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9771000146865845,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.010900000110268593,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.0010000000474974513,"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/electroencephalography","display_name":"Electroencephalography","score":0.5968999862670898},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.519599974155426},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4580000042915344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4499000012874603},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.4269999861717224},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.41269999742507935},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41019999980926514},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.3984000086784363},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3878999948501587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6618000268936157},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5968999862670898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5710999965667725},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.519599974155426},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4580000042915344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4499000012874603},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4375},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3984000086784363},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3862000107765198},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.29989999532699585},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2976999878883362},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28139999508857727},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.2766000032424927},{"id":"https://openalex.org/C152478114","wikidata":"https://www.wikidata.org/wiki/Q660910","display_name":"Neurophysiology","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2635999917984009},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2632000148296356},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44443-025-00411-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44443-025-00411-w","pdf_url":null,"source":{"id":"https://openalex.org/S2764955546","display_name":"Journal of King Saud University - Computer and Information Sciences","issn_l":"1319-1578","issn":["1319-1578","2213-1248"],"is_oa":true,"is_in_doaj":true,"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":"Journal of King Saud University Computer and Information Sciences","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b6a5ddb87a2c4bce940d3006630e1618","is_oa":true,"landing_page_url":"https://doaj.org/article/b6a5ddb87a2c4bce940d3006630e1618","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of King Saud University: Computer and Information Sciences, Vol 38, Iss 2, Pp 1-23 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44443-025-00411-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44443-025-00411-w","pdf_url":null,"source":{"id":"https://openalex.org/S2764955546","display_name":"Journal of King Saud University - Computer and Information Sciences","issn_l":"1319-1578","issn":["1319-1578","2213-1248"],"is_oa":true,"is_in_doaj":true,"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":"Journal of King Saud University Computer and Information Sciences","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1517011095","https://openalex.org/W1947251450","https://openalex.org/W1970727126","https://openalex.org/W1980553000","https://openalex.org/W1998633235","https://openalex.org/W2013194433","https://openalex.org/W2063497316","https://openalex.org/W2105119061","https://openalex.org/W2109773980","https://openalex.org/W2113276962","https://openalex.org/W2142766726","https://openalex.org/W2526600820","https://openalex.org/W2786768213","https://openalex.org/W2790404832","https://openalex.org/W2934123712","https://openalex.org/W2962905870","https://openalex.org/W3021760027","https://openalex.org/W3024961463","https://openalex.org/W3046474724","https://openalex.org/W3082568354","https://openalex.org/W3083218890","https://openalex.org/W3169534597","https://openalex.org/W3171007011","https://openalex.org/W3172498913","https://openalex.org/W3177392932","https://openalex.org/W3183340146","https://openalex.org/W3199638068","https://openalex.org/W4206086399","https://openalex.org/W4220866631","https://openalex.org/W4225411558","https://openalex.org/W4295832380","https://openalex.org/W4304086659","https://openalex.org/W4312192940","https://openalex.org/W4319934143","https://openalex.org/W4321507406","https://openalex.org/W4361791063","https://openalex.org/W4372262620","https://openalex.org/W4379538313","https://openalex.org/W4387431468","https://openalex.org/W4389105052","https://openalex.org/W4392125748","https://openalex.org/W4396523306","https://openalex.org/W4399849687","https://openalex.org/W4400360499","https://openalex.org/W4400975541","https://openalex.org/W4401558832","https://openalex.org/W4402508563","https://openalex.org/W4402735932","https://openalex.org/W4410358679","https://openalex.org/W4414692978"],"related_works":[],"abstract_inverted_index":{"Electroencephalography":[0],"(EEG)":[1],"plays":[2],"a":[3,118,193],"crucial":[4],"role":[5],"in":[6,24,147,178],"emotion":[7,72,184],"recognition,":[8,73],"however,":[9],"its":[10],"real-world":[11],"deployment":[12],"is":[13],"hindered":[14],"by":[15,102],"generalization":[16],"limitations":[17],"due":[18],"to":[19,34,132,170],"subject-specific":[20,157],"variability":[21,158],"and":[22,52,105,128,154,159,189,204,219],"distortions":[23],"EEG":[25,37,71,152],"signals.":[26],"While":[27],"self-supervised":[28],"contrastive":[29,66],"learning":[30,67],"offers":[31],"the":[32,63,76,89,98,110,114,134,148,172,209],"capacity":[33],"leverage":[35],"unlabeled":[36],"data,":[38,211],"existing":[39],"methods":[40],"critically":[41],"depend":[42],"on":[43,78,187,217,221],"manually":[44],"crafted":[45],"negative":[46,79],"sample":[47,80],"pairs,":[48,113],"introducing":[49],"semantic":[50],"ambiguity":[51],"high":[53,214],"design":[54],"costs.":[55],"To":[56],"overcome":[57],"these":[58],"challenges,":[59],"we":[60,139,162],"propose":[61,140],"EmoDNCL+,":[62],"first":[64],"negative-sample-free":[65],"framework":[68],"designed":[69],"for":[70,156],"completely":[74],"eliminating":[75],"reliance":[77],"pairs.":[81],"Dual-stream":[82],"Negative-sample-free":[83],"Contrastive":[84],"Learning":[85],"(DNCL)":[86],"serves":[87],"as":[88],"core":[90],"of":[91,136,151,174,202],"EmoDNCL+.":[92],"It":[93],"constructs":[94],"local":[95,115,127],"pairs":[96,116],"from":[97],"student":[99],"network\u2019s":[100],"outputs":[101],"applying":[103],"strong":[104],"weak":[106],"augmentations.":[107],"Together":[108],"with":[109,199],"student\u2013teacher":[111],"global":[112,129],"form":[117],"dual-stream":[119],"optimization":[120],"mechanism,":[121],"achieving":[122],"feature":[123],"alignment":[124],"at":[125,215],"both":[126],"levels.":[130],"Furthermore,":[131],"guarantee":[133],"reliability":[135],"positive":[137],"samples,":[138],"Neighborhood":[141],"Information":[142],"Node":[143],"Adjustment":[144],"(NINA),":[145],"grounded":[146],"spatial":[149],"continuity":[150],"signals":[153],"accounting":[155],"distortions.":[160],"Moreover,":[161],"dynamically":[163],"construct":[164],"adjacency":[165],"matrices":[166],"using":[167],"cosine":[168],"similarity":[169],"improve":[171],"capability":[173],"Graph":[175],"Neural":[176],"Networks":[177],"extracting":[179],"cross-subject":[180],"emotional":[181],"features.":[182],"Cross-subject":[183],"recognition":[185],"experiments":[186],"SEED":[188,218],"SEED-IV,":[190],"conducted":[191],"under":[192],"leave-one-subject-out":[194],"protocol,":[195],"achieve":[196],"state-of-the-art":[197],"performance":[198],"accuracy":[200,212],"rates":[201],"93.60%":[203],"79.32%,":[205],"respectively.":[206],"With":[207],"half":[208],"training":[210],"remains":[213],"91.88%":[216],"74.87%":[220],"SEED-IV.":[222]},"counts_by_year":[],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-12-19T00:00:00"}
