{"id":"https://openalex.org/W4405653478","doi":"https://doi.org/10.1007/s10462-024-11028-2","title":"Reconstructing damaged fNIRS signals with a generative deep learning model","display_name":"Reconstructing damaged fNIRS signals with a generative deep learning model","publication_year":2024,"publication_date":"2024-12-19","ids":{"openalex":"https://openalex.org/W4405653478","doi":"https://doi.org/10.1007/s10462-024-11028-2"},"language":"en","primary_location":{"id":"doi:10.1007/s10462-024-11028-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-024-11028-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10462-024-11028-2.pdf","source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"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":"Artificial Intelligence Review","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10462-024-11028-2.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045200542","display_name":"Yingxu Zhi","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210115644","display_name":"Chinese Institute for Brain Research","ror":"https://ror.org/029819q61","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210115644"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingxu Zhi","raw_affiliation_strings":["State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China","institution_ids":["https://openalex.org/I4210115644","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101508579","display_name":"Baiqiang Zhang","orcid":"https://orcid.org/0000-0002-8019-7100"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210115644","display_name":"Chinese Institute for Brain Research","ror":"https://ror.org/029819q61","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210115644"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baiqiang Zhang","raw_affiliation_strings":["State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China","institution_ids":["https://openalex.org/I4210115644","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021228982","display_name":"Bingxin Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingxin Xu","raw_affiliation_strings":["Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, 100101, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, 100101, China","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100569624","display_name":"Fei Wan","orcid":null},"institutions":[{"id":"https://openalex.org/I114234892","display_name":"Beijing Union University","ror":"https://ror.org/01hg31662","country_code":"CN","type":"education","lineage":["https://openalex.org/I114234892"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wan","raw_affiliation_strings":["Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, 100101, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, 100101, China","institution_ids":["https://openalex.org/I114234892"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069211368","display_name":"Peisong Niu","orcid":"https://orcid.org/0009-0007-7023-0900"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210115644","display_name":"Chinese Institute for Brain Research","ror":"https://ror.org/029819q61","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210115644"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peisong Niu","raw_affiliation_strings":["State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China","institution_ids":["https://openalex.org/I4210115644","https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007644829","display_name":"Haijing Niu","orcid":"https://orcid.org/0000-0002-3887-1966"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210115644","display_name":"Chinese Institute for Brain Research","ror":"https://ror.org/029819q61","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210115644"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haijing Niu","raw_affiliation_strings":["State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China","institution_ids":["https://openalex.org/I4210115644","https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5045200542"],"corresponding_institution_ids":["https://openalex.org/I25254941","https://openalex.org/I4210115644"],"apc_list":{"value":2490,"currency":"EUR","value_usd":3090},"apc_paid":{"value":2490,"currency":"EUR","value_usd":3090},"fwci":0.5416,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64092049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"58","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9715999960899353,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9714999794960022,"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/computer-science","display_name":"Computer science","score":0.7681728601455688},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6103967428207397},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5789294838905334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.552115261554718},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4997522830963135},{"id":"https://openalex.org/keywords/functional-near-infrared-spectroscopy","display_name":"Functional near-infrared spectroscopy","score":0.4911322295665741},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12160760164260864},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.11251994967460632}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7681728601455688},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6103967428207397},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5789294838905334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.552115261554718},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4997522830963135},{"id":"https://openalex.org/C130796691","wikidata":"https://www.wikidata.org/wiki/Q750537","display_name":"Functional near-infrared spectroscopy","level":4,"score":0.4911322295665741},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12160760164260864},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.11251994967460632},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.0},{"id":"https://openalex.org/C2781195155","wikidata":"https://www.wikidata.org/wiki/Q18680","display_name":"Prefrontal cortex","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10462-024-11028-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-024-11028-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10462-024-11028-2.pdf","source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"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":"Artificial Intelligence Review","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10462-024-11028-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10462-024-11028-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10462-024-11028-2.pdf","source":{"id":"https://openalex.org/S122814990","display_name":"Artificial Intelligence Review","issn_l":"0269-2821","issn":["0269-2821","1573-7462"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"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":"Artificial Intelligence Review","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2193529120","display_name":null,"funder_award_id":"81761148026","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3797627652","display_name":null,"funder_award_id":"4242020","funder_id":"https://openalex.org/F4320334977","funder_display_name":"Beijing Municipal Natural Science Foundation"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6058138561","display_name":null,"funder_award_id":", No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G685742449","display_name":null,"funder_award_id":"62006020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7024628391","display_name":null,"funder_award_id":"[2019]","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7418900372","display_name":null,"funder_award_id":"81571755","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8863666567","display_name":null,"funder_award_id":"and No.","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/F4320321496","display_name":"Capital Medical University","ror":"https://ror.org/013xs5b60"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4405653478.pdf"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W1996776986","https://openalex.org/W1999340799","https://openalex.org/W2024038024","https://openalex.org/W2025564775","https://openalex.org/W2029802912","https://openalex.org/W2060568420","https://openalex.org/W2060653236","https://openalex.org/W2064515517","https://openalex.org/W2106943414","https://openalex.org/W2117829824","https://openalex.org/W2137523819","https://openalex.org/W2167775278","https://openalex.org/W2170432972","https://openalex.org/W2313339984","https://openalex.org/W2332309863","https://openalex.org/W2604847698","https://openalex.org/W2756203131","https://openalex.org/W2765346048","https://openalex.org/W2897094884","https://openalex.org/W2942192867","https://openalex.org/W2946145454","https://openalex.org/W2946985871","https://openalex.org/W2962822388","https://openalex.org/W2963608065","https://openalex.org/W2982118753","https://openalex.org/W3005867646","https://openalex.org/W3012317771","https://openalex.org/W3030939193","https://openalex.org/W3041361970","https://openalex.org/W3088738441","https://openalex.org/W3092384632","https://openalex.org/W3103720336","https://openalex.org/W3159456745","https://openalex.org/W3197435135","https://openalex.org/W4210329175","https://openalex.org/W4284961077","https://openalex.org/W4291910522","https://openalex.org/W4307572272","https://openalex.org/W4309694784","https://openalex.org/W4310790298","https://openalex.org/W4382199608","https://openalex.org/W4383218913","https://openalex.org/W4388554780","https://openalex.org/W4391774550","https://openalex.org/W4391807011","https://openalex.org/W4392865184","https://openalex.org/W4396642289","https://openalex.org/W4399107575","https://openalex.org/W6603242443"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W4365211920","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756"],"abstract_inverted_index":{"Functional":[0],"near-infrared":[1],"spectroscopy":[2],"(fNIRS)":[3],"imaging":[4],"offers":[5],"a":[6,51,86,134,229],"promising":[7],"avenue":[8],"for":[9,164,232],"measuring":[10],"brain":[11,242],"function":[12],"in":[13,22,37,73,96,109,146,208,223,238],"both":[14],"healthy":[15,139],"and":[16,106,125,142,151,206,241],"diseased":[17],"cohorts.":[18],"However,":[19],"signal":[20],"quality":[21,57],"fNIRS":[23,60,71,94,114,136,169,181,226],"data":[24,115,237],"frequently":[25],"encounters":[26],"challenges,":[27],"such":[28],"as":[29],"low":[30],"signal-to-noise":[31],"ratio":[32],"or":[33,39,98],"substantial":[34],"motion":[35],"artifacts":[36],"one":[38,97],"multiple":[40,198],"measurement":[41,100],"channels,":[42],"impeding":[43],"the":[44,48,56,66,110,131,157,165,175,200,216,233],"comprehensive":[45],"exploitation":[46],"of":[47,58,69,113,148,167,210,218,236],"data.":[49],"Developing":[50],"valid":[52],"method":[53],"to":[54,91],"improve":[55],"damaged":[59,93,168,180,225],"signals":[61,95],"is":[62],"crucial,":[63],"particularly":[64],"given":[65],"extensive":[67],"use":[68],"wearable":[70],"devices":[72],"natural":[74],"settings":[75],"where":[76],"noise":[77],"issues":[78],"are":[79],"even":[80],"more":[81,99],"unavoidable.":[82],"Here,":[83],"we":[84],"proposed":[85,158],"generative":[87,219],"deep":[88,220],"learning":[89,221],"approach":[90],"recover":[92],"channels.":[101],"The":[102],"model":[103,132,159,176,201],"captured":[104],"spatial":[105],"temporal":[107],"variations":[108],"time":[111,170,182],"series":[112,183],"by":[116],"integrating":[117],"multiscale":[118],"convolutional":[119],"layers,":[120],"gated":[121],"recurrent":[122],"units":[123],"(GRUs),":[124],"linear":[126],"regression":[127],"analyses.":[128],"We":[129],"trained":[130],"on":[133],"resting-state":[135],"dataset":[137],"from":[138],"elderly":[140],"individuals":[141],"evaluated":[143],"its":[144],"performance":[145,163],"terms":[147,209],"reconstruction":[149,166,204],"accuracy":[150,205],"functional":[152,211],"connectivity":[153],"matrix":[154],"similarity.":[155],"Collectively,":[156],"exhbited":[160],"an":[161],"excellent":[162],"series.":[171],"In":[172,197],"individual":[173],"channel-level,":[174,199],"can":[177],"accurately":[178],"reconstruct":[179],"(mean":[184],"correlation":[185],"=":[186,195],"0.80":[187],"\u00b1":[188],"0.14)":[189],"while":[190],"preserving":[191],"intervariable":[192],"relationships":[193],"(correlation":[194],"0.93).":[196],"maintained":[202],"robust":[203],"consistency":[207],"connectivity.":[212],"Our":[213],"findings":[214],"underscore":[215],"potential":[217],"techniques":[222],"reconstructing":[224],"signals,":[227],"providing":[228],"novel":[230],"perspective":[231],"efficient":[234],"utilization":[235],"clinical":[239],"diagnosis":[240],"research.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
