{"id":"https://openalex.org/W7164418078","doi":"https://doi.org/10.1016/j.compbiomed.2026.111801","title":"Reconfiguring brain networks via lightweight dynamic connectivity framework: An EEG-based stress validation","display_name":"Reconfiguring brain networks via lightweight dynamic connectivity framework: An EEG-based stress validation","publication_year":2026,"publication_date":"2026-06-11","ids":{"openalex":"https://openalex.org/W7164418078","doi":"https://doi.org/10.1016/j.compbiomed.2026.111801","pmid":"https://pubmed.ncbi.nlm.nih.gov/42275813"},"language":"en","primary_location":{"id":"doi:10.1016/j.compbiomed.2026.111801","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2026.111801","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.compbiomed.2026.111801","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000907475","display_name":"Sayantan Acharya","orcid":"https://orcid.org/0000-0002-8007-3001"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sayantan Acharya","raw_affiliation_strings":["Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-8007-3001","affiliations":[{"raw_affiliation_string":"Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138416663","display_name":"Abbas Khosravi","orcid":null},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Abbas Khosravi","raw_affiliation_strings":["Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046519614","display_name":"Douglas Creighton","orcid":"https://orcid.org/0000-0002-9217-1231"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Douglas Creighton","raw_affiliation_strings":["Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083567791","display_name":"Roohallah Alizadehsani","orcid":"https://orcid.org/0000-0003-0898-5054"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Roohallah Alizadehsani","raw_affiliation_strings":["Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia. Electronic address: r.alizadehsani@deakin.edu.au"],"raw_orcid":"https://orcid.org/0000-0003-0898-5054","affiliations":[{"raw_affiliation_string":"Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Waurn Ponds, VIC, Australia. Electronic address: r.alizadehsani@deakin.edu.au","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138426625","display_name":"U Rajendra Acharya","orcid":null},"institutions":[{"id":"https://openalex.org/I185523456","display_name":"University of Southern Queensland","ror":"https://ror.org/04sjbnx57","country_code":"AU","type":"education","lineage":["https://openalex.org/I185523456"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"U Rajendra Acharya","raw_affiliation_strings":["School of Science, Engineering and Digital Technologies, University of Southern Queensland, Springfield, Australia; Centre for Health Research, University of Southern Queensland, Springfield, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science, Engineering and Digital Technologies, University of Southern Queensland, Springfield, Australia; Centre for Health Research, University of Southern Queensland, Springfield, Australia","institution_ids":["https://openalex.org/I185523456"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083567791"],"corresponding_institution_ids":["https://openalex.org/I149704539"],"apc_list":{"value":2610,"currency":"USD","value_usd":2610},"apc_paid":{"value":2610,"currency":"USD","value_usd":2610},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78593472,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"213","issue":null,"first_page":"111801","last_page":"111801"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.7455999851226807,"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":0.7455999851226807,"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":0.20100000500679016,"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":0.021299999207258224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8134999871253967},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6496000289916992},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5942000150680542},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.49959999322891235},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.4964999854564667},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.4765999913215637},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4578000009059906},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4090999960899353}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8134999871253967},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.754800021648407},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6496000289916992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.633899986743927},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5942000150680542},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5072000026702881},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.49959999322891235},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.4964999854564667},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.4765999913215637},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4578000009059906},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4036000072956085},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.3840000033378601},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.3804999887943268},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C3018390542","wikidata":"https://www.wikidata.org/wiki/Q1073","display_name":"Brain function","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1016/j.compbiomed.2026.111801","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2026.111801","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},{"id":"pmid:42275813","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42275813","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":"Computers in biology and medicine","raw_type":null},{"id":"pmh:oai:arXiv.org:2511.05505","is_oa":true,"landing_page_url":"https://arxiv.org/abs/2511.05505","pdf_url":"https://arxiv.org/pdf/2511.05505","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1016/j.compbiomed.2026.111801","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2026.111801","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7588319778442383,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320970","display_name":"Deakin University","ror":"https://ror.org/02czsnj07"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1964769652","https://openalex.org/W1966827292","https://openalex.org/W1978520484","https://openalex.org/W1999653836","https://openalex.org/W2009914532","https://openalex.org/W2025366179","https://openalex.org/W2050995101","https://openalex.org/W2086498469","https://openalex.org/W2139564752","https://openalex.org/W2202134196","https://openalex.org/W2227520796","https://openalex.org/W2421101021","https://openalex.org/W2523494305","https://openalex.org/W2523525429","https://openalex.org/W2553272317","https://openalex.org/W2606321326","https://openalex.org/W2757047268","https://openalex.org/W2773478070","https://openalex.org/W2896118681","https://openalex.org/W2920509382","https://openalex.org/W2941146140","https://openalex.org/W2945032471","https://openalex.org/W2958197594","https://openalex.org/W2998342169","https://openalex.org/W2998525532","https://openalex.org/W3014933423","https://openalex.org/W3023481128","https://openalex.org/W3159938151","https://openalex.org/W3199166979","https://openalex.org/W3206297467","https://openalex.org/W4205734780","https://openalex.org/W4211136643","https://openalex.org/W4231265947","https://openalex.org/W4286631276","https://openalex.org/W4308980546","https://openalex.org/W4313062885","https://openalex.org/W4321480413","https://openalex.org/W4366609029","https://openalex.org/W4367181541","https://openalex.org/W4378901626","https://openalex.org/W4380201808","https://openalex.org/W4384558420","https://openalex.org/W4385304163","https://openalex.org/W4401567062","https://openalex.org/W4409291053","https://openalex.org/W4410773088","https://openalex.org/W4415121640","https://openalex.org/W7155485674"],"related_works":[],"abstract_inverted_index":{"In":[0,23],"recent":[1],"years,":[2],"Electroencephalographic":[3],"(EEG)":[4],"analysis":[5,184],"has":[6],"gained":[7],"prominence":[8],"in":[9,46,142,151],"stress":[10,221],"research":[11],"when":[12],"combined":[13],"with":[14,137,146],"AI":[15],"and":[16,65,122,145,158,165,189,216],"Machine":[17,111],"Learning":[18],"(ML)":[19],"models":[20],"for":[21,32],"validation.":[22],"this":[24],"study,":[25],"a":[26,209],"lightweight":[27,206],"dynamic":[28,43,98,178],"brain":[29,214],"connectivity":[30,45,75,162],"framework":[31],"estimating":[33],"Time-Varying":[34],"Directed":[35],"Transfer":[36],"Function":[37],"(TV-DTF)":[38],"is":[39],"proposed":[40],"to":[41,155],"capture":[42],"effective":[44],"EEG":[47,56,77],"signals.":[48],"TV-DTF":[49,100,207],"estimates":[50],"the":[51,80,97,133,171,175,194,205],"directional":[52,217],"information":[53],"flow":[54],"between":[55],"channels":[57],"across":[58,170,219],"distinct":[59],"frequency":[60],"bands,":[61],"thereby":[62],"capturing":[63],"temporal":[64],"directed":[66],"influences":[67,218],"that":[68,130],"are":[69],"often":[70],"overlooked":[71],"by":[72],"static":[73,180],"functional":[74,161],"measures.":[76,181],"recordings":[78],"from":[79],"32-channel":[81],"SAM":[82],"40":[83],"dataset":[84],"were":[85],"employed,":[86],"focusing":[87],"on":[88],"mental":[89],"arithmetic":[90],"task":[91],"trials.":[92],"The":[93],"discriminative":[94,135],"capability":[95],"of":[96,177,197],"EEG-based":[99],"features":[101],"was":[102],"validated":[103],"through":[104],"ML":[105,172],"-based":[106],"experiments":[107],"utilizing":[108],"Support":[109],"Vector":[110],"(SVM),":[112],"Random":[113],"Forest":[114],"(RF),":[115],"Gradient":[116,124],"Boosting":[117,120,125],"(GB),":[118],"Adaptive":[119],"(AdaBoost),":[121],"Extreme":[123],"(XGBoost).":[126],"Experimental":[127],"results":[128],"show":[129],"alpha-TV-DTF":[131,164],"provides":[132],"strongest":[134],"power,":[136],"SVM":[138],"achieving":[139,148],"89.73%":[140],"accuracy":[141,150],"3-class":[143],"classification":[144],"XGBoost":[147],"93.69%":[149],"2-class":[152],"classification.":[153],"Relative":[154],"absolute":[156],"power":[157],"phase":[159],"locking-based":[160],"features,":[163],"beta-TV-DTF":[166],"achieved":[167],"higher":[168],"performance":[169],"models,":[173],"highlighting":[174],"advantages":[176],"over":[179],"Feature":[182],"importance":[183],"further":[185],"highlighted":[186],"prominent":[187],"frontal-parietal":[188],"frontal-occipital":[190],"informational":[191],"influences,":[192],"emphasizing":[193],"regulatory":[195],"role":[196],"frontal":[198],"regions":[199],"under":[200],"stress.":[201],"These":[202],"findings":[203],"validate":[204],"as":[208],"robust":[210],"framework,":[211],"revealing":[212],"spatiotemporal":[213],"dynamics":[215],"different":[220],"levels.":[222]},"counts_by_year":[],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2026-06-12T00:00:00"}