{"id":"https://openalex.org/W4406612748","doi":"https://doi.org/10.1109/smc54092.2024.10831723","title":"Closed-Loop Phase Selection in EEG-TMS Using Bayesian Optimization","display_name":"Closed-Loop Phase Selection in EEG-TMS Using Bayesian Optimization","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4406612748","doi":"https://doi.org/10.1109/smc54092.2024.10831723"},"language":"en","primary_location":{"id":"doi:10.1109/smc54092.2024.10831723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5053625820","display_name":"Miriam Kirchhoff","orcid":"https://orcid.org/0000-0002-6099-0283"},"institutions":[{"id":"https://openalex.org/I143910747","display_name":"TH Bingen University of Applied Sciences","ror":"https://ror.org/01pxkj057","country_code":"DE","type":"education","lineage":["https://openalex.org/I143910747"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Miriam Kirchhoff","raw_affiliation_strings":["University of Tübingen,Department of Neurology & Stroke,Tübingen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tübingen,Department of Neurology & Stroke,Tübingen,Germany","institution_ids":["https://openalex.org/I143910747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000920105","display_name":"Dania Humaidan","orcid":"https://orcid.org/0000-0003-1381-257X"},"institutions":[{"id":"https://openalex.org/I143910747","display_name":"TH Bingen University of Applied Sciences","ror":"https://ror.org/01pxkj057","country_code":"DE","type":"education","lineage":["https://openalex.org/I143910747"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dania Humaidan","raw_affiliation_strings":["University of Tübingen,Department of Neurology & Stroke,Tübingen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tübingen,Department of Neurology & Stroke,Tübingen,Germany","institution_ids":["https://openalex.org/I143910747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070374515","display_name":"Ulf Ziemann","orcid":"https://orcid.org/0000-0001-8372-3615"},"institutions":[{"id":"https://openalex.org/I143910747","display_name":"TH Bingen University of Applied Sciences","ror":"https://ror.org/01pxkj057","country_code":"DE","type":"education","lineage":["https://openalex.org/I143910747"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ulf Ziemann","raw_affiliation_strings":["University of Tübingen,Department of Neurology & Stroke,Tübingen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tübingen,Department of Neurology & Stroke,Tübingen,Germany","institution_ids":["https://openalex.org/I143910747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143910747"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1730","last_page":"1735"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8086000084877014,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8086000084877014,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.7932999730110168,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.6858999729156494,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.6584391593933105},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6278703212738037},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6021401882171631},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.569294810295105},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.5603419542312622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5443827509880066},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.5282052159309387},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.43389129638671875},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38809406757354736},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32829490303993225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15006884932518005},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.14841696619987488},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11975795030593872},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07353636622428894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6584391593933105},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6278703212738037},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6021401882171631},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.569294810295105},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.5603419542312622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443827509880066},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.5282052159309387},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.43389129638671875},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38809406757354736},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32829490303993225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15006884932518005},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.14841696619987488},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11975795030593872},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07353636622428894},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc54092.2024.10831723","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831723","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1996864540","https://openalex.org/W2004808074","https://openalex.org/W2030006024","https://openalex.org/W2052032974","https://openalex.org/W2104584406","https://openalex.org/W2128495200","https://openalex.org/W2136022845","https://openalex.org/W2166073443","https://openalex.org/W2757881549","https://openalex.org/W2899430109","https://openalex.org/W2990903842","https://openalex.org/W2997901555","https://openalex.org/W3012410602","https://openalex.org/W3037668166","https://openalex.org/W3110151578","https://openalex.org/W4226083754","https://openalex.org/W4284991747","https://openalex.org/W4311255680"],"related_works":["https://openalex.org/W24774503","https://openalex.org/W3106461837","https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2130428257","https://openalex.org/W4308951944","https://openalex.org/W2057366091","https://openalex.org/W2014821076","https://openalex.org/W4312960290","https://openalex.org/W4401858220"],"abstract_inverted_index":{"Research":[0],"on":[1],"transcranial":[2],"magnetic":[3],"stimulation":[4,34],"(TMS)":[5],"combined":[6],"with":[7,59,69,98,158,190,197,232,239,289,293],"encephalography":[8],"feedback":[9],"(EEG-TMS)":[10],"has":[11],"shown":[12],"that":[13,180,271],"the":[14,17,28,52,56,108,125,154,163,184,194,223,227,236,260,275,284],"phase":[15,31,53,102,200,252,267],"of":[16,23,86,203,248,262],"sensorimotor":[18],"mu":[19],"rhythm":[20],"is":[21,32],"predictive":[22],"corticospinal":[24],"excitability.":[25],"Thus,":[26],"if":[27],"subject-specific":[29],"optimal":[30,126],"known,":[33],"can":[35,273],"be":[36,39],"timed":[37],"to":[38,50,55,123],"more":[40],"efficient.":[41],"In":[42,226,255],"this":[43],"paper,":[44],"we":[45,94,119,257,272],"present":[46],"a":[47,84,99,134,150,167,173,198,240],"closed-loop":[48,263],"algorithm":[49],"determine":[51],"linked":[54],"highest":[57],"excitability":[58],"as":[60,63,72,153],"few":[61],"trials":[62],"possible.":[64],"We":[65,110,128,144,161,178,269],"used":[66,120],"Bayesian":[67,121,137,185,213,230,264,291],"optimization":[68,122,169,175,265,292],"different":[70],"configurations":[71],"an":[73,79],"automated,":[74],"online":[75],"search":[76],"tool":[77],"in":[78,136,166,188,222],"EEG-TMS":[80],"simulation":[81],"exneriment.":[82],"From":[83],"sample":[85],"38":[87],"healthy":[88],"participants":[89,97],"(25":[90],"f,":[91],"18":[92],"m),":[93],"selected":[95],"all":[96],"significant":[100],"single-subject":[101],"effect":[103],"(N":[104],"=":[105],"5)":[106],"for":[107,181,266],"simulation.":[109],"then":[111],"simulated":[112],"1000":[113],"experimental":[114],"sessions":[115],"per":[116],"participant":[117],"where":[118],"find":[124],"phase.":[127],"tested":[129,146],"two":[130],"objective":[131],"functions:":[132],"Fitting":[133],"sinusoid":[135],"linear":[138,186,214],"regression":[139,187,215,221,231],"or":[140],"Gaussian":[141,219,294],"Process":[142,220,295],"regression.":[143,296],"additionally":[145],"adaptive":[147,191],"sampling":[148,192,211,234],"using":[149,280],"knowledge":[151,282],"gradient":[152],"acquisition":[155],"function":[156,286],"compared":[157,288],"random":[159,233],"sampling.":[160],"evaluated":[162],"algorithm's":[164],"performance":[165,247],"fast":[168,182,224],"(100":[170],"trials)":[171],"and":[172,244,277],"long-term":[174,228],"(1000":[176],"trials).":[177],"found":[179],"optimization,":[183,229],"combination":[189],"gives":[193],"best":[195,237],"results":[196],"mean":[199,251],"location":[201,253],"accuracy":[202,278],"79":[204],"%":[205,250],"after":[206],"100":[207],"trials.":[208],"With":[209],"either":[210],"approach,":[212],"performs":[216],"better":[217],"than":[218],"optimization.":[225],"shows":[235],"trajectory,":[238],"rather":[241],"steep":[242],"improvement":[243],"good":[245],"final":[246],"87":[249],"accuracy.":[254],"summary,":[256],"could":[258],"show":[259,270],"suitability":[261],"selection.":[268],"increase":[274],"speed":[276],"by":[279],"prior":[281],"about":[283],"expected":[285],"shape":[287],"traditional":[290]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}