{"id":"https://openalex.org/W4313136752","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892022","title":"Multiple Kernel Learning for Modeling Resting State EEG Connectomes using Structural Connectivity of the Brain","display_name":"Multiple Kernel Learning for Modeling Resting State EEG Connectomes using Structural Connectivity of the Brain","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4313136752","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892022"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892022","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5035803890","display_name":"P. L. Ammar Ahmed","orcid":null},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"P. L. Ammar Ahmed","raw_affiliation_strings":["International Institute of Information Technology,Hyderabad","International Institute of Information Technology, Hyderabad"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology,Hyderabad","institution_ids":["https://openalex.org/I64189192"]},{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036789034","display_name":"Archi Yadav","orcid":null},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Archi Yadav","raw_affiliation_strings":["International Institute of Information Technology,Hyderabad","International Institute of Information Technology, Hyderabad"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology,Hyderabad","institution_ids":["https://openalex.org/I64189192"]},{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060714797","display_name":"Avinash Sharma","orcid":"https://orcid.org/0000-0001-5013-5024"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Avinash Sharma","raw_affiliation_strings":["International Institute of Information Technology,Hyderabad","International Institute of Information Technology, Hyderabad"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology,Hyderabad","institution_ids":["https://openalex.org/I64189192"]},{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad","institution_ids":["https://openalex.org/I64189192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049423985","display_name":"Raju S. Bapi","orcid":"https://orcid.org/0000-0003-2204-0890"},"institutions":[{"id":"https://openalex.org/I64189192","display_name":"International Institute of Information Technology, Hyderabad","ror":"https://ror.org/05f11g639","country_code":"IN","type":"education","lineage":["https://openalex.org/I64189192"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Raju S. Bapi","raw_affiliation_strings":["International Institute of Information Technology,Hyderabad","International Institute of Information Technology, Hyderabad"],"affiliations":[{"raw_affiliation_string":"International Institute of Information Technology,Hyderabad","institution_ids":["https://openalex.org/I64189192"]},{"raw_affiliation_string":"International Institute of Information Technology, Hyderabad","institution_ids":["https://openalex.org/I64189192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5035803890"],"corresponding_institution_ids":["https://openalex.org/I64189192"],"apc_list":null,"apc_paid":null,"fwci":0.201,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.38321596,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":1.0,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":1.0,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/connectome","display_name":"Connectome","score":0.7592909336090088},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.6882018446922302},{"id":"https://openalex.org/keywords/human-connectome-project","display_name":"Human Connectome Project","score":0.6676239967346191},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6408176422119141},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6147664785385132},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5997589826583862},{"id":"https://openalex.org/keywords/resting-state-fmri","display_name":"Resting state fMRI","score":0.5746152997016907},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.4904634654521942},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4896300435066223},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4783044159412384},{"id":"https://openalex.org/keywords/diffusion-mri","display_name":"Diffusion MRI","score":0.46960553526878357},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4602365493774414},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4492935240268707},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42857739329338074},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.4174482226371765},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.32968103885650635},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.24612438678741455},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.22337573766708374},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22137683629989624},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.21425214409828186},{"id":"https://openalex.org/keywords/functional-connectivity","display_name":"Functional connectivity","score":0.2001049816608429},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11138102412223816},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09785136580467224},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.09399634599685669}],"concepts":[{"id":"https://openalex.org/C45715564","wikidata":"https://www.wikidata.org/wiki/Q1292103","display_name":"Connectome","level":3,"score":0.7592909336090088},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.6882018446922302},{"id":"https://openalex.org/C97820695","wikidata":"https://www.wikidata.org/wiki/Q387749","display_name":"Human Connectome Project","level":3,"score":0.6676239967346191},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6408176422119141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6147664785385132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5997589826583862},{"id":"https://openalex.org/C66324658","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Resting state fMRI","level":2,"score":0.5746152997016907},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.4904634654521942},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4896300435066223},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4783044159412384},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.46960553526878357},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4602365493774414},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4492935240268707},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42857739329338074},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.4174482226371765},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.32968103885650635},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.24612438678741455},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.22337573766708374},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22137683629989624},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.21425214409828186},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.2001049816608429},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11138102412223816},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09785136580467224},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.09399634599685669},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892022","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W40389337","https://openalex.org/W1528119265","https://openalex.org/W1979957238","https://openalex.org/W1980189836","https://openalex.org/W1983740074","https://openalex.org/W1997680969","https://openalex.org/W2005821483","https://openalex.org/W2024892001","https://openalex.org/W2063171028","https://openalex.org/W2097982135","https://openalex.org/W2100235615","https://openalex.org/W2101135654","https://openalex.org/W2127186958","https://openalex.org/W2129483560","https://openalex.org/W2131181615","https://openalex.org/W2148821883","https://openalex.org/W2151139045","https://openalex.org/W2163254535","https://openalex.org/W2166866921","https://openalex.org/W2167822639","https://openalex.org/W2267939148","https://openalex.org/W2341661195","https://openalex.org/W2601707947","https://openalex.org/W2744012576","https://openalex.org/W2747820551","https://openalex.org/W2806674386","https://openalex.org/W2951984334","https://openalex.org/W3027466761","https://openalex.org/W3041266626","https://openalex.org/W3106834533","https://openalex.org/W3112543203"],"related_works":["https://openalex.org/W3136590534","https://openalex.org/W4280586040","https://openalex.org/W2523870064","https://openalex.org/W4298370694","https://openalex.org/W4306360841","https://openalex.org/W3126842272","https://openalex.org/W3117051909","https://openalex.org/W2775079844","https://openalex.org/W2963045269","https://openalex.org/W2182367256"],"abstract_inverted_index":{"An":[0],"active":[1],"area":[2],"of":[3,56,134,177,187,198,202],"research":[4],"in":[5,28],"cognitive":[6],"science":[7],"is":[8,181,205],"characterizing":[9],"the":[10,16,41,54,63,103,108,160,164,170,175,182,199,214,219],"relationship":[11,109],"between":[12,110,139],"brain":[13,42,49],"structure":[14,43],"and":[15,47,112,124,131,142,163],"observed":[17],"functional":[18,35,88,221],"activations.":[19],"Recent":[20],"graph":[21,59,190],"diffusion":[22,46,60,81,191],"models":[23],"have":[24],"had":[25,169],"great":[26],"success":[27],"mapping":[29],"whole-brain,":[30],"resting-state":[31],"dynamics":[32],"measured":[33],"using":[34,45,76],"Magnetic":[36],"Resonance":[37],"Imaging":[38],"(fMRI)":[39],"to":[40,86,208],"derived":[44],"T1":[48],"imaging.":[50],"Here":[51],"we":[52],"test":[53],"application":[55,186],"one":[57],"such":[58,184],"method":[61],"called":[62],"Multiple":[64],"Kernel":[65],"Learning":[66],"(MKL)":[67],"model.":[68],"MKL":[69,104,203],"model,":[70],"formulated":[71],"as":[72],"a":[73,93],"reaction-diffusion":[74],"system":[75],"Wilson-Cowan":[77],"equations,":[78],"combines":[79],"multiple":[80,188],"kernels":[82],"at":[83],"different":[84,116],"scales":[85],"predict":[87],"connectome":[89,96],"(FC)":[90],"arising":[91],"from":[92,114],"fixed":[94],"structural":[95,210],"(SC).":[97],"Our":[98],"simulation":[99],"results":[100],"demonstrate":[101],"that":[102,217],"model":[105,204,216],"successfully":[106],"mapped":[107],"SC":[111],"FC":[113,141,145],"five":[115],"Electroen-cephalogram":[117],"(EEG)":[118],"bands":[119,150],"(delta,":[120],"theta,":[121],"alpha,":[122],"beta,":[123],"gamma).":[125],"We":[126],"used":[127],"simultaneously":[128],"acquired":[129],"EEG-fMRI":[130],"NODDI":[132],"dataset":[133],"17":[135],"participants.":[136],"The":[137,155],"correlation":[138],"predicted":[140],"ground":[143],"truth":[144],"was":[146],"higher":[147],"for":[148,152,159,193],"EEG":[149,195,220],"than":[151],"fMRI":[153],"data.":[154,196],"prediction":[156,172],"accuracy":[157],"peaked":[158],"alpha":[161],"band,":[162,167],"highest":[165],"frequency":[166],"gamma":[168],"lowest":[171],"accuracy.":[173],"To":[174],"best":[176],"our":[178],"knowledge,":[179],"this":[180],"first":[183],"end-to-end":[185],"kernel":[189],"framework":[192],"modeling":[194],"One":[197],"important":[200],"features":[201,212],"its":[206],"ability":[207],"incorporate":[209],"connectivity":[211],"into":[213],"generative":[215],"predicts":[218],"connectivity.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
