{"id":"https://openalex.org/W2581716267","doi":"https://doi.org/10.1109/biocas.2016.7833776","title":"Multi-scale analysis of the dynamics of brain functional connectivity using EEG","display_name":"Multi-scale analysis of the dynamics of brain functional connectivity using EEG","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2581716267","doi":"https://doi.org/10.1109/biocas.2016.7833776","mag":"2581716267"},"language":"en","primary_location":{"id":"doi:10.1109/biocas.2016.7833776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas.2016.7833776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Biomedical Circuits and Systems Conference (BioCAS)","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/A5054608297","display_name":"Ali Haddad","orcid":"https://orcid.org/0000-0002-4579-4559"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Haddad","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rutgers University, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rutgers University, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029389730","display_name":"Laleh Najafizadeh","orcid":"https://orcid.org/0000-0002-6658-4112"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Laleh Najafizadeh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rutgers University, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rutgers University, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102322142"],"apc_list":null,"apc_paid":null,"fwci":1.7857,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84917617,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"2016","issue":null,"first_page":"240","last_page":"243"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9994999766349792,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9994999766349792,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9983999729156494,"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/T11434","display_name":"Electrochemical Analysis and Applications","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1603","display_name":"Electrochemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6271559000015259},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6019861698150635},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5874763131141663},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5497470498085022},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.47093334794044495},{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.44854918122291565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44123610854148865},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.43794769048690796},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4110494554042816},{"id":"https://openalex.org/keywords/biological-system","display_name":"Biological system","score":0.3396727442741394},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.324265718460083},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1414923369884491},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.11534136533737183},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.11497294902801514}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6271559000015259},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6019861698150635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5874763131141663},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5497470498085022},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.47093334794044495},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.44854918122291565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44123610854148865},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.43794769048690796},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4110494554042816},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.3396727442741394},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.324265718460083},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1414923369884491},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.11534136533737183},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.11497294902801514},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/biocas.2016.7833776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/biocas.2016.7833776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Biomedical Circuits and Systems Conference (BioCAS)","raw_type":"proceedings-article"},{"id":"mag:2751677660","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/20090422/201702245006264291","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1994341528","https://openalex.org/W2016474464","https://openalex.org/W2043087183","https://openalex.org/W2048667491","https://openalex.org/W2064165550","https://openalex.org/W2065588278","https://openalex.org/W2101865311","https://openalex.org/W2117988264","https://openalex.org/W2130031954","https://openalex.org/W2130863149","https://openalex.org/W2143570911","https://openalex.org/W2148791497","https://openalex.org/W2169294617","https://openalex.org/W2293551727","https://openalex.org/W2336652848","https://openalex.org/W6697266645","https://openalex.org/W6703065632"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W2922348724","https://openalex.org/W1861706286","https://openalex.org/W200322357","https://openalex.org/W2130428257","https://openalex.org/W2219338811","https://openalex.org/W4308951944","https://openalex.org/W2167092671","https://openalex.org/W2149583853"],"abstract_inverted_index":{"This":[0,85],"paper":[1],"presents":[2],"a":[3,189],"new":[4],"approach":[5],"to":[6,30,42,47,82,136,180],"investigate":[7],"the":[8,18,32,57,67,71,90,115,137,143,148,152,182],"dynamics":[9],"of":[10,70,74,96,122,142,154,162,185],"functional":[11,186],"connectivity":[12,187],"at":[13,193],"multiple":[14,160],"temporal":[15,134,183],"scales":[16,194],"from":[17],"recordings":[19],"obtained":[20],"through":[21,88,131],"electroencephalography":[22],"(EEG).":[23],"Discrete":[24],"wavelet":[25],"transform":[26],"(DWT)":[27],"is":[28,80,86,118,177],"utilized":[29],"decompose":[31],"recorded":[33],"signals":[34,40],"into":[35,63],"several":[36],"frequency":[37,44],"bands,":[38],"and":[39,76,172,198,203],"corresponding":[41,144],"each":[43,97,112],"band":[45],"(referred":[46],"as":[48],"subband":[49,58,98],"components)":[50],"are":[51,60,129,201],"reconstructed.":[52],"Using":[53],"\"source-informed":[54],"segmentation\"":[55],"technique,":[56],"components":[59],"then":[61,178],"segmented":[62],"intervals":[64],"during":[65,147,188],"which":[66],"spatial":[68],"distribution":[69],"underlying":[72],"ensembles":[73,121,128,161],"active":[75],"functionally":[77,123,163],"connected":[78,124,164],"neurons":[79],"expected":[81],"stay":[83],"quasi-stationary.":[84],"achieved":[87],"monitoring":[89],"running":[91],"dominant":[92,138,156],"left":[93],"singular":[94,140,158],"subspace":[95],"component":[99],"matrix":[100,117],"for":[101,111,120],"statistically":[102],"significant":[103],"shifts":[104],"in":[105],"its":[106],"span":[107],"over":[108],"time.":[109],"Finally,":[110],"identified":[113],"segment,":[114],"source":[116,145],"analyzed":[119],"cortical":[125,165],"points.":[126],"These":[127],"localized":[130,169],"correlating":[132],"their":[133],"activity":[135],"right":[139,157],"vectors":[141],"matrix,":[146],"segment.":[149],"Depending":[150],"on":[151],"number":[153],"extracted":[155],"vectors,":[159],"points":[166],"can":[167],"be":[168],"per":[170],"segment":[171],"subband.":[173],"The":[174],"proposed":[175],"method":[176],"used":[179],"explore":[181],"evolution":[184],"visual":[190],"oddball":[191],"task,":[192],"spanning":[195],"\u03b4-,":[196],"\u03b8-,":[197],"\u03b1-bands.":[199],"Results":[200],"presented":[202],"discussed.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}