{"id":"https://openalex.org/W2437438233","doi":"https://doi.org/10.1109/isbi.2016.7493433","title":"Multivariate hurst exponent estimation in FMRI. Application to brain decoding of perceptual learning","display_name":"Multivariate hurst exponent estimation in FMRI. Application to brain decoding of perceptual learning","publication_year":2016,"publication_date":"2016-04-01","ids":{"openalex":"https://openalex.org/W2437438233","doi":"https://doi.org/10.1109/isbi.2016.7493433","mag":"2437438233"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2016.7493433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2016.7493433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","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/A5062550541","display_name":"H. Pelle","orcid":null},"institutions":[{"id":"https://openalex.org/I2738703131","display_name":"Commissariat \u00e0 l'\u00c9nergie Atomique et aux \u00c9nergies Alternatives","ror":"https://ror.org/00jjx8s55","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2738703131"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210128565","display_name":"CEA Paris-Saclay","ror":"https://ror.org/03n15ch10","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210128565"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"H. Pelle","raw_affiliation_strings":["CEA DSV/I2BM, NeuroSpin Center, Universit\u00e9 Paris-Saclay, F-91191 Gif-sur-Yvette, France"],"affiliations":[{"raw_affiliation_string":"CEA DSV/I2BM, NeuroSpin Center, Universit\u00e9 Paris-Saclay, F-91191 Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I2738703131","https://openalex.org/I4210128565"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011405123","display_name":"Ph. Ciuciu","orcid":null},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I2738703131","display_name":"Commissariat \u00e0 l'\u00c9nergie Atomique et aux \u00c9nergies Alternatives","ror":"https://ror.org/00jjx8s55","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2738703131"]},{"id":"https://openalex.org/I4210128565","display_name":"CEA Paris-Saclay","ror":"https://ror.org/03n15ch10","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210128565"]},{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I4210126360","display_name":"Inria Saclay - \u00cele de France","ror":"https://ror.org/0315e5x55","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210126360"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ph. Ciuciu","raw_affiliation_strings":["CEA DSV/IBM NeuroSpin Center, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France","INRIA, Parietal team, Universit\u00e9 Paris-Saclay, France"],"affiliations":[{"raw_affiliation_string":"CEA DSV/IBM NeuroSpin Center, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I2738703131","https://openalex.org/I4210128565"]},{"raw_affiliation_string":"INRIA, Parietal team, Universit\u00e9 Paris-Saclay, France","institution_ids":["https://openalex.org/I4210126360","https://openalex.org/I1326498283","https://openalex.org/I277688954"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039387200","display_name":"M. Rahim","orcid":"https://orcid.org/0000-0002-6395-8115"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I2738703131","display_name":"Commissariat \u00e0 l'\u00c9nergie Atomique et aux \u00c9nergies Alternatives","ror":"https://ror.org/00jjx8s55","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2738703131"]},{"id":"https://openalex.org/I4210128565","display_name":"CEA Paris-Saclay","ror":"https://ror.org/03n15ch10","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210128565"]},{"id":"https://openalex.org/I4210126360","display_name":"Inria Saclay - \u00cele de France","ror":"https://ror.org/0315e5x55","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210126360"]},{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en informatique et en automatique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"M. Rahim","raw_affiliation_strings":["CEA DSV/IBM NeuroSpin Center, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France","INRIA, Parietal team, Universit\u00e9 Paris-Saclay, France"],"affiliations":[{"raw_affiliation_string":"CEA DSV/IBM NeuroSpin Center, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I2738703131","https://openalex.org/I4210128565"]},{"raw_affiliation_string":"INRIA, Parietal team, Universit\u00e9 Paris-Saclay, France","institution_ids":["https://openalex.org/I4210126360","https://openalex.org/I1326498283","https://openalex.org/I277688954"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040199022","display_name":"Elvis Dohmatob","orcid":null},"institutions":[{"id":"https://openalex.org/I2738703131","display_name":"Commissariat \u00e0 l'\u00c9nergie Atomique et aux \u00c9nergies Alternatives","ror":"https://ror.org/00jjx8s55","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2738703131"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210128565","display_name":"CEA Paris-Saclay","ror":"https://ror.org/03n15ch10","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210128565"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"E. Dohmatob","raw_affiliation_strings":["CEA DSV/I2BM, NeuroSpin Center, Universit\u00e9 Paris-Saclay, F-91191 Gif-sur-Yvette, France"],"affiliations":[{"raw_affiliation_string":"CEA DSV/I2BM, NeuroSpin Center, Universit\u00e9 Paris-Saclay, F-91191 Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I2738703131","https://openalex.org/I4210128565"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050643672","display_name":"Patrice Abry","orcid":"https://orcid.org/0000-0002-7096-8290"},"institutions":[{"id":"https://openalex.org/I113428412","display_name":"\u00c9cole Normale Sup\u00e9rieure de Lyon","ror":"https://ror.org/04zmssz18","country_code":"FR","type":"education","lineage":["https://openalex.org/I113428412","https://openalex.org/I203339264"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"P. Abry","raw_affiliation_strings":["Ecole normale superieure de Lyon, Lyon, Rh\u00c3\u00b4ne-Alpes, FR","Ecole normale superieure de Lyon, Lyon, Rh\u00f4ne-Alpes, FR"],"affiliations":[{"raw_affiliation_string":"Ecole normale superieure de Lyon, Lyon, Rh\u00c3\u00b4ne-Alpes, FR","institution_ids":["https://openalex.org/I113428412"]},{"raw_affiliation_string":"Ecole normale superieure de Lyon, Lyon, Rh\u00f4ne-Alpes, FR","institution_ids":["https://openalex.org/I113428412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063401681","display_name":"Virginie van Wassenhove","orcid":"https://orcid.org/0000-0002-2569-5502"},"institutions":[{"id":"https://openalex.org/I4210128565","display_name":"CEA Paris-Saclay","ror":"https://ror.org/03n15ch10","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210128565"]},{"id":"https://openalex.org/I2738703131","display_name":"Commissariat \u00e0 l'\u00c9nergie Atomique et aux \u00c9nergies Alternatives","ror":"https://ror.org/00jjx8s55","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2738703131"]},{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"V van Wassenhove","raw_affiliation_strings":["CEA DSV/I2BM, NeuroSpin Center, Universit\u00e9 Paris-Saclay, F-91191 Gif-sur-Yvette, France"],"affiliations":[{"raw_affiliation_string":"CEA DSV/I2BM, NeuroSpin Center, Universit\u00e9 Paris-Saclay, F-91191 Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I2738703131","https://openalex.org/I4210128565"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5062550541"],"corresponding_institution_ids":["https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210128565"],"apc_list":null,"apc_paid":null,"fwci":0.4875,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.65236873,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"21","issue":null,"first_page":"996","last_page":"1000"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9968000054359436,"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":0.9968000054359436,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9950000047683716,"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/T12946","display_name":"Fractal and DNA sequence analysis","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hurst-exponent","display_name":"Hurst exponent","score":0.7912122011184692},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.7117252349853516},{"id":"https://openalex.org/keywords/resting-state-fmri","display_name":"Resting state fMRI","score":0.5996582508087158},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5891827344894409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5712635517120361},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5588687658309937},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.5143023729324341},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4988691806793213},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4526037573814392},{"id":"https://openalex.org/keywords/neurofeedback","display_name":"Neurofeedback","score":0.42577776312828064},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4189620018005371},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.39613819122314453},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.34994959831237793},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3077471852302551},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28080934286117554},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.261433482170105},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.165185809135437}],"concepts":[{"id":"https://openalex.org/C96835011","wikidata":"https://www.wikidata.org/wiki/Q1638718","display_name":"Hurst exponent","level":2,"score":0.7912122011184692},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.7117252349853516},{"id":"https://openalex.org/C66324658","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Resting state fMRI","level":2,"score":0.5996582508087158},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5891827344894409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5712635517120361},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5588687658309937},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.5143023729324341},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4988691806793213},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4526037573814392},{"id":"https://openalex.org/C2434490","wikidata":"https://www.wikidata.org/wiki/Q1306920","display_name":"Neurofeedback","level":3,"score":0.42577776312828064},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4189620018005371},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.39613819122314453},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.34994959831237793},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3077471852302551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28080934286117554},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.261433482170105},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.165185809135437}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2016.7493433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2016.7493433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.44999998807907104,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1965601051","https://openalex.org/W1989728430","https://openalex.org/W2004240500","https://openalex.org/W2021053759","https://openalex.org/W2022894179","https://openalex.org/W2058642012","https://openalex.org/W2063804532","https://openalex.org/W2075130585","https://openalex.org/W2082442136","https://openalex.org/W2101234009","https://openalex.org/W2106873519","https://openalex.org/W2109488753","https://openalex.org/W2128144507","https://openalex.org/W2139852582","https://openalex.org/W2148791497","https://openalex.org/W2150928879","https://openalex.org/W2164214015","https://openalex.org/W2166500681","https://openalex.org/W2183239258","https://openalex.org/W3021380660","https://openalex.org/W6675354045","https://openalex.org/W6686351652"],"related_works":["https://openalex.org/W2601707947","https://openalex.org/W2991396235","https://openalex.org/W2168298321","https://openalex.org/W2387620927","https://openalex.org/W2294986132","https://openalex.org/W2365936003","https://openalex.org/W2790620361","https://openalex.org/W1964455563","https://openalex.org/W2319066238","https://openalex.org/W2371524820"],"abstract_inverted_index":{"So":[0],"far":[1],"considered":[2],"as":[3,180],"noise":[4],"in":[5,21,38,85,111,141],"neuroscience,":[6],"irregular":[7],"arrhythmic":[8],"field":[9],"potential":[10],"activity":[11,28],"accounts":[12],"for":[13,106],"the":[14,17,39,59,89,107,130,133,173,177],"majority":[15],"of":[16,41,48,92,132,144,175],"signal":[18],"power":[19,31],"recorded":[20,140],"EEG":[22],"or":[23,74],"MEG":[24,158],"[1,2].":[25],"This":[26],"brain":[27],"follows":[29],"a":[30,46,121,152,157,162],"law":[32],"spectrum":[33],"P":[34],"(f)":[35],"\u223c":[36],"1/f\u03b2":[37],"limit":[40],"low":[42],"frequencies,":[43],"which":[44],"is":[45],"hallmark":[47],"scale":[49],"invariance.":[50],"Recently,":[51],"several":[52],"studies":[53],"[1,":[54],"3-6]":[55],"have":[56],"shown":[57],"that":[58],"slope":[60],"\u03b2":[61],"(or":[62],"equivalently":[63],"Hurst":[64,117],"exponent":[65,118],"H)":[66],"tends":[67],"to":[68,104,120,151,170,182],"be":[69],"modulated":[70],"by":[71],"task":[72,155],"performance":[73],"cognitive":[75],"state":[76],"(eg,":[77],"sleep":[78],"vs":[79],"awake).":[80],"These":[81],"observations":[82],"were":[83,148],"confirmed":[84],"fMRI":[86,93,138],"[7-9]":[87],"although":[88],"short":[90],"length":[91],"time":[94],"series":[95],"makes":[96],"these":[97],"findings":[98],"less":[99],"reliable.":[100],"In":[101,161],"this":[102],"paper,":[103],"compensate":[105],"slower":[108],"sampling":[109],"rate":[110],"fMRI,":[112],"we":[113,128],"extend":[114],"univariate":[115,184],"wavelet-based":[116],"estimator":[119],"multivariate":[122,167],"setting":[123],"using":[124],"spatial":[125],"regularization.":[126],"Next,":[127],"demonstrate":[129],"relevance":[131],"proposed":[134],"tools":[135],"on":[136],"resting-state":[137],"data":[139],"three":[142],"groups":[143],"individuals":[145],"once":[146],"they":[147],"specifically":[149],"trained":[150],"visual":[153],"discrimination":[154],"during":[156],"experiment":[159],"[10].":[160],"supervised":[163],"classification":[164],"framework,":[165],"our":[166],"approach":[168],"permits":[169],"better":[171],"predict":[172],"type":[174],"training":[176],"participants":[178],"received":[179],"compared":[181],"their":[183],"counterpart.":[185]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
