{"id":"https://openalex.org/W1588471727","doi":"https://doi.org/10.1109/isbi.2004.1398674","title":"Semi-blind deconvolution of neural impulse response in event-related fMRI using a gibbs sampler","display_name":"Semi-blind deconvolution of neural impulse response in event-related fMRI using a gibbs sampler","publication_year":2005,"publication_date":"2005-04-12","ids":{"openalex":"https://openalex.org/W1588471727","doi":"https://doi.org/10.1109/isbi.2004.1398674","mag":"1588471727"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2004.1398674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","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/A5000008272","display_name":"Salima Makni","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106966","display_name":"Centre Hospitalier d'Orsay","ror":"https://ror.org/01bchmt70","country_code":"FR","type":"healthcare","lineage":["https://openalex.org/I4210106966"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"S. Makni","raw_affiliation_strings":["Service Hospitalier Fr\u00e9d\u00e9ric Joliot, Orsay, France"],"affiliations":[{"raw_affiliation_string":"Service Hospitalier Fr\u00e9d\u00e9ric Joliot, Orsay, France","institution_ids":["https://openalex.org/I4210106966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019588779","display_name":"Philippe Ciuciu","orcid":"https://orcid.org/0000-0001-5374-962X"},"institutions":[{"id":"https://openalex.org/I4210106966","display_name":"Centre Hospitalier d'Orsay","ror":"https://ror.org/01bchmt70","country_code":"FR","type":"healthcare","lineage":["https://openalex.org/I4210106966"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"P. Ciuciu","raw_affiliation_strings":["Service Hospitalier Fr\u00e9d\u00e9ric Joliot, Orsay, France"],"affiliations":[{"raw_affiliation_string":"Service Hospitalier Fr\u00e9d\u00e9ric Joliot, Orsay, France","institution_ids":["https://openalex.org/I4210106966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062028668","display_name":"J\u00e9r\u00f4me Idier","orcid":"https://orcid.org/0000-0003-4087-0302"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"J. Idier","raw_affiliation_strings":["CNRS, IRCCyN, Nantes, France"],"affiliations":[{"raw_affiliation_string":"CNRS, IRCCyN, Nantes, France","institution_ids":["https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069918313","display_name":"Jean\u2010Baptiste Poline","orcid":"https://orcid.org/0000-0002-9794-749X"},"institutions":[{"id":"https://openalex.org/I4210106966","display_name":"Centre Hospitalier d'Orsay","ror":"https://ror.org/01bchmt70","country_code":"FR","type":"healthcare","lineage":["https://openalex.org/I4210106966"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"J.-B. Poline","raw_affiliation_strings":["Service Hospitalier Fr\u00e9d\u00e9ric Joliot, Orsay, France"],"affiliations":[{"raw_affiliation_string":"Service Hospitalier Fr\u00e9d\u00e9ric Joliot, Orsay, France","institution_ids":["https://openalex.org/I4210106966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000008272"],"corresponding_institution_ids":["https://openalex.org/I4210106966"],"apc_list":null,"apc_paid":null,"fwci":0.7362,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72293765,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"860","last_page":"863"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI 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"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI 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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9991000294685364,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/voxel","display_name":"Voxel","score":0.8188795447349548},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.7323296070098877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.67828369140625},{"id":"https://openalex.org/keywords/impulse-response","display_name":"Impulse response","score":0.6310591101646423},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.6237215995788574},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5966436266899109},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5829735994338989},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.5587937831878662},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5095546245574951},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4507552981376648},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4501582682132721},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.43755194544792175},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4239773452281952},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3550475835800171},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2710574269294739},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13790389895439148},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12204587459564209},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.12096676230430603},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.11192861199378967}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.8188795447349548},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.7323296070098877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.67828369140625},{"id":"https://openalex.org/C72279823","wikidata":"https://www.wikidata.org/wiki/Q1139726","display_name":"Impulse response","level":2,"score":0.6310591101646423},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.6237215995788574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5966436266899109},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5829735994338989},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.5587937831878662},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5095546245574951},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4507552981376648},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4501582682132721},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.43755194544792175},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4239773452281952},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3550475835800171},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2710574269294739},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13790389895439148},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12204587459564209},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.12096676230430603},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.11192861199378967},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2004.1398674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2004.1398674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821)","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":7,"referenced_works":["https://openalex.org/W1541214133","https://openalex.org/W1978641348","https://openalex.org/W2093366270","https://openalex.org/W2107187638","https://openalex.org/W2128080092","https://openalex.org/W2151590495","https://openalex.org/W6632151163"],"related_works":["https://openalex.org/W3090782779","https://openalex.org/W2053307699","https://openalex.org/W1998481501","https://openalex.org/W1570747078","https://openalex.org/W2222745574","https://openalex.org/W2058895457","https://openalex.org/W4313520541","https://openalex.org/W2085560699","https://openalex.org/W2115857766","https://openalex.org/W2586325539"],"abstract_inverted_index":{"Identification":[0],"of":[1,19,27,48,91,140],"the":[2,28,59,93,112,137,141],"hemodynamic":[3],"response":[4,95],"function":[5],"(HRF)":[6],"in":[7,58,69,129],"functional":[8],"magnetic":[9],"resonance":[10],"imaging":[11],"(fMRI)":[12],"is":[13],"essential":[14],"for":[15,66],"a":[16,23,70,75,99,106,130],"better":[17],"understanding":[18],"cerebral":[20],"activity.":[21],"In":[22,61],"given":[24,71,131],"region-of-interest":[25],"(ROI)":[26],"brain,":[29],"several":[30,80],"works":[31],"have":[32,37],"demonstrated":[33],"that":[34],"neighbor":[35],"voxels":[36],"close":[38],"shape":[39,78,139],"responses,":[40],"but":[41,79],"with":[42,133],"potentially":[43],"different":[44,56],"magnitude.":[45],"This":[46],"property":[47],"similarity":[49],"also":[50],"holds":[51],"between":[52],"HRFs":[53],"corresponding":[54],"to":[55,110],"stimuli":[57],"paradigm.":[60],"this":[62],"paper,":[63],"we":[64,104],"account":[65],"these":[67],"features":[68],"ROI":[72,132],"and":[73,85,121],"estimate":[74,111],"single":[76],"HRF":[77],"magnitude":[81],"coefficients":[82],"per":[83],"voxel":[84],"condition,":[86],"which":[87],"may":[88],"be":[89],"thought":[90],"representing":[92],"neural":[94],"level.":[96],"Identified":[97],"as":[98],"semiblind":[100],"deconvolution":[101],"inverse":[102],"problem,":[103],"use":[105],"Gibbs":[107],"sampling":[108],"approach":[109],"unknown":[113],"quantities.":[114],"Our":[115],"method,":[116],"validated":[117],"both":[118],"on":[119,136],"synthetic":[120],"real":[122],"fMRI":[123],"data":[124],"provides":[125],"spatial":[126],"activation":[127],"maps":[128],"no":[134],"assumptions":[135],"exact":[138],"HRF.":[142]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}