{"id":"https://openalex.org/W2039849644","doi":"https://doi.org/10.1109/icassp.2010.5494915","title":"An entropy based method for activation detection of functional MRI data using Independent Component Analysis","display_name":"An entropy based method for activation detection of functional MRI data using Independent Component Analysis","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2039849644","doi":"https://doi.org/10.1109/icassp.2010.5494915","mag":"2039849644"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2010.5494915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5494915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5103200182","display_name":"Mahsa Akhbari","orcid":"https://orcid.org/0000-0002-0623-4751"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Mahsa Akhbari","raw_affiliation_strings":["Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran","Department of Electrical Engineering, Sharif university of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]},{"raw_affiliation_string":"Department of Electrical Engineering, Sharif university of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083199991","display_name":"Massoud Babaie\u2010Zadeh","orcid":"https://orcid.org/0000-0001-8864-4756"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Massoud Babaie-Zadeh","raw_affiliation_strings":["Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran","Department of Electrical Engineering, Sharif university of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]},{"raw_affiliation_string":"Department of Electrical Engineering, Sharif university of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060762919","display_name":"Emad Fatemizadeh","orcid":"https://orcid.org/0000-0001-5017-7136"},"institutions":[{"id":"https://openalex.org/I133529467","display_name":"Sharif University of Technology","ror":"https://ror.org/024c2fq17","country_code":"IR","type":"education","lineage":["https://openalex.org/I133529467"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Emad Fatemizadeh","raw_affiliation_strings":["Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran","Department of Electrical Engineering, Sharif university of Technology, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]},{"raw_affiliation_string":"Department of Electrical Engineering, Sharif university of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I133529467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055562421","display_name":"Christian Jutten","orcid":"https://orcid.org/0000-0002-4477-4847"},"institutions":[{"id":"https://openalex.org/I4210124956","display_name":"Grenoble Images Parole Signal Automatique","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I185839726","display_name":"Institut Universitaire de France","ror":"https://ror.org/055khg266","country_code":"FR","type":"education","lineage":["https://openalex.org/I185839726"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Christian Jutten","raw_affiliation_strings":["GIPSA-Lab, Institut Universitaire de France, Grenoble, France","GIPSA-LAB, Grenoble and Institut Universitaire de France, France"],"affiliations":[{"raw_affiliation_string":"GIPSA-Lab, Institut Universitaire de France, Grenoble, France","institution_ids":["https://openalex.org/I185839726","https://openalex.org/I4210124956"]},{"raw_affiliation_string":"GIPSA-LAB, Grenoble and Institut Universitaire de France, France","institution_ids":["https://openalex.org/I185839726"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103200182"],"corresponding_institution_ids":["https://openalex.org/I133529467"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.11690333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2014","last_page":"2017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9944000244140625,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.9067535400390625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7038622498512268},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.6974409222602844},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6595267653465271},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6501107215881348},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6231155395507812},{"id":"https://openalex.org/keywords/component-analysis","display_name":"Component analysis","score":0.4607999622821808},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3690599203109741},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.06502005457878113}],"concepts":[{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.9067535400390625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7038622498512268},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.6974409222602844},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6595267653465271},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6501107215881348},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6231155395507812},{"id":"https://openalex.org/C2780692498","wikidata":"https://www.wikidata.org/wiki/Q16950721","display_name":"Component analysis","level":2,"score":0.4607999622821808},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3690599203109741},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.06502005457878113},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2010.5494915","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5494915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","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":10,"referenced_works":["https://openalex.org/W1502702231","https://openalex.org/W2016444985","https://openalex.org/W2066053111","https://openalex.org/W2082207932","https://openalex.org/W2084056788","https://openalex.org/W2103402739","https://openalex.org/W2106219595","https://openalex.org/W2123499768","https://openalex.org/W2947000318","https://openalex.org/W6675835146"],"related_works":["https://openalex.org/W1791688437","https://openalex.org/W1971575144","https://openalex.org/W2369494890","https://openalex.org/W2139404519","https://openalex.org/W1513845058","https://openalex.org/W2123927273","https://openalex.org/W2121025724","https://openalex.org/W2393502243","https://openalex.org/W3112853371","https://openalex.org/W2370924545"],"abstract_inverted_index":{"Independent":[0],"Component":[1],"Analysis":[2],"(ICA)":[3],"can":[4],"be":[5,26,51],"used":[6],"to":[7,25,86,98],"decompose":[8],"functional":[9],"Magnetic":[10],"Resonance":[11],"Imaging":[12],"(fMRI)":[13],"data":[14],"into":[15],"a":[16,35,44,54,77],"set":[17,36],"of":[18,29,37,57,83,91,103],"statistically":[19],"independent":[20,38],"images":[21],"which":[22],"are":[23,40,59],"likely":[24],"the":[27,63,81,89,100,104],"sources":[28],"fMRI":[30],"data.":[31],"After":[32],"applying":[33],"ICA,":[34],"components":[39,49,58,64,90],"produced,":[41],"and":[42,68],"then,":[43],"\u201cmeaningful\u201d":[45],"subset":[46],"from":[47],"these":[48],"must":[50],"identified,":[52],"because":[53],"large":[55],"majority":[56],"non-interesting.":[60],"So,":[61],"interpreting":[62],"is":[65],"an":[66],"important":[67],"also":[69],"difficult":[70],"task.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75],"propose":[76],"criterion":[78],"based":[79],"on":[80],"entropy":[82],"time":[84],"courses":[85],"automatically":[87],"select":[88],"interest.":[92],"This":[93],"method":[94],"does":[95],"not":[96],"require":[97],"know":[99],"stimulus":[101],"pattern":[102],"experiment.":[105]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}