Independent Component versus Local Sparse Component Analysis in Resting State fMRI

Página do item simplificado
dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorVIEIRA, Gilson
dc.contributor.authorAMARO, Edson
dc.contributor.authorSATO, Joao R.
dc.contributor.authorBACCALA, Luiz A.
dc.date.accessioned2017-03-09T18:12:29Z
dc.date.available2017-03-09T18:12:29Z
dc.date.issued2015
dc.description.abstractIndependent Component Analysis (ICA) algorithms are potentially powerful ways of localizing sources of cerebral activity in resting state functional Magnetic Resonance Imaging (fMRI). But the assumptions underling the nature of identified sources limits this tool. By creating local one-dimensional approximations, Local Sparse Component Analysis (LSCA) can separate contiguous sources on the basis of their sparse representation into smoothness spaces via the 3D wavelet transformation. In this paper we systematically compare Probabilistic ICA (PICA) and LSCA for analyzing resting state fMRI across healthy participants. We show that the PICA sources usually representing biologically plausible components can in fact be decomposed into several LSCA sources that are not necessarily independent from each other. In addition, we show that LSCA identifies sources that approximate much better the local variations of the blood oxygenation level-dependent (BOLD) signal than PICA sources.
dc.description.conferencedateAUG 25-29, 2015
dc.description.conferencelocalMilan, ITALY
dc.description.conferencename37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.description.indexMEDLINE
dc.identifier.citation2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), p.1817-1820, 2015
dc.identifier.isbn978-1-4244-9270-1
dc.identifier.issn1557-170X
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/18443
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartof2015 37th Annual International Conference of the Ieee Engineering in Medicine and Biology Society (embc)
dc.relation.ispartofseriesIEEE Engineering in Medicine and Biology Society Conference Proceedings
dc.rightsrestrictedAccess
dc.rights.holderCopyright IEEE
dc.subject.otherbrain-function
dc.subject.wosEngineering, Biomedical
dc.subject.wosEngineering, Electrical & Electronic
dc.titleIndependent Component versus Local Sparse Component Analysis in Resting State fMRI
dc.typeconferenceObject
dc.type.categoryproceedings paper
dc.type.versionpublishedVersion
dspace.entity.typePublication
hcfmusp.author.externalVIEIRA, Gilson:Univ Sao Paulo, Interinst Grad Program Bioinformat, Sao Paulo, Brazil
hcfmusp.author.externalSATO, Joao R.:Univ Fed ABC, Ctr Math Computat & Cognit, Santo Andre, Brazil
hcfmusp.author.externalBACCALA, Luiz A.:Univ Sao Paulo, Interinst Grad Program Bioinformat, Sao Paulo, Brazil
hcfmusp.contributor.author-fmusphcEDSON AMARO JUNIOR
hcfmusp.description.beginpage1817
hcfmusp.description.endpage1820
hcfmusp.origemWOS
hcfmusp.origem.wosWOS:000371717202027
hcfmusp.publisher.cityNEW YORK
hcfmusp.publisher.countryUSA
hcfmusp.relation.referenceBeckmann CF, 2004, IEEE T MED IMAGING, V23, P137, DOI 10.1109/TMI.2003.822821
hcfmusp.relation.referenceBiswal BB, 2010, P NATL ACAD SCI USA, V107, P4734, DOI 10.1073/pnas.0911855107
hcfmusp.relation.referenceCalhoun VD, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0073309
hcfmusp.relation.referenceDamoiseaux JS, 2006, P NATL ACAD SCI USA, V103, P13848, DOI 10.1073/pnas.0601417103
hcfmusp.relation.referenceDaubechies I, 2009, P NATL ACAD SCI USA, V106, P10415, DOI 10.1073/pnas.0903525106
hcfmusp.relation.referenceFaro Scott H, 2006, FUNCTIONAL MRI BASIC
hcfmusp.relation.referenceGeorgiev Pando, 2007, SPRINGER OPTIMIZATIO, P91
hcfmusp.relation.referenceRaichle ME, 2001, P NATL ACAD SCI USA, V98, P676, DOI 10.1073/pnas.98.2.676
hcfmusp.relation.referenceSmith SM, 2012, NEUROIMAGE, V62, P1257, DOI 10.1016/j.neuroimage.2012.01.022
hcfmusp.relation.referenceVieira Gilson, 2015, BRAIN INFORM FEB
hcfmusp.relation.reference[Anonymous], 2014, LOCAL SPARSE COMPONE
hcfmusp.relation.referenceZibulevsky M, 2001, NEURAL COMPUT, V13, P863, DOI 10.1162/089976601300014385
relation.isAuthorOfPublicationd75a3ac2-5bdd-4774-ad4d-ea749b1fb4d3
relation.isAuthorOfPublication.latestForDiscoveryd75a3ac2-5bdd-4774-ad4d-ea749b1fb4d3
Arquivos
Pacote Original
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
art_VIEIRA_Independent_Component_versus_Local_Sparse_Component_Analysis_in_2015.PDF
Tamanho:
2.72 MB
Formato:
Adobe Portable Document Format
Descrição:
publishedVersion (English)
Baixar
Coleções
Comunicações em Eventos - FM/MDR
Comunicações em Eventos - HC/InRad
Comunicações em Eventos - LIM/44