Show simple item record

dc.contributor.authorOu, Wanmei
dc.contributor.authorRaij, Tommi
dc.contributor.authorLin, Fa-Hsuan
dc.contributor.authorGolland, Polina
dc.contributor.authorHamalainen, Matti S.
dc.date.accessioned2014-05-16T16:36:37Z
dc.date.available2014-05-16T16:36:37Z
dc.date.issued2009
dc.identifier.isbn978-3-642-04267-6
dc.identifier.isbn978-3-642-04268-3
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttp://hdl.handle.net/1721.1/87029
dc.descriptionavailable in PMC 2013 June 30en_US
dc.description.abstractThe standard general linear model (GLM) for rapid event-related fMRI design protocols typically ignores reduction in hemodynamic responses in successive stimuli in a train due to incomplete recovery from the preceding stimuli. To capture this adaptation effect, we incorporate a region-specific adaptation model into GLM. The model quantifies the rate of adaptation across brain regions, which is of interest in neuroscience. Empirical evaluation of the proposed model demonstrates its potential to improve detection sensitivity. In the fMRI experiments using visual and auditory stimuli, we observed that the adaptation effect is significantly stronger in the visual area than in the auditory area, suggesting that we must account for this effect to avoid bias in fMRI detection.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH R01 NS048279)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH R01 EB006385)en_US
dc.description.sponsorshipNational Institute for Biomedical Imaging and Bioengineering (U.S.) (NIH NIBIB NAMIC U54-EB005149)en_US
dc.description.sponsorshipNational Center for Research Resources (U.S.) (NIH NCRR P41-RR14075)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (NSF CAREER Award 0642971)en_US
dc.description.sponsorshipSigrid Jusélius Foundationen_US
dc.description.sponsorshipAcademy of Finlanden_US
dc.description.sponsorshipFinnish Cultural Foundationen_US
dc.description.sponsorshipUnited States. Public Health Service (PHS training grant DA022759-03)en_US
dc.language.isoen_US
dc.publisherSpringer-Verlag Berlin Heidelbergen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/978-3-642-04268-3_124en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleModeling Adaptation Effects in fMRI Analysisen_US
dc.typeArticleen_US
dc.identifier.citationOu, Wanmei, Tommi Raij, Fa-Hsuan Lin, Polina Golland, and Matti Hamalainen. “Modeling Adaptation Effects in fMRI Analysis.” in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009, (Lecture Notes in Computer Science; Volume 5761) (2009): 1009–1017.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorOu, Wanmeien_US
dc.contributor.mitauthorGolland, Polinaen_US
dc.relation.journalMedical Image Computing and Computer-Assisted Intervention – MICCAI 2009en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsOu, Wanmei; Raij, Tommi; Lin, Fa-Hsuan; Golland, Polina; Hämäläinen, Mattien_US
dc.identifier.orcidhttps://orcid.org/0000-0003-2516-731X
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record