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dc.contributor.authorWILSON, SIMON PAUL
dc.date.accessioned2013-09-04T10:19:41Z
dc.date.available2013-09-04T10:19:41Z
dc.date.issued2010
dc.date.submitted2010en
dc.identifier.citationAlicia Quiros Carretero, Raquel Montes Diez and Simon P. Wilson, Bayesian spatiotemporal model of fMRI data using transfer functions, Neuroimage, 52, 3, 2010, 995-1004en
dc.identifier.otherY
dc.identifier.urihttp://hdl.handle.net/2262/67366
dc.descriptionPUBLISHEDen
dc.description.abstractThis research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. In the spatial dimension, we use a Gaussian Markov random field prior on the parameter indicating activations that embody our prior knowledge that evoked responses are spatially contiguous. The proposal constitutes an extension of the spatiotemporal model presented in a previous approach [Quir'os, A., Montes Diez, R. and Gamerman, D. (2010). Bayesian spatiotemporal model of fMRI data, Neuroimage, 49: 442-456.], o?ering more flexibility in the estimation of the HRF and computational advantages in the resulting MCMC algorithm. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters, as well as to check the model sensitivity to signal to noise ratio. Results are shown on synthetic data and on a real data set from a block-design fMRI experiment, showing good performance in the detection of activity and significant flexibility in the estimation of theen
dc.description.sponsorshipThis work was partially supported by grants from MEC (MTM2006- 14961-C05-05, TEC2006-13966-C03-01 and TSI2007-66706-C04-01) and URJC and CAM (URJC-CM-2006-CET-0371).en
dc.format.extent995-1004en
dc.language.isoenen
dc.relation.ispartofseriesNeuroimage;
dc.relation.ispartofseries52;
dc.relation.ispartofseries3;
dc.rightsYen
dc.subject.otherStatistics
dc.titleBayesian spatiotemporal model of fMRI data using transfer functionsen
dc.typeJournal Articleen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/swilson
dc.identifier.rssinternalid63354
dc.rights.ecaccessrightsOpenAccess


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