Assessing certainty of activation or inactivation in test–retest fMRI studies

dc.contributor.author Maitra, Ranjan
dc.contributor.department Statistics
dc.date 2018-02-17T18:39:27.000
dc.date.accessioned 2020-07-02T06:58:06Z
dc.date.available 2020-07-02T06:58:06Z
dc.date.copyright Thu Jan 01 00:00:00 UTC 2009
dc.date.issued 2009-08-01
dc.description.abstract <p><a href="http://topics.sciencedirect.com/topics/page/Functional_magnetic_resonance_imaging">Functional Magnetic Resonance Imaging</a> (<a href="http://topics.sciencedirect.com/topics/page/Functional_magnetic_resonance_imaging">fMRI</a>) is widely used to study activation in the human brain. In most cases, data are commonly used to construct activation maps corresponding to a given paradigm. Results can be very variable, hence quantifying certainty of identified activation and inactivation over studies is important. This paper provides a model-based approach to certainty estimation from data acquired over several replicates of the same experimental paradigm. Specifically, the <em>p</em>-values derived from the statistical analysis of the data are explicitly modeled as a mixture of their underlying distributions; thus, unlike the methodology currently in use, there is no subjective thresholding required in the estimation process. The parameters governing the mixture model are easily obtained by the principle of maximum likelihood. Further, the estimates can also be used to optimally identify voxel-specific activation regions along with their corresponding certainty measures. The methodology is applied to a study involving a motor paradigm performed on a single subject several times over a period of two months. Simulation experiments used to calibrate performance of the method are promising. The methodology is also seen to be robust in determining areas of activation and their corresponding certainties.</p>
dc.description.comments <p>NOTICE: this is the author's version of a work that was accepted for publication in NeuroImage. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this documents. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in NeuroImage, [v.47,iss.1,(2009)] doi: 10.1016/j.neuroimage.2009.03.073.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/81/
dc.identifier.articleid 1079
dc.identifier.contextkey 8831946
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/81
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90683
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/81/2009_MaitraR_AssessingCertaintyActivation.pdf|||Sat Jan 15 02:06:24 UTC 2022
dc.source.uri 10.1016/j.neuroimage.2009.03.073
dc.subject.disciplines Radiology
dc.subject.disciplines Statistics and Probability
dc.subject.keywords fMRI
dc.subject.keywords quantification
dc.subject.keywords intra-class correlation coefficient
dc.subject.keywords maximum likelihood estimation
dc.subject.keywords mixture distribution
dc.subject.keywords motor task
dc.subject.keywords percent overlap
dc.subject.keywords true activation certainty
dc.subject.keywords true inactivation certainty
dc.title Assessing certainty of activation or inactivation in test–retest fMRI studies
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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