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Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI
by
Seurinck, Ruth
, Durnez, Joke
, Bandettini, Peter A.
, Gonzalez-Castillo, Javier
, Degryse, Jasper
, Moerkerke, Beatrijs
in
alternative distribution
/ Brain mapping
/ Brain research
/ effect size
/ fMRI
/ Functional magnetic resonance imaging
/ functional ROI
/ Hypotheses
/ Localization
/ localizer task
/ Neuroscience
/ NMR
/ Nuclear magnetic resonance
/ Researchers
2017
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Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI
by
Seurinck, Ruth
, Durnez, Joke
, Bandettini, Peter A.
, Gonzalez-Castillo, Javier
, Degryse, Jasper
, Moerkerke, Beatrijs
in
alternative distribution
/ Brain mapping
/ Brain research
/ effect size
/ fMRI
/ Functional magnetic resonance imaging
/ functional ROI
/ Hypotheses
/ Localization
/ localizer task
/ Neuroscience
/ NMR
/ Nuclear magnetic resonance
/ Researchers
2017
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Do you wish to request the book?
Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI
by
Seurinck, Ruth
, Durnez, Joke
, Bandettini, Peter A.
, Gonzalez-Castillo, Javier
, Degryse, Jasper
, Moerkerke, Beatrijs
in
alternative distribution
/ Brain mapping
/ Brain research
/ effect size
/ fMRI
/ Functional magnetic resonance imaging
/ functional ROI
/ Hypotheses
/ Localization
/ localizer task
/ Neuroscience
/ NMR
/ Nuclear magnetic resonance
/ Researchers
2017
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Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI
Journal Article
Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI
2017
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Overview
In fMRI research, one often aims to examine activation in specific functional regions of interest (fROIs). Current statistical methods tend to localize fROIs inconsistently, focusing on avoiding detection of false activation. Not missing true activation is however equally important in this context. In this study, we explored the potential of an alternative-based thresholding (ABT) procedure, where evidence against the null hypothesis of no effect and evidence against a prespecified alternative hypothesis is measured to control both false positives and false negatives directly. The procedure was validated in the context of localizer tasks on simulated brain images and using a real data set of 100 runs per subject. Voxels categorized as active with ABT can be confidently included in the definition of the fROI, while inactive voxels can be confidently excluded. Additionally, the ABT method complements classic null hypothesis significance testing with valuable information by making a distinction between voxels that show evidence against both the null and alternative and voxels for which the alternative hypothesis cannot be rejected despite lack of evidence against the null.
Publisher
Frontiers Research Foundation,Frontiers Media S.A
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