Confidence intervals for fMRI activation maps.

Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location. This data presentation, however, omits information critical for interpretation of experime...

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Main Authors: Stephen A Engel, Philip C Burton
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3846673?pdf=render
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spelling doaj-def9c71679694a68ba1216718fc49c502020-11-25T01:21:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01812e8241910.1371/journal.pone.0082419Confidence intervals for fMRI activation maps.Stephen A EngelPhilip C BurtonNeuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location. This data presentation, however, omits information critical for interpretation of experimental results. First, no information is represented about trends at voxels that do not pass the statistical test. Second, no information is given about the range of probable effect sizes at voxels that do pass the statistical test. This leads to a fundamental error in interpreting activation maps by naïve viewers, where it is assumed that colored, "active" voxels are reliably different from uncolored "inactive" voxels. In other domains, confidence intervals have been added to data graphics to reduce such errors. Here, we first document the prevalence of the fundamental error of interpretation, and then present a method for solving it by depicting confidence intervals in fMRI activation maps. Presenting images where the bounds of confidence intervals at each voxel are coded as color allows readers to visually test for differences between "active" and "inactive" voxels, and permits for more proper interpretation of neuroimaging data. Our specific graphical methods are intended as initial proposals to spur broader discussion of how to present confidence intervals for fMRI data.http://europepmc.org/articles/PMC3846673?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Stephen A Engel
Philip C Burton
spellingShingle Stephen A Engel
Philip C Burton
Confidence intervals for fMRI activation maps.
PLoS ONE
author_facet Stephen A Engel
Philip C Burton
author_sort Stephen A Engel
title Confidence intervals for fMRI activation maps.
title_short Confidence intervals for fMRI activation maps.
title_full Confidence intervals for fMRI activation maps.
title_fullStr Confidence intervals for fMRI activation maps.
title_full_unstemmed Confidence intervals for fMRI activation maps.
title_sort confidence intervals for fmri activation maps.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location. This data presentation, however, omits information critical for interpretation of experimental results. First, no information is represented about trends at voxels that do not pass the statistical test. Second, no information is given about the range of probable effect sizes at voxels that do pass the statistical test. This leads to a fundamental error in interpreting activation maps by naïve viewers, where it is assumed that colored, "active" voxels are reliably different from uncolored "inactive" voxels. In other domains, confidence intervals have been added to data graphics to reduce such errors. Here, we first document the prevalence of the fundamental error of interpretation, and then present a method for solving it by depicting confidence intervals in fMRI activation maps. Presenting images where the bounds of confidence intervals at each voxel are coded as color allows readers to visually test for differences between "active" and "inactive" voxels, and permits for more proper interpretation of neuroimaging data. Our specific graphical methods are intended as initial proposals to spur broader discussion of how to present confidence intervals for fMRI data.
url http://europepmc.org/articles/PMC3846673?pdf=render
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