An iterative jackknife approach for assessing reliability and power of FMRI group analyses.

For functional magnetic resonance imaging (fMRI) group activation maps, so-called second-level random effect approaches are commonly used, which are intended to be generalizable to the population as a whole. However, reliability of a certain activation focus as a function of group composition or gro...

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Main Author: Marko Wilke
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3328456?pdf=render
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spelling doaj-7b1510eaf30b49199e5f6d9e47cebcfa2020-11-25T01:12:16ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0174e3557810.1371/journal.pone.0035578An iterative jackknife approach for assessing reliability and power of FMRI group analyses.Marko WilkeFor functional magnetic resonance imaging (fMRI) group activation maps, so-called second-level random effect approaches are commonly used, which are intended to be generalizable to the population as a whole. However, reliability of a certain activation focus as a function of group composition or group size cannot directly be deduced from such maps. This question is of particular relevance when examining smaller groups (<20-27 subjects). The approach presented here tries to address this issue by iteratively excluding each subject from a group study and presenting the overlap of the resulting (reduced) second-level maps in a group percent overlap map. This allows to judge where activation is reliable even upon excluding one, two, or three (or more) subjects, thereby also demonstrating the inherent variability that is still present in second-level analyses. Moreover, when progressively decreasing group size, foci of activation will become smaller and/or disappear; hence, the group size at which a given activation disappears can be considered to reflect the power necessary to detect this particular activation. Systematically exploiting this effect allows to rank clusters according to their observable effect size. The approach is tested using different scenarios from a recent fMRI study (children performing a "dual-use" fMRI task, n = 39), and the implications of this approach are discussed.http://europepmc.org/articles/PMC3328456?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Marko Wilke
spellingShingle Marko Wilke
An iterative jackknife approach for assessing reliability and power of FMRI group analyses.
PLoS ONE
author_facet Marko Wilke
author_sort Marko Wilke
title An iterative jackknife approach for assessing reliability and power of FMRI group analyses.
title_short An iterative jackknife approach for assessing reliability and power of FMRI group analyses.
title_full An iterative jackknife approach for assessing reliability and power of FMRI group analyses.
title_fullStr An iterative jackknife approach for assessing reliability and power of FMRI group analyses.
title_full_unstemmed An iterative jackknife approach for assessing reliability and power of FMRI group analyses.
title_sort iterative jackknife approach for assessing reliability and power of fmri group analyses.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2012-01-01
description For functional magnetic resonance imaging (fMRI) group activation maps, so-called second-level random effect approaches are commonly used, which are intended to be generalizable to the population as a whole. However, reliability of a certain activation focus as a function of group composition or group size cannot directly be deduced from such maps. This question is of particular relevance when examining smaller groups (<20-27 subjects). The approach presented here tries to address this issue by iteratively excluding each subject from a group study and presenting the overlap of the resulting (reduced) second-level maps in a group percent overlap map. This allows to judge where activation is reliable even upon excluding one, two, or three (or more) subjects, thereby also demonstrating the inherent variability that is still present in second-level analyses. Moreover, when progressively decreasing group size, foci of activation will become smaller and/or disappear; hence, the group size at which a given activation disappears can be considered to reflect the power necessary to detect this particular activation. Systematically exploiting this effect allows to rank clusters according to their observable effect size. The approach is tested using different scenarios from a recent fMRI study (children performing a "dual-use" fMRI task, n = 39), and the implications of this approach are discussed.
url http://europepmc.org/articles/PMC3328456?pdf=render
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