Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies

The quantitative analysis of pooled data from related fMRI experiments has the potential to significantly accelerate progress in brain mapping. Such data-pooling can be achieved through meta-analysis (the pooled analysis of published results), mega-analysis (the pooled analysis of raw data) or multi...

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Main Author: Sergi G Costafreda
Format: Article
Language:English
Published: Frontiers Media S.A. 2009-09-01
Series:Frontiers in Neuroinformatics
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/neuro.11.033.2009/full
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spelling doaj-2b27e05d06ba459f95e29eec8c21342a2020-11-24T22:00:24ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962009-09-01310.3389/neuro.11.033.2009639Pooling fMRI data: meta-analysis, mega-analysis and multi-center studiesSergi G Costafreda0Biomedical Research Center Nucleus,Section of Neurobiology of Psychosis,Institute of Psychiatry, King's College LondonThe quantitative analysis of pooled data from related fMRI experiments has the potential to significantly accelerate progress in brain mapping. Such data-pooling can be achieved through meta-analysis (the pooled analysis of published results), mega-analysis (the pooled analysis of raw data) or multi-site studies which can be seen as designed mega-analyses. Current limitations in function-location brain mapping and how data-pooling can be used to remediate them are reviewed, with particular attention to power aggregation and mitigation of false positive results. Some recently developed analysis tools for meta- and mega-analysis are also presented, and recommendations for the conduct of valid fMRI data pooling are formulated.http://journal.frontiersin.org/Journal/10.3389/neuro.11.033.2009/fullfMRIMeta-analysispowerfalse positive resultsmega-analysismulti-center studies
collection DOAJ
language English
format Article
sources DOAJ
author Sergi G Costafreda
spellingShingle Sergi G Costafreda
Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies
Frontiers in Neuroinformatics
fMRI
Meta-analysis
power
false positive results
mega-analysis
multi-center studies
author_facet Sergi G Costafreda
author_sort Sergi G Costafreda
title Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies
title_short Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies
title_full Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies
title_fullStr Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies
title_full_unstemmed Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies
title_sort pooling fmri data: meta-analysis, mega-analysis and multi-center studies
publisher Frontiers Media S.A.
series Frontiers in Neuroinformatics
issn 1662-5196
publishDate 2009-09-01
description The quantitative analysis of pooled data from related fMRI experiments has the potential to significantly accelerate progress in brain mapping. Such data-pooling can be achieved through meta-analysis (the pooled analysis of published results), mega-analysis (the pooled analysis of raw data) or multi-site studies which can be seen as designed mega-analyses. Current limitations in function-location brain mapping and how data-pooling can be used to remediate them are reviewed, with particular attention to power aggregation and mitigation of false positive results. Some recently developed analysis tools for meta- and mega-analysis are also presented, and recommendations for the conduct of valid fMRI data pooling are formulated.
topic fMRI
Meta-analysis
power
false positive results
mega-analysis
multi-center studies
url http://journal.frontiersin.org/Journal/10.3389/neuro.11.033.2009/full
work_keys_str_mv AT sergigcostafreda poolingfmridatametaanalysismegaanalysisandmulticenterstudies
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