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...
Main Author: | |
---|---|
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 |
id |
doaj-2b27e05d06ba459f95e29eec8c21342a |
---|---|
record_format |
Article |
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 |
_version_ |
1725844665261883392 |