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Pooling fMRI Data: Meta-Analysis, Mega-Analysis and Multi-Center Studies
The quantitative analysis of pooled data from related functional magnetic resonance imaging (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 (t...
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Formato: | Texto |
Lenguaje: | English |
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Frontiers Research Foundation
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759345/ https://www.ncbi.nlm.nih.gov/pubmed/19826498 http://dx.doi.org/10.3389/neuro.11.033.2009 |
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author | Costafreda, Sergi G. |
author_facet | Costafreda, Sergi G. |
author_sort | Costafreda, Sergi G. |
collection | PubMed |
description | The quantitative analysis of pooled data from related functional magnetic resonance imaging (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. |
format | Text |
id | pubmed-2759345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Frontiers Research Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-27593452009-10-13 Pooling fMRI Data: Meta-Analysis, Mega-Analysis and Multi-Center Studies Costafreda, Sergi G. Front Neuroinformatics Neuroscience The quantitative analysis of pooled data from related functional magnetic resonance imaging (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. Frontiers Research Foundation 2009-09-30 /pmc/articles/PMC2759345/ /pubmed/19826498 http://dx.doi.org/10.3389/neuro.11.033.2009 Text en Copyright © 2009 Costafreda. http://www.frontiersin.org/licenseagreement This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited. |
spellingShingle | Neuroscience Costafreda, Sergi G. Pooling fMRI Data: Meta-Analysis, Mega-Analysis and Multi-Center Studies |
title | 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_short | Pooling fMRI Data: Meta-Analysis, Mega-Analysis and Multi-Center Studies |
title_sort | pooling fmri data: meta-analysis, mega-analysis and multi-center studies |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759345/ https://www.ncbi.nlm.nih.gov/pubmed/19826498 http://dx.doi.org/10.3389/neuro.11.033.2009 |
work_keys_str_mv | AT costafredasergig poolingfmridatametaanalysismegaanalysisandmulticenterstudies |