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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 |
Sumario: | 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. |
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