On the validity of fMRI mega-analyses using data processed with different pipelines.

ABSTRACT: In neuroimaging and functional magnetic resonance imaging (fMRI), many derived data are made openly available in public databases. These can be re-used to increase sample sizes in studies and thus, improve robustness. In fMRI studies, raw data are first preprocessed using a given analysis pipeline to obtain subject-level contrast maps, which are then combined into a group analysis. Typically, the subject-level analysis pipeline is identical for all participants. However, derived data shared on public databases often come from different workflows, which can lead to different results. Here, we investigate how this analytical variability, if not accounted for, can induce false positive detections in mega-analyses combining subject-level contrast maps processed with different pipelines. We use

SUBMITTER: Germani E 

PROVIDER: S-EPMC12319730 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature