ArticleScientific data2025
HCP Multi-Pipeline: a derived dataset to investigate analytical variability in fMRI.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- On the validity of fMRI mega-analyses using data processed with different pipelines.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Statistical inference for same data meta-analysis in neuroimaging multiverse analyzes.Imaging neuroscience (Cambridge, Mass.) · 2025Article
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4 authors.
Funding
Abstract
Results of functional Magnetic Resonance Imaging (fMRI) studies can be impacted by many sources of variability, including different sampling strategies for the participants, different acquisition protocols and materials, but also different analytical choices in the processing of the fMRI data. While variability across participants or acquisition instruments has been extensively studied in the neuroimaging literature, the root causes of analytical variability remain an open question. Here, we share the HCP Multi-Pipeline dataset, which provides the resulting statistic maps for 24 typical fMRI pipelines on 1,080 participants of the HCP Young Adult dataset. We share both individual and group results for 1,000 groups of 50 participants over 5 motor contrasts. We hope this large dataset, covering a wide range of analysis conditions, will provide new opportunities to study analytical variability in fMRI.
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Registered trials
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