The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis

Fuente: arXiv
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Main Authors: Germani, Elodie, Fromont, Elisa, Maurel, Pierre, Maumet, Camille
Format: Preprint
Published: 2023
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author Germani, Elodie
Fromont, Elisa
Maurel, Pierre
Maumet, Camille
author_facet Germani, Elodie
Fromont, Elisa
Maurel, Pierre
Maumet, Camille
contents Results of functional Magnetic Resonance Imaging (fMRI) studies can be impacted by many sources of variability including differences due to: the sampling of the participants, differences in acquisition protocols and material but also due to different analytical choices in the processing of the fMRI data. While variability across participants or across acquisition instruments have been extensively studied in the neuroimaging literature the root causes of analytical variability remain an open question. Here, we share the \textit{HCP multi-pipeline dataset}, including the resulting statistic maps for 24 typical fMRI pipelines on 1,080 participants of the HCP-Young Adults dataset. We share both individual and group results - for 1,000 groups of 50 participants - over 5 motor contrasts. We hope that this large dataset covering a wide range of analysis conditions will provide new opportunities to study analytical variability in fMRI.
format Preprint
id arxiv_https___arxiv_org_abs_2312_14493
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis
Germani, Elodie
Fromont, Elisa
Maurel, Pierre
Maumet, Camille
Neurons and Cognition
Results of functional Magnetic Resonance Imaging (fMRI) studies can be impacted by many sources of variability including differences due to: the sampling of the participants, differences in acquisition protocols and material but also due to different analytical choices in the processing of the fMRI data. While variability across participants or across acquisition instruments have been extensively studied in the neuroimaging literature the root causes of analytical variability remain an open question. Here, we share the \textit{HCP multi-pipeline dataset}, including the resulting statistic maps for 24 typical fMRI pipelines on 1,080 participants of the HCP-Young Adults dataset. We share both individual and group results - for 1,000 groups of 50 participants - over 5 motor contrasts. We hope that this large dataset covering a wide range of analysis conditions will provide new opportunities to study analytical variability in fMRI.
title The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis
topic Neurons and Cognition
url https://arxiv.org/abs/2312.14493