Analysis of task-based functional MRI data preprocessed with fMRIPrep.

Nature Protocols
Oscar EstebanKrzysztof J Gorgolewski

Abstract

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time consuming, error prone and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure to standardize both the input datasets (MRI data as stored by the scanner) and the outputs (data ready for modeling and analysis), fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.

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Methods Mentioned

BETA
imaging technique

Key Resources (RRID) Mentioned

SCR_016216
SCR_002502

Software Mentioned

Advanced Normalization Tools ( ANTs )
HeuDiConv
fMRIPrep
Docker
FMRIB analysis of mixed FLAME
SPM
DataLad
MCFLIRT
FLAME
C - PAC Configurable Pipeline for the Analysis of Connectomes

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