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Journal Articles Nature Protocols Year : 2020

Analysis of task-based functional MRI data preprocessed with fMRIPrep

Oscar Esteban
Rastko Ciric
  • Function : Author
Karolina Finc
Ross Blair
  • Function : Author
Craig Moodie
  • Function : Author
Zhifang Ye
Taylor Salo
Inge Amlien
Nir Jacoby
Russell Poldrack


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 (, 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.

Dates and versions

hal-04576176 , version 1 (15-05-2024)



Oscar Esteban, Rastko Ciric, Karolina Finc, Ross Blair, Christopher Markiewicz, et al.. Analysis of task-based functional MRI data preprocessed with fMRIPrep. Nature Protocols, 2020, 15 (7), pp.2186-2202. ⟨10.1038/s41596-020-0327-3⟩. ⟨hal-04576176⟩
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