As of FMRIPREP 1.0.12, the software includes a tracking system to report usage statistics and errors. Users can opt-out using the --notrack command line argument.

Execution and the BIDS format

The fmriprep workflow takes as principal input the path of the dataset that is to be processed. The input dataset is required to be in valid BIDS format, and it must include at least one T1w structural image and (unless disabled with a flag) a BOLD series. We highly recommend that you validate your dataset with the free, online BIDS Validator.

The exact command to run fmriprep depends on the Installation method. The common parts of the command follow the BIDS-Apps definition. Example:

fmriprep data/bids_root/ out/ participant -w work/

Command-Line Arguments

The docker wrapper CLI

The fMRIPrep on Docker wrapper

This is a lightweight Python wrapper to run fMRIPrep. Docker must be installed and running. This can be checked running

docker info

Please report any feedback to our GitHub repository ( and do not forget to credit all the authors of software that fMRIPrep uses (

usage: fmriprep-docker [-h] [--version] [-i IMG] [-w WORK_DIR]
                       [--output-grid-reference OUTPUT_GRID_REFERENCE]
                       [--template-resampling-grid TEMPLATE_RESAMPLING_GRID]
                       [--fs-license-file PATH] [--use-plugin PATH] [-f PATH]
                       [-n PATH] [-p PATH] [--shell] [--config PATH]
                       [-e ENV_VAR value] [-u USER]
                       [bids_dir] [output_dir] [{participant}]

Positional Arguments

analysis_level Possible choices: participant

Named Arguments

-h, --help show this help message and exit
--version show program’s version number and exit
-i, --image image name

Wrapper options

Standard options that require mapping files into the container

-w, --work-dir path where intermediate results should be stored
 Deprecated after FMRIPREP 1.0.8. Please use –template-resampling-grid instead.
 Keyword (“native”, “1mm”, or “2mm”) or path to an existing file. Allows to define a reference grid for the resampling of BOLD images in template space. Keyword “native” will use the original BOLD grid as reference. Keywords “1mm” and “2mm” will use the corresponding isotropic template resolutions. If a path is given, the grid of that image will be used. It determines the field of view and resolution of the output images, but is not used in normalization.
 Path to FreeSurfer license key file. Get it (for free) by registering at
--use-plugin nipype plugin configuration file

Developer options

Tools for testing and debugging FMRIPREP

-f, --patch-fmriprep
 working fmriprep repository
-n, --patch-niworkflows
 working niworkflows repository
-p, --patch-nipype
 working nipype repository
--shell open shell in image instead of running FMRIPREP
--config Use custom nipype.cfg file
-e, --env Set custom environment variable within container
-u, --user Run container as a given user/uid


Logs and crashfiles are outputted into the <output dir>/fmriprep/sub-<participant_label>/log directory. Information on how to customize and understand these files can be found on the nipype debugging page.

Support and communication

The documentation of this project is found here:

All bugs, concerns and enhancement requests for this software can be submitted here:

If you have a problem or would like to ask a question about how to use fmriprep, please submit a question to with an fmriprep tag. is a platform similar to StackOverflow but dedicated to neuroinformatics.

All previous fmriprep questions are available here:

To participate in the fmriprep development-related discussions please use the following mailing list: Please add [fmriprep] to the subject line when posting on the mailing list.

Not running on a local machine? - Data transfer

If you intend to run fmriprep on a remote system, you will need to make your data available within that system first.

For instance, here at the Poldrack Lab we use Stanford’s HPC system, called Sherlock. Sherlock enables the following data transfer options.

Alternatively, more comprehensive solutions such as Datalad will handle data transfers with the appropriate settings and commands. Datalad also performs version control over your data.