Warning
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.
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 (Brain Imaging Data
Structure) 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/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.
The documentation of this project is found here: http://fmriprep.readthedocs.org/en/latest/.
All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/poldracklab/fmriprep/issues.
If you have a problem or would like to ask a question about how to use fmriprep, please submit a question to NeuroStars.org with an fmriprep tag. NeuroStars.org is a platform similar to StackOverflow but dedicated to neuroinformatics.
All previous fmriprep questions are available here: http://neurostars.org/tags/fmriprep/
To participate in the fmriprep development-related discussions please use the following mailing list: http://mail.python.org/mailman/listinfo/neuroimaging Please add [fmriprep] to the subject line when posting on the mailing list.
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 (high-performance computing) 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.