MNE-BIDS

This is a repository for creating BIDS-compatible datasets with MNE.

The documentation can be found under the following links:

• for the stable release
• for the latest (development) version

Dependencies

• numpy (>=1.14)
• scipy (>=0.18.1)
• mne (>=0.19.1)
• nibabel (optional)
• pybv (optional)

Installation

We recommend the Anaconda Python distribution. We require that you use Python 3. You may choose to install mne-bids via pip or via conda

Installation via pip

Besides numpy and scipy (which are included in the standard Anaconda installation), you will need to install the most recent version of MNE using the pip tool:

$ pip install -U mne

Then install mne-bids:

$ pip install -U mne-bids

These pip commands also work if you want to upgrade if a newer version of mne-bids is available. If you do not have administrator privileges on the computer, use the --user flag with pip.

To check if everything worked fine, the following command should not give any error messages:

$ python -c 'import mne_bids'

For full functionality of mne-bids, you will also need to pip install the following packages:

• nibabel, for interacting with MRI data
• pybv, to convert EEG data to BrainVision if input format is not valid according to EEG BIDS specifications

If you want to use the latest development version of mne-bids, use the following command:

$ pip install https://api.github.com/repos/mne-tools/mne-bids/zipball/master

Installation via conda

If you have followed the MNE-Python installation instructions, all that's left to do is to install mne-bids without its dependencies, as they've already been installed during the MNE installation process.

Activate the correct conda environment and install mne-bids:

$ conda activate mne
$ conda install --channel conda-forge --no-deps mne-bids

This approach ensures that the installation of mne-bids doesn't alter any other packages in your existing conda environment.

Alternatively, you may wish to take advantage of the fact that the mne-bids package on conda-forge in fact depends on mne, meaning that a "full" installation of mne-bids (i.e., including its dependencies) will provide you with a working copy of of both mne and mne-bids at once:

$ conda create --name mne --channel conda-forge mne-bids

After activating the environment, you should be ready to use mne-bids:

$ conda activate mne
$ python -c 'import mne_bids'

Quickstart

Currently, we support writing of BIDS datasets for MEG and EEG. Support for iEEG is experimental at the moment.

>>> from mne import io
>>> from mne_bids import write_raw_bids
>>> raw = io.read_raw_fif('my_old_file.fif')
>>> write_raw_bids(raw, 'sub-01_ses-01_run-05', output_path='./bids_dataset')

Command Line Interface

In addition to import mne_bids, you can use the command line interface. Simply type mne_bids in your command line and press enter, to see the accepted commands. Then type mne_bids <command> --help, where <command> is one of the accepted commands, to get more information about that <command>.

Example:

$ mne_bids raw_to_bids --subject_id sub01 --task rest --raw data.edf --output_path new_path

Bug reports

Use the github issue tracker to report bugs.

Cite

If you use mne-bids in your work, please cite one of the following papers, depending on which modality you used:

MEG

Niso, G., Gorgolewski, K. J., Bock, E., Brooks, T. L., Flandin, G., Gramfort, A.,
Henson, R. N., Jas, M., Litvak, V., Moreau, J., Oostenveld, R., Schoffelen, J.,
Tadel, F., Wexler, J., Baillet, S. (2018). MEG-BIDS, the brain imaging data
structure extended to magnetoencephalography. Scientific Data, 5, 180110.
http://doi.org/10.1038/sdata.2018.110

EEG

Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G.,
Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension
to the brain imaging data structure for electroencephalography. Scientific
Data, 6, 103. https://doi.org/10.1038/s41597-019-0104-8

iEEG

Holdgraf, C., Appelhoff, S., Bickel, S., Bouchard, K., D'Ambrosio, S.,
David, O., … Hermes, D. (2019). iEEG-BIDS, extending the Brain Imaging Data
Structure specification to human intracranial electrophysiology. Scientific
Data, 6, 102. https://doi.org/10.1038/s41597-019-0105-7