A standardized processing pipeline for your MEG and EEG data
Project description
The MNE-BIDS-Pipeline
The MNE-BIDS-Pipeline is a full-flegded processing pipeline for your MEG and EEG data. It operates on data stored according to the Brain Imaging Data Structure (BIDS). Under the hood, it uses MNE-Python.
💡 Basic concepts and features
- 🐾 Data processing as a sequence of processing steps.
- ⏏ Your data can be "ejected" from the pipeline at any stage. No lock-in!
- 🧾 Extensive processing and analysis summary reports.
- 🎬 Process just a single participant, or as many as several hundreds of participants – in parallel.
- 🛠 Configuration via a simple text file.
- 💻 Execution via an easy-to-use command-line utility.
- 🆘 Helpful error messages in case something goes wrong.
📘 Installation and usage instructions
Please find the documentation at mne.tools/mne-bids-pipeline.
❤ Acknowledgments
The original pipeline for MEG/EEG data processing with MNE-Python was built jointly by the Cognition and Brain Dynamics Team and the MNE Python Team, based on scripts originally developed for this publication:
M. Jas, E. Larson, D. A. Engemann, J. Leppäkangas, S. Taulu, M. Hämäläinen, A. Gramfort (2018). A reproducible MEG/EEG group study with the MNE software: recommendations, quality assessments, and good practices. Frontiers in neuroscience, 12. https://doi.org/10.3389/fnins.2018.00530
The current iteration is based on BIDS and relies on the extensions to BIDS for EEG and MEG. See the following two references:
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
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. https://doi.org/10.1038/sdata.2018.110
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