https://github.com/mne-tools/mne-bids-pipeline

Automatically process entire electrophysiological datasets using MNE-Python.
https://github.com/mne-tools/mne-bids-pipeline

bids group-analysis mne-python neuroscience pipeline python

Last synced: 18 days ago
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Automatically process entire electrophysiological datasets using MNE-Python.

• Host: GitHub
• URL: https://github.com/mne-tools/mne-bids-pipeline
• Owner: mne-tools
• License: bsd-3-clause
• Created: 2019-01-28T12:18:07.000Z (over 6 years ago)
• Default Branch: main
• Last Pushed: 2025-04-28T21:25:11.000Z (21 days ago)
• Last Synced: 2025-04-28T21:39:10.069Z (21 days ago)
• Topics: bids, group-analysis, mne-python, neuroscience, pipeline, python
• Language: Python
• Homepage: https://mne.tools/mne-bids-pipeline/
• Size: 1.03 GB
• Stars: 146
• Watchers: 12
• Forks: 73
• Open Issues: 84
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.txt

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README

        
#  MNE-BIDS-Pipeline

**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)](https://bids.neuroimaging.io/).

* Under the hood, it uses [MNE-Python](https://mne.tools).

## 💡 Basic concepts and features

* 🏆 Automated processing of MEG and EEG data from raw data to inverse solutions.

* 🛠️ Configuration via a simple text file.

* 📘 Extensive processing and analysis summary reports.

* 🧑‍🤝‍🧑 Process just a single participant, or as many as several hundreds of participants – in parallel.

* 💻 Execution via an easy-to-use command-line utility.

* 🆘 Helpful error messages in case something goes wrong.

* 👣 Data processing as a sequence of standard processing steps.

* ⏩ Steps are cached to avoid unnecessary recomputation.

* ⏏️ Data can be "ejected" from the pipeline at any stage. No lock-in!

* ☁️ Runs on your laptop, on a powerful server, or on a high-performance cluster via Dask.

## 📘 Installation and usage instructions

Please find the documentation at

[**mne.tools/mne-bids-pipeline**](https://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](https://brainthemind.com/)

and the [MNE Python Team](https://mne.tools), 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. 

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. 

> 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.

>