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Process Near-Infrared Spectroscopy Data in MNE

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rob-luke/mne-nirs

 
 

MNE-NIRS: Near-Infrared Spectroscopy Analysis

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MNE-NIRS is an MNE-Python compatible near-infrared spectroscopy processing package.

MNE-Python provides support for fNIRS analysis, this package extends that functionality and adds GLM analysis, helper functions, additional algorithms, data quality metrics, plotting, and file format support.

Documentation

Documentation for this project is hosted here.

You can find a list of examples within the documentation.

Features

MNE-NIRS and MNE-Python provide a wide variety of tools to use when processing fNIRS data including:

Contributing

Contributions are welcome (more than welcome!). Contributions can be feature requests, improved documentation, bug reports, code improvements, new code, etc. Anything will be appreciated. Note: this package adheres to the same contribution standards as MNE.

Acknowledgements

This package is built on top of many other great packages. If you use MNE-NIRS you should also acknowledge these packages.

MNE-Python: https://mne.tools/dev/overview/cite.html

Nilearn: http://nilearn.github.io/authors.html#citing

statsmodels: https://www.statsmodels.org/stable/index.html#citation

Until there is a journal article specifically on MNE-NIRS, please cite this article.

Docker

To start a jupyter lab server with a specified MNE-NIRS version, and mount a local directory on a mac or nix computer use:

docker run -p 8888:8888 -v `pwd`:/home/mne_user ghcr.io/mne-tools/mne-nirs:v0.1.2 jupyter-lab --ip="*"

Or on windows:

docker run -p 8888:8888 -v %cd%:/home/mne_user ghcr.io/mne-tools/mne-nirs:v0.1.2 jupyter-lab --ip="*"

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