MNE-Python

MNE-Python is an open-source Python package developed by the MNE Developers for exploring, visualizing, and analyzing human neurophysiological data, including MEG, EEG, sEEG, ECoG, and NIRS. The documentation site lists version 1.13.2 as the current stable release, alongside a 1.14 development version.

What It Is

MNE-Python is a scientific analysis library for neurophysiology researchers. Users work with recordings in Python, applying documented analysis methods and producing visualizations of their data. The project is released under the BSD 3-Clause license and hosted on GitHub.

Analysis Capabilities

The homepage highlights several areas of analysis, each linked to tutorials:

• Source estimation, including distributed, sparse, mixed-norm, beamformer, and dipole-fitting methods.
• Machine learning, with decoding models including time generalization.
• Encoding models, such as receptive field estimation with optional smoothness priors.
• Statistics, covering parametric and non-parametric tests, permutation tests, and clustering.
• Connectivity, with all-to-all spectral and effective connectivity measures, documented through the related mne-connectivity project.
• Data visualization, to explore data from multiple perspectives.

Documentation and Community

The site provides installation instructions, tutorials, an API reference, a changelog, citation guidance, and contribution guides. Support channels include a Q&A forum, Discord office hours, and Mastodon.