mne-tools/mne-python

Health v2 · maintenance only

Adoption not part of the score

3495 stars · 1585 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

MNE-Python is an open-source Python library for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, and ECoG. It provides modules for data I/O, preprocessing, source estimation, time-frequency and connectivity analysis, statistics, and machine learning.

Use cases

• analyze EEG data in Python
• process MEG recordings
• visualize neurophysiological signals
• perform source estimation from EEG/MEG
• run time-frequency analysis on brain signals
• compute connectivity analysis on MEG data
• apply machine learning to EEG data
• do statistics on neuroimaging data

When to choose

• you need to read, preprocess, or analyze MEG/EEG/sEEG/ECoG data in Python
• you want source estimation or time-frequency analysis of brain signals
• you need publication-quality visualizations of neurophysiological data
• you want a comprehensive, well-documented neuroimaging library with an active community

When to avoid

• you only need general-purpose signal processing without neuroimaging-specific features
• you work exclusively with fMRI or other non-MEG/EEG modalities better served by tools like Nilearn
• you need a GUI-only workflow without programming

Facets

library · maturity stable

data-visualization machine-learning nlp data-science image-processing data-science data-visualization machine-learning python cross-platform eeg meg neuroimaging ecog seeg neurophysiology time-frequency-analysis source-estimation signal-processing brain-imaging neuroscience

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