Signal processing · Processing
MNE-Python
The standard open-source Python package for exploring, analysing and visualising MEG, EEG and intracranial data.
- Mature
- Widely used
- Active
What problem does it solve?
Turning raw electrophysiology into clean, analysable signals takes filtering, artefact handling, epoching, statistics and source modelling. MNE-Python provides them in one consistent API.
Who is it for?
Researchers and engineers working with EEG, MEG, ECoG or sEEG
At a glance
- Primary use
- Signal processing
- Licence
- BSD-3-Clause · permissive
- Language
- Python
- Current release
- v1.13.2, published 11 Sep 2026
- Development activity
- Last commit 2 Oct 2026 · repository created 28 Jan 2011
- Maintainers
- MNE developers
- GitHub stars
- 3,536 as of 3 Oct 2026
- Standards
- BIDS, EDF / EDF+
Repository facts are a snapshot read from the GitHub API on 3 Oct 2026; they are reported as found, not scored.
Supported modalities and use
How it fits into a BCI stack
Hardware
2 tools
Acquisition
3 tools
Streaming
3 tools
Processing
MNE-Python
Decoding
4 tools
Applications
2 tools
Data & standards
3 tools
- Build a real-time EEG BCIas Preprocessing
- Analyse an ECoG speech datasetas Preprocessing
Getting started
pip install mne, then work through the introductory tutorials, which download a sample dataset and walk from raw data to evoked responses.
Publications
- MEG and EEG data analysis with MNE-Python
Gramfort A et al. · Frontiers in Neuroscience · 2013 · reference paper
- Simultaneous speech and gesture decoding for multimodal communication in paralysis
Brosler SC et al. · Nature Neuroscience · 2026
Sources
- 01
github.com/mne-tools/mne-python (opens in a new tab)
Open-source repositoryGitHubChecked against source 3 Oct 2026
Repository metadata read from the GitHub API.