MNE-RT: Open-Source Real-Time M/EEG Processing Library Released

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Our lab’s open-source Python library for real-time EEG/MEG signal processing, neurofeedback, and BCI applications is now publicly available.
Author

REA.lab

Published

June 19, 2026

MNE-RT is Live

We are excited to announce the public release of MNE-RT — an open-source Python library for real-time M/EEG signal processing built on MNE-Python and MNE-LSL.

MNE-RT covers the full real-time pipeline — from amplifier to 3-D brain display — in a single, researcher-friendly API designed for neurofeedback, BCI, and clinical or basic-science monitoring applications.

Key Highlights

  • 20+ real-time feature modalities — sensor power, ERD/ERS, connectivity, cross-frequency coupling, graph-theory metrics, and more
  • Sensor and source-space processing using MNE inverse operators (eLORETA, dSPM, MNE)
  • Live artifact correction — ORICA, adaptive LMS, ASR, and real-time Maxwell filtering for MEG
  • Adaptive feedback protocols — threshold, z-score, reinforcement learning, sham, and operant schedules
  • Nine real-time visualisation windows including scalp topomaps, 3-D brain surface, and TFR heatmaps
  • Dual feedback output via OSC (Max/MSP, SuperCollider) and LSL (PsychoPy, OpenViBE, BCI2000)

Install

pip install mne-rt

The library was developed with support from the Swiss National Science Foundation (grant 208164).