Real-time framework integrated with MNE-Python for online neuroscience research through LSL-compatible devices.
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Project description
MNE-LSL (Documentation website)
provides a real-time brain signal streaming framework.
MNE-LSL contains an improved python-binding for the Lab Streaming Layer C++ library,
mne_lsl.lsl, replacing pylsl. This low-level binding is used in high-level objects
to interact with LSL streams.
Any signal acquisition system supported by native LSL or OpenVibe is also supported by MNE-LSL. Since the data communication is based on TCP, signals can be transmitted wirelessly. For more information about LSL, please visit the LSL github.
Install
MNE-LSL supports python ≥ 3.10 and is available on
PyPI and on
conda-forge.
Install instruction can be found on the
documentation website.
Acknowledgment
MNE-LSL is based on BSL and NeuroDecode. The original version developed by Kyuhwa Lee was recognised at Microsoft Brain Signal Decoding competition with the First Prize Award (2016). MNE-LSL is based on the refactor version, BSL by Mathieu Scheltienne and Arnaud Desvachez for the Fondation Campus Biotech Geneva (FCBG) and development is still supported by the Fondation Campus Biotech Geneva (FCBG).
Copyright and license
The code is released under the BSD 3-Clause License.
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