MNE-LSL🔗
Open-source Python package for real-time brain signal streaming framework based on the Lab Streaming Layer (LSL).
Install🔗
MNE-LSL is available on PyPI and conda-forge.
As of MNE-Python 1.6, mne-lsl is distributed in the
MNE standalone installers.
The installers create a conda environment with the entire MNE-ecosystem setup, and more! This installation method is recommended for beginners.
mne-lsl can be installed from PyPI using pip:
$ pip install mne-lsl
mne-lsl can be installed from conda-forge using conda:
$ conda install -c conda-forge mne-lsl
mne-lsl can be installed from GitHub or from the Source
distribution. In this case, the installation will build liblsl.
$ pip install git+https://github.com/mne-tools/mne-lsl
If you wish to skip building liblsl, you can set the environment
variable MNE_LSL_SKIP_LIBLSL_BUILD to 1 before running the installation,
and use the environment variable MNE_LSL_LIB or PYLSL_LIB to specify the
path to the liblsl library on your system.
$ MNE_LSL_SKIP_LIBLSL_BUILD=1 pip install git+https://github.com/mne-tools/mne-lsl
Cite🔗
If you use MNE-LSL, please consider citing our paper[1].
Scheltienne, M., Larson, E., Desvachez, A., & Lee, K. (2025). MNE-LSL: Real-time framework integrated with MNE-Python for online neuroscience research through LSL-compatible devices.. Journal of Open Source Software, 10(111), 8088. https://doi.org/10.21105/joss.08088
@article{Scheltienne_MNE-LSL_Real-time_framework_2025,
author = {Scheltienne, Mathieu and Larson, Eric and Desvachez, Arnaud and Lee, Kyuhwa},
doi = {10.21105/joss.08088},
journal = {Journal of Open Source Software},
month = jul,
number = {111},
pages = {8088},
title = {{MNE-LSL: Real-time framework integrated with MNE-Python for online neuroscience research through LSL-compatible devices.}},
url = {https://joss.theoj.org/papers/10.21105/joss.08088},
volume = {10},
year = {2025}
}
Supporting institutions🔗
The development of MNE-LSL was supported by the
Fondation Campus Biotech Geneva.