Metadata-Version: 2.4
Name: mne_lsl
Version: 0.0.0
Summary: Real-time framework integrated with MNE-Python for online neuroscience research through LSL-compatible devices.
Author-email: Mathieu Scheltienne <mathieu.scheltienne@gmail.com>
Maintainer-email: Mathieu Scheltienne <mathieu.scheltienne@gmail.com>
License-Expression: BSD-3-Clause
Project-URL: documentation, https://mne.tools/mne-lsl
Project-URL: homepage, https://mne.tools/mne-lsl
Project-URL: source, https://github.com/mne-tools/mne-lsl
Project-URL: tracker, https://github.com/mne-tools/mne-lsl/issues
Keywords: brain,EEG,eeg,electroencephalography,labstreaminglayer,LSL,neuroimaging,neurophysiology,neuroscience,python,real-time
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: click>=8.1
Requires-Dist: mne>=1.6
Requires-Dist: numpy<3,>=1.21
Requires-Dist: packaging
Requires-Dist: pooch
Requires-Dist: psutil
Requires-Dist: pyqtgraph
Requires-Dist: qtpy
Requires-Dist: scipy
Dynamic: license-file

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<img align="right" src="https://raw.githubusercontent.com/mne-tools/mne-lsl/main/doc/_static/logos/logo-mne-hex.svg" alt="logo" width="200"/>

**MNE-LSL** [(Documentation website)](https://mne.tools/mne-lsl)
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](https://github.com/sccn/labstreaminglayer).

# Install

MNE-LSL supports `python ≥ 3.11` and is available on
[PyPI](https://pypi.org/project/mne-lsl/) and on
[conda-forge](https://anaconda.org/conda-forge/mne-lsl).
Install instruction can be found on the
[documentation website](https://mne.tools/mne-lsl/stable/resources/install.html).

# Acknowledgment

<img align="right" src="https://raw.githubusercontent.com/mne-tools/mne-lsl/main/doc/_static/partners/FCBG.svg" width=100>

**MNE-LSL** is based on **BSL** and **NeuroDecode**. The original version developed by
[**Kyuhwa Lee**](https://github.com/dbdq) was recognised at
[Microsoft Brain Signal Decoding competition](https://github.com/dbdq/microsoft_decoding)
with the First Prize Award (2016).
**MNE-LSL** is based on the refactor version, **BSL** by
[**Mathieu Scheltienne**](https://github.com/mscheltienne) and
[**Arnaud Desvachez**](https://github.com/dnastars) for the
[Fondation Campus Biotech Geneva (FCBG)](https://github.com/fcbg-platforms) and
development is still supported by the
[Fondation Campus Biotech Geneva (FCBG)](https://fcbg.ch/).

# Copyright and license

The code is released under the
[BSD 3-Clause License](https://opensource.org/license/bsd-3-clause/).
