LSL Real-time acquisition

Many amplifier manufacturers have adopted the Lab Streaming Layer protocol to offer a real-time access to the data stream. Real-time access enables closed-loop experiments where the data is processed and analyzed in real-time to provide feedback to the subject.

Lab Streaming Layer

Lab Streaming Layer (LSL) is an open-source networked middleware ecosystem to stream, receive, synchronize, and record neural, physiological, and behavioral data streams acquired from diverse sensor hardware.

This protocol is based on a C++ library, liblsl, which is available for all major platforms (Windows, macOS, Linux) and architectures (x86, x64, ARM). Once available on a system, the library can be used from many programming languages including Python, C#, MATLAB, .. see this meta-package labstreaminglayer for more information.

Many devices are compatible through native or third-party applications with LSL. See this non-exhaustive list of the LSL-compatible devices.

Python interface

Lab Streaming Layer has 2 interfaces in python:

• pylsl: the legacy interface which offers the basic LSL objects and functions.

• mne-lsl: the MNE-Python interface which offers both an efficient re-implementation of the low-level LSL API available in pylsl (mne_lsl.lsl.StreamInfo, mne_lsl.lsl.StreamOutlet, mne_lsl.lsl.StreamInlet, …) and a high-level API to easily connect to LSL streams handles them like MNE-Python objects (mne_lsl.stream.StreamLSL, mne_lsl.stream.EpochsStream, …).

mne-lsl also bundles the liblsl C++ library inside its wheels, thus you don’t need to manually install or compile the library.

PyPI

$ pip install mne-lsl

Conda

$ conda install -c conda-forge mne-lsl

MNE installers

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.

Source

If you have the required compilers and libraries available, you can install from source to build liblsl for your platform with:

$ pip install mne-lsl --no-binary mne-lsl

Or you can set the environment variable MNE_LSL_SKIP_LIBLSL_BUILD=1 to skip the building phase of liblsl and provide your own compiled version in the environment variable MNE_LSL_LIB or PYLSL_LIB.

MATLAB interface

A MATLAB interface is available here.