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.

This package provides a new backend based on pyqtgraph for the 2D-Data-Browser in MNE-Python.

This package provides I/O functions for the CNT format from ANT Neuro.

This package provides a cross-platform interactive viewer to inspect the final results and quality of any spike sorter supported by spikeinterface.

This library implements a simple lossless compression scheme adapted to time-dependent high-frequency, high-dimensional signals. It is being developed within the International Brain Laboratory with the aim of being the compression library used for all large-scale electrophysiological recordings based on Neuropixels. The signals are typically recorded at 30 kHz and 10 bit depth, and contain several hundreds of channels.

MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more.

mffpy is a lean reader for EGI's MFF file format. These files are directories containing several files of mostly xml files, but also binary files.

pyRiemann is a Python machine learning package based on scikit-learn API. It provides a high-level interface for processing and classification of real (resp. complex)-valued multivariate data through the Riemannian geometry of symmetric (resp. Hermitian) positive definite (SPD) (resp. HPD) matrices.

YASA is a Python package to analyze polysomnographic sleep recordings.

MNELAB is a GUI for MNE-Python, a Python package for EEG/MEG analysis.

This package provides a C++ library for multi-modal time-synched data transmission over the local network.

This package provides denoising tools for M/EEG processing in Python.

Python library for reading, writing, and validating SNIRF files

mne-icalabel is a Python package for labeling independent components that stem from an Independent Component Analysis (ICA).

This package contains code to compute the standard EEG electrode locations on a spherical head model for the 10-20, 10-10, and 10-05 system.

nwb2bids reorganizes NWB files into a BIDS directory layout.

Features:

• Automatically renames NWB files and their directories to conform to BIDS conventions.

• Extracts relevant metadata from NWB files to populate BIDS sidecar TSV & JSON files.

• Currently supports BEP32 (micro-electrode electrophysiology) data types, such as extracellular (ecephys) and intracellular (icephys) electrophysiology, as well as associated behavioral events.

MNE-Connectivity is an open-source Python package for connectivity and related measures of MEG, EEG, or iEEG data built on top of the MNE-Python API. It includes modules for data input/output, visualization, common connectivity analysis, and post-hoc statistics and processing.

This package provides a Python implementation of a multitaper window method for estimating Wigner spectra for certain locally stationary processes.

MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.

This package provides a library for sleep stage classification using ECG data.

Tensor-based Phase-Amplitude Coupling.

The OpenMEEG software is a C++ package for solving the forward problems of electroencephalography (EEG) and magnetoencephalography (MEG).

This package provides an electrophysiological data analysis library for Python.

This package provides tools for finding sharp-wave ripple events (150-250 Hz) from local field potentials.