GHDL Language Server Protocol (LSP) is a server for VHDL based on GHDL.

UVVM Light is a low threshold version of UVVM and is intended for developers who want to start using UVVM Utilty library and Bus Functional Models.

pyVHDLModel provides an unified abstract language model for VHDL written in Python.

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

This package provides code for feature extraction with M/EEG data.

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

This package implements both parametric and permutation-based ARI, and is meant to be compatible with the MNE-Python ecosystem.

Tensor-based Phase-Amplitude Coupling.

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

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

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.

klusta is an open source package for automatic spike sorting of multielectrode neurophysiological recordings made with probes containing up to a few dozens of sites.

Picard provides Python/Octave/MATLAB code for the preconditionned ICA for real data.

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.

Python parser for Igor Binary Waves (.ibw) and Packed Experiment (.pxp) files written by WaveMetrics' IGOR Pro software.

Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats.

XDF is a general-purpose container format for multi-channel time series data with extensive associated meta information. XDF is tailored towards biosignal data such as EEG, EMG, EOG, ECG, GSR, MEG, but it can also handle data with high sampling rate (like audio) or data with a high number of channels (like fMRI or raw video). Meta information is stored as XML.

Meggie is an open-source software designed for intuitive MEG and EEG analysis. With its user-friendly graphical interface, Meggie brings the powerful analysis methods of MNE-Python to researchers without requiring programming skills.

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

Fast, efficient, and physiologically-informed tool to parameterize neural power spectra

This package provides a simple open source Python package for EEG microstate segmentation.

This is a library to automatically reject bad trials and repair bad sensors in magneto-/electroencephalography (M/EEG) data.

bycycle is a tool for quantifying features of neural oscillations in the time domain, as opposed to the frequency domain, using a cycle-by-cycle approach.

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