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

pyEDFlib is a Python library to read/write EDF+/BDF+ files based on EDFlib. EDF means European Data Format

AntroPy is a Python package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to extract features from EEG signals.

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

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.

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.

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

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

This package provides an electrophysiological data analysis library for Python.

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 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.

This package provides tools for calculating smoothed 2D position, speed, head direction.

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

Elephant (Electrophysiology Analysis Toolkit) is an open-source, community centered library for the analysis of electrophysiological data in the Python programming language. The focus of Elephant is on generic analysis functions for spike train data and time series recordings from electrodes, such as the local field potentials (LFP) or intracellular voltages. In addition to providing a common platform for analysis code from different laboratories, the Elephant project aims to provide a consistent and homogeneous analysis framework that is built on a modular foundation. Elephant is the direct successor to Neurotools and maintains ties to complementary projects such as OpenElectrophy and spykeviewer.

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

SpikeInterface is a Python framework designed to unify preexisting spike sorting technologies into a single code base.

It can:

• read/write many extracellular file formats.

• pre-process extracellular recordings.

• run many popular, semi-automatic spike sorters (kilosort1-4, mountainsort4-5, spykingcircus, tridesclous, ironclust, herdingspikes, yass, waveclus)

• run sorters developed in house (lupin, spkykingcicus2, tridesclous2, simple) that compete with kilosort4

• run theses polar sorters without installation using containers (Docker/Singularity).

• post-process sorted datasets using th SortingAnalyzer

• compare and benchmark spike sorting outputs.

• compute quality metrics to validate and curate spike sorting outputs.

• visualize recordings and spike sorting outputs in several ways (matplotlib, sortingview, jupyter, ephyviewer)

• export a report and/or export to phy

• curate your sorting with several strategies (ml-based, metrics based, manual, ...)

• have powerful sorting components to build your own sorter.

• have a full motion/drift correction framework.

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

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.

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.

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.

edfio is a Python package for reading and writing EDF and EDF+C files.

This is a Python package for performing representational similarity analysis (RSA) using MNE-Python data structures. The main use-case is to perform RSA using a “searchlight” approach through time and/or a volumetric or surface source space.

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