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.

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

spike sorting pipeline.

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

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.

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

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

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

PyNWB is a Python package for working with NWB files. It provides a high-level API for efficiently working with Neurodata stored in the NWB format.

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

pyABF is a Python package for reading electrophysiology data from ABF files. It was created with the goal of providing a Pythonic API to access the content of ABF files which is so intuitive to use (with a predictive IDE) that documentation is largely unnecessary.

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.

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

This inspector is meant as a companion to the PyNWB validator, which checks for strict schema compliance. This tool attempts to apply some common sense to find components of the file that are technically compliant, but possibly incorrect, suboptimal in their representation, or deviate from best practices.

This is a library to perform shift-invariant sparse dictionary learning, also known as convolutional sparse coding (CSC), on time-series data.

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.

This package provides a Python library implementing the DICS beamformer for connectivity analysis and power mapping on the cortex.

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.

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

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.

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.

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.

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