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

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

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

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

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

This is an open-source tool which allows to load CURRY data into Python. It supports: raw float (.cdt), ascii (.cdt), legacy raw float (.dat) and legacy ascii (.dat).

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

Tools to analyze and simulate neural time series, using digital signal processing.

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.

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

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

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.

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.

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

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

FASTER is a fully automated, unsupervised method for processing of high density EEG data.

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

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

A Python package to handle the layout, geometry, and wiring of silicon probes for extracellular electrophysiology experiments.

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.

deviceXlib is a library that wraps device-oriented routines and utilities, such as device data allocation, host-device data transfers. It supports CUDA language, together with OpenACC and OpenMP programming paradigms. It wraps a subset of functions from Nvidia cuBLAS, Intel oneMKL BLAS and AMD rocBLAS libraries.

deviceXlib is a library that wraps device-oriented routines and utilities, such as device data allocation, host-device data transfers. It supports CUDA language, together with OpenACC and OpenMP programming paradigms. It wraps a subset of functions from Nvidia cuBLAS, Intel oneMKL BLAS and AMD rocBLAS libraries.

Fypp is a Python powered preprocessor. It can be used for any programming languages but its primary aim is to offer a Fortran preprocessor, which helps to extend Fortran with condititional compiling and template metaprogramming capabilities. Instead of introducing its own expression syntax, it uses Python expressions in its preprocessor directives, offering the consistency and versatility of Python when formulating metaprogramming tasks.