mne

MNELAB – a GUI for MNE-Python

PyPREP: A Python implementation of the Preprocessing Pipeline (PREP) for EEG data

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

🧠 + 🚗 Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system

User-friendly MNE-python based graphical user interface to do MEG and EEG analysis with multiple subjects

Python routines for parsing of combined EEG and eye-tracking data

MNE-preprocessing is a python repository to reduce artifacts based on basic and unanimous approaches step by step from electroencephalographic (EEG) raw data.

Sleep stage automatic classifier using CNNs and LSTMs to process frequency signals of brain activity recorded via ElectroEncephaloGram EEG. Undergraduate thesis

We introduce XBrainLab, an open-source user-friendly software, for accelerated interpretation of neural patterns from EEG data based on cutting-edge computational approach.

🧠⚡A CLI to access and process the THINGS-EEG2 dataset by Gifford et al. (2022)

MNE: Multi-relational Network Embedding

This repository contains a Python implementation for solving a two-class classification problem using CSP features extracted from EEG data. The classification task involves discriminating between mental tasks, specifically imagining foot movement and performing mental discrimination.

Hand gesture classification by optomyographical sensor signals

I/O support for EEGLAB files in Python.

It features tutorials on using the EEGLAB toolbox and MNE-Python, guiding users through the basics of EEG data handling, pre-processing, and artifact removal.

[DEPRECATED] EEG Frequency Visualizer - MNE

Scripts for the emotion EEG, ECG, sociability ISRSA analysis

Predicting Workload in Virtual Flight Simulations using EEG Spectral and Connectivity Features

A Deep Learning Library for State-Based EEG Analysis

Preprocessing the fNIRS data from the paper "The use of broad vs restricted regions of interest in functional near-infrared spectroscopy for measuring cortical activation to auditory-only and visual-only speech"