MNELAB – a GUI for MNE

MNE-CPP: A Framework for Electrophysiology

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.

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

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

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

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

MNE: Multi-relational Network Embedding

I/O support for EEGLAB files in Python.

Hand gesture classification by optomyographical sensor signals

Detecting ASD with Models Trained on EEG/IRT Data

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

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

Scripts for the emotion EEG, ECG, sociability ISRSA analysis

🧠Quality assessor for EEG recordings 🧠

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.

Sparsity enables subcortical source estimation, Krishnaswamy et al, PNAS 2017