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

MNELAB – a GUI for MNE

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

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

I/O support for EEGLAB files in Python.

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

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

🧠Quality assessor for EEG recordings 🧠

Classify whether a patient is having ASD or not using EEG Data. [NOTE] This project is no longer maintained. An active version is now in https://github.com/nirdslab/asd-detection

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

Mne-python source localization template

Basic repo to test BIDS app on MNE sample data (ds000248)

A runner for the MNE BIDS Pipeline.

[DEPRECATED] EEG Frequency Visualizer - MNE

Detecting ASD with Models Trained on EEG/IRT Data

A Deep Learning Library for State-Based EEG Analysis

End-to-end automated EEG analysis to manuscript pipeline (MNE-BIDS → AI writing → Manubot/Carbone)

EEG Classification using MiniRocket + Ridge Classifier on BCI Competition IV Dataset 2a. Reproducible pipeline for Time-Series feature extraction and classification.

A Python package to write data processing pipelines with. Initially designed for eeg/meg analysis using MNE-Python with MNE-BIDS.

Interface cerveau-machine (EEG) avec Machine Learning. Préprocessing MNE, réduction de dimension (PCA/CSP), pipeline scikit-learn, classification en “temps réel”, validation croisée et évaluation multi-sujets. Projet 42 orienté data science appliquée aux signaux cérébraux.