mne-tools/mne-python

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

What it solves

It provides a comprehensive toolkit for processing and analyzing human neurophysiological data, such as MEG, EEG, sEEG, and ECoG, which is often complex and requires specialized tools for visualization and analysis.

How it works

It operates as a Python package containing specialized modules for various stages of the data pipeline, including data input/output, preprocessing, time-frequency and connectivity analysis, and source estimation.

Who it’s for

Researchers and scientists studying human brain activity and neurophysiological signals.

Highlights

  • Comprehensive data I/O and preprocessing tools.
  • Built-in support for machine learning and statistics.
  • Advanced visualization and source estimation capabilities.
  • Support for multiple data types including MEG, EEG, sEEG, and ECoG.

Related

  • Project
    fieldtrip/fieldtrip

    A MATLAB toolbox for the advanced analysis of MEG, EEG, and iEEG data, supporting multiple hardware formats and source reconstruction.

  • Project
    GAA-UAM/scikit-fda

    A Python package for Functional Data Analysis (FDA) that provides tools for the representation, preprocessing, and statistical analysis of data depending on a continuous parameter.

  • Project
    braindecode/braindecode

    Braindecode is a Python toolbox that brings deep‑learning models to raw brain‑signal data (EEG/ECoG/MEG). It provides dataset loaders, preprocessing, several ready‑made neural‑network architectures, and visualisation utilities, all built on top of PyTorch and MNE‑Python. Installable via `pip install braindecode`, it targets neuroscientists and ML researchers working with neurophysiological data.

  • Project
    alexandrebarachant/muse-lsl

    A Python package for streaming, visualizing, and recording EEG and sensor data from Muse headbands using the Lab Streaming Layer (LSL) protocol.

  • Project
    nltk/nltk

    The Natural Language Toolkit (NLTK) is a suite of Python modules and data sets that supports research and development in Natural Language Processing.