EEG-Notebooks - Democratizing the cognitive neuroscience experiment

EEG notebooks is a collection of classic EEG experiments, implemented in Python and Jupyter notebooks. The experimental protocols and analyses are quite generic, but are primarily taylored for low-budget / consumer EEG hardware such as the MUSE. The goal is to make cognitive neuroscience and neurotechnology more accessible, affordable, and scalable.

Overview

TO DO

Documentation

Documentation for eeg-notebooks is available on the documentation site.

This documentation includes:

  • Setup: with information on supported hardware, software requirements, installation and setup

  • Tutorials: with a step-by-step guide on how to set up and run a variety of eeg-based cognitive neuroscience experiments

  • Examples: demonstrating example analyses and use cases, and other functionality

  • API list: which lists and describes all the code and functionality available in the module

  • FAQ: answering frequency asked questions

  • Glossary: which defines all the key terms used in the module

  • Reference: with information for reporting on using and reference the module

Dependencies

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We recommend using the Anaconda distribution to manage these requirements.

Installation

The current version of eeg-noteboks is the 0.X.X series. The code-base and API are under major development and subject to change.

Check the changelog for notes on changes from previous versions.

Stable Version

Coming soon…

Development Version

To get the current development version, first clone this repository:

$ git clone https://neurotechx/eeg-notebooks

To install this cloned copy, move into the directory you just cloned, and run:

$ pip install .

Editable Version

To install an editable version, download the development version as above, and run:

$ pip install -e .

Quickstart

TO DO

Acknowledgments

EEG-Notebooks was created by the NeurotechX hacker/developer/neuroscience community. The ininitial idea and majority of the groundwork was due to Alexandre Barachant - including the muse-lsl library, which is core dependency. Lead developer on the project is now John Griffiths .

Key contributors include:

Alexandre Barachant

Hubert Banville

Dano Morrison

Ben Shapiro

John Griffiths

Amanda Easson

Kyle Mathewson

Reference

Coming soon…

Contribute

This project welcomes and encourages contributions from the community!

If you have an idea of something to add to eeg-notebooks, please start by opening an issue. Note that this issue tracker is used for code specific questions and suggestions. If you have a question or suggestion related to the model or conceptual ideas, check out the development page.

When writing code to add to eeg-notebooks, please follow the Contribution Guidelines , and also make sure to follow our Code of Conduct.

Bug reports

Please use the Github issue tracker to file bug reports and/or ask questions about this project.