Giter Site home page Giter Site logo

pellet / eeg-expy Goto Github PK

View Code? Open in Web Editor NEW

This project forked from neurotechx/eeg-expy

1.0 1.0 0.0 101.85 MB

A collection of classic EEG experiments implemented with Python and Jupyter notebooks

Home Page: https://neurotechx.github.io/eeg-notebooks

License: BSD 3-Clause "New" or "Revised" License

Python 97.79% HTML 1.85% CSS 0.36%

eeg-expy's Introduction

EEG-Notebooks

Democratizing the cognitive neuroscience experiment

badge_test badge_binder

image

EEG-Notebooks is a collection of classic EEG experiments, implemented in Python 3 and Jupyter notebooks. The experimental protocols and analyses are quite generic, but are primarily taylored for low-budget / consumer EEG hardware such as the InteraXon MUSE and OpenBCI Cyton. The goal is to make cognitive neuroscience and neurotechnology more accessible, affordable, and scalable.


Note: eeg-notebooks underwent major changes to the API in v0.2. The old v0.1 is still available if you need it, in this repo.


Overview

Conventional lab-based EEG research typically uses research-grade (often high-density) EEG devices, dedicated stimulus delivery software and hardware, and dedicated technicians responsible for operating this equipment. The price tag for these items can easily extend into hundreds of thousands of dollars, which naturally places major limits on their acquisition and usage.

In recent years, however, developments in hardware and software technologies are making it possible for many classic EEG cognitive neuroscience experiments to be conducted using a standard laptop/personal computer and a relatively cheap consumer-grade EEG device, with a combined minimum cost of less than 1000 dollars. This opens dramatic new possibilities for neurotechnology and cognitive neuroscience education (at both University and High School levels), as well as more ambitious and larger-scale research and clinical applications using large numbers of devices, and/or in more naturalistic (i.e. out-of-the-lab) settings. We like to think of this as contributing to the democratization of the cognitive neuroscience experiment.

The core aim of the EEG-Notebooks project is to provide the critical 'glue' that pulls together the various enabling technologies necessary for running these experiments and analyzing the data. This includes functionality for

  • streaming data from various relatively new wireless consumer-grade EEG devices
  • visual and auditory stimulus presentation, concurrent with and time-locked to the EEG recordings
  • a growing library of well-documented, ready-to-use, and ready-to-modify experiments
  • signal processing, statistical, and machine learning data analysis functionalities

A real one-stop-shop!

For more discussion on these social/scientific/technological contexts and trajectories, a) feel free to get in touch directly (see #Contact info below) and b) keep an eye out for the forthcoming eeg-notebooks research paper.

Documentation

The current version of eeg-notebooks is the 0.2.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.

Installation instructions, steps for getting started, common troubleshooting solutions and more can be found in the documentation for eeg-notebooks, available on the documentation site.

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, Jadin Tredup, Erik Bjäreholt.

Thanks also to Andrey Parfenov for the excellent brainflow library, which has allowed us to dramatically expand the range of supporte devices; as well as the developers of PsychoPy and MNE, which together make up the central scaffolding of eeg-notebooks.

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.

Contact

The best place for general discussion on eeg-notebooks functionality is the issues page. For more general questions and discussions, you can e-mail [email protected], or ping us on the NeuroTechX Discord or NeuroTechX slack.

image

eeg-expy's People

Contributors

johngriffiths avatar erikbjare avatar jadintredup avatar hvjay avatar danielemarinazzo avatar retiutut avatar jartuso avatar jnaulty avatar ayrusgit avatar orehga avatar hubertjb avatar kylemath avatar pellet avatar div12345 avatar tmorshed avatar

Stargazers

 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.