Skip to main content

Deep learning software to decode EEG, ECG or MEG signals

Project description

Join the chat at https://gitter.im/braindecodechat/community https://github.com/braindecode/braindecode/workflows/docs/badge.svg Doc build on CircleCI Code Coverage

Braindecode

Braindecode is an open-source Python toolbox for decoding raw electrophysiological brain data with deep learning models. It includes dataset fetchers, data preprocessing and visualization tools, as well as implementations of several deep learning architectures and data augmentations for analysis of EEG, ECoG and MEG.

For neuroscientists who want to work with deep learning and deep learning researchers who want to work with neurophysiological data.

Installation Braindecode

  1. Install pytorch from http://pytorch.org/ (you don’t need to install torchvision).

  2. If you want to download EEG datasets from MOABB, install it:

pip install moabb
  1. Install latest release of braindecode via pip:

pip install braindecode

If you want to install the latest development version of braindecode, please refer to contributing page

Documentation

Documentation is online under https://braindecode.org, both in the stable and dev versions.

Contributing to Braindecode

Guidelines for contributing to the library can be found on the braindecode github:

https://github.com/braindecode/braindecode/blob/master/CONTRIBUTING.md

Braindecode chat

https://gitter.im/braindecodechat/community

Citing

If you use this code in a scientific publication, please cite us as:

@article {HBM:HBM23730,
author = {Schirrmeister, Robin Tibor and Springenberg, Jost Tobias and Fiederer,
  Lukas Dominique Josef and Glasstetter, Martin and Eggensperger, Katharina and Tangermann, Michael and
  Hutter, Frank and Burgard, Wolfram and Ball, Tonio},
title = {Deep learning with convolutional neural networks for EEG decoding and visualization},
journal = {Human Brain Mapping},
issn = {1097-0193},
url = {http://dx.doi.org/10.1002/hbm.23730},
doi = {10.1002/hbm.23730},
month = {aug},
year = {2017},
keywords = {electroencephalography, EEG analysis, machine learning, end-to-end learning, brain–machine interface,
  brain–computer interface, model interpretability, brain mapping},
}

as well as the MNE-Python software that is used by braindecode:

@article{10.3389/fnins.2013.00267,
author={Gramfort, Alexandre and Luessi, Martin and Larson, Eric and Engemann, Denis and Strohmeier, Daniel and Brodbeck, Christian and Goj, Roman and Jas, Mainak and Brooks, Teon and Parkkonen, Lauri and Hämäläinen, Matti},
title={{MEG and EEG data analysis with MNE-Python}},
journal={Frontiers in Neuroscience},
volume={7},
pages={267},
year={2013},
url={https://www.frontiersin.org/article/10.3389/fnins.2013.00267},
doi={10.3389/fnins.2013.00267},
issn={1662-453X},
}

Licensing

This project is primarily licensed under the BSD-3-Clause License.

Additional Components

Some components within this repository are licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

Please refer to the LICENSE and NOTICE files for more detailed information.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

braindecode-1.2.0.dev169062562.tar.gz (258.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

braindecode-1.2.0.dev169062562-py3-none-any.whl (287.5 kB view details)

Uploaded Python 3

File details

Details for the file braindecode-1.2.0.dev169062562.tar.gz.

File metadata

  • Download URL: braindecode-1.2.0.dev169062562.tar.gz
  • Upload date:
  • Size: 258.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for braindecode-1.2.0.dev169062562.tar.gz
Algorithm Hash digest
SHA256 860018abc09c7e37d2bd35b86d96701b41ee0e616045aa83562ff424be729eee
MD5 9f6b1cd5c4a9929d424e8b13516e666e
BLAKE2b-256 87dfc262a75067e4c77f3f03fbd4883405b91e121a428bfec5ac5e64bff527e3

See more details on using hashes here.

File details

Details for the file braindecode-1.2.0.dev169062562-py3-none-any.whl.

File metadata

File hashes

Hashes for braindecode-1.2.0.dev169062562-py3-none-any.whl
Algorithm Hash digest
SHA256 705ffbdda3bbbbc8027aae06eead5678dd51bb73dcb1b74d12a30ce5a24b0e3f
MD5 520ddc61a7cbc47a2a3e99dc570d061e
BLAKE2b-256 4395ea5dfa15436b80dd1094f58111a471d8b5207be3b9217ae10fa22f525df4

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page