Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

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.

Metadata

Release files for braindecode 1.3.0.dev173577785

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for braindecode 1.3.0.dev173577785
File Size Uploaded
braindecode-1.3.0.dev173577785.tar.gz 293.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for braindecode 1.3.0.dev173577785
File Interpreter ABI Platform
braindecode-1.3.0.dev173577785-py3-none-any.whl Python 3 none any Details

Total release size: 608.2 kB

Release files / braindecode-1.3.0.dev173577785.tar.gz

Download URL braindecode-1.3.0.dev173577785.tar.gz
Size 293.3 kB
Tags Source
SHA-256 checksum
How to use checksums
b4e7f5223138a748c8c9cfdf20e7c0417c557df54d0606832d15778be0a9cf14
BLAKE2b-256 checksum
How to use checksums
7b7108ed3faf87f095c7167784fdcd7dcd66b7e3b41b5066b501e360d5bf1f2b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.7

Release files / braindecode-1.3.0.dev173577785-py3-none-any.whl

Download URL braindecode-1.3.0.dev173577785-py3-none-any.whl
Size 314.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
dd75519fc15ac24e9282017690d4ad3c50114f777ff89f1f42ca242dc38e997e
BLAKE2b-256 checksum
How to use checksums
c7655d13accd9afd9f0f3e3f5287b2384fcf6a065b3d972b6d010d60b43cab7f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.7

Release history Release notifications | RSS feed

1.8.1

2 release files

1.8.0

2 release files

1.7.0

2 release files

1.6.1

2 release files

1.5.2

2 release files

1.5.1

2 release files

1.5.0

2 release files

1.4.0

2 release files

1.3.2

2 release files

1.3.1

2 release files

1.3.0

2 release files

This release

1.2.0

2 release files

1.1.0

2 release files

1.0.0

2 release files

0.8.1

2 release files

0.7

2 release files

0.6

2 release files

0.5.1

2 release files

0.5

1 release file

0.4.85

1 release file

0.4.84

1 release file

0.4.83

1 release file

0.4.82

1 release file

0.4.81

1 release file

0.4.8

1 release file

0.4.7

1 release file

0.4.6

1 release file

0.4.5

1 release file

0.4.4

1 release file

0.4.3

1 release file

0.4.1

1 release file

0.4.0

1 release file

0.3.2

1 release file

0.3.1

1 release file

0.3.0

1 release file

0.2.1

1 release file

0.2.0

1 release file

0.1.9

1 release file

0.1.8

1 release file

0.1.7

1 release file

0.1.6.4

1 release file

0.1.6.3

1 release file

0.1.6.2

1 release file

0.1.6.1

1 release file

0.1.6

1 release file

0.1.5

1 release file

0.1.4

1 release file

0.1.3

1 release file

0.1.2

1 release file

0.1.1

1 release file

0.1.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page