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.dev169361694

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.dev169361694
File Size Uploaded
braindecode-1.3.0.dev169361694.tar.gz 369.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for braindecode 1.3.0.dev169361694
File Interpreter ABI Platform
braindecode-1.3.0.dev169361694-py3-none-any.whl Python 3 none any Details

Total release size: 765.8 kB

Release files / braindecode-1.3.0.dev169361694.tar.gz

Download URL braindecode-1.3.0.dev169361694.tar.gz
Size 369.3 kB
Tags Source
SHA-256 checksum
How to use checksums
5194eba13aa2f64fcbfee0993a6b02740787bbd0620ef54e61934d4be33dbc6f
BLAKE2b-256 checksum
How to use checksums
83698a55e32ebbedec8387117c4e4d7fd02a601e97686e8b2cbea69d74ef638d
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.dev169361694-py3-none-any.whl

Download URL braindecode-1.3.0.dev169361694-py3-none-any.whl
Size 396.5 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d7fb704aa483719a237ccdafb8b77c6a668e992ae87ce646b62410eadd5ed260
BLAKE2b-256 checksum
How to use checksums
c8ff2c0a024daa4647e02ca418c3595a421200eac3aec93f2eae1450c87ce379
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