GitHub - facebookresearch/brain2qwerty: Non-invasive decoding of typed sentences from MEG and EEG brain recordings using a convolutional encoder, transformer, and character-level language model. · GitHub
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Brain2Qwerty
Decoding Sentences from Non-Invasive Recordings of the Brain.
Documentation
Project website
Meta blog
Publications
Non-invasive decoding of typed sentences from human brain activity (Nature Neuroscience, 2026).
Accurate Decoding of Natural Sentences from Non-Invasive Brain Recordings (preprint, 2026).
Code
brain2qwerty_v1/
brain2qwerty_v2/
Infrastructure
NeuralSet
NeuralTrain
License
The code is released under CC BY-NC 4.0.
Data
Brain2Qwerty v1: https://huggingface.co/datasets/bcbl190626/SpanishBCBL
Brain2Qwerty v2: under embargo until the paper acceptation.
The datasets are collected by and belong to the BCBL — Basque Center on Cognition, Brain and Language.
About
Non-invasive decoding of typed sentences from MEG and EEG brain recordings using a convolutional encoder, transformer, and character-level language model.
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Readme
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Code of conduct
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Contributing
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Python<br>100.0%
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