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license: gpl-3.0 |
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## Neuro-GPT: Towards a Foundation Model for EEG [paper](https://arxiv.org/abs/2311.03764) |
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#### Published on IEEE - ISBI 2024 |
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We propose Neuro-GPT, a foundation model consisting of an EEG encoder and a GPT model. The foundation model is pre-trained on a large-scale data set using a self-supervised task that learns how to reconstruct masked EEG segments. We then fine-tune the model on a Motor Imagery Classification task to validate its performance in a low-data regime (9 subjects). Our experiments demonstrate that applying a foundation model can significantly improve classification performance compared to a model trained from scratch. |
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## Installation |
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```console |
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git clone [email protected]:wenhui0206/NeuroGPT.git |
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pip install -r requirements.txt |
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cd NeuroGPT/scripts |
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./train.sh |
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``` |
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## Requirements |
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pip install -r requirements.txt |
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## Datasets |
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- [TUH EEG Corpus](https://isip.piconepress.com/projects/tuh_eeg/html/downloads.shtml#c_tueg) |
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- [BCI Competition IV 2a Dataset](https://www.bbci.de/competition/iv/#datasets) |
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