| license: mit | |
| pipeline_tag: feature-extraction | |
| # BrainOmni 🧠 | |
| <div align="center"> | |
| [](https://arxiv.org/abs/2505.18185) | |
| [](https://neurips.cc/virtual/2025/poster/117066) | |
| [](https://huggingface.co/sigureling/BrainOmni) | |
| [](https://github.com/OpenTSLab/BrainOmni) | |
| </div> | |
| Official Repository of the paper: | |
| BrainOmni: A Brain Foundation Model for Unified EEG and MEG Signals (NeurIPS 2025) | |
| ## Method | |
| <p align="center"> | |
| <img src="./assets/braintokenizer.png" width="600"> | |
| </p> | |
| <p align="center"> | |
| <img src="./assets/brainomni.png" width="600"> | |
| </p> | |
| <div align="center"> | |
| <b>Overview of BrainOmni</b> | |
| </div> | |
| ## 📢 Citation | |
| If you use BrainOmni model or code, please cite the following paper: | |
| > Qinfan Xiao, Ziyun Cui, Chi Zhang, Siqi Chen, Wen Wu, Andrew Thwaites, Alexandra Woolgar, | |
| Bowen Zhou, Chao Zhang (2025) BrainOmni: A Brain Foundation Model for Unified EEG and MEG Signals, | |
| _arXiv_, [https://arxiv.org/abs/2505.18185](https://arxiv.org/abs/2505.18185) |