A Simple Review of EEG Foundation Models: Datasets, Advancements and Future Perspectives

Electroencephalogram (EEG) signals play a crucial role in understanding brain activity and diagnosing neurological disorders. This review focuses on the recent development of EEG foundation models(EEG-FMs), which have shown great potential in processing and analyzing EEG data. We discuss various EEG-FMs, including their architectures, pre-training strategies, their pre-training and downstream datasets and other details. The review also highlights the challenges and future directions in this field, aiming to provide a comprehensive overview for researchers and practitioners interested in EEG analysis and related EEG-FMs.

@article{lai2025_2504.20069,
  title={ A Simple Review of EEG Foundation Models: Datasets, Advancements and Future Perspectives },
  author={ Junhong Lai and Jiyu Wei and Lin Yao and Yueming Wang },
  journal={arXiv preprint arXiv:2504.20069},
  year={ 2025 }
}