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

• URL: http://arxiv.org/abs/2504.20069v1
• Date: Thu, 24 Apr 2025 14:14:17 GMT
• Title: A Simple Review of EEG Foundation Models: Datasets, Advancements and Future Perspectives
• Authors: Junhong Lai, Jiyu Wei, Lin Yao, Yueming Wang,
• Abstract summary: Review focuses on the recent development of EEG foundation models (EEG-FMs)<n>EEG-FMs have shown great potential in processing and analyzing EEG data.
• Score: 6.377263838338411
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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