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eess.SP2025
Data Normalization Strategies for EEG Deep Learning
Dung Truong, Arnaud Delorme
Normalization is a critical yet often overlooked component in the preprocessing pipeline for EEG deep learning applications. The rise of large-scale pretraining paradigms such as s…
eess.SP2025
EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding
Bruno Aristimunha, Dung Truong, Pierre Guetschel +16
Current electroencephalogram (EEG) decoding models are typically trained on small numbers of subjects performing a single task. Here, we introduce a large-scale, code-submission-ba…
cs.LG2025
From Theory to Application: Fine-Tuning Large EEG Model with Real-World Stress Data
Siwen Wang, Shitou Zhang, Wan-Lin Chen +2
Recent advancements in Large Language Models have inspired the development of foundation models across various domains. In this study, we evaluate the efficacy of Large EEG Models…