2 papers
q-bio.NC2026
Scaling Laws for EEG Decoding: How Much Data Is Enough?
José Maurício Nunes de Oliveira, Bruna J. Lopes, Léo Burgund +2
Deep learning has become a cornerstone of EEG-based brain decoding, with a growing number of architectures proposed every day. However, how the performance of these different model…
eess.SP2026
Automated Artifact Removal in EEG Age Prediction: A systematic comparison
Davoud Hajhassani, Paul-Adrien Graignic, Bruno Aristimunha +8
Automated EEG artifact removal may improve downstream analysis but can also alter predictive information. We benchmarked nine automated artifact removal methods against a common no…