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EEG-Bench: A Benchmark for EEG Foundation Models in Clinical Applications

Ard Kastrati
Josua Bürki
Jonas Lauer
Cheng Xuan
Raffaele Iaquinto
Roger Wattenhofer
Main:5 Pages
1 Figures
Bibliography:2 Pages
22 Tables
Appendix:13 Pages
Abstract

We introduce a unified benchmarking framework focused on evaluating EEG-based foundation models in clinical applications. The benchmark spans 11 well-defined diagnostic tasks across 14 publicly available EEG datasets, including epilepsy, schizophrenia, Parkinson's disease, OCD, and mild traumatic brain injury. It features minimal preprocessing, standardized evaluation protocols, and enables side-by-side comparisons of classical baselines and modern foundation models. Our results show that while foundation models achieve strong performance in certain settings, simpler models often remain competitive, particularly under clinical distribution shifts. To facilitate reproducibility and adoption, we release all prepared data and code in an accessible and extensible format.

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