IESSEEG: An Open EEG Dataset Towards Better Understanding of Infantile Epileptic Spasms Syndrome

We introduce IESSEEG, the first open electroencephalography (EEG) dataset dedicated to infantile epileptic spasms syndrome (IESS). IESSEEG comprises approximately 3,172 hours of EEG from 100 pediatric participants, together with diagnosis and treatment-response labels, clinician annotations, Burden of Amplitudes and Epileptiform Discharges (BASED) scores, and clinical metadata. We establish shared benchmarks for diagnosis and treatment-response prediction, comparing traditional quantitative EEG (qEEG) methods with eight EEG foundation models. Both traditional qEEG methods and foundation models achieve strong performance on the diagnosis task, while treatment-response prediction remains more challenging and benefits less consistently from fine-tuning. Further analyses suggest that combining qEEG features, learned representations, and clinical metadata can improve treatment-response prediction. By making these data available with shared benchmarks, IESSEEG enables the community to investigate EEG characteristics associated with IESS and develop more effective methods for diagnosis and treatment-response prediction.