Self‐supervised data‐driven approach defines pathological high‐frequency oscillations in epilepsy

作者：Yipeng Zhang, Atsuro Daida, Lawrence Liu, Naoto Kuroda, Yuanyi Ding, Shingo Oana, Sotaro Kanai, Tonmoy Monsoor, Chenda Duan, Shaun A. Hussain, Joe X Qiao, Noriko Salamon, Aria Fallah, Myung‐Shin Sim, Raman Sankar, Richard J. Staba, Jerome Engel, Eishi Asano, Vwani Roychowdhury, Hiroki Nariai · 发表于：Epilepsia · 年份：2025 · DOI：10.1111/epi.18545 · 被引用次数：9 · 研究领域：Epilepsy research and treatment、EEG and Brain-Computer Interfaces、Functional Brain Connectivity Studies

OBJECTIVE: Interictal high-frequency oscillations (HFOs) are a promising neurophysiological biomarker of the epileptogenic zone (EZ). However, objective criteria for distinguishing pathological from physiological HFOs remain elusive, hindering clinical application. We investigated whether the distinct mechanisms underlying pathological and physiological HFOs are encapsulated in their signal morphology in intracranial electroencephalographic (iEEG) recordings and whether this distinction could be captured by a deep generative model. METHODS: In a retrospective cohort of 185 epilepsy patients who underwent iEEG monitoring, we analyzed 686 410 HFOs across 18 265 brain contacts. To learn morphological characteristics, each event was transformed into a time-frequency plot and input into a variational autoencoder. We characterized latent space clusters containing morphologically defined putative pathological HFOs (mpHFOs) using interpretability analysis, including latent space disentanglement and time-domain perturbation. We built a predictive model to forecast postoperative seizure outcomes at 12 months based on the resection status of brain regions exhibiting mpHFOs. This model was compared to current clinical standards that evaluate outcomes based on the extent of seizure onset zone (SOZ) removal. RESULTS: mpHFOs showed strong associations with expert-defined spikes and were predominantly located within the SOZ. The interpretability analysis discovered novel pathological feature...