The paper introduces HyBrain, a model that uses spatiotemporal hyperedges to capture coordinated EEG seizure activity more efficiently than pairwise edge approaches. By generating one token per channel per second and pooling them into shared hyperedge embeddings, HyBrain performs well across detection and prediction tasks on TUSZ and CHB‑MIT datasets, achieving top AUROC scores and competitive training resources. A qualitative example shows a single hyperedge tracking the preictal‑ictal‑postictal progression of a real seizure.
By Hyunju Kim, Sheo Yon Jhin, Noseong Park, Nabil Imam
The study evaluates how different graph topologies influence the localization of the epileptogenic zone (EZ) from resting‑state stereo‑EEG recordings in 40 patients. Using a consistent learning model and leave‑one‑patient‑out validation, the authors compare dense graphs, anatomy‑ and geometry‑informed priors, budgeted sparsification, learned sparsification, and a new Region‑Bridge‑c topology. At about 30% edge retention, Region‑Bridge‑c achieves the highest mean PR‑AUC and ROC‑AUC while using roughly 69% fewer edges than a dense graph, indicating that graph construction significantly impacts EZ localization performance.
By Daniel Wendelken (University of Cincinnati, Cincinnati, USA), Brian Ervin (Cincinnati Children's Hospital Medical Center, Cincinnati, USA), Ravindra Arya (Cincinnati Children's Hospital Medical Center, Cincinnati, USA), Ali A. Minai (University of Cincinnati, Cincinnati, USA)
arXiv:2607. 14314v1 Announce Type: new Abstract: Seizure diagnosis from EEG signals is a critical yet persistently challenging task, due to the complicated neural dynamics and the spurious connections in inter-channel modeling.
By Lincan Li, Zheng Chen, Yushun Dong
arXiv:2607. 19429v1 Announce Type: new Abstract: Electroencephalographic (EEG) abnormalities arise from dynamic changes in neural synchrony across spatial and temporal scales, yet many computational approaches reduce these dynamics to static features.
By Maryam Rahimimovassagh, Md Elias Hossain, Ivan Garibay, Niloofar Yousefi
arXiv:2604. 00163v2 Announce Type: replace-cross Abstract: Epileptic seizures are neurological disorders characterized by abnormal and excessive electrical activity in the brain, resulting in recurrent seizure events.
By Ferdaus Anam Jibon, Fazlul Hasan Siddiqui, F. Deeba, Gahangir Hossain
Forecasting time-varying functional connectivity from electroencephalography (EEG) requires modeling both history-dependent trends and structured variability across channels. Conditional flow matching...