Discriminating interictal and ictal brain states is important for both seizure-state classification and the characterization of seizure-related network reorganization in drug-resistant epilepsy. Intracranial electroencephalography (iEEG) provides high-resolution recordings of brain activity, but its sparse, irregular,...
Qing Cai, Yu-Shi Hao, Jian-Peng An et al.· Chaos· 0 citations
A novel Multi-Frequency Topological Neural Network that jointly captures topological and spatial–temporal characteristics of EEG signals is proposed that underscores the importance of incorporating brain topology into deep learning frameworks and highlights the effectiveness of multi-frequency feature fusion for improv...
Ying-Chun Mei, Jia-Lu Sun, Da-Wan Wang et al.· Italian National Conference...· 0 citations
The proposed MTGNet framework provides a practical approach to task-aware EEG denoising, while future work should further validate its applicability across real-world EEG settings involving diverse tasks, artifact types, and acquisition conditions.
Jin-Cheng Hu, Zhong-Ke Gao, Yu-Shi Hao et al.· Journal of Neural Engineerin...· 0 citations
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