From Noise to Insight: Visualizing Neural Dynamics with Segmented SNR Topographies for Improved EEG-BCI Performance
专题命中 EEG解码 :BCI(title,abstract);EEG(title,abstract);brain-computer interface(abstract);分类 q-bio.NC
科学与医疗
脑机接口、EEG、神经信号解码、神经假体和脑控交互。
专题命中 EEG解码 :BCI(title,abstract);EEG(title,abstract);brain-computer interface(abstract);分类 q-bio.NC
专题命中 EEG解码 :EEG(abstract);分类 q-bio.NC
Comments The last two listed authors contributed equally
机构 * Lab for Artificial Intelligence in Medical Imaging, Institute for Diagnostic and Interventional Radiology, School of Medicine and Health, TUM Klinikum, Technical University of Munich (TUM)(人工智能在医学影像中的实验室、诊断与介入放射学研究所、医学与健康学院、TUM医院、慕尼黑技术大学) ; Munich Center for Machine Learning (MCML)(慕尼黑机器学习中心) ; Department of Neuroradiology, School of Medicine and Health, TUM Klinikum, Technical University of Munich (TUM)(神经放射科、医学与健康学院、TUM医院、慕尼黑技术大学)
专题命中 神经信号处理 :cortical(title,abstract)
Comments Accepted for publication in Medical Image Analysis
机构 * Electrical and Computer Engineering, 2 Computer Science, 3 Biomedical Engineering(电气与计算机工程、计算机科学、生物医学工程) ; Viterbi School of Engineering, University of Southern California (USC)(维特比工程学院,南加州大学)
专题命中 神经信号处理 :cortical(abstract);分类 q-bio.NC、cs.LG
Comments Published at the International Conference on Learning Representations (ICLR) 2025. Code is available at GitHub https://github.com/ShanechiLab/BRAID
Journal ref ICLR 2025