1 citations · 1 across the 3 of their papers we have counts for
5 papers
Beyond Flattened Tokens: Structure-Preserving EEG Decoding with Reusable TriDim Blocks
Shiyue Su, Song Wang, Zekai Zhan +7
Effective EEG decoding requires representations that preserve organization among channels, local waveform dynamics, and long-range temporal context. Existing EEG architectures ofte…
Omni-Sleep: A Sleep Foundation Model via Hierarchical Contrastive Learning of CNS-ANS Dynamics
Zhoujie Hou, Song Wang, Kexin Lou +3
Sleep physiology arises from the coordinated dynamics of the central nervous system (CNS) and autonomic nervous system (ANS), as reflected by multimodal polysomnography signals inc…
A geometry aware framework enhances noninvasive mapping of whole human brain dynamics
Song Wang, Kexin Lou, Chen Wei +8
Non-invasive electrophysiology lacks methods that accurately reconstruct whole-brain spatiotemporal dynamics while incorporating individual cortical geometry, leaving current elect…
Uncovering the EEG Temporal Representation of Low-dimensional Object Properties
Jiahua Tang, Song Wang, Jiachen Zou +2
Understanding how the human brain encodes and processes external visual stimuli has been a fundamental challenge in neuroscience. With advancements in artificial intelligence, soph…
Advancing EEG/MEG Source Imaging with Geometric-Informed Basis Functions
Song Wang, Chen Wei, Kexin Lou +2
Electroencephalography (EEG) and Magnetoencephalography (MEG) are pivotal in understanding brain activity but are limited by their poor spatial resolution. EEG/MEG source imaging (…