A framework combining pretrained neural representations, geometric constraint embedding, and multidimensional diffusion synthesizes enhanced EEG signals that recover neural activity patterns lost in scalp-to-intracranial propagation.
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Bridging scalp and intracranial EEG in BCI via pretrained neural representations and geometric constraint embedding
A framework combining pretrained neural representations, geometric constraint embedding, and multidimensional diffusion synthesizes enhanced EEG signals that recover neural activity patterns lost in scalp-to-intracranial propagation.