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Electroencephalography (EEG) based brain-computer interfaces enable direct brain-to-device communication for applications such as rehabilitation and communication. However, their practical utility is often limited as the non-stationary nature of the EEG data introduces distribution shifts across domains (e.g., sessions...
Brain-to-language decoding translates neural activity associated with language production, internal speech and perception into linguistic or expressive outputs. It offers a route to restoring communication after speech loss and a means of studying how the brain represents language. Advances in neural recording and repr...
Hybrid brain-computer interfaces combining electroencephalography and functional near-infrared spectroscopy utilize neurovascular coupling to improve decoding. Current fusion strategies rely on shallow aggregation or complex attention, which struggle to capture complex temporal dynamics and complex dependencies in long...
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