Open access
Oct 2026
Biophysically constrained learning from healthy neural priors improves motor decoding in pathological cortical networks
High-performance brain-computer interfaces (BCIs) rely on stable neural representations, yet brain functional impairments inherently disrupt canonical encoding, creating a fundamental decoding paradox. Conventional data-driven approaches struggle to bridge this gap because of pathological data scarcity and heterogeneit...
Yi-Han Wu, Tao Chang, Si-Liang Chen et al.
· Science Advances · 0 citations