Kai Liu

This paper presents a dataset of neural and kinematic recordings from a macaque performing complex hand-object interactions, showing variation in decoding performance across algorithms and channel availability.

This paper introduces Meta-AlignNN, a meta-learning framework that improves BCI stability across subjects, time, and tasks by leveraging neural population dynamics consistency.