Liang-Yin Lu

Abstract Reward-based learning requires neural circuits to rapidly register outcomes and adapt behavior, yet how subcortical circuits contribute to temporally precise reward signaling remains elusive. Here, we identify a cerebellar mechanism encoding rewards with single-trial precision.

Abstract Understanding brain behaviour encoding or designing neuroprosthetics requires identifying precise, consistent neural algorithms across individuals. However, cerebral microstructures and activities are individually variable, posing challenges for identifying precise codes. Here, despite cerebral variability, we report that the cerebellum shapes motor kinematics by encoding dynamic motor frequencies with remarkable numerical precision and cross-individual uniformity.