Human motor cortex encodes complex handwriting through a sequence of stable neural states
Yu Qi, Xinyun Zhu, Xinzhu Xiong, Xiaomeng Yang, Nai Ding, Hemmings Wu, Kedi Xu, Junming Zhu, Jianmin Zhang, Yueming Wang
Abstract
How the human motor cortex (MC) orchestrates sophisticated sequences of fine movements such as handwriting remains a puzzle. Here we investigate this question through Utah array recordings from human MC during attempted handwriting of Chinese characters (n = 306, each consisting of 6.3 ± 2.0 strokes). We find that MC activity evolves through a sequence of states corresponding to the writing of stroke fragments during complicated handwriting. The directional tuning curve of MC neurons remains stable within states, but its gain or preferred direction strongly varies across states. By building models that can automatically infer the neural states and implement state-dependent directional tuning, we can significantly better explain the firing pattern of individual neurons and reconstruct recognizable handwriting trajectories with 69% improvement compared with baseline models. Our findings unveil that skilled and sophisticated movements are encoded through state-specific neural configurations. How does the brain encode complex movement sequences? Qi et al. reveal that the brain decomposes sequences into temporal states, each corresponding to a small movement fragment, with motor cortex neurons dynamically altering their encoding across states.