Human motor cortex encodes complex handwriting through a sequence of stable neural states

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.

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Publication Details

Journal
Nature Human Behaviour
Published
2025-04-02
DOI
https://doi.org/10.1038/s41562-025-02157-x
Citations
20
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
28.62

Funders

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article

Human motor cortex encodes complex handwriting through a sequence of stable neural states

Nai Ding, Yu Qi, Hemmings Wu, Kedi Xu et al.
20 citations
Nature Human Behaviour
EEG and Brain-Computer Interfaces
28.62
article

Human motor cortex encodes complex handwriting through a sequence of stable neural states

Nai Ding, Yu Qi, Hemmings Wu, Kedi Xu, Jianmin Zhang, Xiaomeng Yang, Junming Zhu, Yueming Wang, Xinzhu Xiong, Xinyun Zhu
article en
20 citations

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.

Nature Human BehaviourVol. 9(6)
Interface (United States) (US), Zhejiang Lab (CN), Hangzhou Seventh Peoples Hospital (CN), Second Affiliated Hospital of Zhejiang University (CN), Zhejiang University of Technology (CN), Zhejiang University (CN)
National Natural Science Foundation of China, Zhejiang University, Natural Science Foundation of Zhejiang Province
Quality Education
Openalex Percentile: Top 0%
EEG and Brain-Computer Interfaces
28.62
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