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

Bibliographic Data

ID4696820
AuthorsY Qi (0000-0002-9789-8907, Interface (United States), corresponding author), Xinyun Zhu (0009-0007-3820-4761, Zhejiang University), Xinzhu Xiong (Zhejiang University), Xiaomeng Yang (0000-0001-7199-6085, Zhejiang University), Nai Ding (0000-0003-3428-2723, Zhejiang University), Hemmings Wu (0000-0001-9665-2617, Second Affiliated Hospital of Zhejiang University), Kedi Xu (0000-0002-9059-3860, Zhejiang University), Junming Zhu (0000-0002-6160-1323, Second Affiliated Hospital of Zhejiang University, corresponding author), Jianmin Zhang (0000-0002-3184-1502, Second Affiliated Hospital of Zhejiang University), Yueming Wang (0000-0001-7742-0722, Interface (United States), corresponding author)
Year2025
Volume9
Issue6
Pages1260-1271
Publication date2025-04-02
Open AccessYes
TypeARTICLE
VenueNature Human Behaviour (JOURNAL)
Journal identifiersISSN: 2397-3374 • E-ISSN: 2397-3374
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1038/s41562-025-02157-x
PMID40175631
OpenAlexW4409148785
LanguageEN
Citations received1
References cited47

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

Algorithm · Artificial neural network · Biology · Handwriting · Motor cortex · Neural activity · Speech recognition · Action Observation and Synchronization · Computer Science · EEG and Brain-Computer Interfaces · Motor Control and Adaptation · Neuroscience · Psychology · Artificial Intelligence

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

    Open Access•Y Qi, Xinyun Zhu et al.•Nature Human Behaviour•2025

  • Cortical tracking of hierarchical linguistic structures in connected speech

    Open Access•Nai Ding, Lucia Melloni et al.•Nature Neuroscience•2016

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

    Open Access•Y Qi, Xinyun Zhu et al.•Nature Human Behaviour•2025

Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

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