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Updated: Nov 5, 2025
Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment
Published on: March 11, 2021
Functional brain networks underlying automatic and controlled handwriting in Chinese.
Junjun Li1, Lei Hong2, Hong-Yan Bi1
1CAS Key Laboratory of Behavioral Science, Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
This study reveals that automatic and controlled Chinese handwriting rely on distinct functional brain networks, not different brain activation levels. Network reorganization, not local changes, underlies handwriting automaticity.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Neuroimaging
Background:
- Handwriting involves complex cognitive processes.
- Distinguishing automatic from controlled handwriting is crucial for understanding motor control.
- Previous research has not fully elucidated the neural underpinnings of these distinctions.
Purpose of the Study:
- To identify the functional brain networks differentiating automatic and controlled Chinese handwriting.
- To investigate the neural basis of handwriting automaticity.
Main Methods:
- Functional magnetic resonance imaging (fMRI) was used.
- Network-based analysis was applied to fMRI data.
- Participants performed Chinese character copying tasks under automatic and speed-controlled conditions.
Main Results:
- Significant differences in functional connectivity were observed within and between multiple brain networks (frontoparietal, default mode, dorsal attention, somatomotor, visual networks).
- These connectivity differences correlate with variations in attentional control and visuomotor operations.
- No significant differences in local brain activation were found between the two handwriting conditions.
Conclusions:
- The distinction between automatic and controlled handwriting is primarily based on the reorganization of functional brain networks.
- Handwriting automaticity is underpinned by network dynamics rather than localized activation changes.
- Findings offer insights into handwriting disruptions in neurological disorders.
