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Updated: Jul 21, 2025

The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors
Published on: May 2, 2021
A randomized controlled trial of changes in resting-state functional connectivity associated with short-term motor
Sayori Takeda1, Reiko Miyamoto2
1Department of Occupational Therapy, Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10 Higashi-Ogu, Arakawa-ku, Tokyo, Japan.
Introduction:
This study identified the offline brain networks associated with motor learning of non-dominant hand chopstick use within-session.
Methods:
40 healthy right-handed adults were randomly assigned to the practice and control groups (20 each). The performance, resting-state functional connectivity (RSFC), and their correlation were compared within and between groups. Both groups repeated 9 cycles of 30 s task and rest. During the task, the practice group performed the chopstick-use practice with their left hand, while the control group held chopsticks without acquiring any skills. During the rest, both groups fixated their gaze on a fixation point. The number of times candies were moved using chopsticks with the left hand in 30 s was used to evaluate the performance. RSFC was obtained by resting-state fMRI scanning and extracting Z-scores between the right primary motor cortex and all other brain regions.
Results:
Both the groups improved in the post-task performance; the practice group improved more. The RSFC of the two networks increased in the practice group. One network was the RSFC between the right M1 and the right cerebellar Crus I, positively correlated with performance in the post-task. Another was the RSFC between the right M1 and the left cerebellar Crus II, positively correlated with skills in the amount of change pre- and post-task.
Conclusion:
Offline enhancement of RSFC in these networks was shown to contribute to early chopstick-use motor learning with the left hand. These results serve as a basis for future studies on compensatory networks in individuals with stroke.
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