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Updated: Jun 3, 2025

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another
Published on: September 18, 2017
Contributions of the Primary Sensorimotor Cortex and Posterior Parietal Cortex to Motor Learning and Transfer
Chenyu Wang1, Yinghua Yu1, Jiajia Yang1
1Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama 700-8530, Japan.
Background:
Transferring learned manipulations to new manipulation tasks has enabled humans to realize thousands of dexterous object manipulations in daily life. Two-digit grasp and three-digit grasp manipulations require different fingertip forces, and our brain can switch grasp types to ensure good performance according to motor memory. We hypothesized that several brain areas contribute to the execution of the new type of motor according to the motor memory. However, the motor memory mechanisms during this transfer period are still unclear. In the present functional magnetic resonance imaging (fMRI) study, we aimed to investigate the cortical mechanisms involved in motor memory during the transfer phase of learned manipulation tasks.
Methods:
Using a custom-built T-shaped object with an adjustable weight distribution, the participants performed grasp and lift manipulation tasks under different conditions to simulate the learning and transfer phases. The learning phase consisted of four grasp-and-lift repetitions with one motor type, followed by a transfer phase with four repetitions involving different motors (adding or removing a digit).
Results:
By comparing brain activity in the learning and transfer phases, we identified three regions (the superior frontal gyrus, supramarginal gyrus, and postcentral gyrus) associated with motor memory during the transfer of learned manipulations.
Conclusions:
Our findings improve the understanding of the role of the posterior parietal cortex in motor memory, highlighting how sensory information from memory and real-time input is integrated to generate novel motor control signals that guide the precise reapplication of control strategies. Furthermore, we believe that these areas contribute to motor learning from motor memory and may serve as key regions of interest for investigating neurodegenerative diseases.
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