| Summary: | 碩士 === 國立成功大學 === 物理治療學系 === 102 === Objective: It is increasingly prevalent to train visuo-manual skills with a computer monitor. It is functionally important to guide a manual action with sufficient visual gain that determines the amount of spatial visual information on computer monitor. Previous studies have shown that force steadiness and complexity of force variability vary jointly with visual gain, despite that underlying neurophysiological mechanism is still unclear. The purpose of this study was to investigate the effect of visual gain on motor unit (MU) discharge that could link to force variability characteristics.
Methods: Fifteen healthy adults (age: 25.80 ± 3.76 years) without any history of neurological disease were recruited in this study. All participants were instructed to match a target force at 10% maximal voluntary contraction (MVC) on a computer screen under low visual gain (4.8 pixels/%MVC) and high visual gain condition (48 pixels/%MVC). Multi-electrode surface EMG was applied on the first dorsal interosseus muscle to characterize MU discharge pattern following decomposition procedure. Paired-t test was used to compare force variability characteristics (the size, complexity, and mean frequency) and MU discharge patterns (mean inter-spike interval (ISI), ISI complexity, coefficients of variance (CVs) of mean ISI/ISI complexity; mean discharge rate (DR), DR complexity, CVs of mean DR/DR complexity) between low and high visual gain conditions. In addition, Pearson’s correlation analysis was used to determine the correlation between force variability characteristics and MU discharge patterns.
Results: High visual gain led to a smaller size of force variability and an enhanced complexity of force variability than low visual gain. Mean ISI/DR and ISI/DR complexity were not significantly different between the two visual conditions. CVs of mean ISI/DR and ISI/DR complexity among motor units were greater in the high visual gain condition than those in the low visual gain condition. Pearson’s correlation analysis revealed that only the size of force variability was significantly correlated with MU discharge pattern in low visual gain condition, but the complexity and mean frequency of force were not. However, there were no significant correlation between the force variability characteristics and MU discharge patterns in high visual gain condition.
Conclusions: High visual gain for an isometric force task could reduce force steadiness with richer corrective actions, underlying enhanced variations in inter-motor unit discharge pattern. The present studies partly explain the reason why sufficient spatial visual information due to higher visual gain is advantageous to train a visuomotor task on a computer screen.
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