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Practice reduces task relevant variance modulation and forms nominal trajectory
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DOI：10.1038/srep17659.png)
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摘要
En 中文
Humans are capable of achieving complex tasks with redundant degrees of freedom. Much attention has been paid to task relevant variance modulation as an indication of online feedback control strategies to cope with motor variability. Meanwhile, it has been discussed that the brain learns internal models of environments to realize feedforward control with nominal trajectories. Here we examined trajectory variance in both spatial and temporal domains to elucidate the relative contribution of these control schemas. We asked subjects to learn reaching movements with multiple via-points, and found that hand trajectories converged to stereotyped trajectories with the reduction of task relevant variance modulation as learning proceeded. Furthermore, variance reduction was not always associated with task constraints but was highly correlated with the velocity profile. A model assuming noise both on the nominal trajectory and motor command was able to reproduce the observed variance modulation, supporting an expression of nominal trajectories in the brain. The learning-related decrease in task-relevant modulation revealed a reduction in the influence of optimal feedback around the task constraints. After practice, the major part of computation seems to be taken over by the feedforward controller around the nominal trajectory with feedback added only when it becomes necessary.
Keyword:
OPTIMAL FEEDBACK-CONTROL
SIGNAL-DEPENDENT NOISE
IMPEDANCE CONTROL
MOTOR CONTROL
NEURAL BASIS
MOVEMENTS
REPRESENTATIONS
COORDINATION
VARIABILITY
ACCURACY
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期刊
IF:
3.9
论文数:
27.9W
被引数:
83.5W
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