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神经控制对运动噪声操纵的适应性

Neural Control Adaptation to Motor Noise Manipulation.

作者信息

Hasson Christopher J, Gelina Olga, Woo Garrett

机构信息

Neuromotor Systems Laboratory, Department of Physical Therapy, Movement and Rehabilitation Sciences, Northeastern University Boston, MA, USA.

出版信息

Front Hum Neurosci. 2016 Mar 1;10:59. doi: 10.3389/fnhum.2016.00059. eCollection 2016.

Abstract

Antagonistic muscular co-activation can compensate for movement variability induced by motor noise at the expense of increased energetic costs. Greater antagonistic co-activation is commonly observed in older adults, which could be an adaptation to increased motor noise. The present study tested this hypothesis by manipulating motor noise in 12 young subjects while they practiced a goal-directed task using a myoelectric virtual arm, which was controlled by their biceps and triceps muscle activity. Motor noise was increased by increasing the coefficient of variation (CV) of the myoelectric signals. As hypothesized, subjects adapted by increasing antagonistic co-activation, and this was associated with reduced noise-induced performance decrements. A second hypothesis was that a virtual decrease in motor noise, achieved by smoothing the myoelectric signals, would have the opposite effect: co-activation would decrease and motor performance would improve. However, the results showed that a decrease in noise made performance worse instead of better, with no change in co-activation. Overall, these findings suggest that the nervous system adapts to virtual increases in motor noise by increasing antagonistic co-activation, and this preserves motor performance. Reducing noise may have failed to benefit performance due to characteristics of the filtering process itself, e.g., delays are introduced and muscle activity bursts are attenuated. The observed adaptations to increased noise may explain in part why older adults and many patient populations have greater antagonistic co-activation, which could represent an adaptation to increased motor noise, along with a desire for increased joint stability.

摘要

拮抗肌共同激活可以补偿由运动噪声引起的运动变异性,但代价是能量消耗增加。在老年人中通常观察到更强的拮抗肌共同激活,这可能是对运动噪声增加的一种适应。本研究通过在12名年轻受试者练习使用肌电虚拟手臂的目标导向任务时操纵运动噪声来检验这一假设,该虚拟手臂由他们的肱二头肌和肱三头肌活动控制。通过增加肌电信号的变异系数(CV)来增加运动噪声。正如所假设的,受试者通过增加拮抗肌共同激活来进行适应,这与噪声引起的性能下降减少有关。第二个假设是,通过平滑肌电信号实现的运动噪声虚拟降低会产生相反的效果:共同激活会减少,运动性能会提高。然而,结果表明,噪声降低使性能变差而非变好,共同激活没有变化。总体而言,这些发现表明,神经系统通过增加拮抗肌共同激活来适应运动噪声的虚拟增加,这有助于保持运动性能。由于滤波过程本身的特性,例如引入了延迟和肌肉活动爆发减弱,降低噪声可能未能使性能受益。观察到的对噪声增加的适应可能部分解释了为什么老年人和许多患者群体具有更强的拮抗肌共同激活,这可能代表了对运动噪声增加的一种适应,以及对增加关节稳定性的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13a6/4771770/e7dc92e8030d/fnhum-10-00059-g0001.jpg

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本文引用的文献

1
Effects of kinematic vibrotactile feedback on learning to control a virtual prosthetic arm.
J Neuroeng Rehabil. 2015 Mar 24;12:31. doi: 10.1186/s12984-015-0025-5.
2
Neural representation of muscle dynamics in voluntary movement control.
Exp Brain Res. 2014 Jul;232(7):2105-19. doi: 10.1007/s00221-014-3901-5. Epub 2014 Mar 26.
3
Healthy and dystonic children compensate for changes in motor variability.
J Neurophysiol. 2013 Apr;109(8):2169-78. doi: 10.1152/jn.00908.2012. Epub 2013 Jan 23.
4
Age-related decreases in motor unit discharge rate and force control during isometric plantar flexion.
J Electromyogr Kinesiol. 2012 Dec;22(6):983-9. doi: 10.1016/j.jelekin.2012.05.009. Epub 2012 Jun 28.
5
Muscle coordination is habitual rather than optimal.
J Neurosci. 2012 May 23;32(21):7384-91. doi: 10.1523/JNEUROSCI.5792-11.2012.
6
Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness.
J Neurophysiol. 2012 Jun;107(12):3357-69. doi: 10.1152/jn.00938.2011. Epub 2012 Mar 14.
7
Reduction of metabolic cost during motor learning of arm reaching dynamics.
J Neurosci. 2012 Feb 8;32(6):2182-90. doi: 10.1523/JNEUROSCI.4003-11.2012.
8
Effects of age on mechanical properties of dorsiflexor and plantarflexor muscles.
Ann Biomed Eng. 2012 May;40(5):1088-101. doi: 10.1007/s10439-011-0481-4. Epub 2011 Dec 21.
9
Impedance control reduces instability that arises from motor noise.
J Neurosci. 2009 Oct 7;29(40):12606-16. doi: 10.1523/JNEUROSCI.2826-09.2009.
10
Assisted movement with enhanced sensation (AMES): coupling motor and sensory to remediate motor deficits in chronic stroke patients.
Neurorehabil Neural Repair. 2009 Jan;23(1):67-77. doi: 10.1177/1545968308317437. Epub 2008 Jul 21.

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