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时变肌肉收缩控制中的神经肌肉机制和神经策略。

Neuromuscular mechanisms and neural strategies in the control of time-varying muscle contractions.

机构信息

Laboratory of Systems Physiology, Basic Sciences, Medical School, University of Crete, Heraklion, Greece; and.

出版信息

J Neurophysiol. 2013 Sep;110(6):1404-14. doi: 10.1152/jn.00835.2012. Epub 2013 Jun 26.

Abstract

The organization of the neural input to motoneurons that underlies time-varying muscle force is assumed to depend on muscle transfer characteristics and neural strategies or control modes utilizing sensory signals. We jointly addressed these interlinked, but previously studied individually and partially, issues for sinusoidal (range 0.5-5.0 Hz) force-tracking contractions of a human finger muscle. Using spectral and correlation analyses of target signal, force signal, and motor unit (MU) discharges, we studied 1) patterns of such discharges, allowing inferences on the motoneuronal input; 2) transformation of MU population activity (EMG) into quasi-sinusoidal force; and 3) relation of force oscillation to target, carrying information on the input's organization. A broad view of force control mechanisms and strategies emerged. Specifically, synchronized MU and EMG modulations, reflecting a frequency-modulated motoneuronal input, accompanied the force variations. Gain and delay drops between EMG modulation and force oscillation, critical for the appropriate organization of this input, occurred with increasing target frequency. According to our analyses, gain compensation was achieved primarily through rhythmical activation/deactivation of higher-threshold MUs and secondarily through the adaptation of the input's strength expected during tracking tasks. However, the input's timing was not adapted to delay behaviors and seemed to depend on the control modes employed. Thus, for low-frequency targets, the force oscillation was highly coherent with, but led, a target, this timing error being compatible with predictive feedforward control partly based on the target's derivatives. In contrast, the force oscillation was weakly coherent, but in phase, with high-frequency targets, suggesting control mainly based on a target's rhythm.

摘要

神经输入到运动神经元的组织,是肌肉力量随时间变化的基础,这被认为取决于肌肉传递特性和利用感觉信号的神经策略或控制模式。我们共同解决了这些相互关联的问题,但之前都是分别和部分地进行研究的,这些问题涉及到人类手指肌肉的正弦(0.5-5.0Hz 范围内)力跟踪收缩。我们使用目标信号、力信号和运动单位(MU)放电的频谱和相关分析,研究了 1)这些放电模式,允许对运动神经元输入进行推断;2)MU 群体活动(EMG)转化为准正弦力;以及 3)力振荡与目标的关系,携带有关输入组织的信息。出现了一种对力控制机制和策略的广泛看法。具体而言,伴随着力的变化,同步的 MU 和 EMG 调制反映了频率调制的运动神经元输入。EMG 调制和力振荡之间的增益和延迟下降,对于适当组织这种输入至关重要,随着目标频率的增加而发生。根据我们的分析,增益补偿主要通过较高阈值 MU 的节律性激活/失活来实现,其次通过在跟踪任务中预期的输入强度的适应性来实现。然而,输入的定时并没有适应延迟行为,似乎取决于所采用的控制模式。因此,对于低频目标,力振荡与目标高度相干,但领先于目标,这种定时误差与部分基于目标导数的预测前馈控制相兼容。相比之下,力振荡与高频目标弱相干,但同相,这表明主要基于目标的节律进行控制。

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