Lower complexity of motor primitives ensures robust control of high-speed human locomotion.
Lower complexity of motor primitives ensures robust control of high-speed human locomotion.
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较低的运动原语的复杂性可确保对高速人类运动的强大控制。
DOI：
10.1016/j.heliyon.2020.e05377
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发表时间：
2020-10
期刊：
影响因子：
4
通讯作者：
Arampatzis A
中科院分区：
文献类型：
--
作者：
Santuz A;Ekizos A;Kunimasa Y;Kijima K;Ishikawa M;Arampatzis A
步行和跑步是机械上和能量上不同的运动方式。在进行选择时，速度是最重要的参数。然而，两者可能都是由类似的低维神经网络控制的，这些网络反映了被称为肌肉协同作用的肌肉激活模式。在这里，我们通过让我们的参与者以非常广泛的次最大和最大速度行走和跑步来挑战人类的运动能力。通过非负矩阵分解对肌电图数据进行分解，得到下肢运动肌肉的协同激活。我们分析了运动基元的持续时间和复杂性（通过分形分析），肌肉协同作用的时间成分。我们发现，高速运动的运动控制是如此具有挑战性，以至于神经运动系统被迫产生更广泛、更简单的肌肉激活模式。随着运动速度的变化，电机模块或时间无关系数被重新分配。这些结果表明，人类通过一系列策略来适应神经运动动力学，从而有效地创造和控制运动，从而应对高速运动的挑战。神经科学;生理学;生物医学工程;生物力学;生物力学工程;行为神经科学;系统神经科学;临床研究;运动;肌肉的协同效应;电机控制;短跑;走到跑的过渡；分形维数;复杂性
Walking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we challenged human locomotion by having our participants walk and run at a very broad spectrum of submaximal and maximal speeds. The synergistic activations of lower limb locomotor muscles were obtained through decomposition of electromyographic data via non-negative matrix factorization. We analyzed the duration and complexity (via fractal analysis) over time of motor primitives, the temporal components of muscle synergies. We found that the motor control of high-speed locomotion was so challenging that the neuromotor system was forced to produce wider and less complex muscle activation patterns. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that humans cope with the challenges of high-speed locomotion by adapting the neuromotor dynamics through a set of strategies that allow for efficient creation and control of locomotion. Neuroscience; Physiology; Biomedical engineering; Biomechanics; Biomechanical engineering; Behavioral neuroscience; Systems neuroscience; Clinical research; Locomotion; Muscle synergies; Motor control; Sprinting; Walk to run transition; Fractal dimension; Complexity
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DOI：
10.3390/molecules23082074
发表时间：
2018-08-19
期刊：
Molecules (Basel, Switzerland)
影响因子：
--
作者：
Gentili PL
通讯作者：
Gentili PL
影响因子：
25
作者：
Cregg JM;Leiras R;Montalant A;Wanken P;Wickersham IR;Kiehn O
通讯作者：
Kiehn O
影响因子：
2.4
作者：
Arampatzis, A;Brüggemann, GP;Metzler, V
通讯作者：
Metzler, V
影响因子：
--
作者：
Bizzi, E.;Cheung, V. C. K.;Tresch, M.
通讯作者：
Tresch, M.
影响因子：
5.3
作者：
Akay, Turgay;Ludwar, Bjoern Ch.;Bueschges, Ansgar
通讯作者：
Bueschges, Ansgar