Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria.
Department of Neurobiology, Poznan University of Physical Education, Poznan, Poland.
PLoS Comput Biol. 2021 Apr 26;17(4):e1008282. doi: 10.1371/journal.pcbi.1008282. eCollection 2021 Apr.
The synchronized firings of active motor units (MUs) increase the oscillations of muscle force, observed as physiological tremor. This study aimed to investigate the effects of synchronizing the firings within three types of MUs (slow-S, fast resistant to fatigue-FR, and fast fatigable-FF) on the muscle force production using a mathematical model of the rat medial gastrocnemius muscle. The model was designed based on the actual proportion and physiological properties of MUs and motoneurons innervating the muscle. The isometric muscle and MU forces were simulated by a model predicting non-synchronized firing of a pool of 57 MUs (including 8 S, 23 FR, and 26 FF) to ascertain a maximum excitatory signal when all MUs were recruited into the contraction. The mean firing frequency of each MU depended upon the twitch contraction time, whereas the recruitment order was determined according to increasing forces (the size principle). The synchronization of firings of individual MUs was simulated using four different modes and inducing the synchronization of firings within three time windows (± 2, ± 4, and ± 6 ms) for four different combinations of MUs. The synchronization was estimated using two parameters, the correlation coefficient and the cross-interval synchronization index. The four scenarios of synchronization increased the values of the root-mean-square, range, and maximum force in correlation with the increase of the time window. Greater synchronization index values resulted in higher root-mean-square, range, and maximum of force outcomes for all MU types as well as for the whole muscle output; however, the mean spectral frequency of the forces decreased, whereas the mean force remained nearly unchanged. The range of variability and the root-mean-square of forces were higher for fast MUs than for slow MUs; meanwhile, the relative values of these parameters were highest for slow MUs, indicating their important contribution to muscle tremor, especially during weak contractions.
运动单位(MU)的同步放电会增加肌肉力量的振荡,表现为生理性震颤。本研究旨在使用大鼠内侧腓肠肌的数学模型,研究同步三种 MU(慢-S、抗疲劳快-FR 和易疲劳快-FF)放电对肌肉力量产生的影响。该模型是基于 MU 和支配肌肉的运动神经元的实际比例和生理特性设计的。通过预测 57 个 MU(包括 8 个 S、23 个 FR 和 26 个 FF)的非同步放电的模型来模拟等长肌肉和 MU 力,以确定当所有 MU 都被募集到收缩中时最大兴奋性信号。每个 MU 的平均放电频率取决于抽搐收缩时间,而募集顺序则根据增加的力(大小原则)来确定。使用四种不同模式模拟单个 MU 的放电同步,并在四个不同 MU 组合的三个时间窗口(±2、±4 和±6ms)中诱导放电同步。使用两个参数估计同步,即相关系数和交叉间隔同步指数。四个同步场景增加了均方根、范围和最大力的值,与时间窗口的增加成正比。对于所有 MU 类型以及整个肌肉输出,更高的同步指数值导致更高的均方根、范围和最大力结果;然而,力的平均谱频率降低,而平均力几乎保持不变。快 MU 的力的变异性范围和均方根高于慢 MU;同时,这些参数的相对值对于慢 MU 最高,表明它们对肌肉震颤的重要贡献,尤其是在弱收缩期间。