Avrillon Simon, Hug François, Enoka Roger M, Caillet Arnault H D, Farina Dario
Department of Bioengineering, Faculty of Engineering, Imperial College London, London, United Kingdom.
Nantes Université, Laboratory 'Movement, Interactions, Performance', Nantes, France.
Elife. 2024 Dec 9;13:RP97085. doi: 10.7554/eLife.97085.
Movements are performed by motoneurons transforming synaptic inputs into an activation signal that controls muscle force. The control signal emerges from interactions between ionotropic and neuromodulatory inputs to motoneurons. Critically, these interactions vary across motoneuron pools and differ between muscles. To provide the most comprehensive framework to date of motor unit activity during isometric contractions, we identified the firing activity of extensive samples of motor units in the tibialis anterior (129 ± 44 per participant; n=8) and the vastus lateralis (130 ± 63 per participant; n=8) muscles during isometric contractions of up to 80% of maximal force. From this unique dataset, the rate coding of each motor unit was characterised as the relation between its instantaneous firing rate and the applied force, with the assumption that the linear increase in isometric force reflects a proportional increase in the net synaptic excitatory inputs received by the motoneuron. This relation was characterised with a natural logarithm function that comprised two stages. The initial stage was marked by a steep acceleration of firing rate, which was greater for low- than medium- and high-threshold motor units. The second stage comprised a linear increase in firing rate, which was greater for high- than medium- and low-threshold motor units. Changes in firing rate were largely non-linear during the ramp-up and ramp-down phases of the task, but with significant prolonged firing activity only evident for medium-threshold motor units. Contrary to what is usually assumed, our results demonstrate that the firing rate of each motor unit can follow a large variety of trends with force across the pool. From a neural control perspective, these findings indicate how motor unit pools use gain control to transform inputs with limited bandwidths into an intended muscle force.
运动由运动神经元执行，这些神经元将突触输入转化为控制肌肉力量的激活信号。控制信号源自离子型和神经调节性输入与运动神经元之间的相互作用。关键的是，这些相互作用在不同的运动神经元池之间存在差异，并且在不同肌肉之间也有所不同。为了提供迄今为止关于等长收缩期间运动单位活动的最全面框架，我们确定了在最大力量的80%等长收缩期间，胫骨前肌（每位参与者129±44个；n = 8）和股外侧肌（每位参与者130±63个；n = 8）中大量运动单位样本的放电活动。从这个独特的数据集中，每个运动单位的速率编码被表征为其瞬时放电率与施加力之间的关系，并假设等长力的线性增加反映了运动神经元接收到的净突触兴奋性输入的成比例增加。这种关系用一个包含两个阶段的自然对数函数来表征。初始阶段的特征是放电率急剧加速，低阈值运动单位的加速幅度大于中阈值和高阈值运动单位。第二阶段包括放电率的线性增加，高阈值运动单位的增加幅度大于中阈值和低阈值运动单位。在任务的上升和下降阶段，放电率的变化在很大程度上是非线性的，但只有中阈值运动单位表现出明显的延长放电活动。与通常的假设相反，我们的结果表明，每个运动单位的放电率在整个运动单位池中随力量可以呈现出多种趋势。从神经控制的角度来看，这些发现表明运动单位池如何利用增益控制将有限带宽的输入转化为预期的肌肉力量。
