IEEE Trans Neural Syst Rehabil Eng. 2017 Nov;25(11):1930-1939. doi: 10.1109/TNSRE.2017.2701149. Epub 2017 May 4.
Corticomotor coherence in the beta and/or gamma bands has been described in different motor tasks, but the role of descending brain oscillations on force control has been elusive. Large-scale computational models of a motoneuron pool and the muscle it innervates have been used as tools to advance the knowledge of how neural elements may influence force control. Here, we present a frequency domain analysis of a NARX model fitted to a large-scale neuromuscular model by the means of generalized frequency response functions (GFRF). The results of such procedures indicated that the computational neuromuscular model was capable of transforming an oscillatory synaptic input (e.g., at 20 Hz) into a constant mean muscle force output. The nonlinearity uncovered by the GFRFs of the NARX model was responsible for the demodulation of an oscillatory input (e.g., a beta band oscillation coming from the brain and forming the input to the motoneuron pool). This suggests a manner by which brain rhythms descending as command signals to the spinal cord and acting on a motoneuron pool can regulate a maintained muscle force. In addition to the scientific aspects of these results, they provide new interpretations that may further neural engineering applications associated with quantitative neurological diagnoses and robotic systems for artificial limbs.
在不同的运动任务中已经描述了皮质运动相干性在β和/或γ频段，但下行脑振荡对力控制的作用一直难以捉摸。运动神经元池和它支配的肌肉的大规模计算模型已被用作工具，以提高关于神经元件如何影响力控制的知识。在这里，我们通过广义频率响应函数 (GFRF) 对 NARX 模型进行了频域分析，该模型拟合到大规模神经肌肉模型。这些过程的结果表明，计算神经肌肉模型能够将振荡突触输入（例如，在 20 Hz 时）转换为恒定的平均肌肉力输出。NARX 模型的 GFRF 揭示的非线性负责解调振荡输入（例如，来自大脑的β波段振荡并形成运动神经元池的输入）。这表明了一种方式，即作为脊髓的命令信号下降的脑节律并作用于运动神经元池，可以调节维持的肌肉力量。除了这些结果的科学方面外，它们还提供了新的解释，可能会进一步促进与定量神经诊断和人工肢体的机器人系统相关的神经工程应用。
