Cheng Ernest J, Loeb Gerald E
Department of Biomedical Engineering, University of Southern California, 1042 Downey Way, DRB-B8, Los Angeles, CA 90089-1112, USA.
J Neural Eng. 2008 Jun;5(2):232-53. doi: 10.1088/1741-2560/5/2/014. Epub 2008 May 27.
The intrinsic viscoelastic properties of muscle are central to many theories of motor control. Much of the debate over these theories hinges on varying interpretations of these muscle properties. In the present study, we describe methods whereby a comprehensive musculoskeletal model can be used to make inferences about motor control strategies that would account for behavioral data. Muscle activity and kinematic data from a monkey were recorded while the animal performed a single degree-of-freedom pointing task in the presence of pseudo-random torque perturbations. The monkey's movements were simulated by a musculoskeletal model with accurate representations of musculotendon morphometry and contractile properties. The model was used to quantify the impedance of the limb while moving rapidly, the differential action of synergistic muscles, the relative contribution of reflexes to task performance and the completeness of recorded EMG signals. Current methods to address these issues in the absence of musculoskeletal models were compared with the methods used in the present study. We conclude that musculoskeletal models and kinetic analysis can improve the interpretation of kinematic and electrophysiological data, in some cases by illuminating shortcomings of the experimental methods or underlying assumptions that may otherwise escape notice.
肌肉的内在粘弹性特性是许多运动控制理论的核心。围绕这些理论的许多争论都取决于对这些肌肉特性的不同解释。在本研究中，我们描述了一些方法，通过这些方法可以使用一个综合的肌肉骨骼模型来推断能够解释行为数据的运动控制策略。在猴子执行单自由度指向任务并存在伪随机扭矩扰动的情况下，记录了猴子的肌肉活动和运动学数据。猴子的运动由一个准确表示肌腱形态和收缩特性的肌肉骨骼模型进行模拟。该模型用于量化肢体快速移动时的阻抗、协同肌肉的差异作用、反射对任务表现的相对贡献以及记录的肌电图信号的完整性。将目前在没有肌肉骨骼模型的情况下解决这些问题的方法与本研究中使用的方法进行了比较。我们得出结论，肌肉骨骼模型和动力学分析可以改善对运动学和电生理数据的解释，在某些情况下，通过揭示实验方法的缺点或可能被忽视的潜在假设来实现。
