Prochazka Arthur, Yakovenko Sergiy
Centre for Neuroscience, 507 HMRC University of Alberta, Edmonton, AB T6G 2S2, Canada.
Prog Brain Res. 2007;165:255-65. doi: 10.1016/S0079-6123(06)65016-4.
Simulations performed with neuromechanical models are providing insight into the neural control of locomotion that would be hard if not impossible to obtain in any other way. We first discuss the known properties of the neural mechanisms controlling locomotion, with a focus on mammalian systems. The rhythm-generating properties of central pattern generators (CPGs) are discussed in light of results indicating that cycle characteristics may be preset by tonic drive to spinal interneuronal networks. We then describe neuromechanical simulations that have revealed some basic rules of interaction between CPGs, sensory-mediated switching mechanisms and the biomechanics of locomotor movements. We posit that the spinal CPG timer and the sensory-mediated switch operate in parallel, the former being driven primarily by descending inputs and the latter by the kinematics. The CPG timer produces extensor and flexor phase durations, which covary along specific lines in a plot of phase- versus cycle-duration. We coined the term "phase-duration characteristics" to describe such plots. Descending input from higher centers adjusts the operating points on the phase-duration characteristics according to anticipated biomechanical requirements. In well-predicted movements, CPG-generated phase durations closely match those required by the kinematics, minimizing the corrections in phase duration required of the sensory switching mechanism. We propose the term "neuromechanical tuning" to describe this process of matching the CPG to the kinematics.
使用神经力学模型进行的模拟,正在为深入了解运动的神经控制提供帮助,而以任何其他方式都很难(甚至不可能)获得这样的认识。我们首先讨论控制运动的神经机制的已知特性,重点是哺乳动物系统。鉴于有结果表明,周期特征可能由对脊髓中间神经元网络的紧张性驱动预先设定,我们将讨论中枢模式发生器(CPG)的节律产生特性。然后,我们将描述神经力学模拟,这些模拟揭示了CPG、感觉介导的切换机制与运动动作生物力学之间相互作用的一些基本规则。我们假定脊髓CPG定时器和感觉介导的开关并行运作,前者主要由下行输入驱动,后者由运动学驱动。CPG定时器产生伸肌和屈肌的相位持续时间,在相位与周期持续时间的关系图中,它们沿着特定的线共同变化。我们创造了“相位持续时间特征”这个术语来描述这样的关系图。来自高级中枢的下行输入根据预期的生物力学需求调整相位持续时间特征上的工作点。在预测良好的运动中,CPG产生的相位持续时间与运动学所需的相位持续时间紧密匹配,从而将感觉切换机制所需的相位持续时间校正减至最小。我们提出“神经力学调谐”这个术语来描述使CPG与运动学相匹配的这一过程。