Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
J Comput Neurosci. 2020 Nov;48(4):365-375. doi: 10.1007/s10827-020-00767-0. Epub 2020 Oct 2.
The spinal cord is essential to the control of locomotion in legged animals and humans. However, the actual circuitry of the spinal controller remains only vaguely understood. Here we approach this problem from the viewpoint of learning. More precisely, we assume the circuitry evolves through the transfer of control from the brain to the spinal cord, propose a specific learning mechanism for this transfer based on the error between the cord and brain contributions to muscle control, and study the resulting structure of the spinal controller in a simplified neuromuscular model of human locomotion. The model focuses on the leg rebound behavior in stance and represents the spinal circuitry with 150 muscle reflexes. We find that after learning a spinal controller has evolved that produces leg rebound motions in the absence of a central brain input with only three structural reflex groups. These groups contain individual reflexes well known from physiological experiments but thought to serve separate purposes in the control of human locomotion. Our results suggest a more holistic interpretation of the role of individual sensory projections in spinal networks than is common. In addition, we discuss potential neural correlates for the proposed learning mechanism that may be probed in experiments. Together with such experiments, neuromuscular models of spinal learning likely will become effective tools for uncovering the structure and development of the spinal control circuitry.
脊髓对于有腿动物和人类的运动控制至关重要。然而，脊髓控制器的实际电路仍然只是模糊地了解。在这里，我们从学习的角度来解决这个问题。更准确地说，我们假设电路通过将控制从大脑转移到脊髓来进化，根据脊髓和大脑对肌肉控制的贡献之间的误差，提出了一种特定的学习机制用于这种转移，并在简化的人类运动神经肌肉模型中研究了脊髓控制器的结果结构。该模型侧重于支撑阶段的腿部反弹行为，并使用 150 个肌肉反射来表示脊髓电路。我们发现，经过学习，脊髓控制器已经进化到可以在没有中央大脑输入的情况下产生腿部反弹运动，只需要三个结构反射组。这些组包含了来自生理实验的单个反射，但被认为在人类运动控制中具有不同的作用。我们的结果表明，对于单个感觉投射在脊髓网络中的作用，需要进行更全面的解释，这与常见的解释不同。此外，我们还讨论了拟议学习机制的潜在神经相关物，这些相关物可能在实验中进行探测。与这些实验一起，脊髓学习的神经肌肉模型可能成为揭示脊髓控制电路的结构和发展的有效工具。
