Department of Neurobiology and Anatomy, College of Medicine, Drexel University, Philadelphia, PA 19129, USA.
Int J Mol Sci. 2021 Jun 25;22(13):6835. doi: 10.3390/ijms22136835.
Neuronal circuits in the spinal cord are essential for the control of locomotion. They integrate supraspinal commands and afferent feedback signals to produce coordinated rhythmic muscle activations necessary for stable locomotion. For several decades, computational modeling has complemented experimental studies by providing a mechanistic rationale for experimental observations and by deriving experimentally testable predictions. This symbiotic relationship between experimental and computational approaches has resulted in numerous fundamental insights. With recent advances in molecular and genetic methods, it has become possible to manipulate specific constituent elements of the spinal circuitry and relate them to locomotor behavior. This has led to computational modeling studies investigating mechanisms at the level of genetically defined neuronal populations and their interactions. We review literature on the spinal locomotor circuitry from a computational perspective. By reviewing examples leading up to and in the age of molecular genetics, we demonstrate the importance of computational modeling and its interactions with experiments. Moving forward, neuromechanical models with neuronal circuitry modeled at the level of genetically defined neuronal populations will be required to further unravel the mechanisms by which neuronal interactions lead to locomotor behavior.
脊髓中的神经元回路对于运动的控制至关重要。它们整合来自中枢神经系统的指令和传入的反馈信号，产生协调的肌肉节律性激活，从而实现稳定的运动。几十年来，计算建模通过为实验观察提供机械论解释和得出可通过实验检验的预测，补充了实验研究。这种实验和计算方法之间的共生关系产生了许多基本的认识。随着分子和遗传方法的最新进展，已经可以操纵脊髓回路的特定组成部分，并将其与运动行为联系起来。这导致了针对遗传定义的神经元群体及其相互作用层面的机制进行计算建模研究。我们从计算的角度回顾了有关脊髓运动回路的文献。通过回顾从分子遗传学之前到分子遗传学时代的例子，我们展示了计算建模的重要性及其与实验的相互作用。展望未来，需要具有在遗传定义的神经元群体层面建模的神经元回路的神经力学模型，以进一步揭示神经元相互作用导致运动行为的机制。
