Currently, it is accepted that animal locomotion is controlled by a central pattern generator in the spinal cord. Experiments and models show that rhythm generating neurons and genetically determined network properties could sustain oscillatory output activity suitable for locomotion. However, current central pattern generator models do not explain how a spinal cord circuitry, which has the same basic genetic plan across species, can adapt to control the different biomechanical properties and locomotion patterns existing in these species. Here we demonstrate that rhythmic and alternating movements in pendulum models can be learned by a monolayer spinal cord circuitry model using the Bienenstock–Cooper–Munro learning rule, which has been previously proposed to explain learning in the visual cortex. These results provide an alternative theory to central pattern generator models, because rhythm generating neurons and genetically defined connectivity are not required in our model. Though our results are not in contradiction to current models, as existing neural mechanism and structures, not used in our model, can be expected to facilitate the kind of learning demonstrated here. Therefore, our model could be used to augment existing models.

目前，人们普遍认为动物的运动是由脊髓中的中央模式发生器控制的。实验和模型表明，节律生成神经元和遗传决定的网络特性可以维持适合运动的振荡输出活动。然而，当前的中枢模式生成器模型无法解释跨物种具有相同基本遗传计划的脊髓回路如何适应控制这些物种中存在的不同生物力学特性和运动模式。在这里，我们证明钟摆模型中的节律和交替运动可以通过使用 Bienenstock-Cooper-Munro 学习规则的单层脊髓回路模型来学习，该规则之前已被提出来解释视觉皮层的学习。这些结果为中央模式生成器模型提供了另一种理论，因为我们的模型不需要生成节律的神经元和遗传定义的连接性。尽管我们的结果与当前模型并不矛盾，但由于我们的模型中未使用现有的神经机制和结构，因此可以预期促进此处演示的学习。因此，我们的模型可用于增强现有模型。