Department of Mathematics, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, PA, 15260, USA,
J Math Neurosci. 2015 Dec;5(1):26. doi: 10.1186/s13408-015-0026-5. Epub 2015 Jul 17.
Rhythmic behaviors such as breathing, walking, and scratching are vital to many species. Such behaviors can emerge from groups of neurons, called central pattern generators, in the absence of rhythmic inputs. In vertebrates, the identification of the cells that constitute the central pattern generator for particular rhythmic behaviors is difficult, and often, its existence has only been inferred. For example, under experimental conditions, intact turtles generate several rhythmic scratch motor patterns corresponding to non-rhythmic stimulation of different body regions. These patterns feature alternating phases of motoneuron activation that occur repeatedly, with different patterns distinguished by the relative timing and duration of activity of hip extensor, hip flexor, and knee extensor motoneurons. While the central pattern generator network responsible for these outputs has not been located, there is hope to use motoneuron recordings to deduce its properties. To this end, this work presents a model of a previously proposed central pattern generator network and analyzes its capability to produce two distinct scratch rhythms from a single neuron pool, selected by different combinations of tonic drive parameters but with fixed strengths of connections within the network. We show through simulation that the proposed network can achieve the desired multi-functionality, even though it relies on hip unit generators to recruit appropriately timed knee extensor motoneuron activity, including a delay relative to hip activation in rostral scratch. Furthermore, we develop a phase space representation, focusing on the inputs to and the intrinsic slow variable of the knee extensor motoneuron, which we use to derive sufficient conditions for the network to realize each rhythm and which illustrates the role of a saddle-node bifurcation in achieving the knee extensor delay. This framework is harnessed to consider bistability and to make predictions about the responses of the scratch rhythms to input changes for future experimental testing.
节律行为,如呼吸、行走和抓挠,对许多物种至关重要。这种行为可以从被称为中枢模式发生器的神经元群中产生,而无需节律输入。在脊椎动物中,确定构成特定节律行为的中枢模式发生器的细胞是困难的,并且其存在通常只是推断出来的。例如,在实验条件下,完整的海龟会产生几种节律性抓挠运动模式,这些模式对应于不同身体区域的非节律性刺激。这些模式的特征是运动神经元激活的交替相位反复出现,不同的模式通过髋伸肌、髋屈肌和膝伸肌运动神经元活动的相对时间和持续时间来区分。虽然负责这些输出的中枢模式发生器网络尚未定位,但希望使用运动神经元记录来推断其性质。为此,这项工作提出了一个先前提出的中枢模式发生器网络模型,并分析了它从单个神经元池中产生两种不同抓挠节律的能力,这是通过不同的紧张驱动参数组合选择的,但网络内的连接强度固定。通过模拟我们表明,所提出的网络即使依赖于髋部单位发生器来招募适当计时的膝部伸肌运动神经元活动,包括相对于头侧抓挠的髋部激活的延迟,也可以实现所需的多功能性。此外,我们开发了一个相空间表示,重点是膝伸肌运动神经元的输入和固有慢变量,我们使用它来推导出网络实现每种节律的充分条件,并说明了鞍结分岔在实现膝伸肌延迟中的作用。这个框架被用来考虑双稳定性,并对抓挠节律对输入变化的反应进行预测,以便未来进行实验测试。