Matsugu M, Duffin J, Poon C S
Imaging Research Center, Canon Inc., Tokyo, Japan.
J Comput Neurosci. 1998 Mar;5(1):35-51. doi: 10.1023/a:1008826326829.
We studied the dynamical behavior of a class of compound central pattern generator (CPG) models consisting of a simple neural network oscillator driven by both constant and periodic inputs of varying amplitudes, frequencies, and phases. We focused on a specific oscillator composed of two mutually inhibiting types of neuron (inspiratory and expiratory neurons) that may be considered as a minimal model of the mammalian respiratory rhythm generator. The simulation results demonstrated how a simple CPG model--with a minimum number of neurons and mild nonlinearities--may reproduce a host of complex dynamical behaviors under various periodic inputs. In particular, the network oscillated spontaneously only when both neurons received adequate and proportionate constant excitations. In the presence of a periodic source, the spontaneous rhythm was overridden by an entrained oscillation of varying forms depending on the nature of the source. Stable entrained oscillations were inducible by two types of inputs: (1) anti-phase periodic inputs with alternating agonist-antagonist drives to both neurons and (2) a single periodic drive to only one of the neurons. In-phase inputs, which exert periodic drives of similar magnitude and phase relationships to both neurons, resulted in varying disruptions of the entrained oscillations including magnitude attenuation, harmonic and phase distortions, and quasi-periodic interference. In the absence of significant phasic feedback, chaotic motion developed only when the CPG was driven by multiple periodic inputs. Apneic episodes with repetitive alternation of active (intrinsic oscillation) and inactive (cessation of oscillation) states developed when the network was driven by a moderate periodic input of low frequency. Similar results were demonstrated in other, more complex oscillator models (that is, half-center oscillator and three-phase respiratory network model). These theoretical results may have important implications in elucidating the mechanisms of rhythmogenesis in the mature and developing respiratory CPG as well as other compound CPGs in mammalian and invertebrate nervous systems.
我们研究了一类复合中枢模式发生器(CPG)模型的动力学行为,该模型由一个简单神经网络振荡器组成,其受到幅度、频率和相位各异的恒定输入和周期性输入的驱动。我们聚焦于一个由两种相互抑制类型的神经元(吸气神经元和呼气神经元)构成的特定振荡器,它可被视为哺乳动物呼吸节律发生器的最小模型。模拟结果表明,一个具有最少神经元数量和适度非线性的简单CPG模型,如何在各种周期性输入下重现一系列复杂的动力学行为。特别是,只有当两个神经元都接收到足够且成比例的恒定兴奋时,网络才会自发振荡。在存在周期性源的情况下,自发节律会被取决于源性质的不同形式的夹带振荡所取代。稳定的夹带振荡可由两种类型的输入诱导产生:(1)对两个神经元具有交替激动剂 - 拮抗剂驱动的反相周期性输入,以及(2)仅对其中一个神经元的单个周期性驱动。同相输入对两个神经元施加幅度和相位关系相似的周期性驱动,会导致夹带振荡出现不同程度的干扰,包括幅度衰减、谐波和相位失真以及准周期性干扰。在没有显著相位反馈的情况下,只有当CPG由多个周期性输入驱动时才会出现混沌运动。当网络由低频的适度周期性输入驱动时,会出现具有主动(内在振荡)和非主动(振荡停止)状态重复交替的呼吸暂停发作。在其他更复杂的振荡器模型(即半中枢振荡器和三相呼吸网络模型)中也得到了类似结果。这些理论结果对于阐明成熟和发育中的呼吸CPG以及哺乳动物和无脊椎动物神经系统中其他复合CPG中的节律产生机制可能具有重要意义。