The neuromuscular transform: The dynamic, nonlinear link between motor neuron firing patterns and muscle contraction in rhythmic behaviors
The neuromuscular transform: The dynamic, nonlinear link between motor neuron firing patterns and muscle contraction in rhythmic behaviors
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DOI：
10.1152/jn.2000.83.1.207
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发表时间：
2000-01-01
影响因子：
2.5
通讯作者：
Weiss, KR
中科院分区：
文献类型：
--
作者：
Brezina, V;Orekhova, IV;Weiss, KR
神经系统向肌肉发出运动命令以产生行为。然而，所有这些命令都会通过一个过滤器，我们在此称之为神经肌肉变换（NMT）。 NMT 将运动神经元放电模式转变为肌肉收缩。这项工作的动机是 NMT 远不是运动神经元和肌肉之间直接、透明的联系。 NMT 是一种动态、非线性且可修改的滤波器。因此，运动神经元放电以复杂的方式转化为肌肉收缩。神经系统在发出运动命令时必须考虑到这种复杂性，我们在评估其重要性时也必须考虑到这种复杂性。这是我们讨论 NMT 的属性和功能作用的三篇论文中的第一篇。从生理学上讲，运动神经元-肌肉连接包括突触前和突触后 Ca2+ 升高、递质释放和收缩机制激活的多个步骤。 NMT 将所有这些形式化为运动神经元放电模式和肌肉收缩形状之间的整体输入输出关系。我们在这里开发了一个分析框架，本质上是一种基本的动力系统方法，用它我们可以研究变换的全局属性。我们分析了决定不同射击模式如何转换为收缩以及前者的不同参数如何转换为后者参数的原理。 NMT 的关键特性是其非线性及其相对于发射模式的时间尺度的时间依赖性。然后我们讨论神经肌肉预测、控制和编码的问题。放电模式是否包含运动神经元放电的特定参数控制肌肉收缩的特定参数的代码？运动神经元和一般的神经系统必须具有哪些关于外围的信息才能有效地控制它？我们在这里特别关注周期性的、有节奏的收缩，它特别清楚地揭示了原理。在可能的情况下，我们在实验上有利的模型系统（海兔的辅助齿舌闭合器（ARC）开启器神经肌肉系统）中说明了原理。在接下来的论文中，我们使用此处开发的框架来研究 NMT 的特性如何控制神经系统可能命令的不同节律行为的功能表现。
The nervous system issues motor commands to muscles to generate behavior. All such commands muse, however, pass through a filter that we call here the neuromuscular transform (NMT). The NMT transforms patterns of motor neuron firing to muscle contractions. This work is motivated by the fact that the NMT is far from being a straightforward, transparent link between motor neuron and muscle. The NMT is a dynamic, nonlinear, and modifiable filter. Consequently motor neuron firings translates to muscle contraction in a complex way. This complexity must be taken into account by the nervous system when issuing its motor commands, as well as by us when assessing their significance. This is the first of three papers in which we consider the properties and the functional role of the NMT. Physiologically, the motor neuron-muscle link comprises multiple steps of presynaptic and postsynaptic Ca2+ elevation, transmitter release, and activation of the contractile machinery. The NMT formalizes all these into an overall input-output relation between patterns of motor neuron firing and shapes of muscle contractions. We develop here an analytic framework, essentially an elementary dynamical systems approach, with which we can study the global properties of the transformation. We analyze the principles that determine how different firing patterns are transformed to contractions, and different parameters of the former to parameters of the latter. The key properties of the NMT are its nonlinearity and its time dependence, relative to the time scale of the firing pattern. We then discuss issues of neuromuscular prediction, control, and coding. Does the firing pattern contain a code by means of which particular parameters of motor neuron firing control particular parameters of muscle contraction? What information must the motor neuron, and the nervous system generally, have about the periphery to be able to control it effectively? We focus here particularly on cyclical, rhythmic contractions which reveal the principles particularly clearly. Where possible, we illustrate the principles in an experimentally advantageous model system, the accessory radula closer (ARC)-opener neuromuscular system of Aplysia. In the following papers, we use the framework developed here to examine how the properties of the NMT govern functional performance in different rhythmic behaviors that the nervous system may command.