Department of Neurobiology and Behavior, Seeley G. Mudd Hall, Cornell University, Ithaca, NY 14853, USA.
Curr Opin Neurobiol. 2011 Oct;21(5):685-92. doi: 10.1016/j.conb.2011.05.011. Epub 2011 Jun 7.
Central Pattern Generator (CPG) networks, which organize rhythmic movements, have long served as models for neural network organization. Modulatory inputs are essential components of CPG function: neuromodulators set the parameters of CPG neurons and synapses to render the networks functional. Each modulator acts on the network by many effects which may oppose one another; this may serve to stabilize the modulated state. Neuromodulators also determine the active neuronal composition in the CPG, which varies with state changes such as locomotor speed. The pattern of gene expression which determines the electrophysiological personality of each CPG neuron is also under modulatory control. It is not possible to model the function of neural networks without including the actions of neuromodulators.
中枢模式发生器(CPG)网络组织有节奏的运动,长期以来一直是神经网络组织的模型。调制输入是 CPG 功能的重要组成部分:神经调质设定 CPG 神经元和突触的参数,使网络具有功能性。每种调质都通过许多可能相互对立的作用来影响网络;这可能有助于稳定调制状态。神经调质还决定了 CPG 中的活跃神经元组成,这种组成会随着运动速度等状态变化而变化。决定每个 CPG 神经元电生理特性的基因表达模式也受到调质的控制。如果不包括神经调质的作用,就不可能对神经网络的功能进行建模。