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首页> 外文期刊>Journal of Computational Neuroscience >Switching mechanisms and bout times in a pair of reciprocally inhibitory neurons
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Switching mechanisms and bout times in a pair of reciprocally inhibitory neurons

机译:一对相互抑制神经元的转换机制和发作时间

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Within the appropriate parameter regime, a deterministic model of a pair of mutually inhibitory neurons receiving excitatory driving currents exhibits bistability-each of the two stable states corresponds to one neuron being active and the other being quiescent. The presence of noise in the driving currents results in a system that randomly switches back and forth between these two states, causing alternating bouts of spiking activity. In this work, we examine the random bout durations of the two neurons and dependence on system parameters. We find that bout durations of each neuron are exponentially distributed, with changes in system parameters altering only the mean of the distribution. Synaptic inhibition independently controls the bout durations of the two neurons-the mean bout time of a neuron is a function of efferent (or outgoing) inhibition, and is independent of afferent (or incoming) inhibition. Furthermore, we find that the mean bout time of a neuron exhibits a critical dependence on the time course (rather than amplitude) of efferent inhibition-mean bout time of a neuron grows exponentially with the time course of efferent inhibition, and the growth rate of this exponential function depends only on the excitatory driving current to that neuron (and not on any other system parameters). We discuss the relevance of our results to the regulation of sleep-wake cycling by medullary and pontine structures within the brain.
机译:在适当的参数范围内,接收到激励性驱动电流的一对相互抑制的神经元的确定性模型表现出双稳态-两个稳定状态中的每一个对应于一个神经元处于活动状态,而另一个则处于静止状态。驱动电流中存在噪声会导致系统在这两种状态之间来回随机切换,从而导致尖峰活动交替出现。在这项工作中,我们检查了两个神经元的随机搏动持续时间以及对系统参数的依赖性。我们发现每个神经元的回合持续时间呈指数分布,系统参数的变化仅改变分布的均值。突触抑制独立控制两个神经元的发作持续时间-神经元的平均发作时间是传出(或传出)抑制的函数,并且与传出(或传入)抑制无关。此外,我们发现神经元的平均发作时间对传出抑制的时间过程(而不是幅度)表现出关键的依赖性-神经元的平均发作时间随传出抑制的时间过程呈指数增长,并且神经元的生长速率该指数函数仅取决于神经元的兴奋性驱动电流(而不取决于任何其他系统参数)。我们讨论了我们的结果与大脑中髓样和脑桥结构调节睡眠-唤醒循环的相关性。

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