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Firing rate equations require a spike synchrony mechanism to correctly describe fast oscillations in inhibitory networks

机译:点火速率方程式需要一个尖峰同步机制来正确描述抑制网络中的快速振荡

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摘要

Recurrently coupled networks of inhibitory neurons robustly generate oscillations in the gamma band. Nonetheless, the corresponding Wilson-Cowan type firing rate equation for such an inhibitory population does not generate such oscillations without an explicit time delay. We show that this discrepancy is due to a voltage-dependent spike-synchronization mechanism inherent in networks of spiking neurons which is not captured by standard firing rate equations. Here we investigate an exact low-dimensional description for a network of heterogeneous canonical Class 1 inhibitory neurons which includes the sub-threshold dynamics crucial for generating synchronous states. In the limit of slow synaptic kinetics the spike-synchrony mechanism is suppressed and the standard Wilson-Cowan equations are formally recovered as long as external inputs are also slow. However, even in this limit synchronous spiking can be elicited by inputs which fluctuate on a time-scale of the membrane time-constant of the neurons. Our meanfield equations therefore represent an extension of the standard Wilson-Cowan equations in which spike synchrony is also correctly described.
机译:抑制神经元的循环耦合网络会在γ波段强烈产生振荡。但是,在没有明确的时间延迟的情况下,针对这种抑制种群的相应的Wilson-Cowan型点火速率方程不会产生这种振荡。我们表明,这种差异是由于尖峰神经元网络中固有的电压依赖性尖峰同步机制所致,而该机制并未通过标准的发射速率方程式捕获。在这里,我们研究了异类规范的1类抑制神经元网络的精确低维描述,其中包括对产生同步状态至关重要的亚阈值动力学。只要外部输入也很慢,在慢突触动力学的极限内,尖峰共鸣机制就被抑制,标准的Wilson-Cowan方程式就可以正式恢复。然而,即使在该极限下,也可以通过在神经元的膜时间常数的时间尺度上波动的输入引起同步尖峰。因此,我们的均值场方程表示标准Wilson-Cowan方程的扩展,其中也正确描述了尖峰同步。

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