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Chaotic Resonance in Typical Routes to Chaos in the Izhikevich Neuron Model

机译:Izhikevich神经元模型中典型的混沌路径中的混沌共振。

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摘要

Chaotic resonance (CR), in which a system responds to a weak signal through the effects of chaotic activities, is a known function of chaos in neural systems. The current belief suggests that chaotic states are induced by different routes to chaos in spiking neural systems. However, few studies have compared the efficiency of signal responses in CR across the different chaotic states in spiking neural systems. We focused herein on the Izhikevich neuron model, comparing the characteristics of CR in the chaotic states arising through the period-doubling or tangent bifurcation routes. We found that the signal response in CR had a unimodal maximum with respect to the stability of chaotic orbits in the tested chaotic states. Furthermore, the efficiency of signal responses at the edge of chaos became especially high as a result of synchronization between the input signal and the periodic component in chaotic spiking activity.
机译:混沌共振(CR)是神经系统中混沌的一种已知功能,其中系统通过混沌活动的影响来响应微弱的信号。当前的观点表明,在尖峰神经系统中,混沌状态是由不同的混沌路径引起的。但是,很少有研究比较尖峰神经系统中不同混沌状态下CR中信号响应的效率。我们在这里集中于伊热克维奇神经元模型,比较了通过倍增周期或切线分叉路径引起的混沌状态下CR的特征。我们发现,在测试的混沌状态下,相对于混沌轨道的稳定性,CR中的信号响应具有单峰最大值。此外,由于输入信号与混沌尖峰活动中周期分量之间的同步,在混沌边缘的信号响应效率变得特别高。

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