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Spike-timing-dependent plasticity optimized coherence resonance and synchronization transitions by autaptic delay in adaptive scale-free neuronal networks

机译:自动尺度无尺度神经元网络自触发延迟的峰值定时依赖性塑性优化的相干共振和同步转换

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In this paper, we numerically study the effect of spike-timing-dependent plasticity on multiple coherence resonance and synchronization transitions induced by autaptic time delay in adaptive scale-free Hodgkin-Huxley neuron networks. As the adjusting rate A(p) of spike-timing-dependent plasticity increases, multiple coherence resonance and synchronization transitions enhance and become strongest at an intermediate A(p) value, indicating that there is optimal spike-timing-dependent plasticity that can most strongly enhance the multiple coherence resonance and synchronization transitions. As A(p) increases, increasing network average degree has a small effect on multiple coherence resonance, but its effect on synchronization transitions changes from suppressing to enhancing it. As network size is varied, multiple coherence resonance and synchronization transitions nearly do not change. These results show that spike-timing-dependent plasticity can simultaneously optimize multiple coherence resonance and synchronization transitions by autaptic delay in the adaptive scale-free neuronal networks. These findings provide a new insight into spike-timing-dependent plasticity and autaptic delay for the information processing and transmission in neural systems. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文在数值上研究了自适应尺度无霍格金 - Huxley Nuuron网络自触发时间延迟诱导的多个相干谐振和同步转变的效果。由于峰值时序依赖性塑性的调节率A(P)增加,在中间A(P)值中,多个相干谐振和同步转变增强并变得最强,表明最佳的峰值定时依赖性可塑性强大地增强了多个相干谐振和同步转换。随着(P)的增加,网络平均度的增加对多个相干共振的效果很小,但其对同步转换的影响变化从抑制增强它。随着网络大小的变化,多个相干谐振和同步转换几乎不会改变。这些结果表明,峰值定时依赖性可塑性可以同时通过自适应垢的神经元网络中的自动延迟同时优化多个相干谐振和同步转换。这些调查结果提供了对神经系统信息处理和传输的峰值定时依赖性可塑性和自动延迟提供了新的洞察力。 (c)2018年elestvier有限公司保留所有权利。

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