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The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

机译:抑制性神经元对高阶耦合神经振荡器种群演化模型的影响

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摘要

We proposed a higher-order coupling neural network model including the inhibitory neurons and examined the dynamical evolution of average number density and phase-neural coding under the spontaneous activity and external stimulating condition. The results indicated that increase of inhibitory coupling strength will cause decrease of average number density, whereas increase of excitatory coupling strength will cause increase of stable amplitude of average number density. Whether the neural oscillator population is able to enter the new synchronous oscillation or not is determined by excitatory and inhibitory coupling strength. In the presence of external stimulation, the evolution of the average number density is dependent upon the external stimulation and the coupling term in which the dominator will determine the final evolution.
机译:我们提出了一个包含抑制神经元的高阶耦合神经网络模型,并研究了在自发活动和外部刺激条件下平均数密度和相神经编码的动态演化。结果表明,抑制偶合强度的增加将引起平均数密度的降低,而兴奋性偶合强度的增加将引起平均数密度的稳定幅度的增加。神经振子群是否能够进入新的同步振荡取决于兴奋性和抑制性耦合强度。在存在外部刺激的情况下,平均数密度的演化取决于外部刺激和耦合项,在该耦合项中,支配者将决定最终的演化。

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