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基于能量平衡策略的分数阶神经网络同步

Synchronization in fractional-order neural networks by the energy balance strategy.

作者信息

Yao Zhao, Sun Kehui, He Shaobo

机构信息

School of Physics, Central South University, Changsha, 410083 China.

School of Automation and Electronic Information, Xiangtan University, Xiangtan, 411105 China.

出版信息

Cogn Neurodyn. 2024 Apr;18(2):701-713. doi: 10.1007/s11571-023-10023-7. Epub 2023 Nov 2.

Abstract

Considering the individual differences between neurons, the fractional-order framework is introduced, and the neurons with various orders denote the individual differences during the cell differentiation. In this paper, the fractional-order FithzHugh-Nagumo (FHN) neural circuit is used to reproduce the firing patterns. In addition, an energy balance strategy is applied to determine the inter-neuronal communication. The neurons with energy imbalance exchange the information whereas the synaptic channels are blocked when energy balance is achieved. Two neurons coupled by this strategy achieve the phase synchronization and phase lock, and it indicates the two neurons generate spiking at the same time or with an interval. Similarly, the synchronization results are also obtained in the chain neuronal network, and the neurons exhibit the same firing patterns since the synchronization factor is closed to 1. Particularly, the neurons with order diversities lead to the heterogeneity and gradient field in the regular network, and the target wave is developed over time. With the wave spreading in the network, the silent states and exciting states appear in the whole network. The formation and diffusion of the target wave reveals the information transmission in neuronal network, and it indicates the individual differences paly an essential role in the collective behavior of neurons.

摘要

考虑到神经元之间的个体差异,引入了分数阶框架,不同阶数的神经元表示细胞分化过程中的个体差异。本文采用分数阶菲茨休 - 纳古莫(FHN)神经电路来重现放电模式。此外,应用能量平衡策略来确定神经元间的通信。能量不平衡的神经元交换信息,而当达到能量平衡时突触通道被阻断。通过这种策略耦合的两个神经元实现相位同步和相位锁定,这表明两个神经元同时或间隔一定时间产生尖峰放电。类似地,在链式神经元网络中也获得了同步结果,并且由于同步因子接近1,神经元表现出相同的放电模式。特别地,具有阶数多样性的神经元导致规则网络中的异质性和梯度场,并且目标波随时间发展。随着波在网络中传播,整个网络中会出现静息状态和兴奋状态。目标波的形成和扩散揭示了神经元网络中的信息传递,这表明个体个体差异在神经元的集体行为中起着至关重要的作用。

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