忆阻器非挥发性对忆阻器耦合异质神经元同步性的影响。

IF 3.2 2区 数学 Q1 MATHEMATICS, APPLIED
Chaos Pub Date : 2025-09-01 DOI:10.1063/5.0278929
Lin Yan, Tao Luo, Zhiyong Liu, Weiqing Liu
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引用次数: 0

摘要

突触可塑性决定了神经元的同步放电活动,对理解大脑不同区域的学习和记忆过程具有重要意义。为了探讨突触可塑性对不同脑区耦合神经元同步动力学的影响,提出了一种波动可切换记忆电阻器耦合异质神经元模型。随着非挥发性的增加,两个异构神经元之间同步的临界耦合强度与忆阻器的特性参数呈幂律关系降低。利用Lipschitz定理,从理论上预测了在不同的忆阻器挥发性下,忆阻器耦合异构神经元同步的临界耦合强度。非易失性忆阻器被证明有利于实现忆阻器耦合神经元之间的同步。最后,在功率仿真中设计了神经元电路,观察和验证了非易失性对系统同步的影响。忆阻器的非挥发性效应有效地模拟了突触的长期可塑性,有助于理解神经元信号传递和处理的机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of non-volatility of memristor on the synchronizability of memristor-coupled heterogeneous neurons.

Synaptic plasticity is of great significance for understanding the leaning and memory processes in different brain regions since it determines the synchronized firing activities of neurons. A volatility-switchable memristor-coupled heterogeneous neuron model is proposed to explore the effects of the synaptic plasticity on the synchronous dynamics of coupled neurons in different brain regions. With the increment of the non-volatility, the critical coupling strength of synchronization between two heterogeneous neurons decreases in a power-law relationship with the character parameter of the memristor. The critical coupling strength for synchronization of the memristor-coupled heterogeneous neurons under different volatility of the memristor is predicted theoretically with the Lipschitz theorem. The non-volatile memristor is proven to be beneficial to reach synchronization between the memristor-coupled neurons. Finally, a neuron circuit was designed in Power Simulation to observe and validate the influence of non-volatility on system synchronization. The effects of the non-volatility of a memristor efficiently emulate the long-term synaptic plasticity and may contribute to understanding the mechanisms of neuron signal transmission and processing.

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来源期刊
Chaos
Chaos 物理-物理:数学物理
CiteScore
5.20
自引率
13.80%
发文量
448
审稿时长
2.3 months
期刊介绍: Chaos: An Interdisciplinary Journal of Nonlinear Science is a peer-reviewed journal devoted to increasing the understanding of nonlinear phenomena and describing the manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines.
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