Spiking activity in a memcapacitive and memristive emulator-based bionic circuit

IF 5.6 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Quan Xu , Xincheng Ding , Ning Wang , Bei Chen , Fatemeh Parastesh , Mo Chen
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引用次数: 0

Abstract

The diversity of spiking activity of a bionic circuit is a vital footstone in developing spike-based applications. The bionic circuit constructed by membrane theory frequently employs an invariable capacitor to characterize the electrophysiological behaviors of the neuron membrane. Actually, the thickness and medium property of a neuron membrane are regulated by its membrane potential, which leads to the invariable capacitor suffering from inaccuracy in expressing the regulating process. To solve this issue, a memcapacitive emulator with controllable capacitance is deployed to characterize the neuron membrane in this paper. Then, a memcapacitive and memristive emulator-based (MC-MR-emulator-based) bionic circuit is first built, which involves only a memcapacitive emulator, a locally active memristive emulator, a DC voltage source, and an externally applied current stimulus. Numerical explorations display that the MC-MR-emulator-based bionic circuit can generate rich bifurcation behaviors, e.g., period-doubling bifurcation, tangent bifurcation, and crisis scenario, related to the current stimulus, memristive emulator parameters, and memcapacitive emulator parameters. These bifurcation behaviors lead to that the MC-MR-emulator-based bionic circuit can produce abundant periodic and chaotic spiking activities. In analog experiments, memcapacitor and memristor emulators are utilized. PCB-based hardware experimental results well address the validity of the numerical explorations and further exhibit the effectiveness of the MC-MR-emulator-based bionic circuit in generating spiking activities.

基于记忆电容和记忆仿真器的仿生电路中的尖峰活动
仿生电路尖峰活动的多样性是开发基于尖峰的应用的重要基础。根据膜理论构建的仿生电路通常采用不变电容来表征神经元膜的电生理行为。事实上,神经元膜的厚度和介质特性受其膜电位调节,这导致不变电容器在表达调节过程时存在误差。为解决这一问题,本文采用了具有可控电容的膜电容仿真器来表征神经元膜。然后,首先构建了一个基于忆电容和忆电阻仿真器(MC-MR-emulator-based)的仿生电路,其中只涉及一个忆电容仿真器、一个局部激活的忆电阻仿真器、一个直流电压源和一个外部施加的电流刺激。数值研究表明,基于 MC-MR 仿真器的仿生电路可以产生丰富的分岔行为,例如周期加倍分岔、切线分岔和危机情景,这些行为与电流刺激、忆阻仿真器参数和忆容性仿真器参数有关。这些分岔行为表明,基于 MC-MR 仿真器的仿生电路可以产生丰富的周期性和混沌尖峰活动。在模拟实验中,使用了忆电容和忆阻器仿真器。基于 PCB 的硬件实验结果很好地验证了数值探索的有效性,并进一步证明了基于 MC-MR 仿真器的仿生电路在产生尖峰活动方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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