Xincheng Ding , Weiwei Fan , Ning Wang , Yuanhui Su , Mo Chen , Yuan Lin , Quan Xu
{"title":"基于全记忆元件仿真器的仿生电路的动态行为和发射模式","authors":"Xincheng Ding , Weiwei Fan , Ning Wang , Yuanhui Su , Mo Chen , Yuan Lin , Quan Xu","doi":"10.1016/j.chaos.2025.116658","DOIUrl":null,"url":null,"abstract":"<div><div>Memory-element-based bionic circuits can well characterize the electrophysiological behavior of a biological neuron and generate abundant neuron-like firing patterns. This paper deploys a charge-controlled memcapacitor, a voltage-controlled locally active memristor (LAM) with one DC voltage bias, a flux-controlled meminductor, and a sinusoidal stimulus to respectively characterize the neuronal membrane, ion channel, electromagnetic induction, and external stimulus, thereby a fully memory-element emulator-based bionic circuit is constructed. Numerical simulations demonstrate that the bionic circuit achieves diverse pattern transition behaviors through the forward/reverse period-doubling bifurcation routes, tangent bifurcation, and chaos crisis for the circuit parameters, which trigger diverse firing patterns, e.g., periodic and chaotic spiking activities. Besides, a hardware circuit using discrete components is successfully synthesized by memory-element emulators, and experimental measurements are carried out to support the numerical results and demonstrate the capability of the bionic circuit to produce neuron-like firing patterns.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"199 ","pages":"Article 116658"},"PeriodicalIF":5.6000,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamical behaviors and firing patterns in a fully memory-element emulator-based bionic circuit\",\"authors\":\"Xincheng Ding , Weiwei Fan , Ning Wang , Yuanhui Su , Mo Chen , Yuan Lin , Quan Xu\",\"doi\":\"10.1016/j.chaos.2025.116658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Memory-element-based bionic circuits can well characterize the electrophysiological behavior of a biological neuron and generate abundant neuron-like firing patterns. This paper deploys a charge-controlled memcapacitor, a voltage-controlled locally active memristor (LAM) with one DC voltage bias, a flux-controlled meminductor, and a sinusoidal stimulus to respectively characterize the neuronal membrane, ion channel, electromagnetic induction, and external stimulus, thereby a fully memory-element emulator-based bionic circuit is constructed. Numerical simulations demonstrate that the bionic circuit achieves diverse pattern transition behaviors through the forward/reverse period-doubling bifurcation routes, tangent bifurcation, and chaos crisis for the circuit parameters, which trigger diverse firing patterns, e.g., periodic and chaotic spiking activities. Besides, a hardware circuit using discrete components is successfully synthesized by memory-element emulators, and experimental measurements are carried out to support the numerical results and demonstrate the capability of the bionic circuit to produce neuron-like firing patterns.</div></div>\",\"PeriodicalId\":9764,\"journal\":{\"name\":\"Chaos Solitons & Fractals\",\"volume\":\"199 \",\"pages\":\"Article 116658\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chaos Solitons & Fractals\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S096007792500671X\",\"RegionNum\":1,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chaos Solitons & Fractals","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S096007792500671X","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Dynamical behaviors and firing patterns in a fully memory-element emulator-based bionic circuit
Memory-element-based bionic circuits can well characterize the electrophysiological behavior of a biological neuron and generate abundant neuron-like firing patterns. This paper deploys a charge-controlled memcapacitor, a voltage-controlled locally active memristor (LAM) with one DC voltage bias, a flux-controlled meminductor, and a sinusoidal stimulus to respectively characterize the neuronal membrane, ion channel, electromagnetic induction, and external stimulus, thereby a fully memory-element emulator-based bionic circuit is constructed. Numerical simulations demonstrate that the bionic circuit achieves diverse pattern transition behaviors through the forward/reverse period-doubling bifurcation routes, tangent bifurcation, and chaos crisis for the circuit parameters, which trigger diverse firing patterns, e.g., periodic and chaotic spiking activities. Besides, a hardware circuit using discrete components is successfully synthesized by memory-element emulators, and experimental measurements are carried out to support the numerical results and demonstrate the capability of the bionic circuit to produce neuron-like firing patterns.
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.