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Yang F, Guo Q, Ren G, Ma J. Wave propagation in a light-temperature neural network under adaptive local energy balance. J Biol Phys 2024:10.1007/s10867-024-09659-1. [PMID: 38958893 DOI: 10.1007/s10867-024-09659-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 06/18/2024] [Indexed: 07/04/2024] Open
Abstract
External electric and mechanical stimuli can induce shape deformation in excitable media because of its intrinsic flexible property. When the signals propagation in the media is described by a neural network, creation of heterogeneity or defect is considered as the effect of shape deformation due to accumulation or release of energy in the media. In this paper, a temperature-light sensitive neuron model is developed from a nonlinear circuit composed of a phototube and a thermistor, and the physical energy is kept in capacitive and inductive terms. Furthermore, the Hamilton energy for this function neuron is obtained in theoretical way. A regular neural network is built on a square array by activating electric synapse between adjacent neurons, and a few of neurons in local area is excited by noisy disturbance, which induces local energy diversity, and continuous coupling enables energy propagation and diffusion. Initially, the Hamilton energy function for a temperature-light sensitive neuron can be obtained. Then, the finite neurons are applied noise to obtain energy diversity to explore the energy spread between neurons in the network. For keeping local energy balance, one intrinsic parameter is regulated adaptively until energy diversity in this local area is decreased greatly. Regular pattern formation indicates that local energy balance creates heterogeneity or defects and a few of neurons show continuous parameter shift for keeping energy balance in a local area, which supports gradient energy distribution for propagating waves in the network.
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Affiliation(s)
- Feifei Yang
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Qun Guo
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Guodong Ren
- Department of Physics, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Jun Ma
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China.
- Department of Physics, Lanzhou University of Technology, Lanzhou, 730050, China.
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Wu F, Meng H, Ma J. Reproduced neuron-like excitability and bursting synchronization of memristive Josephson junctions loaded inductor. Neural Netw 2024; 169:607-621. [PMID: 37956577 DOI: 10.1016/j.neunet.2023.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 09/25/2023] [Accepted: 11/05/2023] [Indexed: 11/15/2023]
Abstract
Employing electronic component including memristor and Josephson junction to mimic biological neuron or synapse has elicited intense research in recent years. Neurons described by nonlinear oscillators can exhibit complex electrical activities. Josephson junctions are excellent candidates for neuron-inspired components because of their physical properties with low energy costs and high efficiency. In this paper, we revisit a prior work on memristive Josephson junction (MJJ) to identify the dynamical mechanisms to mimic neuron-like excitability and spiking. The inductive memristive Josephson junction (L-MJJ) model is further developed by adding an inductor with internal resistor. It is found that the L-MJJ model can reproduce square-wave bursting of the classical neuronal model from the neurodynamics point of view. The coupling L-MJJ oscillators can achieve in-phase and antiphase bursting synchronization similar with nonlinear coupling neurons. From the framework of nonlinear dynamics theory, this work aspires to build effective bridge between superconducting physics and theoretical neuroscience. Obtained results confirm the potential feasibility of this junction in designing a neuron-inspired computation to explore dynamics of larger-scale neuromorphic network.
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Affiliation(s)
- Fuqiang Wu
- School of Mathematics and Statistics, Ningxia University, Yinchuan 750021, China.
| | - Hao Meng
- College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China
| | - Jun Ma
- Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China
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Njitacke ZT, Koumetio BN, Ramakrishnan B, Leutcho GD, Fozin TF, Tsafack N, Rajagopal K, Kengne J. Hamiltonian energy and coexistence of hidden firing patterns from bidirectional coupling between two different neurons. Cogn Neurodyn 2021; 16:899-916. [PMID: 35847537 PMCID: PMC9279548 DOI: 10.1007/s11571-021-09747-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 10/27/2021] [Accepted: 11/03/2021] [Indexed: 11/30/2022] Open
Abstract
In this paper, bidirectional-coupled neurons through an asymmetric electrical synapse are investigated. These coupled neurons involve 2D Hindmarsh–Rose (HR) and 2D FitzHugh–Nagumo (FN) neurons. The equilibria of the coupled neurons model are investigated, and their stabilities have revealed that, for some values of the electrical synaptic weight, the model under consideration can display either self-excited or hidden firing patterns. In addition, the hidden coexistence of chaotic bursting with periodic spiking, chaotic spiking with period spiking, chaotic bursting with a resting pattern, and the coexistence of chaotic spiking with a resting pattern are also found for some sets of electrical synaptic coupling. For all the investigated phenomena, the Hamiltonian energy of the model is computed. It enables the estimation of the amount of energy released during the transition between the various electrical activities. Pspice simulations are carried out based on the analog circuit of the coupled neurons to support our numerical results. Finally, an STM32F407ZE microcontroller development board is exploited for the digital implementation of the proposed coupled neurons model.
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Affiliation(s)
- Zeric Tabekoueng Njitacke
- Department of Electrical and Electronic Engineering, College of Technology (COT), University of Buea, P.O. Box 63, Buea, Cameroon
- Research Unit of Automation and Applied Computer (URAIA), Electrical Engineering Department of IUT-FV, University of Dschang, P.O. Box 134, Bandjoun, Cameroon
- Department of Automation, Biomechanics and Mechatronics, Lodz University of Technology, Lodz, Poland
| | - Bernard Nzoko Koumetio
- Research Unit of Automation and Applied Computer (URAIA), Electrical Engineering Department of IUT-FV, University of Dschang, P.O. Box 134, Bandjoun, Cameroon
- Research Unit of Condensed Matter, Department of Physics, Faculty of Sciences, Electronics and Signal Processing (UR-MACETS), University of Dschang, P.O. Box 67, Dschang, Cameroon
| | | | - Gervais Dolvis Leutcho
- Research Unit of Condensed Matter, Department of Physics, Faculty of Sciences, Electronics and Signal Processing (UR-MACETS), University of Dschang, P.O. Box 67, Dschang, Cameroon
- Department of Electrical Engineering, École de Technologie Supérieure (ÉTS), Montréal, Québec H3C1K3 Canada
| | - Theophile Fonzin Fozin
- Department of Electrical and Electronic Engineering, Faculty of Engineering and Technology (FET), University of Buea, P.O. Box 63, Buea, Cameroon
| | - Nestor Tsafack
- Research Unit of Automation and Applied Computer (URAIA), Electrical Engineering Department of IUT-FV, University of Dschang, P.O. Box 134, Bandjoun, Cameroon
- Research Unit of Condensed Matter, Department of Physics, Faculty of Sciences, Electronics and Signal Processing (UR-MACETS), University of Dschang, P.O. Box 67, Dschang, Cameroon
| | - Kartikeyan Rajagopal
- Center for Nonlinear Systems, Chennai Institute of Technology, Chennai, Tamil Nadu India
| | - Jacques Kengne
- Research Unit of Automation and Applied Computer (URAIA), Electrical Engineering Department of IUT-FV, University of Dschang, P.O. Box 134, Bandjoun, Cameroon
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Leutcho GD, Khalaf AJM, Njitacke Tabekoueng Z, Fozin TF, Kengne J, Jafari S, Hussain I. A new oscillator with mega-stability and its Hamilton energy: Infinite coexisting hidden and self-excited attractors. CHAOS (WOODBURY, N.Y.) 2020; 30:033112. [PMID: 32237777 DOI: 10.1063/1.5142777] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 02/16/2020] [Indexed: 06/11/2023]
Abstract
In this paper, we introduce an interesting new megastable oscillator with infinite coexisting hidden and self-excited attractors (generated by stable fixed points and unstable ones), which are fixed points and limit cycles stable states. Additionally, by adding a temporally periodic forcing term, we design a new two-dimensional non-autonomous chaotic system with an infinite number of coexisting strange attractors, limit cycles, and torus. The computation of the Hamiltonian energy shows that it depends on all variables of the megastable system and, therefore, enough energy is critical to keep continuous oscillating behaviors. PSpice based simulations are conducted and henceforth validate the mathematical model.
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Affiliation(s)
- Gervais Dolvis Leutcho
- Research Unit of Laboratory of Condensed Matter, Electronics and Signal Processing (UR-MACETS) Department of Physics, Faculty of Sciences, University of Dschang, P.O. Box 67, Dschang, Cameroon
| | | | - Zeric Njitacke Tabekoueng
- Department of Electrical and Electronic Engineering, College of Technology (COT), University of Buea, P.O. Box 63, Buea, Cameroon
| | - Theophile Fonzin Fozin
- Department of Research, Development, Innovation and Training, Inchtech's, Yaoundé, Cameroon
| | - Jacques Kengne
- Research Unit of Laboratory of Automation and Applied Computer (LAIA), Electrical Engineering Department of IUT-FV, University of Dschang, P.O. Box 134, Bandjoun, Cameroon
| | - Sajad Jafari
- Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413, Iran
| | - Iqtadar Hussain
- Department of Mathematics, Statistics and Physics, Qatar University, Doha 2713, Qatar
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Reza Ahrabi A, Kobravi HR. A chaos to chaos control approach for controlling the chaotic dynamical systems using Hamilton energy feedback and fuzzy-logic system. CHAOS (WOODBURY, N.Y.) 2019; 29:073113. [PMID: 31370410 DOI: 10.1063/1.5087876] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Accepted: 06/20/2019] [Indexed: 06/10/2023]
Abstract
In this article, energy-based feedback control is introduced merely as an approach to suppress chaos. We have also shown in this study that an energy-based feedback controller is capable of changing a chaotic dynamic to other chaotic dynamics. In other words, energy feedback can also be used to convert chaos dynamics to another chaos dynamics, and the use of energy feedback should not be limited to suppress chaos. The importance of the issue lies in relating some practical applications of chaos to chaos control. In this short study, we have shown that an energy feedback control can be combined with a fuzzy self-regulating gain system. A short study has been done on Chua's circuit.
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Affiliation(s)
- Atike Reza Ahrabi
- Department of Electrical Engineering, Islamic Azad University, Mashhad Branch, Mashhad 9187147578, Iran
| | - Hamid Reza Kobravi
- Research Center of Biomedical Engineering, Islamic Azad University, Mashhad Branch, Mashhad 9187147578, Iran
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Effects of ion channel blocks on electrical activity of stochastic Hodgkin–Huxley neural network under electromagnetic induction. Neurocomputing 2018. [DOI: 10.1016/j.neucom.2017.12.036] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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Ma J, Zhou P, Ahmad B, Ren G, Wang C. Chaos and multi-scroll attractors in RCL-shunted junction coupled Jerk circuit connected by memristor. PLoS One 2018; 13:e0191120. [PMID: 29342178 PMCID: PMC5771607 DOI: 10.1371/journal.pone.0191120] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 12/28/2017] [Indexed: 11/18/2022] Open
Abstract
In this paper, a new four-variable dynamical system is proposed to set chaotic circuit composed of memristor and Josephson junction, and the dependence of chaotic behaviors on nonlinearity is investigated. A magnetic flux-controlled memristor is used to couple with the RCL-shunted junction circuit, and the dynamical behaviors can be modulated by changing the coupling intensity between the memristor and the RCL-shunted junction. Bifurcation diagram and Lyapunov exponent are calculated to confirm the emergence of chaos in the improved dynamical system. The outputs and dynamical behaviors can be controlled by the initial setting and external stimulus as well. As a result, chaos can be suppressed and spiking occurs in the sampled outputs under negative feedback, while applying positive feedback type via memristor can be effective to trigger chaos. Furthermore, it is found that the number of multi-attractors in the Jerk circuit can be modulated when memristor coupling is applied on the circuit. These results indicate that memristor coupling can be effective to control chaotic circuits and it is also useful to reproduce dynamical behaviors for neuronal activities.
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Affiliation(s)
- Jun Ma
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing, China
- Department of Physics, Lanzhou University of Technology, Lanzhou, China
- * E-mail:
| | - Ping Zhou
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Bashir Ahmad
- NAAM-Research Group, Department of Mathematics, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Guodong Ren
- Department of Physics, Lanzhou University of Technology, Lanzhou, China
| | - Chunni Wang
- Department of Physics, Lanzhou University of Technology, Lanzhou, China
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