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Intra- and inter-layer dynamics of a two-layer Izhikevich neuron map

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  • Saçu, İbrahim Ethem

Abstract

In this study, along with a flux controlled memristor for inter-layer synaptic connection, an Izhikevich neuron map of two layer has been built where distance dependent chemical coupling among neurons within each layer. The distance term with power-law factor between neurons placed in a square form is included in the chemical coupling. Dynamic behaviors of intra-layer, inter-layer and total neuron map have been evaluated by changing the coupling strength, distance term and its power law factor. Error term, synchronization factor, and incoherence strength have been used to evaluate simulation results quantitatively. Numerical simulation results show that there are disordered, synchronous and chimera states in both intra- and inter-layers depend on the coupling strength. Furthermore, the memristor layer has also same responses parallel to the intra- and inter-layer. On the other hand, network dynamics have been also effected by distance term and its power law factor. When the distance term is set to unity, as the power-law factor decreases, neuronal nodes achieve to synchronization more quickly for same variation of the chemical coupling strength. However, if coupling strength is set to big enough, the effect of distance term disappears. Moreover, when the power-law factor is adjusted to unity, as the distance term increases, neural network can achieve synchronization with greater chemical coupling strength. Additionally, the simulation results have been verified experimentally on a DSP platform.

Suggested Citation

  • Saçu, İbrahim Ethem, 2025. "Intra- and inter-layer dynamics of a two-layer Izhikevich neuron map," Chaos, Solitons & Fractals, Elsevier, vol. 199(P1).
    • Handle: RePEc:eee:chsofr:v:199:y:2025:i:p1:s0960077925007313
    DOI: 10.1016/j.chaos.2025.116718
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    References listed on IDEAS

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    1. Bo Yan & Fatemeh Parastesh & Shaobo He & Karthikeyan Rajagopal & Sajad Jafari & Matjaå½ Perc, 2022. "Interlayer And Intralayer Synchronization In Multiplex Fractional-Order Neuronal Networks," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 30(10), pages 1-11, December.
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    3. Li, Kexin & Bao, Bocheng & Ma, Jun & Chen, Mo & Bao, Han, 2022. "Synchronization transitions in a discrete memristor-coupled bi-neuron model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    4. Muni, Sishu Shankar & Rajagopal, Karthikeyan & Karthikeyan, Anitha & Arun, Sundaram, 2022. "Discrete hybrid Izhikevich neuron model: Nodal and network behaviours considering electromagnetic flux coupling," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    5. Minglin Ma & Kangling Xiong & Zhijun Li & Yichuang Sun, 2023. "Dynamic Behavior Analysis and Synchronization of Memristor-Coupled Heterogeneous Discrete Neural Networks," Mathematics, MDPI, vol. 11(2), pages 1-13, January.
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