Neural behaviors and energy properties of Memcapacitor FitzHugh–Nagumo neuron model with Miller effect

Based on the memcapacitor with the Miller effect, this paper proposes an improved memcapacitor FitzHugh–Nagumo (MCFHN) neuron model. This improved model circuit accounts for the device deformation effect by replacing the capacitor with a memcapacitor. Building on the improved model, the paper explor...

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Veröffentlicht in:Nonlinear dynamics 2025-02, Vol.113 (3), p.2689-2710
Hauptverfasser: Ge, Mengyan, Jia, Kai, Gao, Ruyun, Wang, Xin, Qian, Zhouhan
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Sprache:eng
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Zusammenfassung:Based on the memcapacitor with the Miller effect, this paper proposes an improved memcapacitor FitzHugh–Nagumo (MCFHN) neuron model. This improved model circuit accounts for the device deformation effect by replacing the capacitor with a memcapacitor. Building on the improved model, the paper explores the electrical characteristics, neural behaviors, energy characteristics, and the noise-induced resonance phenomenon. The electrical characteristics of the circuit and the input impedance characteristics of the memcapacitor are analyzed through numerical simulations. It is found that the capacitance and input impedance can be controlled by adjusting the gain value and the trigger flux. The dimensionless neuron model and energy function are derived by scaling the parameters and variables of the circuit equations. The consistency between the Hamiltonian energy and the dimensionless circuit energy of the MCFHN model is verified using the Helmholtz theorem. The enhancement of memory characteristics and the discharge state transition of the MCFHN neuron under different trigger fluxes are observed. Additionally, it was found that the impedance of the memcapacitor exhibits a memory effect, and the energy characteristics of the system under different discharge modes are analyzed. Moreover, under the influence of Gaussian white noise, a peak appears in the energy average curve, indicating that noise-induced resonance occurs. These findings provide a new theoretical and experimental basis for further research into neuronal dynamics.
ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-024-10349-9