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Updated: Jan 7, 2026
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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
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Firing dynamics and phase synchronization in a memristor-coupled heterogeneous neuron network under electromagnetic
Xiuquan Liu1, Dongpo Hu1, Ming Liu1,2
1School of Mathematical Sciences, Qufu Normal University, Qufu 273165, People's Republic of China.
Chaos (Woodbury, N.Y.)
|December 30, 2025
Summary
This study explores how electromagnetic radiation and memristor coupling influence neural networks. Researchers found that these factors can control neuron firing patterns and synchronization in complex neural systems.
Area of Science:
- Computational Neuroscience
- Nonlinear Dynamics
- Memristor Applications
Background:
- Neuronal firing activity is modulated by electromagnetic radiation and synaptic interactions.
- Memristors offer a novel approach to modeling complex neural dynamics and coupling mechanisms.
Purpose of the Study:
- To investigate the firing dynamics of a memristor-coupled Chialvo-Rulkov neuron network under electromagnetic radiation.
- To analyze parameter-induced firing patterns, multistability, and synchronization phenomena.
Main Methods:
- Utilized bifurcation diagrams, Lyapunov exponents, spectral entropy, and C0 complexity to analyze neuron dynamics.
- Modeled external radiation and inter-neuron coupling using discrete memristors.
- Designed and simulated analog circuits for the network using PSIM software.
Main Results:
- Observed parameter-induced spiking-bursting patterns with varying spike counts based on coupling and radiation intensity.
- Revealed heterogeneous multistability and coexisting firing modes within the network.
- Demonstrated the capability of neurons to achieve phase synchronization.
Conclusions:
- Electromagnetic radiation and memristor coupling significantly influence neuronal firing patterns and synchronization.
- The study provides insights into firing pattern transitions and synchronization in heterogeneous neural systems.
- Analog circuit implementation validates the theoretical findings for practical applications.
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