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Coexisting Firing Patterns in an Improved Memristive Hindmarsh-Rose Neuron Model with Multi-Frequency Alternating

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Summary
This summary is machine-generated.

This study introduces a novel Hindmarsh-Rose neuron model incorporating a flux-controlled memristor and multi-frequency stimulation. The model demonstrates diverse firing patterns and unique stability behaviors, verified by an analog circuit.

Keywords:
Hindmarsh–Rose neuron modelcoexisting firing patternflux-controlled memristormagnetic induction

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Area of Science:

  • Computational Neuroscience
  • Nonlinear Dynamics
  • Memristor Applications

Background:

  • Memristor theory is advancing, showing promise for nervous system applications.
  • Flux-controlled memristors can model neuronal magnetic induction effects.

Purpose of the Study:

  • To propose a new Hindmarsh-Rose (HR) neuron model using a flux-controlled memristor and multi-frequency excitation.
  • To investigate various firing patterns and stability phenomena in the proposed model.

Main Methods:

  • Integration of a flux-controlled memristor into the HR neuron model.
  • Application of superimposed high- and low-frequency current stimuli.
  • Analysis of firing patterns under single and multiple stimuli.
  • Investigation of model stability with varying memristor coupling strength.
  • Experimental verification using an analog circuit.

Main Results:

  • The model exhibits diverse coexisting firing patterns under different stimuli.
  • A rare phenomenon of eliminated multiple stability was observed by altering memristor coupling strength.
  • Numerical simulations were successfully validated by analog circuit experiments.

Conclusions:

  • The proposed memristor-based HR neuron model effectively replicates complex neuronal dynamics.
  • The study highlights the potential of flux-controlled memristors in computational neuroscience.
  • The findings offer insights into neuronal firing patterns and stability control.