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

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.