Electromagnetic induction effects on electrical activity within a memristive Wilson neuron model.

Area of Science:

• Computational Neuroscience
• Neuro-inspired Computing
• Circuit Design

Background:

• Neurons exhibit complex electrical activities influenced by their electrophysiological environment.
• Electromagnetic induction effects, triggered by membrane potential changes, can be modeled as memristors.

Purpose of the Study:

• To propose and analyze a three-variable memristor-based Wilson neuron model.
• To investigate the influence of memristor parameters and initial conditions on neuronal electrical activity.
• To validate the model through hardware circuit implementation.

Main Methods:

• Development of a three-variable memristor-based Wilson neuron model.
• Kinetic analysis methods to explore electrical activities.
• Analog circuit implementation using discrete components for hardware verification.

Main Results:

• The memristive Wilson neuron model demonstrates rich and complex electrical activities.
• Observed phenomena include asymmetric coexisting electrical activities and antimonotonicity.
• Numerical simulations were successfully validated by the hardware analog circuit.

Conclusions:

• The memristor-based Wilson neuron model effectively mimics electromagnetic induction effects in neurons.
• The study reveals diverse electrical behaviors, including asymmetric coexisting activities and antimonotonicity.
• This research provides a foundation for advancing neuron-based engineering applications.