Modeling the effect of magnetoelectric nanoparticles on neuronal electrical activity: An analog circuit approach.

This article presents a novel physical neuron model integrating magnetoelectric nanoparticles (MENPs) as circuit elements to enable wireless, noninvasive control of local neural activity via applied magnetic fields. MENPs, due to their magnetoelectric effect, act as magnetic-field-controlled electric dipoles on neuronal membranes, generating local electric fields that modulate ion channel activity and can initiate action potentials without invasive procedures. The study develops a MENP-based memristive Hodgkin–Huxley (HH) circuit model, extending classical neuron models to incorporate MENPs' effects on single neurons and populations, highlighting their potential for high-resolution brain-machine interfaces and therapies for neurological disorders. Two configurations are proposed depending on MENPs' positioning relative to the membrane, with corresponding circuit models describing their influence on neuronal excitability. The model also incorporates stochastic elements to reflect biological noise, providing a framework for understanding and optimizing MENPs' role in neural modulation.