A sound-sensitive neuron incorporating a memristive-ion channel

Abstract The nonlinear memory characteristic of memristors is similar to that of biological synapses/ion channels. Therefore, memristors become an ideal component for constructing neurons. This paper presents a sound-sensitive neuron circuit featuring a memristor-based hybrid ion channel, aiming to simulate the dynamic response mechanism of biological auditory neurons to acoustic signals. In this neural circuit, a piezoelectric ceramic element captures external sound signals, while a hybrid ion channel is constructed by connecting a charge-controlled memristor in series with an inductor. The circuit achieves selective encoding of sound frequency and amplitude and investigates the effects of external electric fields on neuronal ion channels. In the dynamic analysis, bifurcation diagrams and Lyapunov exponents are employed to reveal the rich nonlinear behaviors (such as chaotic oscillations and periodic oscillations) generated by the circuit during the acoustic-electric conversion process, and the validity of the circuit model is experimentally verified. The simulation results show that by adjusting the threshold of the ratio between electric field energy and magnetic field energy, the firing mode and parameters of neurons can be adaptively regulated. Moreover, this model exhibits the phenomenon of stochastic resonance in a noisy environment. This research provides a theoretical basis for the development of new bionic auditory sensor hardware. At the same time, it opens up a new path for the bio-inspired design of the memristor-ion channel hybrid system.