A sound-sensitive neuron incorporating a memristive-ion channel

Abstract The nonlinear memory characteristics of memristors resemble those of biological synapses and ion channels. Therefore, memristors serve as ideal components for constructing artificial neurons. This paper presents a sound-sensitive neuron circuit featuring a memristor-based hybrid ion channel, designed to simulate the dynamic response mechanisms of biological auditory neurons to acoustic signals. In this neural circuit, a piezoelectric ceramic element captures external sound signals, while the hybrid ion channel is formed by connecting a charge-controlled memristor in series with an inductor. The circuit realizes selective encoding of sound frequency and amplitude and investigates the influence of external electric fields on neuronal ion-channel dynamics. In the dynamic analysis, bifurcation diagrams and Lyapunov exponents are employed to reveal the rich nonlinear behaviors, such as chaotic oscillations and periodic oscillations, exhibited by the circuit during the acoustic–electric conversion process, and the validity of the circuit model is experimentally verified. Simulation results show that by adjusting the threshold of the ratio between electric-field energy and magnetic-field energy, the firing modes and parameters of neurons can be adaptively regulated. Moreover, the model exhibits stochastic resonance in noisy environments. This research provides a theoretical foundation for the development of new bionic auditory sensing hardware and opens a new path for the bio-inspired design of memristor–ion-channel hybrid systems.