Bio-inspired spatiotemporal encoding of sound in a dual-capacitor neuron circuit

Auditory neurons exhibit remarkable sensitivity to temporal and spatial variations in sound, a property increasingly leveraged in the design of bio-inspired neuromorphic circuits. This study presents a neuromorphic circuit model based on a dual-capacitor FitzHugh–Nagumo (FHN) framework, in which each capacitor incorporates an elastic dielectric layer responsive to external acoustic stimulation. The model provides a biophysically inspired and mathematically tractable approach to capturing key spatiotemporal features of auditory processing, including frequency discrimination, timbre encoding, and spatial localization. We systematically examine the dynamic behaviors of the system under both silent and acoustically driven conditions, with particular emphasis on how the capacitor ratio and driving parameters modulate neuronal excitability and firing regimes. Through bifurcation analysis and time-domain simulations, we demonstrate that single-frequency acoustic stimulation induces transitions between clustered, bursting, and chaotic firing patterns, depending on the acoustic frequency. Dual-frequency acoustic stimulation, associated with timbral variations, enables robust control over firing stability, suppressing chaos and promoting periodic spiking. Additionally, we investigate the role of interaural phase difference in regulating neural synchrony, revealing that phase-shifted acoustic signals modulate both complete and phase synchronization metrics. These findings reveal the dual-capacitor architecture’s unique capacity for encoding acoustic information through rich and tunable nonlinear dynamics. The results not only offer a theoretical foundation for acoustically gated neuromorphic computing but also suggest novel principles for non-invasive ultrasound-based neuromodulation strategies and bio-inspired auditory neural interface design.