Filtering regulation of synchronization and energy balance in functional memristor networks

The frequency-selective response of the nervous system bears a strong resemblance to filtering mechanisms. However, how concurrent cross-modal filtering influences neuronal synchronization remains unclear. This study constructed a coupled photosensitive-auditory neuron model incorporating flux-controlled memristors. Through inductive coil connections, we investigated its synchronous dynamics under frequency-swept signal excitation. The key innovation lies in simultaneously applying swept chirp excitation to both light and sound inputs, achieving biophysically plausible bandpass filtering based on the intrinsic frequency tuning of sensory pathways, while employing an adaptive coupling strategy based on Hamiltonian energy differences. Results demonstrate that bimodal filtering significantly enhances frequency-dependent synchronization. When the sweeping signal traverses the dual passbands, the system exhibits robust synchronization characterized by phase locking and energy minimization, significantly outperforming unfiltered or unimodal conditions. This study reveals cross-modal collaborative filtering as a fundamental mechanism for neural synchronization, providing a computational framework for multisensory integration. It offers significant implications for developing novel neural prostheses synchronized by photoacoustic cues.