Bridged artificial neurons based on memristor circuit for spiking propagation network and coincidence detection

The biological nervous system relies on precise temporal integration for efficient information processing and perception. Among these, spiking propagation and coincidence detection play a crucial role in neural coding and signal processing. Here, we proposed a bridged artificial neuron unit based on a memristor emulator circuit, capable of mimicking ion-channel-like spiking behavior, including spike generation and refractory periods. These units can be connected in series to form chains or networks for spike propagation and interaction, enabling reliable unidirectional action potential transmission and coincidence detection. As a proof of concept, we developed a bioinspired auditory processing system that emulates the interaural time difference-processing mechanism of the barn owl. The system achieves microsecond-level sound localization with outstanding noise resistance. These findings demonstrate the potential of bridged artificial neuron units for advancing neuromorphic computing, bioinspired perception systems, and high-precision biosensing applications.