Optoelectronic artificial synapse for lateral inhibition-enhanced retinal biomimicry

Abstract Optoelectronic synaptic devices enable in-sensor processing of enhanced edge detection and contrast resolution in complex visual scenes due to their excellent capability to emulate the functions of visual neurons, such as light perception and image processing, while lateral inhibition synaptic plasticity refines spatial selectivity and extends the dynamic range by suppressing redundant signals and amplifying subtle variations in input intensity. The incorporation of lateral inhibition into a single optoelectronic synaptic device will offer a cost-effective and energy-efficient route for directing a robotic arm to perform responding motions and developing highly efficient machine vision systems. Herein, we demonstrate an optoelectronic artificial synapse established on a novel heterostructure consisting of metal oxide In ₂ O ₃ , polycrystalline Cs ₂ AgBiBr ₆ perovskite, and indium-gallium-zinc oxide thin film, which enhances the optoelectronic response and corresponding synaptic plasticity of the devices, enabling the emulation of neural behaviour and advanced information processing. The structure simulates excitatory synaptic activity through light stimulation and mimics lateral inhibition through electrical stimulation, effectively replicating the neural mechanisms of synaptic plasticity in processes such as Mach bands, contrast enhancement, and Hermann’s grid. Leveraging these properties, we develop a lateral inhibition network for image recognition, achieving 97% accuracy-surpassing conventional networks at 93%. Additionally, through seamless integration with robotic arms, it can execute colour chip recognition on a machine cart, providing a promising strategy for the design of intelligent autonomous devices and bioinspired robots.