A Pupillary Light Reflex Inspired Self‐Adaptive Spiking Visual Neuron

Abstract

Abstract The development of neuromorphic visual systems aims to address the energy‐efficiency and adaptability constraints in machine vision. However, artificial visual neurons in these systems mostly encode amplitude‐modulated signals and adjust the perception range through passive gate voltage modulation, resulting in low biological fidelity. A pupillary‐light‐reflex‐inspired self‐adaptive spiking visual neuron with a superior perception range and active visual adaptation is proposed. The device functionally emulates the hierarchical visual adaptation process of human eyes through the active optical regulation of a photochromic film, photoelectric conversion through an IGCdO‐based transistor, and spiking encoding through a TaO X ‐based memristor‐based memristor). This configuration possesses a perception range of 160 dB and active visual adaptation under extreme light intensity conditions ranging from 0.2 µW cm −2 to 1.64 W cm −2 , outperforming previous artificial visual neurons. The advantage of active visual adaptation has been validated by integration with a spiking neural network, achieving an 86% recognition accuracy in classification tasks, a 66% improvement over non‐adaptive counterparts. This bio‐inspired design would endow machine vision systems with a high‐level of biological fidelity.