School of Electronic Engineering, Heilongjiang University, Harbin 150080, China; Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China.
School of Electronic Engineering, Heilongjiang University, Harbin 150080, China; Heilongjiang Provincial Key Laboratory of Micro-nano Sensitive Devices and Systems, Heilongjiang University, Harbin 150080, China.
J Colloid Interface Sci. 2025 Jan 15;678(Pt B):325-335. doi: 10.1016/j.jcis.2024.09.030. Epub 2024 Sep 5.
The human perception and learning heavily rely on the visual system, where the retina plays a vital role in preprocessing visual information. Developing neuromorphic vision hardware is based on imitating the neurobiological functions of the retina. In this work, an optoelectronic neuron is developed by combining a gate-modulated PDVT-10 channel with a volatile threshold switching memristor, enabling the achievement of optoelectronic performance through a resistance-matching mechanism. The optoelectronic spiking neuron exhibits the ability to alter its spiking behavior in a manner resembling that of a retina. Incorporating electrical and optical modulation, the artificial neuron accurately replicates neuronal signal transmission in a biologically manner. Moreover, it demonstrates inhibition of neuronal firing during darkness and activation upon exposure to light. Finally, the evaluation of a perceptron spiking neural network utilizing these leaky integrate-and-fire neurons is conducted through simulation to assess its capability in classifying image recognition algorithms. This research offers a hopeful direction for the development of easily expandable and hierarchically structured spiking electronics, broadening the range of potential applications in biomimetic vision within the emerging field of neuromorphic hardware.
人类的感知和学习在很大程度上依赖于视觉系统，而视网膜在预处理视觉信息方面起着至关重要的作用。神经形态视觉硬件的开发是基于模仿视网膜的神经生物学功能。在这项工作中，通过将栅极调制 PDVT-10 沟道与易失性阈值开关忆阻器相结合，开发出一种光电神经元，通过电阻匹配机制实现光电性能。光电尖峰神经元表现出改变其尖峰行为的能力，这种行为类似于视网膜的行为。通过电和光的调制，人工神经元精确地以生物方式复制神经元信号传输。此外，它还能在黑暗中抑制神经元的发射，而在光照下激活神经元的发射。最后，通过模拟评估利用这些漏电流积分点火神经元的感知机尖峰神经网络，评估其在分类图像识别算法方面的能力。这项研究为开发易于扩展和具有层次结构的尖峰电子学提供了一个有希望的方向，拓宽了在神经形态硬件新兴领域中仿生视觉的潜在应用范围。
