Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Nano Lett. 2020 Nov 11;20(11):8015-8023. doi: 10.1021/acs.nanolett.0c02892. Epub 2020 Oct 16.
Drawing inspiration from biology, neuromorphic systems are of great interest in direct interaction and efficient processing of analogue signals in the real world and could be promising for the development of smart sensors. Here, we demonstrate an artificial sensory neuron consisting of an InGaZnO (IGZO)-based optical sensor and NbO-based oscillation neuron in series, which can simultaneously sense the optical information even beyond the visible light region and encode them into electrical impulses. Such artificial vision sensory neurons can convey visual information in a parallel manner analogous to biological vision systems, and the output spikes can be effectively processed by a pulse coupled neural network, demonstrating the capability of image segmentation out of a complex background. This study could facilitate the construction of artificial visual systems and pave the way for the development of light-driven neurorobotics, bioinspired optoelectronics, and neuromorphic computing.
受生物学启发，神经形态系统在直接与现实世界中的模拟信号交互以及高效处理方面具有重要意义，有望开发出智能传感器。在这里，我们展示了一种由基于 InGaZnO（IGZO）的光传感器和基于 NbO 的振荡神经元串联而成的人工感觉神经元，它可以同时感知甚至超出可见光区域的光信息，并将其编码成电脉冲。这种人工视觉感觉神经元可以以类似于生物视觉系统的方式进行并行传递视觉信息，并且输出的尖峰可以通过脉冲耦合神经网络进行有效处理，从而展示出从复杂背景中进行图像分割的能力。这项研究有助于构建人工视觉系统，并为光驱动神经机器人技术、仿生光电学和神经形态计算的发展铺平道路。
