当前位置: X-MOL 学术ACS Photonics › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Brain-Like Device Simulating Dendrites Perception Process and Optical Induced Excitatory Postsynaptic Current
ACS Photonics ( IF 6.5 ) Pub Date : 2025-01-23 , DOI: 10.1021/acsphotonics.4c01535
Jia-Ying Chen, Wen-Min Zhong, Qi-Zhong Ren, Ang He, Xiao-Bin Guo, Yan-Ping Jiang, Qiu-Xiang Liu, Xin-Gui Tang

The traditional von Neumann computing architecture leads to hidden costs in terms of computing resources and energy demand, and the brain-inspired neuromorphic artificial intelligence architecture is receiving increasing attention as one of the main competitors in improving computing power. Based on the issues above, a brain-like device based on Mg0.1Zn0.9O thin film is fabricated. This device can simulate various synaptic behaviors, including typical long/short-term plasticity. In neuromorphic computing, an artificial neural network is built to achieve handwritten digit recognition. The accuracy of recognition was improved through the nonlinearity modulation of synaptic weights (conductance). The brain-like device simulated dendrite sensing processes and exhibits four behavioral outcomes. Excitatory postsynaptic current (EPSC) is induced by 365 nm ultraviolet stimulation with an intensity of 23.5 mW/cm2 on the brain-like device. The memory effect of EPSC is modulated through changing the duration of light, which is similar to the learning process of the human brain and shows potential in optical neuromorphic devices.

中文翻译:


模拟树突感知过程和光学诱导兴奋性突触后电流的类脑装置



传统的冯·诺依曼计算架构在计算资源和能源需求方面存在隐性成本,而受脑启发的神经形态人工智能架构作为提升计算能力的主要竞争者之一,越来越受到关注。基于上述问题,制造了一种基于 Mg0.1Zn0.9O 薄膜的类脑器件。该设备可以模拟各种突触行为,包括典型的长期/短期可塑性。在神经形态计算中,构建人工神经网络以实现手写数字识别。通过突触权重 (电导率) 的非线性调制提高了识别的准确性。这个类似大脑的设备模拟了树突感应过程,并表现出四种行为结果。兴奋性突触后电流 (EPSC) 由脑状设备上强度为 23.5 mW/cm2 的 365 nm 紫外线刺激诱导。EPSC 的记忆效应是通过改变光的持续时间来调节的,这类似于人脑的学习过程,并在光学神经形态器件中显示出潜力。
更新日期:2025-01-23
down
wechat
bug