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Synaptic plasticity in self-powered artificial striate cortex for binocular orientation selectivity

Engineering and Technology

Synaptic plasticity in self-powered artificial striate cortex for binocular orientation selectivity

Y. Ren, X. Bu, et al.

Dive into groundbreaking research conducted by Yanyun Ren, Xiaobo Bu, Ming Wang, and their team, as they unveil a bioinspired striate cortex powered by self-powered memristors. This innovative system showcases plasticity modulated by optical stimuli and demonstrates remarkable edge and corner detection capabilities for machine vision.

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~3 min • Beginner • English
Abstract
Get in-depth understanding of each part of visual pathway yields insights to conquer the challenges that classic computer vision is facing. Here, we first report the bioinspired striate cortex with binocular and orientation selective receptive field based on the crossbar array of self-powered memristors which is solution-processed monolithic all-perovskite system with each cross-point containing one CsFAPbI₃ solar cell directly stacking on the CsPbBr₃I memristor. The plasticity of self-powered memristor can be modulated by optical stimuli following triplet-STDP rules. Furthermore, plasticity of 3 × 3 flexible crossbar array of self-powered memristors has been successfully modulated based on generalized BCM learning rule for optical-encoded pattern recognition. Finally, we implemented artificial striate cortex with binocularity and orientation selectivity based on two simulated 9 × 9 self-powered memristors networks. The emulation of striate cortex with binocular and orientation selectivity will facilitate the brisk edge and corner detection for machine vision in the future applications.
Publisher
Nature Communications
Published On
Sep 23, 2022
Authors
Yanyun Ren, Xiaobo Bu, Ming Wang, Yue Gong, Junjie Wang, Yuyang Yang, Guijun Li, Meng Zhang, Ye Zhou, Su-Ting Han
Tags
bioinspired
memristors
plasticity
pattern recognition
machine vision
striate cortex
optical stimuli
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