视觉运动在昆虫神经系统中的刚性传播

IF 6 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Hao Chen , Boquan Fan , Haiyang Li , Jigen Peng
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引用次数: 0

摘要

为了开发用于视觉运动检测的高效人工视觉系统,研究人员从昆虫神经系统中对视觉运动敏感的神经通路中找到了灵感。尽管多个已提出的神经计算模型表现出了与昆虫观察到的模型一致的显著性能,但这些模型如何描述视觉神经元对相应运动模式的敏感性的数学基础仍有待阐明。为了填补这一研究空白,本研究最初提出视觉运动的刚性传播是昆虫视觉神经系统模型的基本数学特性,这意味着模型输出的动态与输入所反映的视觉运动动态保持一致。为了验证这一特性,本研究以昆虫神经系统中对视觉运动敏感的通路之一--小目标运动探测器(STMD)神经通路为例,严格证明了平移视觉运动的动态是通过STMD计算模型中的视网膜测量编码刚性传播的。数值实验结果进一步证实了所提出的 STMD 模型特性。这项研究为探索昆虫视觉神经系统底层视觉运动感知的本质提供了一个新颖的理论框架,并为昆虫视觉运动感知和人工视觉系统这一更广泛的研究领域带来了一个创新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rigid propagation of visual motion in the insect’s neural system
In the pursuit of developing an efficient artificial visual system for visual motion detection, researchers find inspiration from the visual motion-sensitive neural pathways in the insect’s neural system. Although multiple proposed neural computational models exhibit significant performance aligned with those observed from insects, the mathematical basis for how these models characterize the sensitivity of visual neurons to corresponding motion patterns remains to be elucidated. To fill this research gap, this study originally proposed that the rigid propagation of visual motion is an essential mathematical property of the models for the insect’s visual neural system, meaning that the dynamics of the model output remain consistent with the visual motion dynamics reflected in the input. To verify this property, this study uses the small target motion detector (STMD) neural pathway — one of the visual motion-sensitive pathways in the insect’s neural system — as an exemplar, rigorously demonstrating that the dynamics of translational visual motion are rigidly propagated through the encoding of retinal measurements in STMD computational models. Numerical experiment results further substantiate the proposed property of STMD models. This study offers a novel theoretical framework for exploring the nature of the visual motion perception underlying the insect’s visual neural system and brings an innovative perspective to the broader research field of insect visual motion perception and artificial visual systems.
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来源期刊
Neural Networks
Neural Networks 工程技术-计算机:人工智能
CiteScore
13.90
自引率
7.70%
发文量
425
审稿时长
67 days
期刊介绍: Neural Networks is a platform that aims to foster an international community of scholars and practitioners interested in neural networks, deep learning, and other approaches to artificial intelligence and machine learning. Our journal invites submissions covering various aspects of neural networks research, from computational neuroscience and cognitive modeling to mathematical analyses and engineering applications. By providing a forum for interdisciplinary discussions between biology and technology, we aim to encourage the development of biologically-inspired artificial intelligence.
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