论文标题
建模果蝇运动视觉途径，用于解码针对混乱的运动背景转换对象的方向
Modelling Drosophila Motion Vision Pathways for Decoding the Direction of Translating Objects Against Cluttered Moving Backgrounds
论文作者
论文摘要
准确，有效地解码在混乱的移动背景前转换对象的方向仍然是一个具有挑战性的问题。在自然界中，轻巧和低功率的飞行昆虫采用运动视觉来检测飞行高度可变环境中的移动目标，这是学习运动感知策略的绝佳范式。本文研究了果蝇\ textit {果蝇}运动视觉途径，并根据最先进的生理研究介绍了计算建模。所提出的视觉系统模型具有生物学成分，可在路径上，宽场水平敏感（HS）和垂直敏感（VS）系统。这项研究的主要贡献是在两个方面：1）提出的模型表达了方向选择性（DS）和方向 - oppontement（do）响应的形成，以馈送方式显示为运动感知神经回路的主要特征； 2）它还通过建模时空动力学的建模，包括运动前过滤机制的组合以及开路内和关闭路径内部相关器的局部相关器的组合，从而有效地抑制了无关的背景运动或提高动力学响应，它还显示了在混乱的运动背景前转换对象的强大选择性，包括运动前进行过滤机制和局部相关器的合并。因此，翻译对象的方向被解码为带有正或负输出的HS和VS系统的全局响应，表明首选方向（PD）或NULL方向（ND）转换。该实验验证了提出的神经系统模型的有效性，并证明了其响应性偏爱嵌入在混乱的运动背景中的更快移动，更高对比度和较大尺寸的目标。
Decoding the direction of translating objects in front of cluttered moving backgrounds, accurately and efficiently, is still a challenging problem. In nature, lightweight and low-powered flying insects apply motion vision to detect a moving target in highly variable environments during flight, which are excellent paradigms to learn motion perception strategies. This paper investigates the fruit fly \textit{Drosophila} motion vision pathways and presents computational modelling based on cutting-edge physiological researches. The proposed visual system model features bio-plausible ON and OFF pathways, wide-field horizontal-sensitive (HS) and vertical-sensitive (VS) systems. The main contributions of this research are on two aspects: 1) the proposed model articulates the forming of both direction-selective (DS) and direction-opponent (DO) responses, revealed as principal features of motion perception neural circuits, in a feed-forward manner; 2) it also shows robust direction selectivity to translating objects in front of cluttered moving backgrounds, via the modelling of spatiotemporal dynamics including combination of motion pre-filtering mechanisms and ensembles of local correlators inside both the ON and OFF pathways, which works effectively to suppress irrelevant background motion or distractors, and to improve the dynamic response. Accordingly, the direction of translating objects is decoded as global responses of both the HS and VS systems with positive or negative output indicating preferred-direction (PD) or null-direction (ND) translation. The experiments have verified the effectiveness of the proposed neural system model, and demonstrated its responsive preference to faster-moving, higher-contrast and larger-size targets embedded in cluttered moving backgrounds.
