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通过一种蜥蜴模拟和测量对生态相关运动的视觉检测。

Modeling and measuring the visual detection of ecologically relevant motion by an Anolis lizard.

机构信息

Department of Biological Sciences, Union College, Schenectady, NY 12308, USA.

出版信息

J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 2010 Jan;196(1):1-13. doi: 10.1007/s00359-009-0487-7. Epub 2009 Nov 12.

DOI:10.1007/s00359-009-0487-7
PMID:19908049
Abstract

Motion in the visual periphery of lizards, and other animals, often causes a shift of visual attention toward the moving object. This behavioral response must be more responsive to relevant motion (predators, prey, conspecifics) than to irrelevant motion (windblown vegetation). Early stages of visual motion detection rely on simple local circuits known as elementary motion detectors (EMDs). We presented a computer model consisting of a grid of correlation-type EMDs, with videos of natural motion patterns, including prey, predators and windblown vegetation. We systematically varied the model parameters and quantified the relative response to the different classes of motion. We carried out behavioral experiments with the lizard Anolis sagrei and determined that their visual response could be modeled with a grid of correlation-type EMDs with a spacing parameter of 0.3 degrees visual angle, and a time constant of 0.1 s. The model with these parameters gave substantially stronger responses to relevant motion patterns than to windblown vegetation under equivalent conditions. However, the model is sensitive to local contrast and viewer-object distance. Therefore, additional neural processing is probably required for the visual system to reliably distinguish relevant from irrelevant motion under a full range of natural conditions.

摘要

蜥蜴和其他动物的视觉边缘运动通常会引起视觉注意力向运动物体转移。这种行为反应必须对相关运动(捕食者、猎物、同种动物)比不相关运动(风吹草动)更敏感。视觉运动检测的早期阶段依赖于简单的局部电路,称为基本运动探测器(EMD)。我们提出了一个由网格相关型 EMD 组成的计算机模型,其中包括自然运动模式的视频,包括猎物、捕食者和风吹草动。我们系统地改变了模型参数,并量化了不同类别的运动的相对响应。我们用蜥蜴 Anolis sagrei 进行了行为实验,并确定他们的视觉反应可以用网格相关型 EMD 模型来模拟,其空间参数为 0.3 度视角,时间常数为 0.1 秒。在相同条件下,具有这些参数的模型对相关运动模式的反应明显强于风吹草动。然而,该模型对局部对比度和观察者-物体距离很敏感。因此,视觉系统可能需要额外的神经处理,以便在各种自然条件下可靠地区分相关运动和不相关运动。

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