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PNAS Plus: Linkage between retinal ganglion cell density and the nonuniform spatial integration across the visual field

机译:PNAS Plus:视网膜神经节细胞密度与视野内非均匀空间整合之间的联系

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摘要

The ability to integrate visual information over space is a fundamental component of human pattern vision. Regardless of whether it is for detecting luminance contrast or for recognizing objects in a cluttered scene, the position of the target in the visual field governs the size of a window within which visual information is integrated. Here we analyze the relationship between the topographic distribution of ganglion cell density and the nonuniform spatial integration across the visual field. The extent of spatial integration for luminance detection (Ricco’s area) and object recognition (crowding zone) are measured at various target locations. The number of retinal ganglion cells (RGCs) underlying Ricco’s area or crowding zone is estimated by computing the product of Ricco’s area (or crowding zone) and RGC density for a given target location. We find a quantitative agreement between the behavioral data and the RGC density: The variation in the sampling density of RGCs across the human retina is closely matched to the variation in the extent of spatial integration required for either luminance detection or object recognition. Our empirical data combined with the simulation results of computational models suggest that a fixed number of RGCs subserves spatial integration of visual input, independent of the visual-field location.
机译:在空间上整合视觉信息的能力是人类模式视觉的基本组成部分。不管是检测亮度对比还是识别杂乱场景中的物体,目标在视场中的位置都决定着整合视觉信息的窗口的大小。在这里,我们分析了神经节细胞密度的地形分布与整个视野中非均匀空间整合之间的关系。在各个目标位置处测量用于亮度检测(Ricco的区域)和对象识别(拥挤区域)的空间整合程度。通过计算给定目标位置的Ricco面积(或拥挤区)和RGC密度的乘积,可以估算Ricco区域或拥挤区下面的视网膜神经节细胞(RGC)的数量。我们在行为数据和RGC密度之间找到了定量的一致性:整个人视网膜上RGC的采样密度的变化与亮度检测或物体识别所需的空间整合程度的变化紧密匹配。我们的经验数据与计算模型的仿真结果相结合,表明一定数量的RGC可以为视觉输入提供空间整合,而不受视野位置的影响。

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