Department of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL 35294
Department of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL 35294.
Proc Natl Acad Sci U S A. 2019 Feb 26;116(9):3827-3836. doi: 10.1073/pnas.1817076116. Epub 2019 Feb 8.
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.
跨空间整合视觉信息的能力是人类模式视觉的基本组成部分。无论目标是检测亮度对比度还是识别杂乱场景中的物体,目标在视野中的位置决定了视觉信息整合的窗口大小。在这里,我们分析了神经节细胞密度的地形分布与视野中非均匀空间整合之间的关系。在不同的目标位置测量亮度检测(Ricco 区域)和物体识别(拥挤区)的空间整合程度。Ricco 区域或拥挤区的视网膜神经节细胞 (RGC) 数量通过计算给定目标位置的 Ricco 区域(或拥挤区)和 RGC 密度的乘积来估计。我们发现行为数据与 RGC 密度之间存在定量一致性:人视网膜中 RGC 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密切匹配。我们的经验数据结合计算模型的模拟结果表明,固定数量的 RGC 用于视觉输入的空间整合,与视野位置无关。