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用于在小鼠视网膜中进行视觉空间的区域性增强分析的亚地形图。

Sub-topographic maps for regionally enhanced analysis of visual space in the mouse retina.

机构信息

Department of Neurobiology, Stanford University School of Medicine, Stanford, California.

Department of Ophthalmology, Stanford University School of Medicine, Stanford, California.

出版信息

J Comp Neurol. 2019 Jan 1;527(1):259-269. doi: 10.1002/cne.24457. Epub 2018 Dec 19.

Abstract

In many species, neurons are unevenly distributed across the retina, leading to nonuniform analysis of specific visual features at certain locations in visual space. In recent years, the mouse has emerged as a premiere model for probing visual system function, development, and disease. Thus, achieving a detailed understanding of mouse visual circuit architecture is of paramount importance. The general belief is that mice possess a relatively even topographic distribution of retinal ganglion cells (RGCs)-the output neurons of the eye. However, mouse RGCs include ∼30 subtypes; each responds best to a specific feature in the visual scene and conveys that information to central targets. Given the crucial role of RGCs and the prominence of the mouse as a model, we asked how different RGC subtypes are distributed across the retina. We targeted and filled individual fluorescently tagged RGC subtypes from across the retinal surface and evaluated the dendritic arbor extent and soma size of each cell according to its specific retinotopic position. Three prominent RGC subtypes: On-Off direction selective RGCs, object-motion-sensitive RGCs, and a specialized subclass of nonimage-forming RGCs each had marked topographic variations in their dendritic arbor sizes. Moreover, the pattern of variation was distinct for each RGC subtype. Thus, there is increasing evidence that the mouse retina encodes visual space in a region-specific manner. As a consequence, some visual features are sampled far more densely at certain retinal locations than others. These findings have implications for central visual processing, perception, and behavior in this prominent model species.

摘要

在许多物种中,神经元在视网膜上的分布不均匀,导致在视觉空间的某些位置对特定视觉特征的分析不均匀。近年来,老鼠已成为研究视觉系统功能、发育和疾病的首选模型。因此,详细了解老鼠的视觉回路结构至关重要。人们普遍认为,老鼠的视网膜神经节细胞(RGC)——眼睛的输出神经元具有相对均匀的拓扑分布。然而,老鼠的 RGC 包括约 30 种亚型;每种亚型对视觉场景中的特定特征反应最好,并将该信息传递给中枢靶标。鉴于 RGC 的关键作用以及老鼠作为模型的突出地位,我们想知道不同的 RGC 亚型在视网膜上是如何分布的。我们针对来自视网膜表面的各个荧光标记的 RGC 亚型进行靶向和填充,并根据其特定的视网膜位置评估每个细胞的树突分支范围和体细胞大小。三种主要的 RGC 亚型:开-关方向选择性 RGC、物体运动敏感 RGC 和专门的非成像 RGC 亚类,其树突分支大小都有明显的拓扑变化。此外,每种 RGC 亚型的变化模式都不同。因此,越来越多的证据表明,老鼠的视网膜以特定区域的方式对视觉空间进行编码。因此,某些视觉特征在某些视网膜位置被采样得远远比其他位置更密集。这些发现对该重要模型物种的中枢视觉处理、感知和行为都有影响。

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本文引用的文献

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Architecture, Function, and Assembly of the Mouse Visual System.鼠类视觉系统的结构、功能与组装
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