Moore Bret A, Kamilar Jason M, Collin Shaun P, Bininda-Emonds Olaf R P, Dominy Nathaniel J, Hall Margaret I, Heesy Christopher P, Johnsen Sönke, Lisney Thomas J, Loew Ellis R, Moritz Gillian, Nava Saúl S, Warrant Eric, Yopak Kara E, Fernández-Juricic Esteban
Dept. of Biological Sciences, Purdue Univ., West Lafayette, IN, USA.
J Vis. 2012 Nov 20;12(12):13. doi: 10.1167/12.12.13.
Vertebrates possess different types of retinal specializations that vary in number, size, shape, and position in the retina. This diversity in retinal configuration has been revealed through topographic maps, which show variations in neuron density across the retina. Although topographic maps of about 300 vertebrates are available, there is no method for characterizing retinal traits quantitatively. Our goal is to present a novel method to standardize information on the position of the retinal specializations and changes in retinal ganglion cell (RGC) density across the retina from published topographic maps. We measured the position of the retinal specialization using two Cartesian coordinates and the gradient in cell density by sampling ganglion cell density values along four axes (nasal, temporal, ventral, and dorsal). Using this information, along with the peak and lowest RGC densities, we conducted discriminant function analyses (DFAs) to establish if this method is sensitive to distinguish three common types of retinal specializations (fovea, area, and visual streak). The discrimination ability of the model was higher when considering terrestrial (78%-80% correct classification) and aquatic (77%-86% correct classification) species separately than together. Our method can be used in the future to test specific hypotheses on the differences in retinal morphology between retinal specializations and the association between retinal morphology and behavioral and ecological traits using comparative methods controlling for phylogenetic effects.
脊椎动物拥有不同类型的视网膜特化结构，这些结构在数量、大小、形状以及在视网膜中的位置上存在差异。视网膜结构的这种多样性已通过地形图得以揭示，地形图展示了整个视网膜神经元密度的变化。尽管已有约300种脊椎动物的地形图，但尚无定量表征视网膜特征的方法。我们的目标是提出一种新方法，用于标准化已发表地形图中视网膜特化结构的位置信息以及整个视网膜中视网膜神经节细胞（RGC）密度的变化。我们使用两个笛卡尔坐标测量视网膜特化结构的位置，并通过沿四个轴（鼻侧、颞侧、腹侧和背侧）对神经节细胞密度值进行采样来测量细胞密度梯度。利用这些信息，以及RGC密度的峰值和最低值，我们进行了判别函数分析（DFA），以确定该方法是否能灵敏地区分三种常见的视网膜特化类型（中央凹、区域和视觉条纹）。分别考虑陆生（正确分类率78%-80%）和水生（正确分类率77%-86%）物种时，模型的判别能力高于将它们一起考虑时。我们的方法未来可用于通过控制系统发育效应的比较方法，检验关于视网膜特化结构之间视网膜形态差异以及视网膜形态与行为和生态特征之间关联的特定假设。
