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Bret A. Moore, Jason M. Kamilar, Shaun P. Collin, Olaf R. P. Bininda-Emonds, Nathaniel J. Dominy, Margaret I. Hall, Christopher P. Heesy, Sönke Johnsen, Thomas J. Lisney, Ellis R. Loew, Gillian Moritz, Saúl S. Nava, Eric Warrant, Kara E. Yopak, Esteban Fernández-Juricic; A novel method for comparative analysis of retinal specialization traits from topographic maps. Journal of Vision 2012;12(12):13. doi: 10.1167/12.12.13.
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© 2017 Association for Research in Vision and Ophthalmology.
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.
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