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A novel method for comparative analysis of retinal specialization traits from topographic maps

Moore, Bret A.; Kamilar, Jason M.; Collin, Shaun P.; Bininda-Emonds, Olaf R. P.; Dominy, Nathaniel J.; Hall, Margaret I.; Heesy, Christopher P.; Johnsen, Soenke; Lisney, Thomas J. and Loew, Ellis R., et al. (2012) In Journal of Vision 12(12).
Abstract
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... (More)
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. (Less)
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publication status
published
subject
keywords
fovea, ganglion cells, retina, topographic maps, visual ecology, visual, streak
in
Journal of Vision
volume
12
issue
12
publisher
Association for Research in Vision and Ophthalmology
external identifiers
  • wos:000313887400013
  • scopus:84870266321
ISSN
1534-7362
DOI
10.1167/12.12.13
language
English
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yes
id
0cc12175-f9fb-42b1-921c-28a4b6f1d39c (old id 3577768)
date added to LUP
2013-03-20 15:25:12
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2017-10-22 04:04:53
@article{0cc12175-f9fb-42b1-921c-28a4b6f1d39c,
  abstract     = {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.},
  author       = {Moore, Bret A. and Kamilar, Jason M. and Collin, Shaun P. and Bininda-Emonds, Olaf R. P. and Dominy, Nathaniel J. and Hall, Margaret I. and Heesy, Christopher P. and Johnsen, Soenke and Lisney, Thomas J. and Loew, Ellis R. and Moritz, Gillian and Nava, Saul S. and Warrant, Eric and Yopak, Kara E. and Fernandez-Juricic, Esteban},
  issn         = {1534-7362},
  keyword      = {fovea,ganglion cells,retina,topographic maps,visual ecology,visual,streak},
  language     = {eng},
  number       = {12},
  publisher    = {Association for Research in Vision and Ophthalmology},
  series       = {Journal of Vision},
  title        = {A novel method for comparative analysis of retinal specialization traits from topographic maps},
  url          = {http://dx.doi.org/10.1167/12.12.13},
  volume       = {12},
  year         = {2012},
}