Retinal topography maps in R: New tools for the analysis and visualization of spatial retinal data
Author(s) -
Brian A. Cohn,
Shaun P. Collin,
Peter C. Wainwright,
Lars Schmitz
Publication year - 2015
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/15.9.19
Subject(s) - retina , visualization , retinal , computer science , software , stereology , artificial intelligence , computer vision , biology , cartography , pattern recognition (psychology) , neuroscience , geography , biochemistry , programming language , endocrinology
Retinal topography maps are a widely used tool in vision science, neuroscience, and visual ecology, providing an informative visualization of the spatial distribution of cell densities across the retinal hemisphere. Here, we introduce Retina, an R package for computational mapping, inspection of topographic model fits, and generation of average maps. Functions in Retina take cell count data obtained from retinal wholemounts using stereology software. Accurate visualizations and comparisons between different eyes have been difficult in the past, because of deformation and incisions of retinal wholemounts. We account for these issues by incorporation of the R package Retistruct, which results in a retrodeformation of the wholemount into a hemispherical shape, similar to the original eyecup. The maps are generated by thin plate splines, after the data were transformed into a two-dimensional space with an azimuthal equidistant plot projection. Retina users can compute retinal topography maps independent of stereology software choice and assess model fits with a variety of diagnostic plots. Functionality of Retina also includes species average maps, an essential feature for interspecific analyses. The Retina package will facilitate rigorous comparative studies in visual ecology by providing a robust quantitative approach to generate retinal topography maps.
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