Using pattern classification to measure adaptation to the orientation of high order aberrations.

<h4>Background</h4>The image formed by the eye's optics is blurred by the ocular aberrations, specific to each eye. Recent studies demonstrated that the eye is adapted to the level of blur produced by the high order aberrations (HOA). We examined whether visual coding is also adapte...

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Autores principales:	Lucie Sawides, Carlos Dorronsoro, Andrew M Haun, Eli Peli, Susana Marcos
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/df2b8c75fe654041ab4f988e86f42768
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spelling	oai:doaj.org-article:df2b8c75fe654041ab4f988e86f427682021-11-18T08:59:43ZUsing pattern classification to measure adaptation to the orientation of high order aberrations.1932-620310.1371/journal.pone.0070856https://doaj.org/article/df2b8c75fe654041ab4f988e86f427682013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23967123/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>The image formed by the eye's optics is blurred by the ocular aberrations, specific to each eye. Recent studies demonstrated that the eye is adapted to the level of blur produced by the high order aberrations (HOA). We examined whether visual coding is also adapted to the orientation of the natural HOA of the eye.<h4>Methods and findings</h4>Judgments of perceived blur were measured in 5 subjects in a psychophysical procedure inspired by the "Classification Images" technique. Subjects were presented 500 pairs of images, artificially blurred with HOA from 100 real eyes (i.e. different orientations), with total blur level adjusted to match the subject's natural blur. Subjects selected the image that appeared best focused in each random pair, in a 6-choice ranked response. Images were presented through Adaptive Optics correction of the subject's aberrations. The images selected as best focused were identified as positive, the other as negative responses. The highest classified positive responses correlated more with the subject's Point Spread Function, PSF, (r = 0.47 on average) than the negative (r = 0.34) and the difference was significant for all subjects (p<0.02). Using the orientation of the best fitting ellipse of angularly averaged integrated PSF intensities (weighted by the subject's responses) we found that in 4 subjects the positive PSF response was close to the subject's natural PSF orientation (within 21 degrees on average) whereas the negative PSF response was almost perpendicularly oriented to the natural PSF (at 76 degrees on average).<h4>Conclusions</h4>The Classification-Images inspired method is very powerful in identifying the internally coded blur of subjects. The consistent bias of the Positive PSFs towards the natural PSF in most subjects indicates that the internal code of blur appears rather specific to each subject's high order aberrations and reveals that the calibration mechanisms for normalizing blur also operate using orientation cues.Lucie SawidesCarlos DorronsoroAndrew M HaunEli PeliSusana MarcosPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 8, p e70856 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lucie Sawides Carlos Dorronsoro Andrew M Haun Eli Peli Susana Marcos Using pattern classification to measure adaptation to the orientation of high order aberrations.
description	<h4>Background</h4>The image formed by the eye's optics is blurred by the ocular aberrations, specific to each eye. Recent studies demonstrated that the eye is adapted to the level of blur produced by the high order aberrations (HOA). We examined whether visual coding is also adapted to the orientation of the natural HOA of the eye.<h4>Methods and findings</h4>Judgments of perceived blur were measured in 5 subjects in a psychophysical procedure inspired by the "Classification Images" technique. Subjects were presented 500 pairs of images, artificially blurred with HOA from 100 real eyes (i.e. different orientations), with total blur level adjusted to match the subject's natural blur. Subjects selected the image that appeared best focused in each random pair, in a 6-choice ranked response. Images were presented through Adaptive Optics correction of the subject's aberrations. The images selected as best focused were identified as positive, the other as negative responses. The highest classified positive responses correlated more with the subject's Point Spread Function, PSF, (r = 0.47 on average) than the negative (r = 0.34) and the difference was significant for all subjects (p<0.02). Using the orientation of the best fitting ellipse of angularly averaged integrated PSF intensities (weighted by the subject's responses) we found that in 4 subjects the positive PSF response was close to the subject's natural PSF orientation (within 21 degrees on average) whereas the negative PSF response was almost perpendicularly oriented to the natural PSF (at 76 degrees on average).<h4>Conclusions</h4>The Classification-Images inspired method is very powerful in identifying the internally coded blur of subjects. The consistent bias of the Positive PSFs towards the natural PSF in most subjects indicates that the internal code of blur appears rather specific to each subject's high order aberrations and reveals that the calibration mechanisms for normalizing blur also operate using orientation cues.
format	article
author	Lucie Sawides Carlos Dorronsoro Andrew M Haun Eli Peli Susana Marcos
author_facet	Lucie Sawides Carlos Dorronsoro Andrew M Haun Eli Peli Susana Marcos
author_sort	Lucie Sawides
title	Using pattern classification to measure adaptation to the orientation of high order aberrations.
title_short	Using pattern classification to measure adaptation to the orientation of high order aberrations.
title_full	Using pattern classification to measure adaptation to the orientation of high order aberrations.
title_fullStr	Using pattern classification to measure adaptation to the orientation of high order aberrations.
title_full_unstemmed	Using pattern classification to measure adaptation to the orientation of high order aberrations.
title_sort	using pattern classification to measure adaptation to the orientation of high order aberrations.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/df2b8c75fe654041ab4f988e86f42768
work_keys_str_mv	AT luciesawides usingpatternclassificationtomeasureadaptationtotheorientationofhighorderaberrations AT carlosdorronsoro usingpatternclassificationtomeasureadaptationtotheorientationofhighorderaberrations AT andrewmhaun usingpatternclassificationtomeasureadaptationtotheorientationofhighorderaberrations AT elipeli usingpatternclassificationtomeasureadaptationtotheorientationofhighorderaberrations AT susanamarcos usingpatternclassificationtomeasureadaptationtotheorientationofhighorderaberrations
_version_	1718421054286725120

Using pattern classification to measure adaptation to the orientation of high order aberrations.

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