Cargando…

The Bouma law accounts for crowding in 50 observers

Crowding is the failure to recognize an object due to surrounding clutter. Our visual crowding survey measured 13 crowding distances (or “critical spacings”) twice in each of 50 observers. The survey includes three eccentricities (0, 5, and 10 deg), four cardinal meridians, two orientations (radial...

Descripción completa

Detalles Bibliográficos
Autores principales: Kurzawski, Jan W., Burchell, Augustin, Thapa, Darshan, Winawer, Jonathan, Majaj, Najib J., Pelli, Denis G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408772/
https://www.ncbi.nlm.nih.gov/pubmed/37540179
http://dx.doi.org/10.1167/jov.23.8.6
_version_ 1785086235634565120
author Kurzawski, Jan W.
Burchell, Augustin
Thapa, Darshan
Winawer, Jonathan
Majaj, Najib J.
Pelli, Denis G.
author_facet Kurzawski, Jan W.
Burchell, Augustin
Thapa, Darshan
Winawer, Jonathan
Majaj, Najib J.
Pelli, Denis G.
author_sort Kurzawski, Jan W.
collection PubMed
description Crowding is the failure to recognize an object due to surrounding clutter. Our visual crowding survey measured 13 crowding distances (or “critical spacings”) twice in each of 50 observers. The survey includes three eccentricities (0, 5, and 10 deg), four cardinal meridians, two orientations (radial and tangential), and two fonts (Sloan and Pelli). The survey also tested foveal acuity, twice. Remarkably, fitting a two-parameter model—the well-known Bouma law, where crowding distance grows linearly with eccentricity—explains 82% of the variance for all 13 × 50 measured log crowding distances, cross-validated. An enhanced Bouma law, with factors for meridian, crowding orientation, target kind, and observer, explains 94% of the variance, again cross-validated. These additional factors reveal several asymmetries, consistent with previous reports, which can be expressed as crowding-distance ratios: 0.62 horizontal:vertical, 0.79 lower:upper, 0.78 right:left, 0.55 tangential:radial, and 0.78 Sloan-font:Pelli-font. Across our observers, peripheral crowding is independent of foveal crowding and acuity. Evaluation of the Bouma factor, b (the slope of the Bouma law), as a biomarker of visual health would be easier if there were a way to compare results across crowding studies that use different methods. We define a standardized Bouma factor b′ that corrects for differences from Bouma's 25 choice alternatives, 75% threshold criterion, and linearly symmetric flanker placement. For radial crowding on the right meridian, the standardized Bouma factor b′ is 0.24 for this study, 0.35 for Bouma (1970), and 0.30 for the geometric mean across five representative modern studies, including this one, showing good agreement across labs, including Bouma's. Simulations, confirmed by data, show that peeking can skew estimates of crowding (e.g., greatly decreasing the mean or doubling the SD of log b). Using gaze tracking to prevent peeking, individual differences are robust, as evidenced by the much larger 0.08 SD of log b across observers than the mere 0.03 test–retest SD of log b measured in half an hour. The ease of measurement of crowding enhances its promise as a biomarker for dyslexia and visual health.
format Online
Article
Text
id pubmed-10408772
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher The Association for Research in Vision and Ophthalmology
record_format MEDLINE/PubMed
spelling pubmed-104087722023-08-09 The Bouma law accounts for crowding in 50 observers Kurzawski, Jan W. Burchell, Augustin Thapa, Darshan Winawer, Jonathan Majaj, Najib J. Pelli, Denis G. J Vis Article Crowding is the failure to recognize an object due to surrounding clutter. Our visual crowding survey measured 13 crowding distances (or “critical spacings”) twice in each of 50 observers. The survey includes three eccentricities (0, 5, and 10 deg), four cardinal meridians, two orientations (radial and tangential), and two fonts (Sloan and Pelli). The survey also tested foveal acuity, twice. Remarkably, fitting a two-parameter model—the well-known Bouma law, where crowding distance grows linearly with eccentricity—explains 82% of the variance for all 13 × 50 measured log crowding distances, cross-validated. An enhanced Bouma law, with factors for meridian, crowding orientation, target kind, and observer, explains 94% of the variance, again cross-validated. These additional factors reveal several asymmetries, consistent with previous reports, which can be expressed as crowding-distance ratios: 0.62 horizontal:vertical, 0.79 lower:upper, 0.78 right:left, 0.55 tangential:radial, and 0.78 Sloan-font:Pelli-font. Across our observers, peripheral crowding is independent of foveal crowding and acuity. Evaluation of the Bouma factor, b (the slope of the Bouma law), as a biomarker of visual health would be easier if there were a way to compare results across crowding studies that use different methods. We define a standardized Bouma factor b′ that corrects for differences from Bouma's 25 choice alternatives, 75% threshold criterion, and linearly symmetric flanker placement. For radial crowding on the right meridian, the standardized Bouma factor b′ is 0.24 for this study, 0.35 for Bouma (1970), and 0.30 for the geometric mean across five representative modern studies, including this one, showing good agreement across labs, including Bouma's. Simulations, confirmed by data, show that peeking can skew estimates of crowding (e.g., greatly decreasing the mean or doubling the SD of log b). Using gaze tracking to prevent peeking, individual differences are robust, as evidenced by the much larger 0.08 SD of log b across observers than the mere 0.03 test–retest SD of log b measured in half an hour. The ease of measurement of crowding enhances its promise as a biomarker for dyslexia and visual health. The Association for Research in Vision and Ophthalmology 2023-08-04 /pmc/articles/PMC10408772/ /pubmed/37540179 http://dx.doi.org/10.1167/jov.23.8.6 Text en Copyright 2023 The Authors https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License.
spellingShingle Article
Kurzawski, Jan W.
Burchell, Augustin
Thapa, Darshan
Winawer, Jonathan
Majaj, Najib J.
Pelli, Denis G.
The Bouma law accounts for crowding in 50 observers
title The Bouma law accounts for crowding in 50 observers
title_full The Bouma law accounts for crowding in 50 observers
title_fullStr The Bouma law accounts for crowding in 50 observers
title_full_unstemmed The Bouma law accounts for crowding in 50 observers
title_short The Bouma law accounts for crowding in 50 observers
title_sort bouma law accounts for crowding in 50 observers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408772/
https://www.ncbi.nlm.nih.gov/pubmed/37540179
http://dx.doi.org/10.1167/jov.23.8.6
work_keys_str_mv AT kurzawskijanw theboumalawaccountsforcrowdingin50observers
AT burchellaugustin theboumalawaccountsforcrowdingin50observers
AT thapadarshan theboumalawaccountsforcrowdingin50observers
AT winawerjonathan theboumalawaccountsforcrowdingin50observers
AT majajnajibj theboumalawaccountsforcrowdingin50observers
AT pellidenisg theboumalawaccountsforcrowdingin50observers
AT kurzawskijanw boumalawaccountsforcrowdingin50observers
AT burchellaugustin boumalawaccountsforcrowdingin50observers
AT thapadarshan boumalawaccountsforcrowdingin50observers
AT winawerjonathan boumalawaccountsforcrowdingin50observers
AT majajnajibj boumalawaccountsforcrowdingin50observers
AT pellidenisg boumalawaccountsforcrowdingin50observers