September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Measuring crowding in a hundred people
Author Affiliations & Notes
  • Denis Pelli
    New York University
  • Jan Kurzawski
    New York University
  • Augustin Burchell
    Swarthmore College
  • Darshan Thapa
    New York University
  • Najib Majaj
    New York University
  • Jon Winawer
    New York University
  • Footnotes
    Acknowledgements  NIH Grant R01EY027964; NIH Core Grant P30 EY013079
Journal of Vision September 2021, Vol.21, 2725. doi:https://doi.org/10.1167/jov.21.9.2725
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      Denis Pelli, Jan Kurzawski, Augustin Burchell, Darshan Thapa, Najib Majaj, Jon Winawer; Measuring crowding in a hundred people. Journal of Vision 2021;21(9):2725. doi: https://doi.org/10.1167/jov.21.9.2725.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Surrounding an object by similar clutter makes it unrecognizable, a phenomenon called “crowding”. Crowding varies greatly across the visual field and across individuals. To better understand the individual differences, we measured radial crowding distance (i.e. “critical spacing”) and acuity across the visual field in 116 observers using letter stimuli. We compared crowding and acuity, and we assessed crowding’s dependence on eccentricity along several meridians. Fitting the Bouma Law — crowding distance grows linearly with radial eccentricity — we find that the Bouma factor (slope of crowding distance vs. eccentricity) is conserved along each meridian, but varies across meridians, showing three asymmetries: crowding distance and Bouma factor are 14% smaller in the right than left meridian, 10% smaller in lower than upper meridian and 35% smaller on the horizontal than vertical meridian. Previous studies reported the advantage of the lower and horizontal meridians; the left-right asymmetry is new. Power analysis indicates that a minimum of 30 observers is required to detect this effect, more than past studies tested. Taking into account meridional and individual differences we built a model of log crowding distance that explains 73% of the variance (leave-1-condition-out cross-validation). Furthermore, we find that the correlation between crowding and acuity is strongest in the fovea R=0.51 and drops to R=0.27 at 5 deg eccentricity. This indicates that clinical characterization of vision may need to assess both acuity and crowding. In sum, our crowding survey confirms the Bouma law, and characterizes variation of the Bouma factor across meridians and observers.

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