Literature DB >> 18217835

Crowding and eccentricity determine reading rate.

Denis G Pelli1, Katharine A Tillman, Jeremy Freeman, Michael Su, Tracey D Berger, Najib J Majaj.   

Abstract

Bouma's law of crowding predicts an uncrowded central window through which we can read and a crowded periphery through which we cannot. The old discovery that readers make several fixations per second, rather than a continuous sweep across the text, suggests that reading is limited by the number of letters that can be acquired in one fixation, without moving one's eyes. That "visual span" has been measured in various ways, but remains unexplained. Here we show (1) that the visual span is simply the number of characters that are not crowded and (2) that, at each vertical eccentricity, reading rate is proportional to the uncrowded span. We measure rapid serial visual presentation (RSVP) reading rate for text, in both original and scrambled word order, as a function of size and spacing at central and peripheral locations. As text size increases, reading rate rises abruptly from zero to maximum rate. This classic reading rate curve consists of a cliff and a plateau, characterized by two parameters, critical print size and maximum reading rate. Joining two ideas from the literature explains the whole curve. These ideas are Bouma's law of crowding and Legge's conjecture that reading rate is proportional to visual span. We show that Legge's visual span is the uncrowded span predicted by Bouma's law. This result joins Bouma and Legge to explain reading rate's dependence on letter size and spacing. Well-corrected fluent observers reading ordinary text with adequate light are limited by letter spacing (crowding), not size (acuity). More generally, it seems that this account holds true, independent of size, contrast, and luminance, provided only that text contrast is at least four times the threshold contrast for an isolated letter. For any given spacing, there is a central uncrowded span through which we read. This uncrowded span model explains the shape of the reading rate curve. We test the model in several ways. We use a "silent substitution" technique to measure the uncrowded span during reading. These substitutions spoil letter identification but are undetectable when the letters are crowded. Critical spacing is the smallest distance between letters that avoids crowding. We find that the critical spacing for letter identification predicts both the critical spacing and the span for reading. Thus, crowding predicts the parameters that characterize both the cliff and the plateau of the reading rate curve. Previous studies have found worrisome differences across observers and laboratories in the measured peripheral reading rates for ordinary text, which may reflect differences in print exposure, but we find that reading rate is much more consistent when word order is scrambled. In all conditions tested--all sizes and spacings, central and peripheral, ordered and scrambled--reading is limited by crowding. For each observer, at each vertical eccentricity, reading rate is proportional to the uncrowded span.

Mesh:

Year:  2007        PMID: 18217835     DOI: 10.1167/7.2.20

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  100 in total

1.  Extra-large letter spacing improves reading in dyslexia.

Authors:  Marco Zorzi; Chiara Barbiero; Andrea Facoetti; Isabella Lonciari; Marco Carrozzi; Marcella Montico; Laura Bravar; Florence George; Catherine Pech-Georgel; Johannes C Ziegler
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-04       Impact factor: 11.205

2.  Sensory and cognitive influences on the training-related improvement of reading speed in peripheral vision.

Authors:  Yingchen He; Gordon E Legge; Deyue Yu
Journal:  J Vis       Date:  2013-06-24       Impact factor: 2.240

3.  Visual crowding in V1.

Authors:  Rachel Millin; A Cyrus Arman; Susana T L Chung; Bosco S Tjan
Journal:  Cereb Cortex       Date:  2013-07-05       Impact factor: 5.357

4.  Learning to read vertical text in peripheral vision.

Authors:  Ahalya Subramanian; Gordon E Legge; Gunther Harrison Wagoner; Deyue Yu
Journal:  Optom Vis Sci       Date:  2014-09       Impact factor: 1.973

5.  Training peripheral vision to read: Boosting the speed of letter processing.

Authors:  Deyue Yu; Gordon E Legge; Gunther Wagoner; Susana T L Chung
Journal:  Vision Res       Date:  2017-07-19       Impact factor: 1.886

6.  Experience-dependent changes in the topography of visual crowding.

Authors:  Kristin Williamson; Miranda Scolari; Sukeun Jeong; Min-Shik Kim; Edward Awh
Journal:  J Vis       Date:  2009-10-14       Impact factor: 2.240

7.  Dependence of reading speed on letter spacing in central vision loss.

Authors:  Susana T L Chung
Journal:  Optom Vis Sci       Date:  2012-09       Impact factor: 1.973

Review 8.  The uncrowded window of object recognition.

Authors:  Denis G Pelli; Katharine A Tillman
Journal:  Nat Neurosci       Date:  2008-10       Impact factor: 24.884

9.  Visuomotor crowding: the resolution of grasping in cluttered scenes.

Authors:  Paul F Bulakowski; Robert B Post; David Whitney
Journal:  Front Behav Neurosci       Date:  2009-11-16       Impact factor: 3.558

10.  A neurophysiologically plausible population code model for feature integration explains visual crowding.

Authors:  Ronald van den Berg; Jos B T M Roerdink; Frans W Cornelissen
Journal:  PLoS Comput Biol       Date:  2010-01-22       Impact factor: 4.475

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