The nature of letter crowding as revealed by first- and second-order classification images

• Published in: Journal of vision (Charlottesville, Va.) Va.), 2007-02, Vol.7 (2), p.5.1-526
• Main Authors: Nandy, Anirvan S, Tjan, Bosco S
• Format: Article
• Language: English
• Subjects: Adult; Classification; Contrast Sensitivity - physiology; Fovea Centralis - physiology; Humans; Light; Models, Psychological; Pattern Recognition, Visual - physiology; Perceptual Masking - physiology; Photic Stimulation - methods; Psychophysics; Sensory Thresholds; Space Perception; Visual Fields - physiology; Visual Perception - physiology
• ISSN: 1534-7362; 1534-7362
• DOI: 10.1167/7.2.5

Visual crowding refers to the marked inability to identify an otherwise perfectly identifiable object when it is flanked by other objects. Crowding places a significant limit on form vision in the visual periphery; its mechanism is, however, unknown. Building on the method of signal-clamped classification images (Tjan & Nandy, 2006), we developed a series of first- and second-order classification-image techniques to investigate the nature of crowding without presupposing any model of crowding. Using an "o" versus "x" letter-identification task, we found that (1) crowding significantly reduced the contrast of first-order classification images, although it did not alter the shape of the classification images; (2) response errors during crowding were strongly correlated with the spatial structures of the flankers that resembled those of the erroneously perceived targets; (3) crowding had no systematic effect on intrinsic spatial uncertainty of an observer nor did it suppress feature detection; and (4) analysis of the second-order classification images revealed that crowding reduced the amount of valid features used by the visual system and, at the same time, increased the amount of invalid features used. Our findings strongly support the feature-mislocalization or source-confusion hypothesis as one of the proximal contributors of crowding. Our data also agree with the inappropriate feature-integration account with the requirement that feature integration be a competitive process. However, the feature-masking account and a front-end version of the spatial attention account of crowding are not supported by our data.