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Steven C. Dakin, John Cass, John A. Greenwood, Peter J. Bex; Probabilistic, positional averaging predicts object-level crowding effects with letter-like stimuli. Journal of Vision 2010;10(10):14. doi: 10.1167/10.10.14.
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© ARVO (1962-2015); The Authors (2016-present)
We investigated how crowding—a breakdown in object recognition that occurs in the presence of nearby distracting clutter—works for complex letter-like stimuli. Subjects reported the orientation (up/down/left/right) of a T target, abutted by a single flanker composed of randomly positioned horizontal and vertical bars. In addition to familiar retinotopic anisotropies (e.g., more crowding from more eccentric flankers), we report three object-centered anisotropies. First, inversions of the target element were rare: errors included twice as many ±90° as 180° target rotations. Second, flankers were twice as intrusive when they lay above or below (end-flanking) compared to left or right (side-flanking) of an upright T target (an effect that holds under global rotation of the target–flanker pair). Third, end flankers induce subjects to make erroneous reports that resemble the flanker (producing a structured pattern of errors), but errors induced by side flankers do not (instead producing random errors). A model based on probabilistic weighted averaging of the feature positions within contours can account for these effects. Thus, we demonstrate a set of seemingly “high-level” object-centered crowding effects that can arise from “low-level” interactions between the features of letter-like elements.
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