Contour interaction for an easily resolvable stimulus

On the effectiveness of noise masks: naturalistic vs. un-naturalistic image statistics

It has been argued that the human visual system is optimized for identification of broadband objects embedded in stimuli possessing orientation averaged power spectra fall-offs that obey the 1/f(β) relationship typically observed in natural scene imagery (i.e., β=2.0 on logarithmic axes). Here, we were interested in whether individual spatial channels leading to recognition are functionally optimized for narrowband targets when masked by noise possessing naturalistic image statistics (β=2.0). The current study therefore explores the impact of variable β noise masks on the identification of narrowband target stimuli ranging in spatial complexity, while simultaneously controlling for physical or perceived differences between the masks. The results show that β=2.0 noise masks produce the largest identification thresholds regardless of target complexity, and thus do not seem to yield functionally optimized channel processing. The differential masking effects are discussed in the context of contrast gain control.

Crowding--an essential bottleneck for object recognition: a mini-review

Crowding, generally defined as the deleterious influence of nearby contours on visual discrimination, is ubiquitous in spatial vision. Crowding impairs the ability to recognize objects in clutter. It has been extensively studied over the last 80 years or so, and much of the renewed interest is the hope that studying crowding may lead to a better understanding of the processes involved in object recognition. Crowding also has important clinical implications for patients with macular degeneration, amblyopia and dyslexia. There is no shortage of theories for crowding-from low-level receptive field models to high-level attention. The current picture is that crowding represents an essential bottleneck for object perception, impairing object perception in peripheral, amblyopic and possibly developing vision. Crowding is neither masking nor surround suppression. We can localize crowding to the cortex, perhaps as early as V1; however, there is a growing consensus for a two-stage model of crowding in which the first stage involves the detection of simple features (perhaps in V1), and a second stage is required for the integration or interpretation of the features as an object beyond V1. There is evidence for top-down effects in crowding, but the role of attention in this process remains unclear. The strong effect of learning in shrinking the spatial extent of crowding places strong constraints on possible models for crowding and for object recognition. The goal of this review is to try to provide a broad, balanced and succinct review that organizes and summarizes the diverse and scattered studies of crowding, and also helps to explain it to the non-specialist. A full understanding of crowding may allow us to understand this bottleneck to object recognition and the rules that govern the integration of features into objects.

“Crowding” in normal and amblyopic vision assessed with Gaussian and Gabor C’s

The purpose of this study was to investigate the extent and specificity of crowding in the normal fovea and periphery, and the central field of amblyopes, using "C"-like patterns. In the first experiment we measured the extent of crowding for C-patterns comprised of Gaussian patches, over a range of target sizes using a four-alternative forced-choice (up, down, left, right) method. We found that the extent of foveal crowding is proportional to target size. In contrast, in normal periphery and in the central field of amblyopes, crowding extends over large spatial distances and is not size dependent. Crowding for our stimuli occurred with both same-polarity and opposite polarity patches. To test whether the extended crowding in amblyopia resulted from a shift in the spatial scale of analysis, we measured crowding with band-limited C-patterns (comprised of Gabor patches) in a gap localization task (2-AFC). With band-limited stimuli, and a task that does not involve judging the orientation of the gap, the amblyopic eyes showed crowding over a longer distance than that of normal observers. We also tested the orientation specificity of crowding by varying the orientation of the flanks. In normal fovea, crowding is orientation specific: in amblyopia it is not. While crowding in normal fovea can be explained by simple pattern masking, crowding seen in normal periphery and amblyopes cannot. Instead we suggest that crowding in amblyopic and peripheral vision is a result of extended pooling at a stage following the stage of feature detection.

Foveal contour interaction: detection and discrimination

Contour interaction, the detrimental effect of flanking features on the discrimination of optotypes, has been studied mainly close to the visual acuity limit. We were interested to know how these results compare with those for the detection of targets. According to the simplest model of contour interaction, comparable detection effects would be expected. The case for low-level masking would be further strengthened if the form and nature of the dependence on flank separation and flank polarity followed that typically found in studies of lateral spatial masking [Vision Res. 33, 993 (1993)]. Landolt Cs subtending a visual angle of 0.25 degrees, 0.5 degrees, and 1.0 degrees were presented and contrast thresholds for detecting the presence of the Landolt C and discriminating its orientation were measured in five normal subjects as a function of flank separation and flank polarity. The results obtained for the relationship between detection and discrimination depend on the size of the target used. For small letters, discrimination but not detection was significantly affected by flanking bars. For large letters, detection and discrimination were affected to the same extent. However, in this case the effectiveness of opposite-polarity flanks and the finding that facilitation occurred at close, not far, flank separations suggests that the simplest explanation in terms of masking may not be applicable.

Foveal contrast thresholds exhibit spatial-frequency- and polarity-specific contour interactions

Traditionally, contour interaction has been investigated at the visual acuity limit using a Landolt C and flanking bars, performance being quantified in terms of a percent correct measure. More recently, it has been shown that the properties of the contour interaction are different when larger stimuli are used: Contour interaction is not polarity specific, and spatial frequency tuning for an unflanked C is broader. Here we quantify contour interaction for stimuli 5x larger than the resolution limit in terms of contrast thresholds. We show that polarity of bars has little effect on unfiltered stimuli but does show very different effects on the spatial-frequency-tuning curves for discrimination of the Landolt C. This explains the polarity dependence of crowding at the visual acuity limit and its independence for larger unfiltered targets. Thus the underlying filtering function is composed of more than one mechanism, affected differently depending on the relative polarity of the test and flank contours.