When periphery rules: Enhanced sampling weights of the visual periphery in crowding across dimensions

Crowding, our inability to identify a feature or object - the target - due to its proximity to adjacent features or objects - flankers - exhibits a notable inner-outer asymmetry. This asymmetry is characterized by the outer flanker - more peripheral - creating stronger interference than the inner one - closer to the fovea. But crowding is not uniform across different feature dimensions. For example, in the case of orientation, this asymmetry reflects misreport errors: observers are more likely to misidentify the outer flanker as the target than the inner one. However, for spatial frequency (SF), observers tend to average the features of the target and flankers (Yashar et al., 2019). Here, we investigated whether and how the inner-outer asymmetry manifests across various feature dimensions: Gabor orientation and SF, as well as T-shape tilt and color. We reanalyzed continuous estimation reports data published by Yashar et al. (2019), focusing on a previously unanalyzed factor: the relative position of each flanker (inner vs. outer). We fit probabilistic models that assign variable weights to each flanker. Our analysis revealed that observers predominantly misreport the outer flanker as the target with Gabor orientation and T-shape tilt stimuli, and slightly so with color stimuli, whereas with Gabor SF, observers perform a weighted average of all features but also with a bias towards the outer flanker over the inner one. These findings suggest that an increased weighting on the more peripheral items is a general characteristic of crowding in peripheral vision.

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Publication Details

Journal
Psychonomic Bulletin & Review
Published
2024-09-20
DOI
https://doi.org/10.3758/s13423-024-02580-7
Citations
2
Primary Topic
Visual perception and processing mechanisms
Type
article
Field-Weighted Citation Impact
0.69

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article

When periphery rules: Enhanced sampling weights of the visual periphery in crowding across dimensions

M. Carrasco, Amit Yashar
2 citations
Psychonomic Bulletin & Review
Visual perception and processing mechanisms
0.69
article

When periphery rules: Enhanced sampling weights of the visual periphery in crowding across dimensions

M. Carrasco, Amit Yashar
article en
2 citations

Abstract

Crowding, our inability to identify a feature or object - the target - due to its proximity to adjacent features or objects - flankers - exhibits a notable inner-outer asymmetry. This asymmetry is characterized by the outer flanker - more peripheral - creating stronger interference than the inner one - closer to the fovea. But crowding is not uniform across different feature dimensions. For example, in the case of orientation, this asymmetry reflects misreport errors: observers are more likely to misidentify the outer flanker as the target than the inner one. However, for spatial frequency (SF), observers tend to average the features of the target and flankers (Yashar et al., 2019). Here, we investigated whether and how the inner-outer asymmetry manifests across various feature dimensions: Gabor orientation and SF, as well as T-shape tilt and color. We reanalyzed continuous estimation reports data published by Yashar et al. (2019), focusing on a previously unanalyzed factor: the relative position of each flanker (inner vs. outer). We fit probabilistic models that assign variable weights to each flanker. Our analysis revealed that observers predominantly misreport the outer flanker as the target with Gabor orientation and T-shape tilt stimuli, and slightly so with color stimuli, whereas with Gabor SF, observers perform a weighted average of all features but also with a bias towards the outer flanker over the inner one. These findings suggest that an increased weighting on the more peripheral items is a general characteristic of crowding in peripheral vision.

Psychonomic Bulletin & ReviewVol. 32(2)
New York University (US), University of Haifa (IL)
Israel Science Foundation, University of Haifa
Sustainable cities and communities
Openalex Percentile: Top 31%
Visual perception and processing mechanisms
0.69
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