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Updated: Sep 24, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
Multidimensional feature interactions in visual crowding: When configural cues eliminate the polarity advantage
Koen Rummens1,2, Bilge Sayim1,3,4
1University of Bern, Institute of Psychology, Bern, Switzerland.
Configural cues can alter visual crowding, showing that strong target-flanker grouping can reduce interference. This challenges traditional crowding rules by demonstrating non-additive interactions between similarity dimensions.
Area of Science:
- Visual perception
- Cognitive psychology
- Neuroscience
Background:
- Crowding is a phenomenon in visual perception where surrounding objects (flankers) impair target identification.
- Typically, reduced target-flanker similarity lessens crowding, often attributed to ungrouping.
- The polarity advantage, where opposite contrast polarity reduces crowding, is a well-established finding.
Purpose of the Study:
- To investigate how configural cues and target-flanker grouping influence visual crowding.
- To determine if strong target-flanker grouping can mitigate crowding, contrary to established principles.
- To examine the interaction between contrast polarity and flanker configuration on crowding effects.
Main Methods:
- Participants identified the tilt of a central line target presented peripherally.
- Target and flankers varied in contrast polarity (same or opposite).
- Flanker configurations included upright, unidirectional, and bidirectional tilts.
Main Results:
- Flanker configuration interacted with contrast polarity, affecting the polarity advantage.
- Upright and bidirectional flankers showed a polarity advantage, while unidirectional flankers did not.
- Strong target-flanker grouping, particularly with unidirectional flankers, alleviated crowding.
Conclusions:
- Configural cues can override the typical advantage of low target-flanker similarity.
- Strong grouping can reduce, rather than exacerbate, crowding, challenging existing models.
- Crowding strength is modulated by non-additive interactions between features, limiting the universality of simple crowding rules.
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