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Face features and face configurations both contribute to visual crowding

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Abstract

Crowding refers to the inability to recognize an object in peripheral vision when other objects are presented nearby (Whitney & Levi Trends in Cognitive Sciences, 15, 160–168, 2011). A popular explanation of crowding is that features of the target and flankers are combined inappropriately when they are located within an integration field, thus impairing target recognition (Pelli, Palomares, & Majaj Journal of Vision, 4(12), 12:1136–1169, 2004). However, it remains unclear which features of the target and flankers are combined inappropriately to cause crowding (Levi Vision Research, 48, 635–654, 2008). For example, in a complex stimulus (e.g., a face), to what extent does crowding result from the integration of features at a part-based level or at the level of global processing of the configural appearance? In this study, we used a face categorization task and different types of flankers to examine how much the magnitude of visual crowding depends on the similarity of face parts or of global configurations. We created flankers with face-like features (e.g., the eyes, nose, and mouth) in typical and scrambled configurations to examine the impacts of part appearance and global configuration on the visual crowding of faces. Additionally, we used “electrical socket” flankers that mimicked first-order face configuration but had only schematic features, to examine the extent to which global face geometry impacted crowding. Our results indicated that both face parts and configurations contribute to visual crowding, suggesting that face similarity as realized under crowded conditions includes both aspects of facial appearance.

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Notes

  1. It is worth noting that studies have shown that certain facial features (e.g., the eyes, the eyebrows, the mouth, and the face outline) play more influential roles in gender discrimination than do others (Brown & Perrett, 1993; Dupuis-Roy, Fortin, Fiset, & Gosselin, 2009; Yamaguchi, Hirukawa, & Kanazawa, 1995). For example, Dupuis-Roy et al. had participants categorize the gender of a face presented behind a gray mask punctured by randomly located Gaussian apertures (the so-called “bubble mask”). They found that the availability of the eyes, the eyebrows, and the mouth was positively correlated with participants’ gender categorization performance, indicating an influential role of these facial features in gender categorization.

  2. We chose the 6° target eccentricity on the basis of previous crowding studies. For example, Farzin et al. (2009) presented target faces at eccentricities of 0°, 3°, 6°, and 10°, and showed a significant crowding effect only when targets were presented at the 6° eccentricity.

  3. Paired-samples t tests comparing the no-flanker condition with the Chinese character flanker condition in the periphery showed no significant differences [t(24) =1.79, p = .09; t(24) =0.34, p = .74; and t(24) =0.76, p = .46, for Exps. 1, 2, and 3, respectively].

  4. We used one-tailed p values for this and the next test because we hypothesized that line-drawn face flankers, which retained both global and local facial features, would cause more crowding than either scrambled face or electrical socket flankers.

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Author note

B.B. was supported by COBRE Grant No. P20 GM103505 from the National Institute for General Medical Studies (NIGMS) and NSF EPSCoR Grant No. EPS-0814442. The authors thank four anonymous reviewers for their helpful comments on earlier versions of the manuscript. The authors also thank Christopher Tonsager for his assistance with data collection.

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Authors and Affiliations

  1. Department of Psychology, Center for Visual and Cognitive Neuroscience, North Dakota State University, 1210 Albrecht Blvd., Fargo, North Dakota, 58108, USA

    Hsin-Mei Sun & Benjamin Balas

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  1. Hsin-Mei Sun
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  2. Benjamin Balas
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Correspondence to Benjamin Balas.

Appendixes

Appendixes

Appendix 1: Target faces used in Experiments 1–3

figure a

Appendix 2: Mean percentages of accuracy for each experimental condition in Experiments 1–3

The standard errors of the means are in parentheses.

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Sun, HM., Balas, B. Face features and face configurations both contribute to visual crowding. Atten Percept Psychophys 77, 508–519 (2015). https://doi.org/10.3758/s13414-014-0786-0

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