Seeing social events: The visual specialization for dyadic human-human interactions

Detection and recognition of social interactions unfolding in the surroundings is as vital as detection and recognition of faces, bodies, and animate entities in general. We have demonstrated that the visual system is particularly sensitive to a configuration with two bodies facing each other as if...

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Bibliographic Details
Published inJournal of experimental psychology. Human perception and performance Vol. 45; no. 7; p. 877
Main Authors Papeo, Liuba, Abassi, Etienne
Format Journal Article
LanguageEnglish
Published United States 01.07.2019
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Summary:Detection and recognition of social interactions unfolding in the surroundings is as vital as detection and recognition of faces, bodies, and animate entities in general. We have demonstrated that the visual system is particularly sensitive to a configuration with two bodies facing each other as if interacting. In four experiments using backward masking on healthy adults, we investigated the properties of this dyadic visual representation. We measured the inversion effect (IE), the cost on recognition, of seeing bodies upside-down as opposed to upright, as an index of visual sensitivity: the greater the visual sensitivity, the greater the IE. The IE was increased for facing (vs. nonfacing) dyads, whether the head/face direction was visible or not, which implies that visual sensitivity concerns two bodies, not just two faces/heads. Moreover, the difference in IE for facing versus nonfacing dyads disappeared when one body was replaced by another object. This implies selective sensitivity to a body facing another body, as opposed to a body facing anything. Finally, the IE was reduced when reciprocity was eliminated (one body faced another, but the latter faced away). Thus, the visual system is sensitive selectively to dyadic configurations that approximate a prototypical social exchange with two bodies spatially close and mutually accessible to one another. These findings reveal visual configural representations encompassing multiple objects, which could provide fast and automatic parsing of complex relationships beyond individual faces or bodies. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
ISSN:1939-1277
DOI:10.1037/xhp0000646