Looking more masculine among females: Spatial context modulates gender perception of face and biological motion

Abstract

Perception of visual information highly depends on spatial context. For instance, perception of a low-level visual feature, such as orientation, can be shifted away from its surrounding context, exhibiting a simultaneous contrast effect. Although previous studies have demonstrated the adaptation aftereffect of gender, a high-level visual feature, it remains largely unknown whether gender perception can also be shaped by a simultaneously presented context. In the present study, we found that the gender perception of a central face or a point-light walker was repelled away from the gender of its surrounding faces or walkers. A norm-based opponent model of lateral inhibition, which accounts for the adaptation aftereffect of high-level features, can also excellently fit the simultaneous contrast effect. But different from the reported contextual effect of low-level features, the simultaneous contrast effect of gender cannot be observed when the centre and the surrounding stimuli are from different categories, or when the surrounding stimuli are suppressed from awareness. These findings on one hand reveal a resemblance between the simultaneous contrast effect and the adaptation aftereffect of high-level features, on the other hand highlight different biological mechanisms underlying the contextual effects of low-and high-level visual features.

Effect of spatial context on perceived walking direction

“…Although there is limited evidence of spatial contrast effects in high-level vision, a contrast effect has been found in body perception, in which the silhouette of a person's body was judged to be thinner when surrounded by wider silhouettes compared with when surrounded by thinner silhouettes ( Wedell et al, 2005 ). Also, in gender perception, the gender of a central target face/point-light walker was more likely to be perceived as opposite to the surrounding gender, resulting in a contrast effect ( Liu, Cheng, Yuan, & Jiang, 2023 ).…”