Search for: All records

Pareidolic faces—illusory faces in objects—offer a unique context for studying biases in the development of facial processing because they are visually diverse (e.g., color, shape) while lacking key elements of real faces (e.g., race, species). In an online study, 7- and 8-year-old children (n = 32) and adults (n = 32) categorized happy and angry expressions in human and pareidolic face images. We found that children have a robust, adult-like happy face advantage for human and pareidolic faces, reflected in speed and accuracy. These results suggest that the happy face advantage is not unique to human faces, supporting the hypothesis that humans employ comparable face templates for processing pareidolic and human faces. Our findings add to a growing list of other processing similarities between human and pareidolic faces and suggest that children may likewise show these similarities. 

Humans demonstrate enhanced processing of human faces compared with animal faces, known as own-species bias. This bias is important for identifying people who may cause harm, as well as for recognizing friends and kin. However, growing evidence also indicates a more general face bias. Faces have high evolutionary importance beyond conspecific interactions, as they aid in detecting predators and prey. Few studies have explored the interaction of these biases together. In three experiments, we explored processing of human and animal faces, compared with each other and to nonface objects, which allowed us to examine both own-species and broader face biases. We used a dot-probe paradigm to examine human adults’ covert attentional biases for task-irrelevant human faces, animal faces, and objects. We replicated the own-species attentional bias for human faces relative to animal faces. We also found an attentional bias for animal faces relative to objects, consistent with the proposal that faces broadly receive privileged processing. Our findings suggest that humans may be attracted to a broad class of faces. Further, we found that while participants rapidly attended to human faces across all cue display durations, they attended to animal faces only when they had sufficient time to process them. Our findings reveal that the dot-probe paradigm is sensitive for capturing both own-species and more general face biases, and that each has a different attentional signature, possibly reflecting their unique but overlapping evolutionary importance. 

Abstract Humans detect faces efficiently from a young age. Face detection is critical for infants to identify and learn from relevant social stimuli in their environments. Faces with eye contact are an especially salient stimulus, and attention to the eyes in infancy is linked to the emergence of later sociality. Despite the importance of both of these early social skills—attending to faces and attending to the eyes—surprisingly little is known about how they interact. We used eye tracking to explore whether eye contact influences infants' face detection. Longitudinally, we examined 2‐, 4‐, and 6‐month‐olds' (N = 65) visual scanning of complex image arrays with human and animal faces varying in eye contact and head orientation. Across all ages, infants displayed superior detection of faces with eye contact; however, this effect varied as a function of species and head orientation. Infants were more attentive to human than animal faces and were more sensitive to eye and head orientation for human faces compared to animal faces. Unexpectedly, human faces with both averted heads and eyes received the most attention. This pattern may reflect the early emergence of gaze following—the ability to look where another individual looks—which begins to develop around this age. Infants may be especially interested in averted gaze faces, providing early scaffolding for joint attention. This study represents the first investigation to document infants' attention patterns to faces systematically varying in their attentional states. Together, these findings suggest that infants develop early, specialized functional conspecific face detection.