A face detection bias for horizontal orientations develops in middle childhood - Balas, Benjamin J.; Schmidt, Jamie; Saville, Alyson (Frontiers in Psychology, 2015)
Faces are complex stimuli that can be described via intuitive facial features like the eyes, nose, and mouth, “configural” features like the distances between facial landmarks, and features that correspond to computations performed in the early visual system (e.g. oriented edges). With regard to this latter category of descriptors, adult face recognition relies disproportionately on information in specific spatial frequency and orientation bands: Many recognition tasks are performed more accurately when adults have access to mid-range spatial frequencies (8-16 cycles/face) and horizontal orientations (Dakin & Watt, 2009). In the current study, we examined how this information bias develops in middle childhood. We recruited children between the ages of 5-10 years old to participate in a simple categorization task that required them to label images according to whether they depicted a face or a house. Critically, children were presented with face and house images comprised either of primarily horizontal orientation energy, primarily vertical orientation energy, or both horizontal and vertical orientation energy. We predicted that any bias favoring horizontal information over vertical should be more evident in faces than in houses, and also that older children would be more likely to show such a bias than younger children. We designed our categorization task to be sufficiently easy that children would perform at near-ceiling accuracy levels, but with variation in response times that would reflect how they rely on different orientations as a function of age and object category. We found that horizontal bias for face detection (but not house detection) correlated significantly with age, suggesting an emergent category-specific bias for horizontal orientation energy that develops during middle childhood. These results thus suggest that the tuning of high-level recognition to specific low-level visual features takes take place over several years of visual development.