Recognition of facial expressions in autism: Effects of face masks and alexithymia.

It is often assumed that the recognition of facial expressions is impaired in autism. However, recent evidence suggests that reports of expression recognition difficulties in autistic participants may be attributable to co-occurring alexithymia-a trait associated with difficulties interpreting interoceptive and emotional states-not autism per se. Due to problems fixating on the eye-region, autistic individuals may be more reliant on information from the mouth region when judging facial expressions. As such, it may be easier to detect expression recognition deficits attributable to autism, not alexithymia, when participants are forced to base expression judgements on the eye-region alone. To test this possibility, we compared the ability of autistic participants (with and without high levels of alexithymia) and non-autistic controls to categorise facial expressions (a) when the whole face was visible, and (b) when the lower portion of the face was covered with a surgical mask. High-alexithymic autistic participants showed clear evidence of expression recognition difficulties: they correctly categorised fewer expressions than non-autistic controls. In contrast, low-alexithymic autistic participants were unimpaired relative to non-autistic controls. The same pattern of results was seen when judging masked and unmasked expression stimuli. In sum, we find no evidence for an expression recognition deficit attributable to autism, in the absence of high levels of co-occurring alexithymia, either when participants judge whole-face stimuli or just the eye-region. These findings underscore the influence of co-occurring alexithymia on expression recognition in autism.

Are social interactions preferentially attended in real-world scenes? Evidence from change blindness.

In change detection paradigms, changes to social or animate aspects of a scene are detected better and faster compared with non-social or inanimate aspects. While previous studies have focused on how changes to individual faces/bodies are detected, it is possible that individuals presented within a social interaction may be further prioritised, as the accurate interpretation of social interactions may convey a competitive advantage. Over three experiments, we explored change detection to complex real-world scenes, in which changes either occurred by the removal of (a) an individual on their own, (b) an individual who was interacting with others, or (c) an object. In Experiment 1 (N = 50), we measured change detection for non-interacting individuals versus objects. In Experiment 2 (N = 49), we measured change detection for interacting individuals versus objects. Finally, in Experiment 3 (N = 85), we measured change detection for non-interacting versus interacting individuals. We also ran an inverted version of each task to determine whether differences were driven by low-level visual features. In Experiments 1 and 2, we found that changes to non-interacting and interacting individuals were detected better and more quickly than changes to objects. We also found inversion effects for both non-interaction and interaction changes, whereby they were detected more quickly when upright compared with inverted. No such inversion effect was seen for objects. This suggests that the high-level, social content of the images was driving the faster change detection for social versus object targets. Finally, we found that changes to individuals in non-interactions were detected faster than those presented within an interaction. Our results replicate the social advantage often found in change detection paradigms. However, we find that changes to individuals presented within social interaction configurations do not appear to be more quickly and easily detected than those in non-interacting configurations.