Abstract/Summary

In change detection paradigms, changes to social or animate aspects of a scene are detected better and faster compared to non-social or inanimate aspects. Whilst 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 to 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 quicky and easily detected than those in non-interacting configurations.