The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions

TLDR

The study used fMRI repetition suppression to examine how the human action perception system responds to the appearance and motion of human, robot, and android agents. Results showed that the action perception system was not selective for appearance or motion alone but exhibited stronger suppression for the android, especially in bilateral anterior intraparietal sulcus, indicating heightened prediction error that may underlie the uncanny valley.

Abstract

Using functional magnetic resonance imaging (fMRI) repetition suppression, we explored the selectivity of the human action perception system (APS), which consists of temporal, parietal and frontal areas, for the appearance and/or motion of the perceived agent. Participants watched body movements of a human (biological appearance and movement), a robot (mechanical appearance and movement) or an android (biological appearance, mechanical movement). With the exception of extrastriate body area, which showed more suppression for human like appearance, the APS was not selective for appearance or motion per se. Instead, distinctive responses were found to the mismatch between appearance and motion: whereas suppression effects for the human and robot were similar to each other, they were stronger for the android, notably in bilateral anterior intraparietal sulcus, a key node in the APS. These results could reflect increased prediction error as the brain negotiates an agent that appears human, but does not move biologically, and help explain the 'uncanny valley' phenomenon.