The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions - PubMed (original) (raw)

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

Ayse Pinar Saygin et al. Soc Cogn Affect Neurosci. 2012 Apr.

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.

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Figures

Fig. 1

Fig. 1

Still images from the videos used in the experiment, depicting the agents. (A) Robot, (B) Android and (C) Human.

Fig. 2

Fig. 2

Repetition suppression. Whole-brain repetition suppression effect for (A) Robot, (B) Android and (C) Human conditions rendered on the lateral views of the cortical surface of each hemisphere.

Fig. 3

Fig. 3

Interactions. The top panel shows the main effect of Repetition (irrespective of Agent) rendered on the lateral views of the cortical hemispheres. The graphs depict the repetition suppression effect in all the peaks in which there was a significant interaction of Repetition by Agent (see Table 1 for statistics). _Y_-axes are percent signal change (Nonrepeat - Repeat).

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