Uncanny valley effect : an EEG study

Abstract

Facial expressions are widely used for interpersonal communication as they reflect the internal affective or emotional state of an individual. Humans are highly dependent on facial cues and expressions to judge the effective state of people around them. However, humans react differently when they see a human, a humanoid or a mechanical bot. Mori, 1970 showed that humans respond to androids as a function of their feature similarity to humans and is popularly known as the ‘Uncanny Valley effect’(UVE). UVE pertains to an eerie feeling when we see or interact with robots. Given that facial cues play a significant role in human communication we aim to test if UVE is associated with face processing. An electroencephalogram (EEG) provides us access to the electrical activity in our brain via small, metal discs (electrodes) attached to our scalp. The Event-Related Potential (ERP) of N-170 (Negative potential of 170 msec after stimulus onset) from EEG is a robust marker associated with face processing. The amplitude of the N170 component is found to be greater for human faces as compared to non-face stimuli. So we hypothesize that if the uncanny valley effect is related to face processing, then there would be differential characteristics of the N170 component elicited for the human face as compared to the robotic face processing. To test this hypothesis we asked participants to rate human and robotic faces images shown on computer monitor while recording EEG signals simultaneously. The rating was done on an analog scale for each individual image and was done on the basis of two metrics: Likeability and Mechano-humanness. The likeabiltiy defines how friendly is the face to look at and mechano-humanness indicating how mechanical does the face look like. The range of scale for likeability was from -100 to 100 and the range for mechano-humanness being 0 to 100. Rating data when analyzed showed a trend similar to the uncanny valley effect. Epochs of EEG aligned to the onset of face (human/robotic) stimulus were analyzed offline to study the N170 ERP. The results showed the presence of N170 component for both human and robotic faces. However, the magnitude of the N170 component was larger for human faces as compared to robotic faces. While data collection is underway to substantiate the hypothesis statistically, the preliminary results till date suggest the contribution of face processing regions of the brain towards the UVE.