Yamaguchi, Motonori and Bautista, Maemi and Daly, Ian (2026) Electrophysiological Correlates of the Uncanny Valley. International Journal of Human-Computer Interaction. DOI https://doi.org/10.1080/10447318.2026.2621278
Yamaguchi, Motonori and Bautista, Maemi and Daly, Ian (2026) Electrophysiological Correlates of the Uncanny Valley. International Journal of Human-Computer Interaction. DOI https://doi.org/10.1080/10447318.2026.2621278
Yamaguchi, Motonori and Bautista, Maemi and Daly, Ian (2026) Electrophysiological Correlates of the Uncanny Valley. International Journal of Human-Computer Interaction. DOI https://doi.org/10.1080/10447318.2026.2621278
Abstract
The present study investigated the electrophysiological correlates of the uncanny valley effect while human observers viewed pictures of robot faces that varied in the human-likeness of their appearance. We found characteristic non-linear trajectories of the N400 amplitude against the self-rated human-likeness score, similar to the trajectory found for the self-rated likability score. The late positive potential (LPP) and frontal-midline theta showed parabolic trajectories against the human-likeness scores, which peaked at most uncanny faces but did not follow the non-linear uncanny-valley pattern. The frontal alpha asymmetry and the N170 did not produce this trajectory. These results corroborated the proposal that the uncanny valley effect stems from expectancy violation for human faces, but they surprisingly provided little evidence for affective reactions to uncanny robot faces. The LPP and frontal-midline theta could reflect increased cognitive control to process categorically ambiguous faces rather than the uncanniness of the faces. These findings suggest that the uncanny valley effect is primarily a perceptual or cognitive phenomenon, whereas its emotional impact might be less prominent than commonly believed.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | affect; electrophysiology; Human-robot interaction; social robotics; valence |
| Divisions: | Faculty of Science and Health > Computer Science and Electronic Engineering, School of Faculty of Science and Health > Psychology, Department of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 25 Mar 2026 14:56 |
| Last Modified: | 25 Mar 2026 14:56 |
| URI: | http://repository.essex.ac.uk/id/eprint/42579 |
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