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

Source record saygin-2012-predictive-coding · 2012 · Social Cognitive and Affective Neuroscience
Evidence tier: B (peer-reviewed-journal) · Verification: verified-fulltext
Bottom line: Repetition suppression in bilateral anterior intraparietal sulcus was stronger for the android (appearance–motion mismatch) than for the human or robot, interpreted as prediction error; authors state this cannot establish a causal link to the uncanny valley.

Citation

Ayse Pinar Saygin, Thierry Chaminade, Hiroshi Ishiguro, Jon Driver, Chris Frith (2012). The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions. Social Cognitive and Affective Neuroscience, 7(4), 413-422. https://doi.org/10.1093/scan/nsr025

Verification entry (identifiers, resolvers, claims with source locations): /data/citations.json#saygin-2012-predictive-coding

Study design

Field Value
Design Event-related fMRI repetition suppression (3T); 2-s grayscale clips of 8 actions by a human, the Repliee Q2 android (human appearance, mechanical motion) and the same robot with skin removed (mechanical appearance and motion)
Modality video, robot
Stimuli Action videos: Human, Android, Robot
Participants (N) 19
N detail 20 recruited; 1 excluded for head motion
Topics uncanny-valley, neural, predictive-coding

Results

Metric Value Note
aIPS repetition suppression Android > Human and Robot (bilateral) key action-perception node
Left extrastriate body area Human and Android > Robot sensitive to humanlike form
Selectivity for appearance or motion alone little (outside EBA) network responded to the match between them

Mechanism relevance

perceptual-mismatch, predictive-coding

Limitations

Cited in

Verification

Field Value
Status verified-fulltext
Compiler confidence high
Checked on 2026-10-07
Via academic.oup.com article page