Cited by 452Action Observation and SynchronizationSocial Robot Interaction and HRIFace Recognition and Perception

The DOI matches its Crossref record; 97 of the 97 references it cites were found in a registry or an index; none of the 66 sources its claims cite is checked for support yet.

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

Open access
Saygin, Ayse Pinar, Chaminade, Thierry, Ishiguro, Hiroshi, Driver, Jon, Frith, Chris·2012·Social Cognitive and Affective Neuroscience

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.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Using fMRI repetition suppression, this study tested whether the human action perception system is selective for biological appearance or motion by comparing responses to a human, a humanoid android, and the same robot with mechanical appearance. The android—human-like appearance with mechanical movement—produced distinctive repetition suppression, especially in bilateral anterior intraparietal sulcus, which the authors interpret as prediction error relevant to the uncanny valley.

Key findings

  • The action perception system was largely not selective for appearance or motion per se; the main exception was left extrastriate body area (EBA), which showed more suppression for human-like appearance (Agent × Repetition, P = 0.03; Android > Robot, P = 0.02; Human > Robot, P = 0.07).
  • The Android condition produced stronger repetition suppression than both Human and Robot in bilateral anterior intraparietal sulcus (aIPS): left aIPS Agent × Repetition P = 0.002, Android > Robot P = 0.002, Android > Human P = 0.004; right aIPS Agent × Repetition P = 0.002, Android > Robot P = 0.003, Android > Human P = 0.02.
  • Left superior intraparietal sulcus (sIPS) also showed an Agent × Repetition interaction (P = 0.04), with Android > Robot (P = 0.01).
  • Behavioral accuracy on comprehension questions was 0.84 (s.d. = 0.28) and did not differ between conditions; eye movement measures also did not differ between conditions (P > 0.1 for all pairwise comparisons).

Methods

  • Twenty healthy right-handed adults aged 20–36 participated; data from one participant were excluded due to excessive head movement. Participants watched 2-s grayscale video clips of eight actions performed by Human, Android (Repliee Q2 with human-like appearance and mechanical movement), and Robot (same robot stripped of human-like surface appearance, with identical mechanical movement).
  • fMRI was performed on a 3 T Siemens Allegra scanner across 6 runs of 12 blocks; each block contained 12 videos, and each clip was equiprobably a repeat or nonrepeat of the previous clip.
  • Data were analyzed with SPM5 using whole-brain random-effects repetition suppression (Nonrepeat > Repeat, t ≥ 8.86, P < 0.05 FDR-corrected, cluster ≥ 30 voxels), followed by ROI analyses using 5-mm spheres and repeated-measures ANOVA on Agent × Repetition.

Limitations

  • The authors state that the experiment was not designed optimally to “explain” the uncanny valley and can make only a modest contribution to defining its neural basis; they also state that a conclusive or causal link between prediction error and the uncanny valley cannot be made from these data.
  • The authors note there is no agreed-upon localizer for the action perception system, and ventral premotor cortex did not show significant repetition suppression despite being a key node of the APS.
  • Evident from the text: the sample was small (20 recruited, 19 analyzed), and the Android and Robot conditions used the same robot with identical programmed kinematics, so appearance and motion were manipulated in a constrained, non-parametric way rather than independently across many agents.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1093/scan/nsr025

Cites

97 of 97 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 Still images from the videos used in the experiment, depicting the agents. (A) Robot, (B) Android and (C) Human.
Fig. 1 Still images from the videos used in the experiment, depicting the agents. (A) Robot, (B) Android and (C) Human.CC BY-NC · PubMed Central
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. 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.CC BY-NC · PubMed Central
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).
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).CC BY-NC · PubMed Central

Verification

Claims the paper makes

35 Not checked yet · 30 Own result · 10 Own interpretation · 3 Own method · 2 No basis given

Verify all 66 references — free account

Show all 48 claims

  • It may state two separate claims as one. 12
  • The quote only partly states this claim. 2
  • Probably not a substantial claim. 22
32 of 32
  • The paper relies on this without support.

    Robots can have appearance or movement kinematics that are not biological, but can nevertheless be perceived as carrying out recognizable actions.

    “robots can have appearance or movement kinematics that are not biological, but can nevertheless be perceived as carrying out recognizable actions.”
  • The paper relies on this without support.

    We have a lifetime of experience that associates human appearance with biological motion, and machines (such as robots) with mechanical motion.

    “We have a lifetime of experience that associates human appearance with biological motion, and machines (such as robots) with mechanical motion.”
  • The paper relies on this without support.

    For both the Human and Robot conditions, the observed motion kinematics was congruent with what would be predicted from the appearance of the agent.

    “For both our Human condition and our Robot condition, the observed motion kinematics was congruent with what would be predicted from the appearance of the agent.”
3 of 3

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

2 of 2

Citations

Cites

Research works printed but not linked: 2

  1. Levi, 2004, Why Tom Hanks is less than human: While sensors cannot capture how humans act, humans can give life to digital characters, Newsweek, 650, 305
  2. Mori, 1970, The uncanny valley, Energy, 7, 33

Cited by

Sorted by citations

See all 452

Metadata

Authors
Saygin, A. P., Chaminade, T., Ishiguro, H., Driver, J., & Frith, C.
Affiliations
Centre National de la Recherche Scientifique (FR)
Venue
Social Cognitive and Affective Neuroscience
Published
2011-04-22
Volume
7
Issue
4
Pages
413-422
ISSN
  • 1749-5016 (ISSN-L)
  • 1749-5024
OpenAlex
W2121184995
Cited by
452
References
97
Citations by year
2026: 36 · 2025: 34 · 2024: 27 · 2023: 22 · 2022: 30 · 2021: 35 · 2020: 24 · 2019: 36 · 2018: 35 · 2017: 34 · 2016: 29 · 2015: 38 · 2014: 27 · 2013: 22 · 2012: 20
FWCI
30.89
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • Social Cognitive and Affective Neuroscience (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, cc-by-nc)
  • UCL Discovery (University College London) (submittedVersion)
Funders
  • Royal Society
  • National Research Foundation
  • Danmarks Grundforskningsfond
  • University of California, San Diego
  • Japan Society for the Promotion of Science
  • Kavli Institute for Brain and Mind, University of California, San Diego
Topics
  • Social Sciences › Psychology › Social Psychology › Action Observation and Synchronization
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
Keywords
predictive coding, uncanny valley, action perception, humanoid robots, Android, prediction error, intraparietal sulcus, extrastriate body area, human-robot interaction
MeSH terms
Adult, Biomechanical Phenomena, Brain Mapping, Cerebral Cortex, Eye Movements, Female, Gestures, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Motion, Motion Perception, Oxygen, Photic Stimulation, Predictive Value of Tests, Random Allocation, Robotics, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review