Literature DB >> 29704523

Uncanny valley as a window into predictive processing in the social brain.

Burcu A Urgen1, Marta Kutas2, Ayse P Saygin2.   

Abstract

Uncanny valley refers to humans' negative reaction to almost-but-not-quite-human agents. Theoretical work proposes prediction violation as an explanation for uncanny valley but no empirical work has directly tested it. Here, we provide evidence that supports this theory using event-related brain potential recordings from the human scalp. Human subjects were presented images and videos of three agents as EEG was recorded: a real human, a mechanical robot, and a realistic robot in between. The real human and the mechanical robot had congruent appearance and motion whereas the realistic robot had incongruent appearance and motion. We hypothesize that the appearance of the agent would provide a context to predict her movement, and accordingly the perception of the realistic robot would elicit an N400 effect indicating the violation of predictions, whereas the human and the mechanical robot would not. Our data confirmed this hypothesis suggesting that uncanny valley could be explained by violation of one's predictions about human norms when encountered with realistic but artificial human forms. Importantly, our results implicate that the mechanisms underlying perception of other individuals in our environment are predictive in nature.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Action perception; N400; Predictive processing; Social neuroscience; Uncanny valley

Mesh:

Year:  2018        PMID: 29704523      PMCID: PMC6556781          DOI: 10.1016/j.neuropsychologia.2018.04.027

Source DB:  PubMed          Journal:  Neuropsychologia        ISSN: 0028-3932            Impact factor:   3.139


  4 in total

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Authors:  Emmanuele Tidoni; Henning Holle; Michele Scandola; Igor Schindler; Loron Hill; Emily S Cross
Journal:  iScience       Date:  2022-05-25

3.  Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories.

Authors:  Alexander Diel; Karl F MacDorman
Journal:  J Vis       Date:  2021-04-01       Impact factor: 2.240

4.  Impact of Digital Assistant Attributes on Millennials' Purchasing Intentions: A Multi-Group Analysis using PLS-SEM, Artificial Neural Network and fsQCA.

Authors:  Manu Sharma; Sudhanshu Joshi; Sunil Luthra; Anil Kumar
Journal:  Inf Syst Front       Date:  2022-09-23       Impact factor: 5.261

  4 in total

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