Evidence and a Computational Explanation of Cultural Differences in Facial Expression Recognition

Matthew N. Dailey, Carrie Joyce, Michael J. Lyons, Miyuki Kamachi, Hanae Ishi, Jiro Gyoba, Garrison W. Cottrell

    Research output: Contribution to journalArticlepeer-review

    108 Citations (Scopus)

    Abstract

    Facial expressions are crucial to human social communication, but the extent to which they are innate and universal versus learned and culture dependent is a subject of debate. Two studies explored the effect of culture and learning on facial expression understanding. In Experiment 1, Japanese and U.S. participants interpreted facial expressions of emotion. Each group was better than the other at classifying facial expressions posed by members of the same culture. In Experiment 2, this reciprocal in-group advantage was reproduced by a neurocomputational model trained in either a Japanese cultural context or an American cultural context. The model demonstrates how each of us, interacting with others in a particular cultural context, learns to recognize a culture-specific facial expression dialect.

    Original languageEnglish
    Pages (from-to)874-893
    Number of pages20
    JournalEmotion
    Volume10
    Issue number6
    DOIs
    Publication statusPublished - 2010 Dec

    Keywords

    • Computational modeling
    • Cross-cultural emotion recognition
    • Facial expressions

    ASJC Scopus subject areas

    • Psychology(all)

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