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Modelling face memory reveals task-generalizable representations

Author

Listed:
  • Jiayu Zhan

    (University of Glasgow)

  • Oliver G. B. Garrod

    (University of Glasgow)

  • Nicola van Rijsbergen

    (University of Glasgow)

  • Philippe G. Schyns

    (University of Glasgow
    University of Glasgow)

Abstract

Current cognitive theories are cast in terms of information-processing mechanisms that use mental representations1–4. For example, people use their mental representations to identify familiar faces under various conditions of pose, illumination and ageing, or to draw resemblance between family members. Yet, the actual information contents of these representations are rarely characterized, which hinders knowledge of the mechanisms that use them. Here, we modelled the three-dimensional representational contents of 4 faces that were familiar to 14 participants as work colleagues. The representational contents were created by reverse-correlating identity information generated on each trial with judgements of the face’s similarity to the individual participant’s memory of this face. In a second study, testing new participants, we demonstrated the validity of the modelled contents using everyday face tasks that generalize identity judgements to new viewpoints, age and sex. Our work highlights that such models of mental representations are critical to understanding generalization behaviour and its underlying information-processing mechanisms.

Suggested Citation

  • Jiayu Zhan & Oliver G. B. Garrod & Nicola van Rijsbergen & Philippe G. Schyns, 2019. "Modelling face memory reveals task-generalizable representations," Nature Human Behaviour, Nature, vol. 3(8), pages 817-826, August.
  • Handle: RePEc:nat:nathum:v:3:y:2019:i:8:d:10.1038_s41562-019-0625-3
    DOI: 10.1038/s41562-019-0625-3
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    Cited by:

    1. Laurent Caplette & Nicholas B. Turk-Browne, 2024. "Computational reconstruction of mental representations using human behavior," Nature Communications, Nature, vol. 15(1), pages 1-19, December.

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