Deep learning of shared perceptual representations for familiar and unfamiliar faces: Reply to commentaries.

Journal: Cognition
Published Date: Oct 24, 2020

Abstract

We recently argued that human unfamiliar face identity perception reflects substantial perceptual expertise, and that the advantage for familiar over unfamiliar face identity matching reflects a learned mapping between generic high-level perceptual features and a unique identity representation of each individual (Blauch, Behrmann and Plaut, 2020). Here we respond to two commentaries by Young and Burton (2020) and Yovel and Abudarham (2020), clarifying and elaborating our stance on various theoretical issues, and discussing topics for future research in human face recognition and the learning of perceptual representations.

Authors

  • Nicholas M Blauch
    Program in Neural Computation, Carnegie Mellon University, United States; Neuroscience Institute, Carnegie Mellon University, United States. Electronic address: blauch@cmu.edu.
  • Marlene Behrmann
    Neuroscience Institute, Carnegie Mellon University, United States; Department of Psychology, Carnegie Mellon University, United States.
  • David C Plaut
    Department of Psychology and the Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, USA. Electronic address: plaut@cmu.edu.

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