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Related Experiment Videos

Learning innate face preferences.

James A Bednar1, Risto Miikkulainen

  • 1Department of Computer Sciences, University of Texas at Austin, Austin, TX 78712, USA. jbednar@cs.utexas.edu

Neural Computation
|June 21, 2003
PubMed
Summary
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Newborns prefer faces due to prenatal learning via internal brain activity, not just experience. This suggests genetic and environmental factors interact within the same visual areas for face perception development.

Area of Science:

  • Neuroscience
  • Developmental Psychology
  • Computational Biology

Background:

  • Newborns show innate preference for faces, but mature face processing develops over months.
  • Existing models struggle to reconcile newborn face orienting with infant face learning.
  • The interaction of genetic and environmental influences on face perception is not fully understood.

Purpose of the Study:

  • Propose a unified mechanism for genetically specified and environment-driven face preferences.
  • Explain newborn orienting to faces through prenatal learning and internal input.
  • Provide a computational model for the development of face perception circuitry.

Main Methods:

  • Utilized the HLISSOM (Hierarchical Likelihood-Informed Self-Organizing Map) biological model of the visual system.

Related Experiment Videos

  • Simulated prenatal exposure of a learning system to internally generated input patterns (e.g., PGO waves).
  • Investigated how combined learning and internal patterns shape visual circuitry for face perception.

    • Main Results:

    • Demonstrated that learning combined with internal patterns efficiently specifies and develops face perception circuitry.
    • Showed that prenatal learning can account for newborn preferences for schematic and photographic faces.
    • Provided a computational explanation for the interplay of genetic and experiential influences on face processing.

    Conclusions:

    • Newborn face orienting may arise from prenatal learning driven by internally generated neural activity during REM sleep.
    • Genetically specified and environment-driven preferences can coexist within the same visual processing areas.
    • This model offers a computational framework for understanding the development of complex adaptive systems like face perception.