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Holistic face processing, thought to be unique to upright faces, was examined computationally. Results indicate composite faces are processed via multichannel, featural systems, not a single holistic channel.

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Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience
  • Visual Perception

Background:

  • Upright faces are traditionally believed to undergo more holistic processing than inverted faces.
  • The composite face paradigm infers holistic processing from recognition interference between face parts.
  • Holistic processing is often mechanistically defined as pooling facial features into a single processing channel (coactive processing).

Purpose of the Study:

  • To computationally characterize the nature of holistic processing in composite faces.
  • To distinguish holistic processing from other potential processing models, such as failures of selective attention.
  • To test whether composite face processing aligns with the coactive processing definition of holistic processing.

Main Methods:

  • Utilized logical-rule models and Systems Factorial Technology for computational analysis.
  • Operationalized holistic processing as the pooling of features into a single decision process.
  • Examined face recognition performance across upright/inverted and aligned/misaligned composite face conditions.

Main Results:

  • Face processing performance was best explained by a mixture of serial and parallel processing architectures.
  • These processing architectures were consistent across all tested conditions (upright/inverted, aligned/misaligned).
  • Results demonstrated multichannel, featural processing of composite faces.

Conclusions:

  • The findings are inconsistent with the notion of coactive processing as the sole mechanism for composite face recognition.
  • Composite face processing appears to involve multiple, independent feature-processing channels.
  • This challenges the traditional view of holistic processing as a unified, coactive system for faces.