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Prior expectations shape how we see faces. This study reveals the brain uses prediction error processing and sharpened representations to integrate prior knowledge with new sensory face information.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • Sensory perception is heavily influenced by prior expectations.
  • The brain integrates prior and sensory information through mechanisms like prediction error (PE) processing and sharpened representations.

Purpose of the Study:

  • To investigate the neural mechanisms of expectation integration during face perception.
  • To differentiate between prediction error processing and sharpened representations using computational modeling and fMRI.

Main Methods:

  • Employed deep neural networks and representational similarity analysis (RSA) of fMRI data.
  • Used ambiguous face stimuli (face morphs) to probe the influence of prior expectations.
  • Analyzed neural activity across the face-processing hierarchy.

Main Results:

  • Expected faces were identified faster, and perception of ambiguous faces shifted towards priors.
  • Evidence for prediction error processing was found across the occipital face area (OFA), fusiform face area (FFA), and anterior temporal lobe (ATL).
  • Sharpened representations were suggested in the OFA.

Conclusions:

  • The brain integrates prior expectations into face perception.
  • Both prediction error processing and sharpened representations contribute to this integration.
  • Findings support a model where face representation is grounded in prior expectations.