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Revisiting the effective connectivity within the distributed cortical network for face perception.

Roman Kessler1,2,3,4, Kristin M Rusch1,2,5, Kim C Wende1,6

  • 1Laboratory for Multimodal Neuroimaging, Department of Psychiatry and Psychotherapy, University of Marburg, Germany.

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Summary

This study revises the model of face perception, revealing a densely interconnected core system with significant forward, backward, and lateral connections between key brain regions like the OFA, FFA, and STS.

Keywords:
Conceptual replicationDynamic causal modelingEmotion processingFace perceptionfMRI

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Area of Science:

  • Neuroscience
  • Cognitive Psychology

Background:

  • The classical model of face perception involves the occipital face area (OFA), fusiform face area (FFA), and posterior superior temporal sulcus (STS).
  • A 2007 study proposed a hierarchical, feed-forward model with limited connectivity within this core system.

Purpose of the Study:

  • To conceptually replicate and update the 2007 model of face perception's effective connectivity.
  • To investigate how face and emotion perception influence connectivity within the core face perception network.

Main Methods:

  • Utilized four functional magnetic resonance imaging (fMRI) datasets.
  • Applied contemporary versions of dynamic causal modeling (DCM) and hierarchical linear modeling.
  • Assessed effective connectivity within the OFA, FFA, and STS network.

Main Results:

  • The revised model revealed a densely interconnected core system with significant forward, backward, and lateral connections.
  • Face perception enhanced OFA-FFA and OFA-STS forward connectivity, and FFA-OFA backward connectivity, alongside FFA-STS lateral connectivity.
  • Emotion perception modulated OFA-STS forward and FFA-STS lateral connectivity.

Conclusions:

  • The findings revise the classical hierarchical model, proposing a more interconnected network for face perception.
  • The revised model provides a robust framework for future research on face perception network dynamics.
  • Conceptual replication is crucial for advancing our understanding of cognitive neuroscience models.