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Brain Networks Processing Temporal Information in Dynamic Facial Expressions.

Rafal M Skiba1,2, Patrik Vuilleumier1,2

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This fMRI study reveals distinct brain pathways for processing facial movements. Synchronous expressions activate motor areas, while asynchronous ones engage areas for local motion processing, showing how temporal dynamics influence face perception.

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DCManalyticemotionsfMRIholistic

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Area of Science:

  • Neuroscience
  • Cognitive Neuroscience
  • Social Neuroscience

Background:

  • Facial movements convey crucial social and emotional information.
  • Understanding how the brain processes dynamic facial cues is essential for comprehending social interaction.
  • Previous research has explored facial processing, but the specific roles of local versus global motion dynamics remain less clear.

Purpose of the Study:

  • To investigate the neural basis of processing local and global motion information in dynamic facial expressions using fMRI.
  • To differentiate brain activation patterns associated with synchronous versus asynchronous facial movements.
  • To explore the information flow and network interactions underlying the perception of facial dynamics.

Main Methods:

  • Functional Magnetic Resonance Imaging (fMRI) to measure brain activity.
  • Presentation of novel dynamic face stimuli with varying temporal dynamics (synchronous vs. asynchronous).
  • Dynamic Causal Modeling (DCM) to analyze effective connectivity and information flow between brain regions.

Main Results:

  • Synchronous facial expressions activated medial prefrontal cortex (rostral and caudal anterior cingulate cortex - r/cACC), supplementary motor areas, motor cortex, and superior frontal gyrus, indicating global temporal-spatial processing.
  • Asynchronous facial expressions preferentially activated the right superior temporal sulcus (STS) and inferior frontal gyrus, associated with local temporal-spatial processing.
  • No significant differences in visual face-responsive areas were observed based on temporal dynamics; however, DCM revealed distinct information flow for asynchronous expressions, centered on STS, with connections to the occipital cortex and amygdala.
  • Interactions between STS, amygdala, and r/cACC were identified, suggesting a network for integrating local and global motion cues.

Conclusions:

  • Local and global temporal dynamics in facial expressions are processed through partly separate neural pathways.
  • Dynamic facial expressions with synchronous movement cues may specifically engage brain regions involved in motor execution.
  • The superior temporal sulcus (STS) plays a key role in processing local facial motion dynamics and interacts with the amygdala and anterior cingulate cortex (ACC) for integrating motion cues.