Getting into sync: Data-driven analyses reveal patterns of neural coupling that distinguish among different social...

Area of Science:

• Neuroscience
• Social Psychology
• Cognitive Science

Background:

• Social interactions involve dynamic, temporally contingent neural responses between individuals.
• Understanding between-brain coupling is crucial for deciphering social dynamics.

Purpose of the Study:

• To investigate distinct patterns of neural coupling during cooperative and competitive social interactions.
• To compare neural coupling in turn-based versus concurrent interaction paradigms using dual-fMRI.

Main Methods:

• Simultaneous functional magnetic resonance imaging (dual-fMRI) on interacting pairs.
• Application of group-independent component analysis and inter-subject correlation to analyze neural data.
• Assessment of neural coupling patterns during cooperative/competitive and turn-based/concurrent tasks.

Main Results:

• Identified four distinct patterns of temporally aligned brain responses between interactants.
• A cooperative pattern involved social cognitive regions (e.g., temporo-parietal cortex).
• Three competitive patterns involved visuo-motor and social decision-making systems (e.g., cerebellum, anterior cingulate cortex).
• Neural coupling was significantly stronger in concurrent compared to turn-based exchanges.

Conclusions:

• Data-driven analysis of dual-fMRI data effectively reveals interpersonal neural processes.
• Distinct neural coupling patterns underpin different social interaction dynamics.
• Concurrent interactions exhibit stronger between-brain coupling than turn-based interactions.