Interbrain neural correlates of self and other integration in joint statistical learning

Area of Science:

• Cognitive Neuroscience
• Social Psychology
• Neuroscience

Background:

• Statistical learning is typically studied in isolation.
• The collective representation of statistical learning via self-other integration is not well understood.
• Investigating multi-brain mechanisms of dynamic self-other integration is crucial.

Purpose of the Study:

• To examine the dynamics of self-other integration during statistical learning in dyads.
• To explore the multi-brain neural mechanisms underlying this process.
• To determine how brain-to-brain coupling (BtBC) relates to individual learning and interaction.

Main Methods:

• Simultaneous electroencephalography (EEG) recordings from interacting dyads (N=112).
• Participants performed a statistical learning task in either a joint or baseline context.
• Analysis of reaction times (RT), intra-brain neural activity, and theta-band Brain-to-Brain Coupling (BtBC).

Main Results:

• Significant individual statistical learning observed in the joint context, marked by decreased RT and altered intra-brain neural responses.
• A quadratic trend in learning was noted upon introduction of interference.
• Theta-band BtBC demonstrated learning-related trends and correlated with RT and intra-brain functional connectivity dynamics.

Conclusions:

• Self-other integration dynamically modulates joint statistical learning.
• Implicit statistical regularities spontaneously influence social interaction.
• Brain-to-Brain Coupling (BtBC) is a key neural correlate for the dynamics of self-other integration in social learning contexts.