ERP-based interbrain causal model reveals closed-loop information interaction in interpersonal negotiations.

Area of Science:

• Neuroscience
• Social Psychology
• Computational Neuroscience

Background:

• Understanding social decision-making in resource allocation requires insight into interpersonal negotiation.
• Neural mechanisms of negotiation, particularly interbrain dynamics, remain underexplored.

Purpose of the Study:

• To investigate interbrain coupling and dyadic exchange behavior during negotiation using EEG hyperscanning.
• To elucidate the neural mechanisms underlying adaptive negotiation strategies.

Main Methods:

• EEG hyperscanning during an iterated ultimatum game.
• Analysis of frontal cortex event-related potentials (ERPs), including N200 and feedback-related negativity (FRN).
• Development of a novel causal model using directional phase transfer entropy (dPTE) and time-varying ERP amplitudes.

Main Results:

• Distinct ERPs (N200, FRN, N500) reflected partners' behavioral cues (fair/unfair offers, acceptance/rejection).
• A causal model demonstrated a closed-loop interaction: proposer's brain activity influenced the responder's, which in turn influenced the proposer.
• Prediction models incorporating interbrain coupling showed higher accuracy than single-brain models.

Conclusions:

• Dynamic interbrain coupling is crucial for interpersonal coordination and adaptive negotiation.
• The proposed causal model offers a mechanistic explanation for how partners adapt to each other's decisions.
• Findings provide a new framework for studying social behavior through interbrain dynamics and enhancing cooperation.