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Related Experiment Video

Updated: May 10, 2026

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study

Published on: July 21, 2021

Is what I think what you think? Multilayer network-based inter-brain synchrony approach.

Heegyu Kim¹, Sangyeon Kim², Sung Chan Jun³

¹School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), #505 Dasan Building, 123, Choemdangwagi-ro, Buk-gu, Gwangju 61005, South Korea.

Social Cognitive and Affective Neuroscience

|March 14, 2025

Summary

This study introduces a multilayer network approach to better understand neural dynamics in group social interactions. New methods reveal distinct trends between paired brain synchrony and group interactions.

Keywords:

Brain network Electroencephalogram (EEG)Hyperscanning Multilayer network

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Published on: October 6, 2023

Area of Science:

Neuroscience
Social Sciences
Network Science

Background:

Social interaction is fundamental to human societies.
Hyperscanning studies often focus on paired brain synchrony in dyads, potentially missing complex group dynamics.
Existing methods may not fully capture inter-network differences in group interactions.

Purpose of the Study:

To introduce methodological enhancements using a multilayer network approach for analyzing group social interactions.
To extract features from multiple networks to identify group interaction indices.
To validate the multilayer network methodology by comparing triad conditions with paired conditions.

Main Methods:

Application of the multilayer network approach to analyze triad conditions during social behavior.
Comparison of multilayer networks from triad conditions with group synchrony against paired conditions without group synchrony.
Statistical analysis of differences in alpha and beta waves between conditions.
Correlation analysis between inter-brain and group networks.

Main Results:

The multilayer network approach successfully identified group interaction indices.
Statistical differences were observed between alpha and beta waves in triad versus paired conditions.
Correlation analysis confirmed that the methodology accurately reflects behavioral synchrony.
Paired brain synchrony and group interaction measures showed distinct trends.

Conclusions:

The multilayer network approach provides a more comprehensive understanding of neural dynamics in group social interactions.
This methodology offers valuable insights into interpreting group synchrony beyond paired interactions.
Findings suggest that paired and group synchrony measures capture different aspects of social neural dynamics.