Evidence map›Paper›PMID 40085071›Full record

ArticleSocial cognitive and affective neuroscience2025

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

Heegyu Kim, Sangyeon Kim, Sung Chan Jun, Chang S Nam

Abstract read
In one paragraph

Article in Social cognitive and affective neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Heegyu KimSchool 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.
Sangyeon KimDivision of Artificial Intelligence Engineering, Sookmyung Women's University, #515 Suryeon Faculty Building, Cheongpa-ro 47-gil 100, Yongsan-gu, Seoul 04310, Republic of Korea.ORCID 0000-0001-9316-7982
Sung Chan JunSchool of Electrical Engineering and Computer Science and AI Graduate School, Gwangju Institute of Science and Technology (GIST), 505 Dasan Building, 123, Choemdangwagi-ro, Buk-gu, Gwangju 61005, South Korea.
Chang S NamDepartment of Industrial and Systems Engineering Northern Illinois University, 590 Garden Rd, DeKalb, IL 60115, USA.

Funding

National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) 2023S1A5A2A01076552
6 · The paper itself

Abstract

Social interaction plays a crucial role in human societies, encompassing complex dynamics among individuals. To understand social interaction at the neural level, researchers have utilized hyperscanning in several social settings. These studies have mainly focused on inter-brain synchrony and the efficiency of paired functional brain networks, examining group interactions in dyads. However, this approach may not fully capture the complexity of multiple interactions, potentially leading to gaps in understanding inter-network differences. To overcome this limitation, the present study aims to bridge this gap by introducing methodological enhancements using the multilayer network approach, which is tailored to extract features from multiple networks. We applied this strategy to analyze the triad condition during social behavior processes to identify group interaction indices. Additionally, to validate our methodology, we compared the multilayer networks of triad conditions with group synchrony to paired conditions without group synchrony, focusing on statistical differences between alpha and beta waves. Correlation analysis between inter-brain and group networks revealed that this methodology accurately reflects the characteristics of actual behavioral synchrony. The findings of our study suggest that measures of paired brain synchrony and group interaction may exhibit distinct trends, offering valuable insights into interpreting group synchrony.

Indexed as

BrainNerve NetSocial BehaviorSocial InteractionThinkingAdultBrain MappingElectroencephalographyFemaleHumansMaleNeural PathwaysYoung AdultBrain networkElectroencephalogram (EEG)HyperscanningMultilayer network

Identifiers

PMID40085071
PMCPMC11980598

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.