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Neural mechanisms distinguishing two types of cooperative problem-solving approaches: An fNIRS hyperscanning study

Authors :
Mingming Zhang
Zijun Yin
Xue Zhang
Hui Zhang
Mingjing Bao
Bin Xuan
Source :
NeuroImage, Vol 291, Iss , Pp 120587- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Collaborative cooperation (CC) and division of labor cooperation (DLC) are two prevalent forms of cooperative problem-solving approaches in daily life. Despite extensive research on the neural mechanisms underlying cooperative problem-solving approaches, a notable gap exists between the neural processes that support CC and DLC. The present study utilized a functional near-infrared spectroscopy (fNIRS) hyperscanning technique along with a classic cooperative tangram puzzle task to investigate the neural mechanisms engaged by both friends and stranger dyads during CC versus DLC. The key findings of this study were as follows: (1) Dyads exhibited superior behavioral performance in the DLC task than in the CC task. The CC task bolstered intra-brain functional connectivity and inter-brain synchrony (IBS) in regions linked to the mirror neuron system (MNS), spatial perception (SP) and cognitive control. (2) Friend dyads showed stronger IBS in brain regions associated with the MNS than stranger dyads. (3) Perspective-taking predicted not only dyads’ behavioral performance in the CC task but also their IBS in brain regions associated with SP during the DLC task. Taken together, these findings elucidate the divergent behavioral performance and neural connection patterns between the two cooperative problem-solving approaches. This study provides novel insights into the various neurocognitive processes underlying flexible coordination strategies in real-world cooperative contexts.

Details

Language :
English
ISSN :
10959572
Volume :
291
Issue :
120587-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.77333ae44d054c23b330152d222c507e
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2024.120587