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Common brain networks underlying human social interactions: Evidence from large-scale neuroimaging meta-analysis

期刊

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
卷 126, 期 -, 页码 289-303

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neubiorev.2021.03.025

关键词

Social interaction; Neuroimaging; Meta-analysis; Large-scale brain networks

资金

  1. National Natural Science Foundation of China [31900757, 32020103008]

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The study found that different brain regions involved in various social interactions mainly mapped onto the default mode network, salience network, subcortical network, and central executive network, respectively involved in social cognition, motivation, and cognitive control. This discovery provides a heuristic integrative framework for understanding human social life from the perspective of component processes and network integration.
Recent overarching frameworks propose that various human social interactions are commonly supported by a set of fundamental neuropsychological processes, including social cognition, motivation, and cognitive control. However, it remains unclear whether brain networks implicated in these functional constructs are consistently engaged in diverse social interactions. Based on ample evidence from human brain imaging studies (342 contrasts, 7234 participants, 3328 foci), we quantitatively synthesized brain areas involved in broad domains of social interactions, including social interactions versus non-social contexts, positive/negative aspects of social interactions, social learning, and social norms. We then conducted brain network analysis on the ensuing brain regions and characterized the psychological function profiles of identified brain networks. Our findings revealed that brain regions consistently involved in diverse social interactions mapped onto default mode network, salience network, subcortical network and central executive network, which were respectively implicated in social cognition, motivation and cognitive control. These findings implicate a heuristic integrative framework to understand human social life from the perspective of component process and network integration.

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