Functional brain connectivity during social attention predicts individual differences in social skill.

Samantha R Brindley, Amalia M Skyberg, Andrew J Graves, Jessica J Connelly, Meghan H Puglia, James P Morris
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Abstract

Social attention involves selectively attending to and encoding socially relevant information. We investigated the neural systems underlying the wide range of variability in both social attention ability and social experience in a neurotypical sample. Participants performed a selective social attention task, while undergoing fMRI and completed self-report measures of social functioning. Using connectome-based predictive modeling, we demonstrated that individual differences in whole-brain functional connectivity patterns during selective attention to faces predicted task performance. Individuals with more cerebellar-occipital connectivity performed better on the social attention task, suggesting more efficient social information processing. Then, we estimated latent communities of autistic and socially anxious traits using exploratory graph analysis to decompose heterogeneity in social functioning between individuals. Connectivity strength within the identified social attention network was associated with social skills, such that more temporal-parietal connectivity predicted fewer challenges with social communication and interaction. These findings demonstrate that individual differences in functional connectivity strength during a selective social attention task are related to varying levels of self-reported social skill.

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社交注意力过程中的大脑功能连接预测了社交技能的个体差异。
社会关注包括选择性地关注和编码与社会相关的信息。我们在一个神经典型样本中调查了社会注意力能力和社会经验的广泛变异背后的神经系统。参与者在接受功能磁共振成像时进行了选择性的社会关注任务,并完成了社会功能的自我报告测量。使用基于连接组的预测模型,我们证明了在选择性注意面部的过程中,全脑功能连接模式的个体差异可以预测任务表现。小脑-枕叶连接较多的个体在社会注意力任务中表现更好,这表明社会信息处理更有效。然后,我们使用探索性图分析来分解个体之间社会功能的异质性,从而估计自闭症和社会焦虑特征的潜在群体。已确定的社交注意力网络中的连接强度与社交技能有关,因此更多的颞顶叶连接预示着社交沟通和互动的挑战更少。这些发现表明,在选择性社交注意力任务中,功能连接强度的个体差异与不同水平的自我报告社交技能有关。
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