【2h】

Neural mechanisms tracking popularity in real-world social networks

机译:追踪现实世界社交网络中受欢迎程度的神经机制

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摘要

Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others’ popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets’ sociometric popularity, even when controlling for potential confounds. The target popularity–social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity–valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members’ popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.
机译:人气差异是几乎所有人类群体地位的关键方面,并影响着他们内部的社会互动。但是,关于我们如何跟踪和神经表示他人的知名度知之甚少。我们使用社会计量学方法在两个现实世界的社交网络中解决了这个问题,以量化受欢迎程度。在收集全脑功能性MRI数据的同时,每个组成员(感知者)查看了其他所有组成员(目标)的面部。独立的功能定位器任务用于识别分别支持情感评估(前额额叶前皮质,腹侧纹状体,杏仁核)和社交认知(前额背叶皮质,前额神经,颞顶交界处)的大脑系统。在进行面部观察任务期间,即使控制潜在的混杂因素,两种神经系统的活动都可以跟踪目标的社会流行度。目标受欢迎程度与社会认知系统之间的关系是通过评估系统的活动来调节的,这表明观察受欢迎的个人会发出有助于理解其心理状态的价值信号。目标人气与评估系统之间的关系对于受欢迎的感知者最为牢固,这表明对其他组成员受欢迎程度差异的敏感性增强。受欢迎的小组成员还通过更准确地预测社交网络中其他个人如何看待自己的个性而表现出更高的人际敏感性。这些数据提供了对状态指导社会行为的机制的见解。

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