NCS-FO: How real-world interaction networks shape and are shaped by neural information processing

人类的思想和行为植根于社会背景之中。然而，关于社会网络和神经信息处理的研究几乎总是孤立地进行。认知神经学家通常研究心理过程，而不考虑个人如何受到他们的社会网络的影响，研究社会网络的结构和动态通常不考虑组成它们的大脑的运作。这项研究整合了认知神经科学和网络科学的理论和方法，以测试大脑是如何形成的，以及它是如何被社会背景塑造的。它将综合和扩展社会认知神经科学和网络科学的最新发展，以测试在不受限制的自然刺激加工过程中的个体差异是如何塑造的，以及个人在现实世界社交网络中的位置如何塑造个体差异。这个项目将根据所有成员报告的相互关系和互动来描述一个有限社区的多关系社交网络。其中一部分成员将完成一系列功能磁共振成像(FMRI)研究，包括免费观看视听刺激。该项目基于之前的工作，即功能磁共振反应时间序列的受试者之间的相似性预测了社交网络中人与人之间的距离，但将这一工作扩展到了四个新的方向。首先，通过利用多层网络分析的发展，这项研究将把神经反应的相似性与个人在共享的社会网络中的层内和层间的距离联系起来。这将深入了解社交网络亲近性和神经反应的个体间相似性之间的联系在多大程度上是友谊特有的，或者更普遍地延伸到同质性。其次，将多层网络分析和纵向功能磁共振成像相结合，将阐明神经反应相似性在多大程度上是由社区多关系社会网络中个人之间的接近引起或导致的。第三，配对的多层网络方法和纵向功能磁共振成像将揭示一个人在社交网络中各种互动类型的重要性如何与他/她对其他网络成员如何处理周围世界的影响有关。第四，该项目将不仅在功能磁共振反应时间序列方面，而且在与高级事件表示相对应的多体素响应模式以及这些表示如何存储在存储器中方面，将社会网络位置与个体之间的神经可变性联系起来。这项工作还将开发和推进分析多关系网络的方法；这将对研究网络现象的广泛学者有用，特别是在社会和大脑网络中。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Human thought and behavior is embedded in social contexts. However, research on social networks and neural information processing are almost always conducted in isolation. Cognitive neuroscientists typically study mental processing without considering how individuals are influenced by their social networks, and the structure and dynamics of social networks are usually studied without considering the workings of the minds that comprise them. This research effort integrates theory and methods from cognitive neuroscience and network science to test how the brain shapes and is shaped by its social context. It will synthesize and extend recent developments in social cognitive neuroscience and network science to test how individual differences in unconstrained processing of naturalistic stimuli shape and are shaped by individuals' positions in a real-world social network. This project will characterize the multirelational social network of a bounded community based on all members' reported relationships and interactions with each other. A subset of the members will complete a series of functional magnetic resonance imaging (fMRI) studies involving free-viewing of audiovisual stimuli. This project is grounded in prior work that suggests that inter-subject similarities of fMRI response time series predict distances between people in their social network, but extends that work in four novel directions. First, by capitalizing on developments in multilayer network analysis, which will also be advanced further, the research will relate neural response similarities to distances between individuals within and across layers of their shared social network. This will yield insight into the extent to which associations between social network proximity and inter-individual similarities in neural responding are specific to friendship or extend more generally to homophily. Second, integrating multilayer network analysis and longitudinal fMRI will elucidate the extent to which neural response similarities cause or result from proximity between individuals in the multirelational social network of their community. Third, pairing multilayer network methods and longitudinal fMRI will shed light on how a person's importance across interaction types in a social network may relate to his/her influence on how other network members process the world around them. Fourth, the project will relate social network position to inter-individual neural variability not only in terms of fMRI response time series, but also in terms of multi-voxel response patterns corresponding to high-level event representations and how such representations are stored in memory. This work will also develop and advance approaches for analyzing multirelational networks; this will be useful to the broad range of scholars who study network phenomena, particularly in social and brain networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.