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

NCS-FO：现实世界的交互网络如何塑造以及神经信息处理如何塑造

• 批准号: 1835239
• 负责人: Carolyn Parkinson
• 金额: $ 97.67万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1835239&HistoricalAwards=false
• 关键词: NCS; FO; How; real; world

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.

人类的思想和行为根植于社会环境中。然而，对社会网络和神经信息处理的研究几乎总是孤立进行的。认知神经科学家通常在研究心理过程时不考虑个人是如何受到其社会网络的影响的，而在研究社会网络的结构和动态时通常不考虑构成社会网络的思想的运作。这项研究工作整合了认知神经科学和网络科学的理论和方法，以测试大脑是如何被社会环境塑造和塑造的。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，以测试个人在自然刺激的无约束处理中的个体差异如何形成和被个人在现实世界的社会网络中的位置所塑造。这个项目将描述一个基于所有成员报告的相互关系和相互作用的有限社区的多关系社会网络。一部分成员将完成一系列功能磁共振成像（fMRI）研究，包括自由观看视听刺激。该项目基于先前的研究，该研究表明，fMRI反应时间序列的主体间相似性可以预测人们在社交网络中的距离，但将该研究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（这也将进一步推进），研究将把神经反应的相似性与他们共享的社会网络层内和跨层的个人之间的距离联系起来。这将使我们深入了解社会网络接近度和神经反应中个体间相似性之间的关联在多大程度上是特定于友谊的，还是更普遍地延伸到同质性。其次，结合多层网络分析和纵向功能磁共振成像将阐明神经反应相似性在多大程度上是由其社区中多关系社会网络中个体之间的接近引起或导致的。第三，将多层网络方法与纵向功能磁共振成像相结合，将揭示一个人在社交网络中跨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，该项目将社会网络位置与个体间的神经变异性联系起来，不仅根据fMRI响应时间序列，而且根据与高级事件表征相对应的多体素反应模式以及这些表征如何存储在记忆中。这项工作还将发展和推进分析多关系网络的方法；这对于研究网络现象，特别是社会和大脑网络的学者来说是非常有用的。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

How Do Our Brains Support Our Friendships?

我们的大脑如何支持我们的友谊？

• DOI: 10.3389/frym.2022.640262
• 发表时间: 2022
• 期刊: Frontiers for Young Minds
• 作者: Baek, Elisa C.;Hyon, Ryan;Porter, Mason A.;Parkinson, Carolyn
• 通讯作者: Parkinson, Carolyn

Social network proximity predicts similar trajectories of psychological states: Evidence from multi-voxel spatiotemporal dynamics

• DOI: 10.1016/j.neuroimage.2019.116492
• 发表时间: 2020-08-01
• 期刊: NEUROIMAGE
• 影响因子: 5.7
• 作者: Hyon, Ryan;Kleinbaum, Adam M.;Parkinson, Carolyn
• 通讯作者: Parkinson, Carolyn