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

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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.