The cognitive and neural mechanisms supporting naturalistic dyadic social interactions

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Project Summary / Abstract Social interactions are key to well-being. When successful, interactions engender social bonds that reduce stress, loneliness, and depression, and that support longevity. This proposal aims to identify the mechanisms by which social interactions produce social connection. Two studies use state-of-the-art tools in computer vision, natural language processing, and fMRI hyperscanning–where two people are scanned at the same time–to peer into the minds of people as they interact in real time. This project focuses on naturalistic interactions. To date, neuroscience research into social interaction has relied primarily on paradigms that do not actually allow people to interact. The current proposal offers a shift from these conventional paradigms. We will leverage rich data from real-time conversations to investigate two conversation features—social content and positive affect—that may effectively support social connection. We test the direct relation between these conversation features and social connection in Aim 1. Aim 2 will then test the hypothesis that these features promote connection by helping conversation partners to get ‘on the same page’—to align their thoughts and feelings. We will measure alignment using fMRI hyperscanning. Study 1 will use a unique virtual video conversation platform that connects two remote communicators. Dyads will freely converse while we record real-time acoustic, visual, and language data, from which our analysis tools can automatically extract both conversation features. Participants will also complete a post-conversation survey to assess the primary outcome: social connection. We will use factor analysis and cross-validation to optimally cluster our multimodal features and to optimize our model of how conversation features induce alignment, which, in turn, supports social connection. Study 2 aims to replicate this behavioral model, and further, to identify the underlying mechanism that links conversation features to social connection using neuroimaging. If conversation brings about social connection because it induces alignment, then we should see that socially connected dyads experience neural alignment within networks associated with both content and affect: the default and limbic networks, respectively. Our unique research site, with two MRI scanners in adjacent rooms, allows us to use fMRI hyperscanning and high-resolution imaging of cortical and subcortical neural networks, a resolution far beyond what is possible with methods typically employed for studying naturalistic interactions. The proposed investigation into the real-time dynamics of interactions will assess how communication syncs minds, and how this alignment supports social connection. This work will reveal the basic ingredients of successful interactions. In doing so, it offers promising future directions for alleviating the devastating effects of social disconnection, as felt by healthy populations during moments of stress or social distancing during the Covid-19 pandemic and by vulnerable populations with depression, social anxiety, or autism.