The cognitive and neural mechanisms supporting naturalistic dyadic social interactions

项目总结/摘要 社会交往是幸福的关键。当成功的时候，互动会产生社会联系， 压力、孤独和抑郁，这些都有助于长寿。本提案旨在确定 社会互动产生社会联系的方式。两项研究使用了最先进的计算机工具， 视觉，自然语言处理和功能磁共振成像超扫描-其中两个人同时扫描 时间--当人们在真实的时间里互动时，可以窥视他们的思想。 这个项目的重点是自然的互动。迄今为止，神经科学对社会互动的研究 主要依赖于实际上不允许人们互动的范式。目前的提议提供了一个转变 从这些传统的模式中。我们将利用来自实时对话的丰富数据来调查两个 会话特征-社会内容和积极影响-可以有效地支持社会联系。我们 测试目标1中这些会话特征与社会联系之间的直接关系。目标2将测试 假设这些特征通过帮助谈话伙伴获得“相同”来促进联系， 页面“-以调整他们的想法和感受。我们将使用功能磁共振成像超扫描来测量对齐。 研究1将使用一个独特的虚拟视频对话平台，连接两个远程通信。二合体 在我们记录实时声学、视觉和语言数据的同时， 工具可以自动地提取这两种对话特征。参与者还将完成一次会后对话 评估主要结果的调查：社会联系。我们将使用因子分析和交叉验证， 最佳地聚类我们的多模态特征，并优化我们的模型，如何会话功能诱导 这反过来又支持了社会联系。 研究2旨在复制这种行为模式，并进一步确定联系的潜在机制 使用神经成像的社交联系的会话特征。如果谈话能带来社会联系 因为它诱导了对齐，那么我们应该看到，社会连接的二元体经历了神经对齐， 在与内容和情感相关的网络中：分别是默认网络和边缘网络。我们 一个独特的研究地点，在相邻的房间里有两台MRI扫描仪，允许我们使用功能性MRI超扫描， 皮层和皮层下神经网络的高分辨率成像，远远超出可能的分辨率 用通常用于研究自然主义相互作用的方法。 对交互的实时动态的拟议调查将评估通信如何同步 思想，以及这种对齐如何支持社会联系。这项工作将揭示的基本成分， 成功的互动。在这样做的过程中，它为减轻气候变化的破坏性影响提供了有希望的未来方向。 社会脱节，正如健康人群在压力或社会距离的时刻所感受到的那样， 2019冠状病毒病大流行以及患有抑郁症、社交焦虑症或自闭症的弱势人群。

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.