Modeling and manipulating social percepts in individuals

项目总结 在是否以及如何感知社交互动方面的偏见是大多数主要心理疾病的显著症状 疾病(例如，自闭症患者倾向于忽视社交活动，偏执型精神分裂症患者 倾向于过度感知社交互动，抑郁症患者倾向于感知社交互动 负光)。这些偏见可能反映了存在于规范人群中的连续体的极端末端， 这表明，在社会知觉风格中表征个体差异对于进一步发展我们的 对疾病的理解。人类已经做好了感知社会互动的准备，即使是在最简单的情况下， 不逼真的刺激(例如，几何形状的动画)是一种早已被认识到的现象， 被用来研究正常人群和患者群体的社会认知。然而，当涉及到这些时 基本的刺激，虽然我们可能有一种直觉，我们“看到它就知道它”，但我们并不理解它是什么 关于被认为是社会性的刺激，使它们成为社会性-换句话说，需要哪些特定的视觉特征， 以及剂量是多少。此外，因为任务范例通常是简单的二元选择(即，社交或 ‘随机’)，我们不了解个体之间的异质性，就他们决定一个人 给定的刺激代表一种社会互动，如果是这样的话，是哪种社交互动(即，积极或消极)。 理解和纠正精神疾病中有偏见的社会认知的关键一步是定义 基本社交互动的基本感官特征，并决定不同的人如何计算以及为什么计算 对这些特征的不同，会产生不同的社会认知。这将为干预打开大门， 可以防止个人走上一条有偏见的道路。在这个项目中，我们将建立一个社会刺激班 为此，我们对低级视觉特征进行了精确的参数控制。这将允许我们构建 不同类型的社交互动的个人“社交调谐曲线”，并决定这些变化 调谐曲线与性状表型有关。将这些刺激与同步神经成像(FMRI)和 眼球跟踪将揭示处理层次结构中个体内部和跨个体的感知分歧之处， 并允许我们测试这样一种假设，即社会知觉在大脑皮层层次结构中比以前更早出现 想着。这将表明，特殊的社会认知与自动的、感官驱动的更密切相关 过程而不是受控反射，这一区别对于告知诊断和干预非常重要 工具。最后，在一组密集抽样的个体中，我们将直接测试刺激特征之间的因果关系， 大脑活动，以及使用实时功能磁共振成像隐含地引导个人走向给定感知的感知 大脑活动的持续模式。拟议中的研究结果将是一个因果模型，说明刺激是如何 特征和大脑动力学相互作用，在给定的个体中产生给定的社会感知。这款车 将提供关于靶向治疗的可测试假设，以使精神疾病的有偏见的认知正常化。

PROJECT SUMMARY Biases in whether and how social interactions are perceived are a hallmark symptom of most major mental illnesses (e.g., people with autism tend to under-perceive social interactions, people with paranoid schizophrenia tend to over-perceive social interactions, and people with depression tend to perceive social interactions in a negative light). These biases likely reflect the extreme end of a continuum that exists in the normative population, suggesting that characterizing individual differences in social-perceptual styles is critical to furthering our understanding of disease. That humans are primed to perceive social interactions even in stripped-down, unlifelike stimuli (e.g., animations of geometric shapes) is a phenomenon that has long been recognized and exploited to study social cognition in both normative and patient populations. However, when it comes to these basic stimuli, while we may have the intuition that we “know it when we see it”, we do not understand what it is about stimuli deemed social that makes them social—in other words, which specific visual features are required, and in what doses. Furthermore, because task paradigms are often a simple binary choice (i.e., ‘social’ or ‘random’), we do not understand heterogeneity across individuals in terms of their thresholds for deciding if a given stimulus represents a social interaction, and if so, what kind of social interaction (i.e., positive or negative). A critical step toward understanding and correcting biased social cognition in mental illness is to define the fundamental sensory features of basic social interactions, and determine how and why different people compute differently on these features to give rise to different social percepts. This will open the door to interventions that can prevent an individual from going down a biased path. In this project, we will establish a social stimulus class for which we have precise, parametric control over low-level visual features. This will allow us to construct individual “social tuning curves” for various types of social interactions and determine how variability in these tuning curves relates to trait phenotypes. Combining these stimuli with simultaneous neuroimaging (fMRI) and eye-tracking will shed light on where in the processing hierarchy percepts diverge within and across individuals, and allow us to test the hypothesis that social percepts emerge earlier in the cortical hierarchy than previously thought. This would indicate that idiosyncratic social cognition is more closely linked to automatic, sensory-driven processes than controlled reflection, a distinction that is important for informing diagnostic and interventional tools. Finally, within a set of densely sampled individuals, we will directly test causality between stimulus features, brain activity, and percepts using real-time fMRI to implicitly steer individuals toward a given percept based on ongoing patterns of brain activity. The outcome of the proposed research will be a causal model of how stimulus features and brain dynamics interact to give rise to a given social percept within a given individual. This model will provide testable hypotheses regarding targeted therapies to normalize biased cognition in mental illnesses.