Dopaminergic Mechanisms Underlying Human Social Behavior: A Multimodal Approach

项目总结 理解在精神疾病中观察到的社交功能障碍的一个重大挑战是将高层 通过大脑回路进行计算的社会行为和认知理论。具体地说，是如何 大脑是否将社会感知转化为社会评价，这种评价如何影响社会 行为?我们建议利用经济理论和认知神经科学的最新发展来 使用基于模型的计算方法弥合这一鸿沟。在这个提案中，我们假设社会 行为是由受神经递质多巴胺影响的大脑机制支撑的，而且 这些机制可以通过计算模型来捕获，这些计算模型集成了社交网络的内部表示 经验，以及与多巴胺音调相关的参数，为社会行动提供信息。因此，社会评价 关键的是，在数量上，取决于内部的社会表征和大脑 社会环境中的演员。为了评估这一假设，我们采用了两种方法来评估 多巴胺基调：我们使用FDA批准的药物托卡彭来影响多巴胺 一种是我们进行PET成像来测量多巴胺的释放和基线多巴胺 受体D2/D3占有率。然后，我们将社会价值模型应用于受试者的行为，并寻找 使用功能磁共振成像(FMRI)与这一估值的神经相关。为此，我们召集了一个团体 (1)神经经济学和社会和非社会决策的建模，(2)认知方面的专家 神经科学，(3)额纹状体回路的药理学，和(4)神经成像。因此，我们寻求扩大 我们对社交行为背后的计算和回路的理解。此外，我们认为， 对这些行为和神经回路的基于模型的理解可能会指导对 药物操纵对社会价值的影响，并提供量化工具来评估 这种手法对患者群体的影响，可能具有治疗意义。

PROJECT SUMMARY A significant challenge for understanding social dysfunctions observed in mental illness is to link high-level theories of social behavior and cognition with the computations performed by brain circuits. Specifically, how does the brain translate social perception into social valuation, and how does such valuation influence social actions? We propose to leverage recent developments in economic theory and cognitive neuroscience to bridge this divide using a computational, model-based approach. In this proposal, we hypothesize that social behavior is underpinned by brain mechanisms that are influenced by the neurotransmitter dopamine, and that these mechanisms can be captured by computational models that integrate internal representations of social experience, and parameters relevant to dopamine tone, to inform social actions. Social valuation thus critically, and quantitatively, depends upon both internal social representations and the neurochemistry of the actor within the social environment. To assess this hypothesis, we pursue two approaches to evaluate dopamine tone: one in which we use an FDA-approved medication, tolcapone, to influence dopamine metabolism, and one in which we perform PET imaging to measure dopamine release and baseline dopamine receptor D2/D3 occupancy. We then apply a model of social valuation to subjects' behavior, and search for neural correlates of this valuation using functional MRI (fMRI). To this end, we bring together a group of experts in (1) the neuroeconomics and modeling of social and non-social decision-making, (2) cognitive neuroscience, (3) the pharmacology of frontostriatal circuits, and (4) neuroimaging. We thus seek to broaden our understanding of the computations and circuits underlying social behavior. Moreover, we believe that a model-based understanding of these behaviors and neural circuits may guide more robust predictions of the effects of pharmacological manipulations on social valuation, and provide quantitative tools to assess the effects of such manipulations in patient populations, with possible therapeutic implications.