Using Theory- and Data-Driven Neurocomputational Approaches and Digital Phenotyping to Understand RDoC Acute and Potential Threat

尽管人们对有效性的担忧与日俱增，但NIMH研究领域标准(RDoC)框架发挥了关键作用 在组织基础研究、转化研究和临床研究方面的作用。RDoC对恐惧和焦虑的态度是断然的： 威胁要么是严重的，要么是潜在的；涉及杏仁核或终纹床核(BST)； 会引起恐惧或焦虑。最近的研究对这种二元观点提出了质疑，刺激了这一研究的发展 可供选择的方法。维度模型假设威胁响应沿着平滑的连续统一体变化 感知到的危险--从绝对安全到持续攻击。危险的感觉被认为是从 威胁近似度、概率和确定性的参数估计，这些估计是在弱分离条件下计算的 皮质-皮质下环路。到目前为止，还没有系统的、强大的努力来计算 实施这些相互竞争的模型并比较它们的有效性。此外，虽然这两个模型都强调了 关于威胁不确定性的重要性，他们没有具体说明是哪一种。计算精神病学认识到2 在数学上不同类型的不确定性：风险和模棱两可。以下哪一项与威胁更相关 反应性以及它们如何映射到潜在的神经生物学尚不清楚。要解决这些基本问题 问题，我们将招募一个种族多元化的社区样本，以增加恐惧/焦虑症状。二 参数威胁预测范例将允许我们同时探测对分类敏感的电路 (RDoC)和维度变化的威胁首次。智能手机表型将评估现实世界 威胁暴露、不确定性和苦恼。A1.我们将测试一系列相互矛盾的预测 威胁敏感型大脑回路的架构。我们将使用理论驱动的计算建模来超越 二元威胁类别；识别对风险、模糊性和威胁的其他方面敏感的区域；以及 探索与恐惧和焦虑的迹象和症状的一次又一次的审判关系。A2.RDoC暗示急性和 潜在的威胁表现在不同的大脑活动模式中；事实上，这是 创建单独的RDoC构造。维度模型预测有很大的相似性。多体素机器- 学习方法提供了一种严格的方法来裁决这些主张并澄清 杏仁核、BST等区域。A3.融合fMRI和智能手机数据流将使我们能够确定 威胁的特定方面和大脑特定区域与现实世界痛苦的相关性。我们还将探索 神经影像指标与恐惧和焦虑相关的诊断、症状和特征之间的关系。 意义重大。极度恐惧和焦虑是导致人类痛苦和疾病的主要原因。这个项目将 提供了一个潜在的变革性机会，以开发第一个基于计算的恐惧和 焦虑。它将有助于裁决正在进行的理论辩论，验证用于 其他读出和物种，为新型翻译模型和临床研究奠定基础，优先 神经调节和其他治疗药物开发的新靶点，并指导RDoC 2.0的开发。

Despite growing concerns about validity, the NIMH Research Domain Criteria (RDoC) framework plays a key role in organizing basic, translational, and clinical research. RDoC’s approach to fear and anxiety is categorical: threat is either acute or potential; engages either the Amygdala or the bed nucleus of the stria terminalis (BST); and elicits either fear or anxiety. Recent work casts doubt on this binary perspective, spurring the development of alternative approaches. Dimensional models posit that threat responses vary along a smooth continuum of perceived danger—from absolutely safety to on-going attack. Danger perceptions are thought to emerge from parametric estimates of threat proximity, probability, and certainty, which are computed in weakly segregated cortico-subcortical circuits. To date, there have been no systematic, well-powered efforts to computationally implement these competing models and compare their validity. Furthermore, while both models highlight the importance of threat uncertainty, they do not specify which kind. Computational psychiatry recognizes 2 mathematically distinct kinds of uncertainty: Risk and Ambiguity. Which of these is more relevant to threat reactivity and how they map onto the underlying neurobiology is unknown. To address these fundamental questions, we will recruit a racially diverse community sample enriched for elevated fear/anxiety symptoms. Two parametric threat-anticipation paradigms will allow us to simultaneously probe circuits sensitive to categorical (RDoC) and dimensional variation in threat for the first time. Smartphone phenotyping will assess real-world threat exposure, uncertainty, and distress. A1. We will test a series of competing predictions about the architecture of threat-sensitive brain circuits. We will use theory-driven computational modeling to go beyond binary threat categories; identify regions sensitive to risk, ambiguity, and other dimensional facets of threat; and explore trial-by-trial relations with signs and symptoms of fear and anxiety. A2. RDoC implies that Acute and Potential Threat are represented in different patterns of brain activity; indeed, this was the major rationale for creating separate RDoC constructs. Dimensional models predict substantial similarities. Multivoxel machine- learning approaches provide a rigorous means of adjudicating these claims and clarifying the importance of the Amygdala, BST, and other regions. A3. Fusing the fMRI and smartphone data-streams will enable us to establish the relevance of specific facets of threat and specific brain regions to real-world distress. We will also explore relations between neuroimaging metrics and fear- and anxiety-related diagnoses, symptoms, and traits. Significance. Extreme fear and anxiety are leading causes of human misery and morbidity. This project will provide a potentially transformative opportunity to develop the first computationally grounded model of fear and anxiety. It will help adjudicate on-going theoretical debates, validate a new conceptual approach for use with other read-outs and species, set the stage for new kinds of translational models and clinical studies, prioritize new targets for neuromodulation and other therapeutics development, and guide the development of RDoC 2.0.