CRCNS: Computational Foundations for Externalizing/Internalizing Psychopathology

CRCNS：外化/内化精神病理学的计算基础

• 批准号: 10831117
• 负责人: Nathaniel Douglass Daw
• 金额: $ 20.27万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-03 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10831117
• 关键词: Address; Adolescence; Adolescent; Adult; Aggressive behavior; Anxiety; Architecture; Behavior; Brain; Categories; Child; Childhood; Choice Behavior; Clinical; Clinical Data; Compulsive Behavior; Computer Models; Data; Decision Making; Development; Developmental Process; Diagnosis; Diagnostic; Diagnostic tests; Dimensions; Disease; Dissociation; Environment; Foundations; Functional disorder; General Population; Goals; Impulsivity; Individual; Learning; Legal patent; Maps; Measures; Mental Depression; Mental Health; Mental disorders; Methods; National Institute of Mental Health; Participant; Patients; Pattern; Pharmacological Treatment; Population; Process; Psyche structure; Psychiatry; Psychological reinforcement; Psychopathology; Race; Research; Rewards; Sampling; Sorting; Strategic Planning; Symptoms; Taxonomy; Testing; Update; Work; associated symptom; comorbidity; computational neuroscience; experimental study; follow-up; improved; individualized medicine; information gathering; insight; neglect; neural; novel; novel therapeutic intervention; population based; psychiatric symptom; psychologic; response; rumination; simulation; symptom cluster; theories

A core question in mental health is what underlying processes give rise to symptoms (e.g., NIMH strategic plan goal #1). Answers may lie less in individual diagnostic categories, but instead in global, transdiagnostic patterns of symptoms, notably their prominent and clinically useful division into internalizing (e.g., anxiety) vs. externalizing (e.g., aggression) forms. This project aims to characterize these two symptom clusters and their development (per NIMH strategic plan goal #2), by relating them to computational mechanisms for decision making that have been studied in the healthy brain. Previous computational psychiatry research grounds some internalizing symptoms such as worry in dysregulated mental simulation, or "internal information seeking." Here, we propose and test a hypothesis to extend this framework to comprise externalizing symptoms, which we suggest are grounded in parallel dysregulation of external information seeking (exploration of the environment), building on a recent theory. Because these computational capacities, as well as many mental health symptoms, emerge in childhood and adolescence, there is a unique opportunity to understand their relationship via development. We will use computational modelling to derive signatures of both sorts of information seeking from participants' choice behavior in two reinforcement learning tasks. We hypothesize that internalizing vs. externalizing symptoms are associated, respectively, with enhanced internal vs. external information seeking, and further reflect aberrant developmental trajectories. We test this in Aim 1 by comparing task behavior to psychiatric symptoms in two large general population samples collected online in adults. Next, in Aim 2, we examine how these processes develop using the same tasks in children and adolescents, and how this development differs in children with a diagnosed internalizing or externalizing disorder. The present research leverages and tests a unifying computational theory that situates both types of information seeking as parallel options in a tradeoff between acting for immediate reward vs delaying to gather information and improve later choices. This account can overcome a crucial gap in current computational psychiatry research, which only accounts for a relatively narrow range of symptoms. By connecting computational neuroscience, psychiatry, and development, this project will clarify the neurocomputational foundations of a wide range of externalizing and internalizing symptoms.

心理健康的核心问题是基本过程引起了症状（例如，NIMH战略性 计划目标＃1）。答案可能不在个人诊断类别中，而是在全球范围内 症状的转诊模式，特别是它们的突出和临床有用的分裂 内部化（例如焦虑）与外部化（例如侵略）形式。该项目旨在表征 这两个症状簇及其发展（根据NIMH战略计划目标＃2），将它们联系起来 在健康大脑中研究了决策的计算机制。 以前的计算精神病学研究基于一些内在症状，例如担心 心理模拟失调或“寻求内部信息”。在这里，我们提出和检验一个假设 扩展此框架以包含外在症状，我们建议将其平行地接地 基于最新理论的基础，对外部信息寻求（探索环境的探索）的失调。 因为这些计算能力以及许多心理健康症状在童年时出现 和青春期，有一个独特的机会通过发展来理解他们的关系。 我们将使用计算建模来得出从中寻求的两种信息的签名 参与者在两个强化学习任务中的选择行为。我们假设内部化与 外部症状分别与增强的内部信息和外部信息相关联 寻求并进一步反映异常的发展轨迹。我们通过比较任务在AIM 1中对此进行测试 在成人在线收集的两个大型一般人群样本中的精神病症状行为。下一个， 在AIM 2中，我们研究了这些过程如何使用儿童和青少年中相同的任务来发展， 以及这种诊断为内在化或外在疾病的儿童的发展如何不同。 目前的研究利用并测试了一种统一的计算理论，该理论构成了两种类型 在行动立即奖励与延迟到延迟到的权衡中，寻求作为平行选择的信息 收集信息并改善以后的选择。该帐户可以克服当前的关键差距 计算精神病学研究，仅说明症状范围相对较窄。经过 连接计算神经科学，精神病学和发展，该项目将澄清 各种外在化和内在症状的神经计算基础。