Dispositional Negativity and the Pavlovian Control of Active and Passive Defensive Behavior

性格消极性与主动和被动防御行为的巴甫洛夫控制

• 批准号: 10437719
• 负责人: Timothy A Allen
• 金额: $ 17.3万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-13 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10437719
• 关键词: Adult; Aggressive behavior; Amygdaloid structure; Anger; Anxiety; Behavior; Behavior Control; Behavioral; Behavioral Paradigm; Behavioral inhibition; Biological; Clinical; Cognitive; Complex; Computer Models; Cues; Decision Theory; Depressed mood; Desire for food; Development; Diagnosis; Dimensions; Disease; Distal; Distress; Economic Burden; Economics; Emotional; Environment; Equation; Frustration; Functional Magnetic Resonance Imaging; Future; Goals; Impairment; Individual; Individual Differences; Intervention; Label; Laboratories; Learning; Link; Literature; Maintenance; Measures; Mental disorders; Mentors; Methods; Modeling; Modernization; Motivation; National Institute of Mental Health; Neurosciences; Neurotic Disorders; Operant Conditioning; Outcome; Participant; Pattern; Phenotype; Process; Protocols documentation; Psychological reinforcement; Psychometrics; Psychopathology; Punishment; Recurrence; Relapse; Research; Research Domain Criteria; Research Support; Risk Factors; Sampling; Series; Signal Transduction; Site-Directed Mutagenesis; Stimulus; Symptoms; System; Testing; Training; Variant; Ventral Striatum; Work; active control; anxious; base; behavioral response; clinical development; clinical predictors; clinical prognosis; computational neuroscience; conditioning; experimental study; flexibility; functional disability; functional outcomes; imaging modality; improved; indexing; multilevel analysis; negative affect; neural circuit; neurobehavioral; neuroimaging; novel; psychiatric comorbidity; psychologic; recruit; relating to nervous system; response; social; treatment response; vigilance

Individual differences in negative affect are captured by a relatively stable, transdiagnostic dimension known as dispositional negativity, which can be decomposed into two correlated subcomponents: anxious distress (AD; reflecting tendencies toward sadness and anxiety) and irritable distress (ID; reflecting tendencies toward frustration and anger). The goal of this proposal is to provide training in behavioral experiments, computational modeling, and functional magnetic resonance imaging (fMRI) methods that can be used to interrogate the learning processes that underlie the subcomponents of dispositional negativity. Understanding the neurocomputational basis of dispositional negativity is of central importance because it contributes to nearly all forms of psychopathology and is strongly related to clinical prognosis, functional impairment, and economic burden. The central hypothesis of the current proposal is that elevations in dispositional negativity reflect a predominance of an inflexible Pavlovian learning system over instrumental behavioral control in aversive contexts, with AD reflecting a Pavlovian bias to engage in passive avoidance, and ID reflecting a Pavlovian bias to engage in active defense. Specifically, the aims of this project are to 1) demonstrate that passive and active Pavlovian biases are differentially associated with individual differences in AD and ID; 2) characterize the neural circuitry underlying AD, ID, and their associated Pavlovian biases; and 3) show that biases toward active and passive defense are associated with common real-world correlates of AD and ID. Consistent with a transdiagnostic, dimensional approach informed by the Research Domain Criteria (RDoC), 200 adults representing the full spectrum of dispositional negativity and its subcomponents will complete a series of behavioral paradigms that manipulate the influence of the Pavlovian learning system on instrumental behavior in an aversive context, including a novel aversive Pavlovian-Instrumental Transfer (PIT) task. A subsample of 70 participants will complete the aversive PIT task while undergoing fMRI. Behavior will be analyzed using frequentist multi-level models and reinforcement learning (RL) models that formally quantify Pavlovian influence within a Bayesian decision theory framework. RL model-estimated prediction errors will be regressed against BOLD signal, and structural equation modeling will be used to link AD, ID, and their associated Pavlovian biases to real-world outcomes. The proposed training plan leverages a world-class research environment with a team of highly skilled mentors and consultants to provide the candidate with training in experimental learning paradigms, computational modeling, and functional neuroimaging methods. In line with NIMH’s Strategic Objectives, the proposed work will describe the neural circuitry associated with complex forms of learned defensive behavior, enable the development of clinically useful behavioral and biological indices of dispositional negativity, and identify potential targets for transdiagnostic interventions.

消极情感的个体差异被一个相对稳定的、被称为“移情维度”的维度所捕获。 消极性格可分解为两个相关的子成分：焦虑困扰（AD; 反映倾向于悲伤和焦虑）和易怒的痛苦（ID;反映倾向于 愤怒和愤怒）。这项建议的目标是提供行为实验，计算 建模和功能性磁共振成像（fMRI）方法，可用于询问 学习过程是性格消极的子成分。了解 性格消极的神经计算基础是至关重要的，因为它几乎有助于所有 精神病理学的形式，并与临床预后，功能障碍和经济密切相关 负担当前建议的核心假设是，性格消极性的上升反映了一种 在厌恶中，不灵活的巴甫洛夫学习系统优于工具性行为控制 背景下，AD反映了巴甫洛夫偏见从事被动回避，ID反映了巴甫洛夫 倾向于积极防御具体而言，本项目的目的是1）证明被动和 主动巴甫洛夫偏见与AD和ID的个体差异差异相关; 2）表征 AD、ID及其相关巴甫洛夫偏见的神经回路;以及3）表明， 主动和被动防御与AD和ID的常见现实世界相关。 由研究领域标准（RDoC）提供信息的跨诊断、维度方法，200名成人 代表性格消极的全部频谱及其子成分将完成一系列 操纵巴甫洛夫学习系统对工具行为的影响的行为范式 在一个厌恶的背景下，包括一个新的厌恶巴甫洛夫工具转移（PIT）任务。的子样本 70名参与者将在接受fMRI的同时完成令人厌恶的PIT任务。行为将使用 频率主义多层次模型和强化学习（RL）模型，正式量化巴甫洛夫 贝叶斯决策理论框架内的影响。RL模型估计的预测误差将回归 针对BOLD信号，结构方程模型将被用来链接AD，ID，以及它们的关联 巴甫洛夫偏见对现实世界的结果。拟议的培训计划利用了世界级的研究 环境与团队的高技能导师和顾问，为候选人提供培训， 实验学习范例、计算建模和功能性神经成像方法。符合 NIMH的战略目标，拟议的工作将描述与复杂的神经电路相关的 学习防御行为的形式，使临床有用的行为和生物学的发展， 性格消极的指标，并确定transdiagnosis干预的潜在目标。