The effects and neural correlates of combined conscious fear control and extinction learning on fear reduction and relapse

有意识恐惧控制和消退学习相结合对恐惧减少和复发的影响和神经相关性

• 批准号: 9327704
• 负责人: Michael Sun
• 金额: $ 3.57万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-06 至 2019-09-05
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9327704
• 关键词: Anxiety Disorders; Area; Brain; Clinical; Cognitive; Cognitive Therapy; Complement; Conscious; Data; Disease; Effectiveness; Emotional; Emotions; Evaluation; Expectancy; Exposure to; Extinction (Psychology); Fright; Functional Magnetic Resonance Imaging; Individual; Instruction; Intervention; Learning; Measures; Medial; Memory; Modeling; Neurobiology; Outcome; Outcomes Research; Participant; Patient Self-Report; Performance; Prefrontal Cortex; Process; Psychophysiology; Recovery; Regulation; Relapse; Series; Stimulus; Testing; Training; Treatment Effectiveness; attenuation; base; classical conditioning; clinical decision-making; cognitive change; cognitive reappraisal; conditioned fear; cost; design; emotion regulation; experience; experimental study; improved; in vivo; indexing; insight; learning extinction; neural correlate; prevent; relating to nervous system; response; trait

Project Summary/Abstract The best available treatments for fear-based disorders, exposure-based therapies, are vulnerable to relapse through the return of fear. This application will test an intervention that may prevent the return of fear. The Rescorla-Wagner model of associative learning posits that repeated experiences of prediction error (i.e., mismatch between expectancy of US and its non-occurrence) extinguishes conditional fear responses 4. In contrast, the ‘valuation-based’ model of emotion regulation emphasizes cognitive change that modulates the evaluation of a fearful stimulus from “bad for me” to “not bad for me”. While interventions from both models are often used together, there has been theoretical debate as to whether such combinations are advantageous or disadvantageous 6. According to the Rescorla-Wagner model, the more intense the US, the more likely its absence during extinction trials will elicit prediction error, which in turn enhances the formation of a CS-noUS memory important for extinction and preventing the return of fear. Measures taken to reduce US intensity prior to extinction training, such as using cognitive reappraisal strategies, limits prediction error. In contrast, valuation-based models of emotion regulation posit that “not bad for me” cognitive appraisals more strongly reduce emotional responding relative to experience-based learning alone. Neurobiological data suggest that both reappraisal and extinction training increases activation in vmPFC-vACC, indicating that the two processes may complement each other. An extension of the Rescorla-Wagner model, called the computational implementation model, explains how this complementation may come about. It posits that emotional responding is determined by prediction error and the cognitive costs required for regulation. Thus for reappraisals to complement extinction, they should be designed such that the cognitive costs are minimized, and prediction error be preserved. The current application tests this perspective in a series of four studies. Study 1 will examine the neural overlap between reappraisal and extinction learning. Participants will undergo extinction training while in the fMRI scanner and then complete a test of trait reappraisal use. Their performance in the reappraisal task will then be correlated with vmPFC-vACC activation. Studies 2-4 will examine the impact of combining reappraisal with extinction training experimentally to prevent the return of fear. Experiments combine an extinction learning paradigm with either an instructed reappraisal, instructed suppression, or an instruction to the participant to react naturally. Effects will be evaluated in terms of fearful responding after a period of one week under four return of fear conditions: spontaneous recovery (Studies 2-4), rapid reacquisition (Study 2), reinstatement (Study 3), and context renewal (Study 4). These studies will be the first to characterize and test a theoretically potent combination of reappraisal and extinction training. The outcome of this research will provide insight into improving clinical decision-making and maximizing the effectiveness of treatments such as exposure and cognitive restructuring for fear-based disorders.

项目概要/摘要 针对基于恐惧的疾病的最佳可用治疗方法是基于暴露的疗法，但很容易复发 通过恐惧的回归。该应用程序将测试可能防止恐惧卷土重来的干预措施。这 联想学习的 Rescorla-Wagner 模型假设预测错误的重复经历（即， 美国的预期与其不发生之间的不匹配）消除了有条件的恐惧反应 4. 在 相比之下，“基于评估”的情绪调节模型强调调节认知变化 对可怕刺激的评估从“对我有害”到“对我来说不错”。虽然两种模型的干预 经常一起使用，关于这种组合是否有利一直存在理论上的争论 或不利 6. 根据 Rescorla-Wagner 模型，美国越激烈，其可能性越大 灭绝试验期间的缺席将引起预测错误，从而增强 CS-noUS 的形成 记忆对于消除和防止恐惧卷土重来很重要。为降低美国强度而采取的措施 在消退训练之前，例如使用认知重新评估策略，可以限制预测误差。相比之下， 基于评估的情绪调节模型认为“对我来说不错”的认知评估更加强烈 相对于单独的基于经验的学习，减少情绪反应。神经生物学数据表明 重新评估和消退训练都会增加 vmPFC-vACC 的激活，表明这两个过程 可以互相补充。 Rescorla-Wagner 模型的扩展，称为计算模型 实施模型，解释了这种互补是如何实现的。它假定情感 响应取决于预测误差和监管所需的认知成本。因此对于 重新评估以补充灭绝，它们的设计应该使认知成本最小化， 并保留预测误差。当前的应用程序通过一系列四项研究测试了这一观点。 研究 1 将检查重新评估和消退学习之间的神经重叠。参与者将经历 在功能磁共振成像扫描仪中进行消退训练，然后完成特征重新评估使用的测试。他们的 然后，重新评估任务中的表现将与 vmPFC-vACC 激活相关联。研究 2-4 将 通过实验检查重新评估与灭绝训练相结合的影响，以防止回归 害怕。实验将灭绝学习范式与指导性重新评估、指导性评估相结合。 抑制，或指示参与者自然反应。效果将根据可怕程度进行评估 在四种恐惧重现条件下一周后做出反应：自发恢复（研究 2-4）， 快速重新获取（研究 2）、恢复（研究 3）和情境更新（研究 4）。这些研究将是 首先描述并测试了重新评估和消退训练的理论上有效的组合。这 这项研究的结果将为改善临床决策和最大化 暴露和认知重建等治疗方法对恐惧障碍的有效性。