Whole Brain Connectivity and Connectomics of Mindfulness-based Cognitive Therapy for PTSD

基于正念的 PTSD 认知疗法的全脑连接和连接组学

基本信息

批准号：
9892030
负责人：
ANTHONY P KING
金额：
$ 18.66万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-04-16 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9892030
关键词：
Affective Afghanistan Attention Behavior Behavioral Brain Brain scan Chronic Clinical Data Data Set Development Plans Doctor of Philosophy Dropout Drops Emotional Expectancy Family Female Frequencies Functional Magnetic Resonance Imaging Functional disorder Funding General Population Goals Gold Institute of Medicine (U.S.)Intervention Iraq Joints Laboratories Lead Learning Link Major Depressive Disorder Measures Mediating Mediation Mentored Patient-Oriented Research Career Development Award Meta-Analysis Methodology Methods Military Personnel Mindfulness Training National Institute of Mental Health Neurosciences Numbness Outcome Parietal Lobe Pathway Analysis Patients Philadelphia Post-Traumatic Stress Disorders Prevention Probability Psychologist Randomized Reporting Rest Slide Symptoms Testing Therapeutic Thinking Time Training Training Programs Trauma Veterans Work active control avoidance behavior base behavior test career career development causal model cingulate cortex clinically significant cohort combat comorbidity connectome disability effective therapy functional MRI scan improved outcome interest male mindfulness mindfulness based cognitive therapy mindfulness intervention neural circuit neural network neuromechanism novel phenomenological models relating to nervous system standard care stress related disorder success symptom cluster targeted treatment trauma exposure

项目摘要

Project Summary The candidate is a clinical psychologist and neuroscientist with a strong interest in the phenomenology, affective neurocircuitry, and effective treatment of posttraumatic stress disorder (PTSD). PTSD is highly prevalent (7% in males, 12% in females), chronic and highly debilitating. One in every five veterans deployed to Afghanistan and Iraq have clinically significant PTSD symptoms. Empirically supported treatment (ESTs) for PTSD using trauma exposure have very large effect sizes in RCTs; however, recent work finds high rates of refusal and early drop-out among veterans (30-50%). We previously reported deficits in large scale distributed neural networks in PTSD, including increased connectivity between Default Mode Network (DMN) and Salience Network (SN), and we present pilot data that PTSD avoidant symptoms are linked to decreased DMN connectivity with Central Executive Network (CEN). We also reported a mindfulness-based intervention for PTSD decreased avoidance and increased connectivity between DMN and CEN. This K23 training program will allow the candidate to learn and apply the powerful whole-brain connectomic and dynamic connectivity methodologies needed to study the alterations in large scale distributed neural networks underlying PTSD and therapeutic mechanisms. Our hypotheses are H1: Decreased DMN-CEN and increased DMN-SN underlie emotional / behavioral avoidance associated with poor clinical acceptability and outcomes in PTSD patients, H2: Mindfulness-based Cognitive Therapy (MBCT) targets the same DMN-CEN connectivity linked with PTSD avoidance, and H3: MBCT-induced increased DMN-CEN connectivity mediates improvement in PTSD avoidance, emotional / behavioral avoidance, and improved outcomes. The aims are to: 1.) test if behavioral and emotional avoidance in PTSD are associated with decreased DMN-CEN connectivity, 2.) identify effects of MBCT on DMN-CEN using powerful connectomics analyses, and 3.) explore mediation relationships between DMN-CEN connectivity and behavioral and emotional engagement in subsequent therapy and clinical outcomes. fMRI with N=60 combat PTSD patients with rsFC using dynamic causal modeling, and contextual processing paradigms, will test association with avoidance symptoms and laboratory measures of emotional avoidance. An RCT (N=30 MBCT, N=30 control) with pre- post fMRI and group x time interaction analyses will identify effects of MBCT on connectivity among and between DMN, CEN, and SN. Mediation analyses will test neural targets and longitudinal measures of emotional engagement. This study will be the first targeting functional neural networks underlying avoidance behaviors in PTSD treatment, and may lead to additional strategies to help the ~50% PTSD patients who do not fully engage with existing ESTs, and elucidate neural mechanisms associated with a novel potential component of PTSD treatment (mindfulness training). It will also provide the candidate advanced training and pilot data for R-level funding to identify mechanisms of therapeutic change and novel treatments for PTSD.

项目概要候选人是一位临床心理学家和神经科学家，对现象学有浓厚的兴趣，情感神经回路，以及创伤后应激障碍（PTSD）的有效治疗。创伤后应激障碍（PTSD）是高度流行（男性 7%，女性 12%）、慢性且高度衰弱。五分之一的退伍军人部署阿富汗和伊拉克有临床显着的创伤后应激障碍症状。经验支持治疗 (EST) 使用创伤暴露的 PTSD 在随机对照试验中具有非常大的效应量；然而，最近的研究发现，退伍军人拒绝和提前退学（30-50%）。我们之前报告过大规模分布式的赤字 PTSD 中的神经网络，包括默认模式网络 (DMN) 和 Salience Network (SN)，我们提供了试点数据，表明 PTSD 回避症状与 DMN 减少有关与中央执行网络（CEN）的连接。我们还报告了基于正念的干预 PTSD 减少了回避行为并增加了 DMN 和 CEN 之间的联系。本次K23培训项目将使候选人能够学习和应用强大的全脑连接组和动态连接研究 PTSD 背后的大规模分布式神经网络的变化所需的方法治疗机制。我们的假设是 H1：DMN-CEN 减少和 DMN-SN 增加情绪/行为回避与 PTSD 患者的不良临床可接受性和结果相关， H2：基于正念的认知疗法（MBCT）针对与 PTSD 相关的相同 DMN-CEN 连接回避，H3：MBCT 诱导的 DMN-CEN 连接增加介导 PTSD 的改善回避、情绪/行为回避和改善结果。目的是： 1.) 测试行为是否 PTSD 中的情绪回避和情绪回避与 DMN-CEN 连接性降低有关，2.) 确定使用强大的连接组学分析 MBCT 对 DMN-CEN 的影响，以及 3.) 探索中介作用 DMN-CEN 连接与行为和情感参与之间的关系随后的治疗和临床结果。使用 rsFC 对 N=60 名 PTSD 患者进行 fMRI 动态因果建模和情境处理范例将测试与回避的关联情绪回避的症状和实验室测量。一项随机对照试验（N=30 MBCT，N=30 对照） fMRI 后和 x 组时间交互分析将确定 MBCT 对和之间的连接性的影响在 DMN、CEN 和 SN 之间。中介分析将测试神经目标和纵向测量情感投入。这项研究将是第一个针对回避行为的功能神经网络的研究 PTSD 治疗中的行为，并可能导致额外的策略来帮助约 50% 的 PTSD 患者没有完全参与现有的 EST，并阐明与新潜力相关的神经机制 PTSD 治疗的组成部分（正念训练）。它还将为候选人提供高级培训和 R 级资助的试点数据，以确定治疗改变的机制和 PTSD 的新疗法。