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

项目摘要 候选人是一位对现象学有浓厚兴趣的临床心理学家和神经学家， 情感神经回路和创伤后应激障碍(PTSD)的有效治疗。创伤后应激障碍的发病率很高 流行(男性占7%，女性占12%)，慢性和高度衰弱。每五名退伍军人中就有一名 到阿富汗和伊拉克都有临床上显著的创伤后应激障碍症状。经验性支持治疗(EST) 创伤暴露的创伤后应激障碍在随机对照试验中有非常大的影响；然而，最近的研究发现， 退伍军人中的拒绝和提前退学(30%-50%)。我们之前报告了大规模分布的赤字 PTSD中的神经网络，包括增加默认模式网络(DMN)和 显著网络(SN)，我们提供了PTSD避免症状与DMN减少相关的试点数据 与中央执行网络(CEN)的连接。我们还报告了一种基于正念的干预方法 创伤后应激障碍减少了回避，增加了DMN和CEN之间的连通性。这项K23培训计划 将允许应聘者学习和应用强大的全脑连接和动态连接 研究创伤后应激障碍和创伤后应激障碍背后的大规模分布式神经网络变化所需的方法学 治疗机制。我们的假设是H1：DMN-CEN减少，DMN-SN增加 情绪/行为回避与创伤后应激障碍患者较差的临床可接受性和预后相关， H2：基于正念的认知疗法(MBCT)的目标是与创伤后应激障碍联系在一起的DMN-CEN连接 回避和H3：MBCT诱导的DMN-CEN连接性增加中介PTSD的改善 回避、情绪/行为回避和改善的结果。目标是：1.测试行为是否 创伤后应激障碍中的情绪回避与DMN-CEN连接性降低有关，2。识别 用强大的联结分析方法分析MBCT对DMN-CEN的影响，以及3.)探索调解 DMN-CEN连通性与行为和情感投入的关系 随后的治疗和临床结果。60例伴有rsFC的战斗创伤后应激障碍患者的fMRI检查 动态因果建模和语境处理范式将测试与回避的关联性 情绪回避的症状和实验室测量。RCT(N=30 MBCT，N=30对照) 功能磁共振成像后和x组时间相互作用分析将确定MBCT对和之间连接的影响 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潜在回避的功能神经网络 在PTSD治疗中的行为，并可能导致更多的策略来帮助~50%的PTSD患者 没有完全接触到现有的EST，并阐明了与新潜力相关的神经机制 创伤后应激障碍治疗的组成部分(正念训练)。它还将为应聘者提供高级培训和 R级资助的试点数据，以确定创伤后应激障碍的治疗变化和新疗法的机制。

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.