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：
10469876
负责人：
ANTHONY P KING
金额：
$ 18.66万
依托单位：
OHIO STATE UNIVERSITY
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 2023-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10469876
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 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 military veteran 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.

项目摘要候选人是一名临床心理学家和神经科学家，对现象学有浓厚的兴趣，情感神经循环和创伤后应激障碍（PTSD）的有效治疗。 PTSD高度流行（男性为7％，女性为12％），慢性和高度衰弱。每五名退伍军人中有一个对于阿富汗和伊拉克，具有临床明显的PTSD症状。经验支持的治疗（ESTS）使用创伤暴露的PTSD在RCT中具有很大的影响。但是，最近的工作发现退伍军人的拒绝和早辍学（30-50％）。我们以前报道了大规模分布的赤字 PTSD中的神经网络，包括默认模式网络（DMN）和显着网络（SN），我们介绍了PTSD回避症状与DMN降低有关的试验数据与中央执行网络（CEN）的连接。我们还报告了基于正念的干预措施 PTSD降低了DMN和CEN之间的回避和连通性的提高。这个K23培训计划将允许候选人学习并应用强大的全脑连接组和动态连接研究大规模分布神经网络的变化所需的方法论，PTSD和治疗机制。我们的假设是H1：DMN-Cen降低和DMN-SN基础增加与PTSD患者的临床可接受性和结果相关的情绪 /行为避免与 H2：基于正念的认知疗法（MBCT）的目标与PTSD相同避免，H3：MBCT诱导的DMN-CEN连通性介导了PTSD的改善避免，情绪 /行为避免和改善结果。目的是：1。）测试是否行为 PTSD中的情绪避免与DMN-CEN连通性降低有关，2。）识别 MBCT使用强大的连接组学分析对DMN-CEN的影响，3。）探索调解 DMN-cen连通性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的n = 60作战的FMRI使用动态因果建模和上下文处理范例将与回避测试关联症状和实验室避免的措施。 RCT（n = 30 MBCT，n = 30对照） fMRI和X组时间互动分析将确定MBCT对和在DMN，CEN和SN之间。调解分析将测试神经目标和纵向测量情绪参与。这项研究将是避免避免的第一个靶向功能神经网络 PTSD治疗中的行为，可能会导致其他策略来帮助约50％的PTSD患者不完全参与现有的EST，并阐明与新型潜力相关的神经机制 PTSD治疗的组成部分（正念训练）。它还将提供候选人高级培训和 R级资助的试验数据，以识别PTSD治疗变化的机制和新型治疗方法。