From Networks to the Real World: Integrating Neural and Autonomic Processes of Loss

项目摘要/摘要 严重抑郁障碍(MDD)是一种流行的、使人衰弱的疾病，其特征是高水平的 负面影响(NA)。可能作为抑郁症风险表型的一种机制是认知障碍 丢失后NA的控制，这也与对丢失的非典型副交感反应有关。候选人 将扩展他在认知和情感风险因素方面的背景，为MDD检查神经网络 支持认知控制和情感调控，将RDoC损失结构整合到多个 医疗模式。这将发展他在认知和认知之间相互作用方面的机械性理解和专业知识 情绪系统是抑郁症患者自我调节功能失调的基础。候选人将学会：1) 评估基于任务的活动以及支持认知控制的内在连接网络之间的交互 和情绪处理(培训目标1(TA1))；2)整合多模式、多层次数据，学习 在维度上将功能磁共振成像与副交感和情感反应联系起来所需的高级统计建模 (TA2)。此外，在获奖的最后几年，候选人将学习使用EMA和 用于连接支持情绪认知控制的神经网络的动态副交感神经评估 对实验室和现实世界的情感/生理调节(TA3)。根据这些培训目标，候选人的 短期职业目标是了解情绪认知控制背后的神经网络，以及 为了测试基于实验室的神经和副交感神经反应评估的生态学有效性 影响监管。这一职业发展奖将允许应聘者提升认知能力 抑郁症的神经科学，其长期职业目标是识别认知和情感表型风险 情绪障碍发展和进展的标记物。伊利诺伊大学芝加哥分校(UIC) 候选人研究的理想环境，以及当地资源的持续发展，如 独立研究-专用3T扫描仪，全国仅有的22个全国抑郁症网络之一 中锋。斯科特·朗格内克导师是情绪障碍认知和情感神经科学方面的专家 在成年期间，是RDoC研究技术的领导者，并在以下方面拥有成熟的专业知识 研究抑郁症的机械论方法。具体的研究目标提供了一个极好的机会 让候选人学习和展示必要技能方面的专业知识，以推动他走向独立。 支持认知控制和情绪的网络中基于上下文的任务激活 将在35名有以下病史的年轻人(年龄18-27岁)中评估加工(特定目标1) 目前正在缓解的MDD患者(RMDD)和35名匹配的健康对照(HCS)。副交感神经 活动和影响监管将在以实验室为基础的损失范例期间进行评估，并将 从维度上讲，是基于任务的网络激活(具体目标2)。试点数据也是在稍后的奖项中收集的 通过EMA的动态评估进行为期七天的前瞻性评估。特定目标1通过以下方式解决TA1 为候选人提供了评估rMDD中中断的网络运行的机会。具体目标2 通过允许候选人学习新的程序和统计方法来评估，从而支持TA2 维度关系将网络功能中断与副交感和情感反应联系起来。 与方法整合顾问埃里卡·福布斯和统计顾问唐纳德·海德克一起， 指导团队将为候选人提供关于多模式数据和 为建立一个独立的实验室做准备。TA3是通过探索性目标在 奖项的后半部分，通过应用动态副交感神经评估和EMA(与Co. 导师罗宾·梅梅尔斯坦和顾问蒂姆·特鲁尔)将现实世界的情感调控与情感联系起来 在实验室中对失落的反应，以及支持情绪认知控制的神经网络。这将是 最终使应聘者能够将他的研究从实验室转移到现实世界中。数据 这项研究提供的收集将为计划中的R01提交审查提供关键的初步数据 认知-情感机制潜在的影响调节和影响发病和 抑郁症的进展。执行免费和综合的培训和研究目标将 促进应聘者的长期职业目标，并建立其在确定 影响情绪障碍进程的神经、心理生理和行为目标。

PROJECT SUMMARY/ABSTRACT Major depressive disorder (MDD) is a prevalent and debilitating disorder that is characterized by high levels of negative affect (NA). One mechanism that may serve as a phenotype for depression risk is impaired cognitive control of NA following loss, which is also linked to atypical parasympathetic responses to loss. The Candidate will extend his background in cognitive and affective risk factors for MDD to examine the neural networks supporting cognitive control and affect regulation integrating an RDoC loss construct across multiple modalities. This will develop his mechanistic understanding and expertise in interactions between cognitive and affective systems that underlie dysfunctional self-regulation in depression. The Candidate will learn to: 1) evaluate task-based activity and interactions between intrinsic connectivity networks supporting cognitive control and emotion processing (Training Aim 1 (TA1)); 2) integrate multi-modal, multi-level data and learn the advanced statistical modeling necessary to dimensionally link fMRI to parasympathetic and affective responses (TA2). In addition, in the latter years of the award, the candidate will learn to use the methodology of EMA and ambulatory parasympathetic assessment to link neural networks that support the cognitive control of emotion to lab and real-world affective/physiological regulation (TA3). In line with these training aims, the Candidate's short-term career goals are to understand the neural networks underlying the cognitive control of emotion, and to test the ecological validity of lab-based assessments of neural and parasympathetic responses to loss for affect regulation. This Career Development Award will allow the Candidate to advance the cognitive neuroscience of depression with the long-term career goal of identifying cognitive and affective phenotypic risk markers for the development and progression of mood disorders. The University of Illinois at Chicago (UIC) is the ideal setting for the candidate's research, with ongoing development of local resources such as an independent research-dedicated 3T scanner and one of only 22 nationwide National Network of Depression Centers. Mentor Scott Langenecker is an expert in the cognitive and affective neuroscience of mood disorders across the adult lifespan, a leader in RDoC research techniques, and has an established expertise in mechanistic approaches for studying depression. The Specific Research Aims afford an excellent opportunity for the Candidate to learn and demonstrate expertise in the necessary skills to propel him to independence. Contextually-appropriate task-based activation in networks supporting cognitive control and emotion processing (Specific Aim 1) will be evaluated among thirty-five young adults (ages 18-27) with a history of MDD who are currently remitted (rMDD) and thirty-five matched healthy controls (HCs). Parasympathetic activity and affect regulation will be assessed during a laboratory-based loss paradigm and linked dimensionally to task-based network activation (Specific Aim 2). Pilot data also are collected later in the award for a seven-day prospective period via ambulatory assessment with EMA. Specific Aim 1 addresses TA1 by affording the Candidate the opportunity to assess disrupted network functioning in rMDD. Specific Aim 2 supports TA2 by allowing the Candidate to learn novel procedural and statistical methods to assess dimensional relationships to link disrupted network functioning to parasympathetic and affective responses. Along with methodology integration consultant Erika Forbes and statistical consultant Donald Hedeker, the mentoring team will provide the Candidate guidance and supervision on the integration of multi-modal data and preparation toward the development of an independent laboratory. TA3 is met through the Exploratory Aims in the latter part of the award, via the application of ambulatory parasympathetic assessment and EMA (with Co- Mentor Robin Mermelstein and Consultant Tim Trull) to link real-world affect regulation with affective responses to loss in the lab, and with neural networks that support the cognitive control of emotion. This will eventually enable the Candidate to move his research out of the lab and into real world contexts. The data collection provided by this study will provide critical preliminary data for planned R01 submissions examining cognitive-affective mechanisms underlying affect regulation and that influence risk for the onset and progression of depression. Executing the complimentary and integrated training and research aims will promote the long-term career goals of the Candidate and establish his independent expertise in identifying neural, psychophysiological, and behavioral targets that influence the course of mood disorders.