Modeling Dynamic Covariation of Brain Function, Health and Symptoms in Depression

抑郁症中大脑功能、健康和症状的动态协变建模

• 批准号: 7585777
• 负责人: Wesley Kurt Thompson
• 金额: $ 17.29万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7585777
• 关键词: Algorithms; Area; Award; Biological; Brain; Brain region; Cardiovascular system; Complex; Computer Simulation; Consultations; Data; Data Analyses; Emotional; Equation; Functional Magnetic Resonance Imaging; Genetic; Goals; Health; K-Series Research Career Programs; Link; Measures; Mediator of activation protein; Methodology; Modeling; Outcome; Pattern; Process; Psychosocial Stress; Research; Research Design; Research Personnel; Risk Factors; Simulate; Speed; Statistical Models; Stress; Symptoms; System; Techniques; Training; Variant; Work; cardiovascular disorder risk; cardiovascular risk factor; career; career development; depressed; depression; depressive symptoms; design; emotional stimulus; information processing; neuromechanism; novel; physical conditioning; programs; research study; response; social; statistics; stressor; tool

DESCRIPTION (provided by applicant): The applicant's long-term career goal is to become an independent investigator in the field of psychiatric statistics with an emphasis on research into the relationships between depression and physical health. He will dedicate his career to creating and implementing novel statistical methodologies and study designs to research in this area. This career development award will provide crucial support for achieving this goal. The career development activities proposed during the award period will include training in the scientific and computational models of fMRI studies of depression and cardiovascular reactivity and consultations on causal inference in psychiatric research. There are two primary proposed research goals over the next five years. First, the candidate proposes to adapt statistical methodologies from the field of functional data analysis (FDA) for the examination of potentially causal dynamic covariation in multiple functional processes. Causal inferences will be made by using these statistical methodologies to implement the moderator and mediator framework in the functional setting and also by applications of these methodologies to formal causal models, e.g., structural equation and dynamic causal models. Second, these techniques will be validated on and applied to fMRI studies of depression and cardiovascular reactivity. Specific research goals in these applications will be: 1) exploring potential moderators of patterns of brain activation in depressed and non-depressed subjects; 2) modeling functional integration among specialized brain regions related to depression and cardiovascular reactivity; 3) examining the moderating effect of psychopathological variables on patterns of brain activation in response to emotional stimuli and to stressors; and 4) relating patterns of activation in specialized brain regions to cardiovascular responses to stressors. The proposed research program will result in the creation and application to psychiatric research of a cutting-edge body of statistical methodologies for examining dynamic variation in functional processes. Moreover, while the initial applications will focus on fMRI research, these statistical methodologies will have wide applicability to psychiatric research in general.

申请人的长期职业目标是成为精神病学统计领域的一名独立调查员，重点研究抑郁症与身体健康之间的关系。他将致力于创造和实施新的统计方法和研究设计，以在这一领域进行研究。这一职业发展奖将为实现这一目标提供至关重要的支持。在授标期间提出的职业发展活动将包括关于功能磁共振成像的科学和计算模型的培训、抑郁症和心血管反应性的研究以及精神病学研究中关于因果推断的咨询。在接下来的五年里，主要提出了两个研究目标。首先，候选人建议采用功能数据分析(FDA)领域的统计方法来检查多个功能过程中潜在的因果动态协变。因果推断将通过使用这些统计方法在功能环境中实施主持人和调解人框架，并通过将这些方法应用于正式的因果模型，例如结构方程和动态因果模型来进行。其次，这些技术将在抑郁症和心血管反应性的功能磁共振研究中得到验证和应用。这些应用中的具体研究目标将是：1)探索抑郁和非抑郁受试者大脑激活模式的潜在调节因素；2)模拟与抑郁和心血管反应性相关的专门大脑区域之间的功能整合；3)检验精神病理变量对对情绪刺激和应激源反应的大脑激活模式的调节作用；以及4)将专门大脑区域的激活模式与心血管对应激源的反应联系起来。拟议的研究计划将导致创建并应用于精神病学研究，以检验功能过程中的动态变化的统计方法的尖端主体。此外，虽然最初的应用将集中在功能磁共振研究，但这些统计方法将广泛适用于精神病学研究。