Modeling Covariation Brain Function, Health/Depression

协变大脑功能建模，健康/抑郁

• 批准号: 7079853
• 负责人: Wesley Kurt Thompson
• 金额: $ 17.27万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 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/7079853
• 关键词: antidepressants; behavioral /social science research tag; blood pressure; brain mapping; cardiovascular disorder; cardiovascular disorder risk; comorbidity; computational biology; computational neuroscience; computer program /software; emotions; functional magnetic resonance imaging; health behavior; human data; major depression; mathematical model; mental health epidemiology; neural information processing; psychological stressor; psychopathology; psychopharmacology; statistics /biometry

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独立调查员，重点是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，以研究这一领域。这一职业发展奖将为实现这一目标提供至关重要的支持。在奖励期间提出的职业发展活动将包括在抑郁症和心血管反应的功能磁共振成像研究的科学和计算模型方面的培训，以及在精神病学研究中的因果推理方面的咨询。在未来五年内，有两个主要的研究目标。首先，候选人建议调整功能数据分析（FDA）领域的统计方法，以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设置中实施调节者和中介者框架，以及通过将这些方法应用于正式的因果模型来进行，例如，结构方程和动态因果模型。第二，这些技术将被验证，并应用于抑郁症和心血管反应性的功能磁共振成像研究。这些应用的具体研究目标是：1）探索抑郁和非抑郁受试者脑激活模式的潜在调节者; 2）模拟与抑郁和心血管反应相关的专门脑区之间的功能整合; 3）检查精神病理学变量对大脑激活模式的调节作用，以响应情绪刺激和压力;以及4）将专门大脑区域的激活模式与对压力源的心血管反应相关联。拟议的研究计划将导致创建和应用到精神病学研究的一个尖端机构的统计方法，检查功能过程中的动态变化。此外，虽然最初的应用将集中在功能磁共振成像研究，这些统计方法将有广泛的适用性，精神病学研究一般。