Quantitative Methods for Neuroimaging Studies of Interventions in Aging

衰老干预神经影像学研究的定量方法

• 批准号: 8137829
• 负责人: MICHELLE WANG
• 金额: $ 15.08万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8137829
• 关键词: Adult; Aerobic; Age; Aging; Algorithms; American; Area; Attention; Award; Awareness; Bayesian Method; Behavior; Biological Markers; Brain; Brain imaging; Brain region; Clinical; Cognition; Cognitive; Cognitive deficits; Communities; Complement; Computational algorithm; Conflict (Psychology); Data; Detection; Deterioration; Development; Development Plans; Dimensions; Economic Burden; Elderly; Electrical Engineering; Engineering; Exhibits; Faculty; Functional Imaging; Functional Magnetic Resonance Imaging; Funding; Health; Hippocampus (Brain); Human; Hybrids; Image; Image Analysis; Impaired cognition; Individual; Intervention; Intervention Studies; Knowledge; Laboratories; Longevity; Longitudinal Studies; Machine Learning; Magnetic Resonance Imaging; Maps; Markov Chains; Medial; Memory; Mentors; Methodology; Methods; Mind; Modeling; Multivariate Analysis; Neurosciences; Noise; Parietal; Participant; Pattern; Performance; Phase; Physical activity; Population; Prefrontal Cortex; Process; Public Health; Quality of life; Reporting; Research; Resolution; Risk Behaviors; Role; Sample Size; Sampling; Scheme; Seeds; Sensitivity and Specificity; Shapes; Statistical Methods; Structure; Surface; Techniques; Temporal Lobe; Testing; Time; Training; United States National Institutes of Health; Work; age related; aging brain; aging mind; base; bioimaging; career; career development; clinical application; cognitive neuroscience; executive function; experience; fitness; flexibility; gray matter; healthy aging; hemodynamics; improved; interest; intervention effect; morphometry; neural circuit; neuroimaging; new technology; novel; public health relevance; relating to nervous system; relational memory; research study; response; sedentary; shape analysis; social; statistics; therapy design; tool; white matter; young adult

DESCRIPTION (provided by applicant): This proposal for an NIH Mentored Quantitative Research Career Award requests support for Dr. Yongmei Michelle Wang as she embarks on a faculty career focused on imaging studies which examine the influence of longitudinal interventions on brain structure and function, and its relationship to cognition and performance, in older adults. The application proposes a research career development plan in the field of neuroimaging, bridging engineering, statistics, and neuroscience. The plan includes two overlapping phases: 1) a didactic phase that emphasizes training, including coursework and laboratory work in the area of cognitive neuroscience, imaging, aging, and interventions to complement Dr. Wang's doctoral training in Electrical Engineering and existing experience in Statistics; and 2) a development phase that focuses on intense development of the proposed research. These two phases will be closely supervised by the mentor and advisor in the area of cognitive neuroscience, brain plasticity, biomedical imaging, aging and interventions. Neuroimaging techniques, such as magnetic resonance imaging (MRI) and functional MRI (fMRI), have been shown to be powerful for characterizing and understanding the structure and function of the human brain. There remains a need, however, for robust and efficient statistical image analysis methods due to the limitations of existing approaches. It is crucial that these analysis techniques be developed with a full understanding of the neuroimaging methods used and the relevant cognitive neuroscience. We propose to develop, implement, and validate integrated computational algorithms for reliable and sensitive analysis of brain MRI and fMRI images, with the following specific aims: 1) Develop, validate and combine novel and efficient univariate and multivariate morphometry analysis methods. 2) Develop and evaluate integrated functional hemodynamic response and connectivity study approaches. 3) Apply these methods to the MRI and fMRI data being collected from separately funded NIA project of the mentor, to examine the effects of aerobic fitness training on brain structure and function of older adults; the neuroscience hypothesis to be tested are: improvements in aerobic fitness, over the course of a 1 year intervention, will result in i) increases in gray and white matter volume and shape changes of subcortical structures of the human brain; and ii) changes in the underlying neural circuits. 4) Develop a brain image analysis toolbox implementing the above methods. PUBLIC HEALTH RELEVANCE: The development of quantitative image analysis methodology for the characterization of brain structural and functional changes caused by interventions (such as fitness) on the aging brain is of tremendous importance to understanding the effects of interventions on brain, and to the design of interventions that optimize the effects on cognition and brain health.

描述（由申请人提供）：这项关于 NIH 指导定量研究职业奖的提案请求对 Yongmei Michelle Wang 博士的支持，因为她开始了专注于成像研究的教师生涯，该研究检查纵向干预对老年人大脑结构和功能的影响，及其与认知和表现的关系。该申请提出了神经影像、桥接工程、统计学和神经科学领域的研究职业发展计划。该计划包括两个重叠的阶段：1）教学阶段，强调培训，包括认知神经科学、成像、衰老和干预领域的课程和实验室工作，以补充王博士在电气工程方面的博士培训和现有的统计学经验； 2）开发阶段，重点关注拟议研究的深入发展。这两个阶段将受到认知神经科学、大脑可塑性、生物医学成像、衰老和干预领域的导师和顾问的密切监督。神经影像技术，例如磁共振成像 (MRI) 和功能性 MRI (fMRI)，已被证明对于表征和理解人脑的结构和功能非常有效。然而，由于现有方法的局限性，仍然需要稳健且有效的统计图像分析方法。至关重要的是，在充分了解所使用的神经影像方法和相关认知神经科学的情况下开发这些分析技术。我们建议开发、实施和验证集成计算算法，以对脑 MRI 和 fMRI 图像进行可靠和灵敏的分析，具体目标如下：1）开发、验证和结合新颖且高效的单变量和多变量形态测量分析方法。 2) 开发和评估综合功能血流动力学反应和连通性研究方法。 3）将这些方法应用于导师单独资助的NIA项目收集的MRI和fMRI数据，以检查有氧健身训练对老年人大脑结构和功能的影响；待测试的神经科学假设是： 在一年的干预过程中，有氧健身的改善将导致 i) 灰质和白质体积增加以及人脑皮层下结构的形状变化； ii) 基础神经回路的变化。 4）开发一个实现上述方法的脑图像分析工具箱。 公共健康相关性：定量图像分析方法的发展，用于表征衰老大脑的干预措施（例如健身）引起的大脑结构和功能变化，对于理解干预措施对大脑的影响以及设计优化认知和大脑健康影响的干预措施非常重要。