Secondary analysis of functional MRI and resting state connectivity in white matter

摘要/摘要 这项建议旨在对公开的功能磁共振成像的大型档案进行新颖的二次分析 为了量化白质的功能特征及其在脑内的变化 正常衰老和发展为阿尔茨海默病(AD)。血氧水平依赖 多年来，(BOLD)效应一直被用来检测灰质(GM)的神经活动，但 传统上，WM中的信号被忽略，因此在以前的分析中没有考虑到它们。 然而，WM的大胆信号在相对较少的健康大脑中进行了评估，这些 研究表明，WM对刺激的反应表现出强大的、特定于区域的大胆变化 在休眠状态下显示区域间相关性，类似于用于推断 大脑皮质和静息状态下WM束内的信号波动与特定的GM显示出很强的相关性 在功能网络中，皮质体积结合在一起。因此，我们建议调整这些工具 开发用于分析GM连通性和WM的扩散成像以分析功能变化 在西医与年龄在&gt；7900成像研究公开。在目标1中，我们将检测和表征 通过对巴尔的摩纵向研究对象的分析发现正常衰老状态下WM功能网络的变化 老龄化研究(BLSA)、开放获取影像研究系列(OASIS-3)与阿尔茨海默病 神经成像倡议(ADNI)。阿尔茨海默病的神经影像研究表明WM异常存在于 疾病的临床前阶段，因此检测和量化改变的WM功能可能是重要的 衡量这种疾病的功能变化的指标。因此，在目标2中，我们将测量WM泛函的变化 在ADNI、BLSA和OASIS-3数据库中登记的受试者的网络。在这两个目标中，我们还将 通过行为、临床和遗传评估测量WM连接性的协变性，以建立 工作记忆功能指标如何反映行为和认知，并随着认知障碍的增加而变化。 在目标3中，我们将从目前的扩散磁共振研究中扩展地图集的创建和机器学习 通过创建年龄调整的WM功能MRI属性图谱来量化WM功能MRI 实现标准化比较，并为功能和结构提供规范模板 连通性网络分析。我们还将应用数据驱动的深度学习来识别个人签名 在整个大脑的基础上的损害。脑白质功能完整性的失败显然与 衰老和神经退化。这项提议将对中国的职能变化有新的理解。 WM跨越整个生命周期，识别AD中WM功能的病理变化，并创建新的数据驱动 用于解释WM功能磁共振的工具。

Abstract / Summary This proposal aims to perform novel, secondary analyses on large archives of publicly-available fMRI studies in order to quantify the functional characteristics of white matter (WM) and their changes during normal aging and in the progression to Alzheimer’s Disease (AD). Blood oxygenation level dependent (BOLD) effects have been used to detect neural activity in grey matter (GM) for many years, but BOLD signals in WM have traditionally been ignored so they have not been considered in previous analyses. However, WM BOLD signals have been evaluated in relatively small numbers of healthy brains, and these studies have shown that WM shows robust, tract-specific BOLD changes in response to stimuli, WM exhibits inter-regional correlations in a resting state similar to those used to infer functional connectivity in cortex, and signal fluctuations within WM tracts in a resting state show strong correlations to specific GM cortical volumes engaged together in functional networks. We therefore propose to adapt the tools developed for analyzing GM connectivity and for diffusion imaging of WM to analyze the functional changes in WM with age in >7,900 imaging studies available publicly. In Aim 1, we will detect and characterize changes in WM functional networks with normal aging by analyzing subjects from the Baltimore Longitudinal Study of Aging (BLSA), the Open Access Series of Imaging Studies (OASIS-3) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neuroimaging studies of AD suggest that WM abnormalities exist at a preclinical stage of the disease, so detecting and quantifying altered WM function may be an important metric of functional changes in this disorder. In Aim 2 therefore we will measure alterations in WM functional networks in subjects enrolled in the ADNI, BLSA, and OASIS-3 databases. In both Aims we will also measure co-variations of WM connectivities with behavioral, clinical and genetic assessments to establish how WM functional metrics reflect behavior and cognition and change with increasing cognitive impairment. In Aim 3 we will extend the creation of atlases and machine learning from current studies of diffusion MRI to quantifying WM functional MRI by creating age-adjusted atlases of WM functional MRI properties to enable normative comparisons and provide canonical templates for both functional and structural connectivity network analyses. We will also apply data-driven deep learning to identify individual signatures of impairment on a whole-brain basis. A failure of white matter functional integrity is clearly implicated in aging and neurodegeneration. This proposal will develop new understandings of the functional changes in WM across the lifespan, identify pathological changes in WM function with AD, and create new data-driven tools for interpretation of WM fMRI.