Functional Connectome of Brain White Matter

摘要/摘要 这项研究的目标是扩大我们关于血氧水平如何依赖(BOLD)的发现 使用功能磁共振成像(FMRI)检测到的白质(WM)信号与神经相关 灰质(GM)的活动，并实施新的分析，适当地将WM信号纳入模型 从成像数据中得出的大脑功能。在过去的三十年里，几乎所有对脑功能磁共振数据的分析 忽略了WM信号，通常会将它们作为讨厌的回归因素移除。然而，这种观点具有 根据最近的证据进行了更改，这些证据表明WM粗体信号代表着潜在的重要和迄今为止的 被忽视的神经活动指标，与皮质区域如何沟通密切相关，因此 应将其纳入完整的功能连通性评估。我们最近已经证明， 当使用适当的分析时，在WM中可以强烈地检测到大胆的信号，即血流动力学 WM反应函数不同于GM，WM波束表现出可重现的表观模式 可概括为功能连通性矩阵(FCM)的连通性，通过分析获得 节段化的WM和GM之间的静息状态相关性。此外，独特的、可重现的 WM网络以类似于大脑皮层电路的方式从数据驱动的分析中出现。在这项提案中，我们的目标是 开发新的分析，并将其应用于大量公开可用的数据。我们的目标是(1)量化 更精细和更详细的WM纤维和GM电路之间的功能关系。我们将延长 将FCM的概念扩展到三维，以推导出与之同步的WM轨迹 自身从GM-GM连接性矩阵中识别的GM区域对；(2)为了使用数据驱动， 无模型独立成分分析，以识别WM和GM功能网络并量化 它们之间的相互关系；(3)构建一套详细的、定量的地图集 WM中的功能连通性和网络拓扑，并建立它们与行为和 认知测量。模板和数字地图集提供了一种将数据空间归一化到公共空间的方法， 并对正常和异常变化进行了定量测量。从以下方面扩展和应用该方法 用于创建WM功能数据地图集的结构和扩散MRI场将实现可重现的量化， 正常化，并对我们的结果进行解释。每一项分析也将考察性别和年龄的影响 关于WM功能度量。 影响：WM中的BOLD信号反映了与大脑皮质功能相关的神经活动，因此对 WM的功能参与对于正确地模拟大脑网络是必不可少的。这项研究将证明 WM和GM活动是如何联系的，以及如何将它们结合在一起以获得更完整的大脑模型 组织。这一结果将为利用脑白质相关的功能连接奠定坚实的基础 在一系列疾病和疾病中有病理或其他变化。

ABSTRACT / SUMMARY The goals of this research are to extend our discoveries of how blood oxygenation level dependent (BOLD) signals in white matter (WM), detected using functional magnetic resonance imaging (fMRI), are related to neural activity in gray matter (GM), and to implement new analyses that properly incorporate WM signals into models of brain function derived from imaging data. For the past three decades, nearly all analyses of brain fMRI data have ignored WM signals and usually have removed them as nuisance regressors. However, that view has changed in light of more recent evidence that WM BOLD signals represent potentially important and heretofore overlooked indicators of neural activity that are intimately related to how cortical regions communicate, and so should be incorporated into complete assessments of functional connectivity. We have recently shown that BOLD signals are robustly detectable in WM when appropriate analyses are used, that the hemodynamic response function in WM is different from GM, and that WM tracts show reproducible patterns of apparent connectivity which may be summarized in Functional Connectivity Matrices (FCMs), obtained by analyzing resting state correlations between segmented WM and GM parcellations. Furthermore, distinct, reproducible networks of WM emerge from data-driven analyses in similar manner to cortical circuits. In this proposal we aim to develop new analyses and apply them to large numbers of publicly available data. We aim (1) to quantify the functional relationships between WM fibers and GM circuits at a finer scale and in greater detail. We will extend the concept of FCMs to three dimensions to derive those WM tracts that show synchronous time courses with pairs of GM regions that themselves are identified from a matrix of GM-GM connectivity; (2) to use data-driven, model-free independent component analyses to identify WM and GM functional networks and quantify the correlations between them; and (3) to construct a suite of detailed and quantitative atlases characterizing functional connectivity and network topology in WM, and establish their relationships with behavioral and cognitive measures. Templates and digital atlases provide a way to spatially normalize data to common spaces, and measure normal and abnormal variations quantitatively. Extending and applying the methodology from structural and diffusion MRI fields to create atlases of WM functional data will enable reproducible quantification, normalization, and interpretation of our results. Each analysis will also examine the influence of gender and age on WM functional metrics. Impact: BOLD signals in WM reflect neural activity that is related to cortical brain function, so analyses of the functional engagement of WM are essential to properly model brain networks. This research would demonstrate how WM and GM activities are related, and how to integrate them to obtain a more complete model of brain organization. The results will lay a firm foundation for exploiting functional connectivity in white matter associated with pathological or other changes across a spectrum of disorders and conditions.