Project 4

项目摘要/摘要--项目4 我们计划利用我们在理论生物物理和计算方面的最先进的专业知识 流体动力学研究软脑膜神经血管环路的基本特征及其对皮质的影响 血液供应和氧合作用。项目4将提供动物体内反应的定量途径 受试者(项目1和2)解释人类受试者的功能磁共振数据(项目3)。本节目 将在可观察到的神经血管反应和大脑内部状态之间建立联系。特别是， 项目4将与项目1合作，整合软脑膜神经血管回路的实验知识 振荡；它将与项目2合作，整合神经元和 血管活性；最后，它将通过使用血液氧合模型来确定BOLD fMRI来影响项目3 软脑膜神经血管模式的反应信号。 项目4有两个具体目标：(2)捕捉时空神经血管动力学和 软脑膜血管网的类型，即由其光滑的微动脉驱动的小动脉的扩张和收缩 肌鞘；和(Ii)展示血管运动动力学对皮质血液供应的影响和 组织pO2，从而在BOLD/CBV功能磁共振信号和神经元活动模式之间建立了因果联系。 对于目标1，我们将依赖于长期的实验证据，即超低的，~0.1赫兹的振荡 单个小动脉节段，以及项目1关于软脑膜神经血管网络的初步数据。他们的 结合导致我们的大脑小动脉的理论框架形成一个耦合振荡器网络， 控制整个大脑的血液流动。我们的第一个目标是开发基于耦合振荡器的 捕捉观察到的神经血管和神经调节动力学本质的数学模型 并提出实验测试方案。我们的第二个目标是演示 微动脉的调制驱动和固有振荡之间的竞争导致空间分离和 形成时间相关区域的不同星座，如项目1至3所观察到的。 对于目标2，我们将使用详细的血流动力学模拟和现有的三维重建 皮质微循环的研究，以衡量血管运动激活的调节效果，在第一个目标中模拟 并在项目1和2的实验中观察到了皮质血液和氧气供应的诱导变化。 软膜小动脉管径节律性变化对脑血流量和动态阻力的影响 微血管中的再分布将被具体解剖，以建立前馈调节， 血管舒缩运动对皮质血供和组织氧分压的影响。血管运动调节的血流量将是 进一步用于计算整个皮质层深度的时空氧合图 软膜表面。这些图谱将提供氧合动力学和软脑膜网络之间的联系， 这将为我们从BOLD fMRI信号中推断大脑状态和神经调节输入提供信息。

PROJECT SUMMARY/ABSTRACT – PROJECT 4 We propose to leverage our state-of-the-art expertise in theoretical biological physics and computational fluid dynamics to investigate fundamental aspects of the pial neurovascular circuit and its impact upon cortical blood supply and oxygenation. Project 4 will provide a quantitative path from in vivo responses in animal subjects (Projects 1 and 2) to the interpretation of fMRI data across human subjects (Project 3). This program will establish a link between observable neurovascular responses and the internal brain state. In particular, Project 4 will collaborate with Project 1 to integrate experimental knowledge of pial neurovascular circuit oscillations; it will collaborate with Project 2 to incorporate knowledge on the modulation of neuronal and vascular activity; finally, it will impact Project 3 by using blood oxygenation models to determine BOLD fMRI signals in response to pial neurovascular patterns. Project 4 features two specific aims: (ii) Capture the spatiotemporal neurovascular dynamics and the patterns of the pial vascular network, that is, the dilation and constriction of arterioles driven by their smooth muscle sheath; and (ii) Demonstrate the effects of the vasomotor dynamics onto the cortical blood supply and tissue pO2, thereby establishing a causal link between BOLD/CBV fMRI signals and neuronal activity patterns. For Aim 1, we shall rely on long standing experimental evidence for ultraslow, ~ 0.1 Hz oscillations of individual arteriole segments, as well as preliminary data of Project 1 on the pial neurovascular network. Their combination leads to our theoretical framework of brain arterioles forming a network of coupled oscillators that control the flow of blood throughout the entire brain. Our first goal is to develop coupled-oscillator-based mathematical models that capture the essence of the observed neurovascular and neuromodulatory dynamics across the cortical mantle and propose experimental tests. Our second goal is to demonstrate how the competition between modulatory drives and intrinsic oscillations of arterioles results in spatial parcellation and formation of the different constellations of temporally coherent regions, as observed in Projects 1 to 3. For Aim 2, we will use detailed hemodynamic simulations with an existing three dimensional reconstruction of the cortical microcirculation to gauge the regulatory effect of vasomotor actuation, modeled in the first aim and observed in experiments of Projects 1 and 2, on induced changes in cortical blood and oxygen supply. The effects of rhythmic changes in pial arteriole diameter upon the cerebral blood flow and dynamic resistance redistributions in microvessels will be specifically dissected to establish the feed forward regulation that vasomotor exercises upon cortical blood supply and tissue pO2. Vasomotor-modulated blood flow will be further used to compute spatiotemporal oxygenation maps throughout the depth of cortical layers and across the pial surface. Those maps will provide the link between the dynamics of oxygenation and the pial network, which will inform our inferences of the brain state and neuromodulatory inputs from BOLD fMRI signals.