Project 4

项目总结/摘要-项目4 我们建议利用我们在理论生物物理学和计算物理学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回路的基本方面及其对皮质的影响 血液供应和氧合。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）对人类受试者（项目3）的fMRI数据的解释。这个程序 将在可观察到的神经血管反应和内部大脑状态之间建立联系。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，将神经元和 血管活动;最后，它将通过使用血氧模型来确定BOLD fMRI来影响项目3 信号响应软膜神经血管模式。 项目4有两个具体目标：（ii）捕获时空神经血管动力学和 软脑膜血管网络的模式，即由其平滑的微动脉驱动的微动脉的扩张和收缩， 肌肉鞘;和（ii）证明血管动力学对皮质血液供应的影响， 组织pO 2，从而建立BOLD/CBV fMRI信号和神经元活动模式之间的因果关系。 对于目标1，我们将依赖于长期存在的实验证据，用于超低，~ 0.1 Hz的振荡， 单个小动脉段，以及项目1关于软脑膜神经血管网络的初步数据。他们的 结合导致我们的理论框架，大脑小动脉形成了一个耦合振荡器的网络， 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 数学模型，捕捉观察到的神经血管和神经调节动力学的本质 并提出实验测试。我们的第二个目标是展示 小动脉的调节驱动和内在振荡之间的竞争导致空间分割， 时间相干区域的不同星座的形成，如项目1至3所观察到的。 对于目标2，我们将使用现有三维重建的详细血流动力学模拟 皮质微循环的测量血管激动的调节作用，在第一个目标中建模 并在项目1和2的实验中观察到皮质血液和氧气供应的诱导变化。 软脑膜微动脉直径节律性变化对脑血流和动态阻力的影响 微血管中的再分布将被特别解剖以建立前馈调节， 血管收缩对皮质血供和组织pO 2的影响。血管运动调节的血流将是 还用于计算贯穿皮层层的深度和跨皮层层的时空氧合图 软脑膜表面。这些地图将提供氧合动力学和软膜网络之间的联系， 这将为我们推断大脑状态和来自BOLD功能磁共振成像信号的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.