CRCNS-US-German research collaboration on functional neuro-poroelastography

描述(申请人提供)：由施加的神经刺激引起的诱发血流动力学反应，并通过功能磁共振成像捕获，是神经元活动的间接测量，已成为现代临床神经科学研究大脑功能的主力。然而，与神经血管偶联的潜在分子/细胞机制相关的信号解释是一个活跃的研究领域，而且似乎相互矛盾的结果继续出现在文献中。问题的一部分是缺乏直接评估闭合颅骨局部神经活动的非侵入性成像选择，而开发新的成像方法仍然是一个重大挑战。正如本项目所描述的，我们已经确定了一种新的可能性--功能性神经孔弹性成像(FNPE)，它将脑血管搏动的MRI采集与计算方法相结合，以估计空间定位的机械和流体动力学脑组织属性。FNPE捕捉脑组织的机械功能反应，并将根据机械特性的变化，无创和无外源性头部刺激，提供其活动的第一个空间地图。FNPE对神经组织的多尺度机械网络敏感，因此，将揭示感觉信号是如何与大脑结构性适应联系在一起的。这一全新的信息可以被添加到电激活、新陈代谢和结构的神经计算模型中。我们将开发具有非线性反演功能的fNPE，以生成水力传导性、间隙压力和流体分数以及剪切模数的3D图像。这些结果将与一种新的宽带FMRE方法进行比较，在该方法中，也将通过非线性反演但使用粘弹性模型来形成图像。我们将使用既定的刺激方案来定义这些新的MRE方法与脑功能的关联。神经网络不仅在大脑内传输电信号，还提供了维持结构和形状的大部分机械支架。液体的流动性控制着触发神经元活动所需的血流和离子梯度，但它也会减弱组织的运动，并影响颅骨内的动脉、静脉和间质压力。因此，我们假设脑血管流动和相关的组织力学特性有助于正常的脑功能和/或反之亦然-脑功能调节脑血流动力学，并伴随着脑组织力学。目前，对于正常和病理条件下的活体脑力学知识和理解有限；然而，针对大脑的机械和流体动力学特性的MRI方法，即MRE技术，正在兴起，并且将这些特性与脑功能相关的初步研究开始出现在文献中。尽管最近取得了一些进展，但神经计算模型倒置在脑MRE中还不够发达，特别是如果我们要阐明大脑功能与脑机械和流体动力学特性之间关系的根本进展。MRE中的神经计算包括流体动力学、孔弹性和粘弹性网络，它可能在神经元健康(和功能)的框架内开辟一个新的研究领域，将机械结构与脑组织功能联系起来。鉴于神经网络是机械大脑支架的主要贡献者，这些发展也将为神经退化模型提供信息。该项目将巩固最近开始的神经计算成像领域的国际合作。它还将加快实现临床神经科学研究人脑功能的新成像和计算方法，并创建适用于其他器官系统和疾病的计算成像框架。国际间的意见和专门知识交流将加强参与机构的研究基础和有关调查人员的知识。在拟议的资助期结束前，机构和研究团队都将拥有神经计算倒置算法以及提供fNPE研究所需的MRI序列。研究生和博士后研究员不仅将接受先进的核磁共振成像和计算方法方面的培训，而且他们还将通过在每个机构驻留时间，接触并受益于参与多学科国际合作。

DESCRIPTION (provided by applicant): Evoked hemodynamic response caused by an applied neurological stimulus and captured with fMRI is an indirect measure of neuronal activity that has become the work-horse of modern clinical neuroscience research on brain function. However, interpretation of the signal relative to the underlying molecular/cellular mechanisms responsible for the neurovascular coupling is an active area of investigation, and seemingly contradictory results continue to appear in the literature. Part of the problem is lack of noninvasive imaging options that directly assess local neural activity in the closed cranium, and development of new imaging approaches remains a significant challenge. As described in this project, we have identified a new possibility - functional neuro-poroelastography fNPE) which combines MRI acquisition of cerebrovascular pulsation in the brain with computational methods to estimate spatially localized mechanical and hydrodynamical brain tissue properties. fNPE captures mechano-functional responses of brain tissue and will provide the first spatial maps of its activity based on changes in mechanical properties, noninvasively and without exogenous head stimulation. fNPE is sensitive to multiscale mechanical networks of neural tissue, and thus, will reveal how sensory signals are linked to structural brain adaptation. This fundamentally new information can be added to neuro-computational models of electrical activation, metabolism and structure. We will develop fNPE with nonlinear inversion to yield 3D images of hydraulic conductivity, interstitial pressure and fluid fraction in addition to shear modulus. These results will be compared to a new wideband fMRE approach where images will also be formed through nonlinear inversion but with viscoelastic models. We will define the association of these new MRE methods with brain function using established stimulus protocols. The neuronal network not only transmits electrical signals within the brain, it also provides much of the mechanical scaffold which maintains structure and shape. The mobility of fluid controls the blood flow and ionic gradients required to trigger neuronal activity, but it also attenuates tissue motion and influences the arterial, venous and interstitial pressures within the cranium. Thus, we hypothesize that cerebrovascular flow and related tissue mechanical properties contribute to normal brain function and/or vice versa - brain function modulates cerebral hemodynamics, and concomitantly, brain tissue mechanics. Currently, limited knowledge and understanding exist on in vivo brain mechanics under normal and pathological conditions; yet, MRI methods specific to the mechanical and hydrodynamical properties of the brain, namely MRE techniques, are emerging and preliminary studies relating these properties to brain function are beginning to appear in the literature. Despite recent advances, the neurocomputational model inversion is under-developed in brain MRE, especially if fundamental advances in our understanding of the relationships between brain function and brain mechanical and hydrodynamical properties are to be elucidated. Neuro-computation in MRE, which includes fluid dynamics, poroelasticity and viscoelastic networks may open a new field of study within the framework of neuronal health (and function), which relates mechanical structure with brain tissue function. These developments will also inform models of neuro-degeneration given that the neuronal network is major contributor to the mechanical brain scaffold. This project will solidify an international collaboration in neuro-computational imaging that was recently begun. It will also accelerate realization of new imaging and computational methods for clinical neuroscience research on human brain function, as well as create a computational imaging framework that is applicable to other organ systems and diseases. The international exchange of ideas and expertise will strengthen the research base at the participating institutions and the knowledge of the investigators involved. Both institutions and research teams will have the neuro-computational inversion algorithms along with the MRI sequences required to deliver fNPE studies by the end of the proposed funding period. Graduate students and post-doctoral fellows will not only be trained in advanced MRI and computation methods, but they will also be exposed to and benefit from participating in a multi-disciplinary international collaboration by spending time-in-residenc at each institution.