CRCNS: Waste-clearance flows in the brain measured using physics-informed neural network

脑脊液和脑间质的脑运输系统 Nedergaard团队于2012年首次描述了流体系统，该系统主要运行 在睡眠中，并与包括阿尔茨海默病在内的病理神经疾病有关， 创伤性脑损伤(TBI)和中风。获得淋巴流体速度的定量测量 而压力对于理解关节的功能、失败和潜在的康复是至关重要的 淋巴系统。然而，用于获得体内淋巴速度的现有技术仅限于 稀疏测量和特定区域，压力变化基本上不可能测量 在活体内。我们建议通过测量被跟踪的颗粒和对比度来量化淋巴流动 使用物理信息神经网络(PINN)的代理，它可以从 稀疏测量，以前从未在神经科学中使用过。我们将调整PINN以用于 三种常用的淋巴成像方式：双光子血管周围空间成像， 经颅全脑成像和动态增强磁共振成像(DCEMRI)。 对于这些模式，每种模式都可以探测不同区域和规模的淋巴流动，我们 将适应PINNS方程和人工智能超参数，评估 使用合成数据处理噪声、时空分辨率和成像伪影，并通过 将PINN推断的速度与其他技术得出的速度进行比较。使用PINN将允许 美国将获得此前未测到的脑脊液体内速度和压力测量 大脑的不同区域。我们由神经学家、流体动力学家和应用程序组成的协作团队 数学家包括发现了字形系统并发明了大头针的领导人。 此外，我们在所有三种成像方式和速度方面都有丰富的经验。 液态流中的测量(通过自动粒子跟踪和前沿跟踪)。 这项提议试图揭示大脑的脑脊液运输系统和 间质流体起作用。一种新型的脑脊液速度和压力测量方法 体液流动可以证明如何改善睡眠，在此期间，淋巴系统 主要操作，可以中和与淋巴系统衰竭相关的病理过程，包括 阿尔茨海默氏症。

The brain’s transport system for cerebrospinal and interstitial fluid, the glymphatic system, was first described in 2012 by the Nedergaard team, operates primarily during sleep, and has been linked to pathological neurological conditions including Alzheimer’s disease, traumatic brain injury (TBI), and stroke. Obtaining quantitative measurements of glymphatic fluid velocity and pressure is crucial to understanding the function, failures, and potential rehabilitation of the glymphatic system. However, existing techniques for obtaining in vivo glymphatic velocities are limited to sparse measurements and specific regions, and pressure variation is essentially impossible to measure in vivo. We propose to quantify glymphatic flows from measurements of tracked particles and contrast agents using physics-informed neural networks (PINNs), which can infer velocity and pressure from sparse measurements and have not been used previously in neuroscience. We will adapt PINNs for three commonly-employed glymphatic imaging modalities: two-photon perivascular space imaging, transcranial whole-brain imaging, and dynamic contrast-enhanced magnetic resonance imaging (DCEMRI). For these modalities, each of which can probe different regions and scales of glymphatic flows, we will adapt the PINNs equations and artificial intelligence hyperparameters, evaluate the sensitivity of the approach to noise, spatiotemporal resolution, and imaging artifacts using synthetic data, and validate by comparing velocities inferred by PINNs to velocities from alternative techniques. Using PINNs will allow us to obtain in vivo velocity and pressure measurements of cerebrospinal fluid in previously unmeasured regions of the brain. Our collaborative team of neuroscientists, fluid dynamicists, and applied mathematicians includes the leaders who discovered the glymphatic system and invented PINNs. Moreover, we have extensive experience with all three imaging modalities and with velocity measurement (via automated particle tracking and front tracking) in glymphatic flows. This proposal seeks to reveal mechanisms by which the brain's transport system for cerebrospinal and interstitial fluid operates. Our novel velocity and pressure measurements of intracranial cerebral spinal fluid flows may demonstrate how improving sleep, the state during which the glymphatic system primarily operates, can counteract pathological processes related to glymphatic system failure including Alzheimer's disease.