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A Cerebral Functional Unit Model for Multimodal Imaging of Neurovascular Coupling

用于神经血管耦合多模态成像的脑功能单元模型

基本信息

批准号：
7860674
负责人：
Theodore James Huppert
金额：
$ 18.45万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-06-05 至 2012-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7860674
关键词：
Address Biochemical Biological Blood Vessels Brain Cerebrum Characteristics Collection Coupled Coupling Data Analyses Development Electric Stimulation Equilibrium Event Excision Experimental Models Foundations Frequencies Future Head Health Image Lead Linear Regressions Magnetic Resonance Imaging Magnetoencephalography Measurement Measures Metabolic Methodology Methods Modality Modeling Multimodal Imaging Near-Infrared Spectroscopy Nerve Degeneration Noise Optics Pathology Pattern Performance Photic Stimulation Physiologic pulse Physiological Physiology Procedures Process Property Refractory Resolution Signal Transduction Simulate Space Models Stimulus Synapses System Techniques Technology Testing Time Variant Vascular System Vascular blood supply Visual Waste Products Work base design fitness hemodynamics improved instrumentation median nerve neuroimaging novel optical imaging public health relevance relating to nervous system research study response somatosensory spatial relationship tool

项目摘要

DESCRIPTION (provided by applicant): The efficiency of the brain is a measure of the degree to which the neural, metabolic, and vascular systems work together collectively to perform cerebral function. The coordination of physiological events between these systems, which collectively comprise a functional unit of the brain, is believed to be an important marker of brain fitness. Concurrent multimodal hemodynamic and electrophysiological measurements offer the unique ability to quantify these neurovascular relationships and thereby investigate the properties of the cerebral functional unit. In this project, we propose to develop novel multimodal experimental and model-based analysis tools to characterize the properties of the cerebral functional unit. We hypothesize that multimodal characterization of the relationships between neural, metabolic, and vascular changes will provide more robust and intrinsic assessments of the brain in comparison to autonomous (single- modality) measurements alone. We will develop an analysis framework based on a bottom-up model of the cerebral functional unit that will allow us to better utilize the unique attributes of concurrent multimodal measurements. Our model will be applied to simultaneous non-invasive, near-infrared optical imaging (NIRS) and magnetoencephalography (MEG) measurements in order to develop, test, and refine our methods based on the application of our model to a set of somatosensory experiments. The specific aims of this project are: Aim 1. Integrate optical and MEG imaging systems to allow for concurrent neurovascular measurements. We will improve existing instrumentation, hardware, and analysis framework, which will allow for collection and coregistration of concurrent near-infrared optical (NIRS) and MEG signals. Aim 2. Quantify the relationships between neural and hemodynamic evoked signals. Using a combination of visual and somatosensory stimulation paradigms with parametric inputs, we will experimentally investigate the canonical relationships between neural and vascular evoked responses. Aim 3. Develop the cerebral functional unit model. We will develop and characterize an integrated multimodal model of the cerebral functional unit to incorporate information from concurrent neural and vascular measurements. PUBLIC HEALTH RELEVANCE: Within a healthy brain, the neural, metabolic, and vascular systems are highly coupled to balance the use of energy by neural and synaptic processes and the supply of substrates and removal of waste products by the vascular system. While it is generally accepted that such coupling is important to the health of the brain, analysis and interpretation methods to investigate these effects have not been adequately developed to allow detailed characterization of these relationships. In particular, the utility of multimodal neuroimaging experiments can be improved by developing new analysis methodologies that are specific to the unique characteristics of concurrent multimodal measurements. We propose to develop a state-space model of the neural, metabolic, and vascular units of the brain that will allow us to statistically combine concurrent measurements from differing neuroimaging techniques, specifically near-infrared spectroscopy (NIRS) and magnetoencephalography (MEG), into a unified estimate of brain function. This model will provide a new tool to investigate and characterize the underlying relationships between neural, metabolic, and vascular physiology and will offer a novel framework for fusion of experimental multimodal information.

描述（由申请人提供）：大脑的效率是神经系统、代谢系统和血管系统共同工作以执行大脑功能的程度的衡量标准。这些系统共同构成大脑的一个功能单元，它们之间生理事件的协调被认为是大脑健康的重要标志。并行的多模式血流动力学和电生理学测量提供了量化这些神经血管关系的独特能力，从而研究大脑功能单元的特性。在这个项目中，我们建议开发新型多模态实验和基于模型的分析工具来表征大脑功能单元的特性。我们假设，与单独的自主（单模态）测量相比，神经、代谢和血管变化之间关系的多模态表征将为大脑提供更稳健和内在的评估。我们将开发一个基于大脑功能单元自下而上模型的分析框架，这将使我们能够更好地利用并发多模态测量的独特属性。我们的模型将应用于同时无创、近红外光学成像（NIRS）和脑磁图（MEG）测量，以便基于将我们的模型应用于一组体感实验来开发、测试和完善我们的方法。该项目的具体目标是：目标 1. 集成光学和 MEG 成像系统，以允许同时进行神经血管测量。我们将改进现有的仪器、硬件和分析框架，从而实现并发近红外光学 (NIRS) 和 MEG 信号的收集和共同配准。目标 2. 量化神经和血流动力学诱发信号之间的关系。将视觉和体感刺激范例与参数输入相结合，我们将通过实验研究神经和血管诱发反应之间的典型关系。目标 3. 开发大脑功能单元模型。我们将开发并表征大脑功能单元的集成多模态模型，以整合来自并发神经和血管测量的信息。公共健康相关性：在健康的大脑中，神经、代谢和血管系统高度耦合，以平衡神经和突触过程的能量使用以及血管系统的底物供应和废物清除。虽然人们普遍认为这种耦合对大脑的健康很重要，但研究这些影响的分析和解释方法尚未得到充分发展，无法详细描述这些关系。特别是，可以通过开发针对并发多模态测量的独特特征的新分析方法来提高多模态神经影像实验的实用性。我们建议开发大脑神经、代谢和血管单元的状态空间模型，这将使我们能够在统计上将不同神经成像技术（特别是近红外光谱（NIRS）和脑磁图（MEG））的并发测量结果组合成对大脑功能的统一估计。该模型将提供一种新工具来研究和表征神经、代谢和血管生理学之间的潜在关系，并将为实验多模态信息的融合提供一个新的框架。