Relating functional MRI to neuronal activity: accounting for effects of microarchitecture

将功能 MRI 与神经元活动联系起来：解释微结构的影响

• 批准号: 10677777
• 负责人: Anna I Blazejewska
• 金额: $ 24.9万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10677777
• 关键词: Accounting; Address; Affect; Anatomy; Animals; Area; Atlases; Award; BRAIN initiative; Back; Blood; Blood Vessels; Blood flow; Brain; Brain region; Cell Nucleus; Cerebral cortex; Cerebrum; Characteristics; Consultations; Contrast Media; Data; Data Analyses; Experimental Designs; Face; Feedback; Functional Imaging; Functional Magnetic Resonance Imaging; General Hospitals; Goals; Heme; Histologic; Histology; Human; Image; Imaging Techniques; Individual; Investigation; Iron; Knowledge; Magnetic Resonance Imaging; Maps; Masks; Massachusetts; Measurement; Measures; Mentors; Methodology; Methods; Microanatomy; Modeling; Myelin; Neocortex; Neurons; Neurosciences; Output; Pathway interactions; Phase; Physics; Property; Research; Research Personnel; Resolution; Role; Signal Transduction; Source; Specificity; Specimen; Stains; Stimulus; Structure; System; Techniques; Technology; Testing; Tissue Model; Tissues; Training; Variant; Visual Cortex; area striata; biomedical imaging; brain circuitry; career; cerebral blood volume; collaborative environment; computer science; density; experience; experimental study; extrastriate visual cortex; histological specimens; human data; imaging facilities; in vivo; in vivo imaging; indexing; luminance; medical schools; millimeter; monocular; neural; neuronal circuitry; novel; programs; regional difference; response; skills

The central goal of the BRAIN Initiative is to understand the structure and function of human brain circuits. Functional magnetic resonance imaging (fMRI) has great potential to achieve this goal, however fMRI is fundamentally an indirect measure of neuronal activity—it assesses brain function through the measurement of changes in blood flow and oxygenation driven by local neuronal activity, and is also influenced by regional differences in tissue anatomy including vascular density. The cerebral cortex consists of layers that are well- known to serve as inputs or outputs for the connections across brain regions, and so localizing fMRI signals to individual layers will be key to deciphering brain circuitry in humans. However, the cortical microanatomy varies dramatically across layers, introducing biases that have been demonstrated to confound our ability to detect and localize activity within layers with fMRI, and therefore to hinder the interpretation and use of laminar fMRI. Our aim is to characterize and remove these fMRI signal biases due to local differences in microanatomy, in order to address this fundamental limitation of fMRI and to more accurately relate fMRI to neuronal activity. We will achieve this goal by combining histology of human brain specimens with advanced ex vivo and in vivo imaging to develop a framework for enhancing fMRI neuronal specificity—through deriving a mapping between tissue microarchitecture and quantitative MRI, and then correcting fMRI signal bias related to tissue microstructure. The candidate is trained in physics and computer science; has experience in high-resolution structural MRI and in correlating in vivo and ex vivo MRI with histology; and seeks training in experimental neuroscience in order to become an independent researcher in this field. During the mentored phase, she will develop a model of intracortical microstructure using ex vivo data from regions of visual cortex. She will measure vascular density in vivo to map out this additional source of fMRI signal bias, then develop a model to derive predictions of cortical microstructure and fMRI responses in vivo, and validate it through an fMRI experiment using a wide range of acquisition parameters. To achieve these goals, the candidate—with guidance from the experienced mentors, the pioneers of laminar microanatomy and fMRI—will extend her knowledge, gain new skills in advanced ultra- high-field fMRI acquisition and data analysis. Building on this, in the independent phase she will apply the model to laminar fMRI experiments designed to validate the bias correction. This project will prepare the candidate for her long-term career goal of establishing a research program applying non-invasive functional imaging techniques, with aid of quantitative tissue property analyses, to study the circuitry of the human brain. The mentored phase will be carried out at the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, a highly collaborative environment with state-of-the-art imaging facilities and world-class experts available for mentoring/consultation. The K99 award will facilitate the required training and research components of this project to aid the candidate in becoming an independent researcher.

大脑计划的核心目标是了解人脑电路的结构和功能。功能磁共振成像（fMRI）具有实现此目标的巨大潜力，但是fMRI从根本上是对神经元活动的间接测量 - 它通过测量局部神经元活性驱动的血流变化和氧合作用，评估脑功能，并且也受到包括血流术（包括血管造口）的组织差异的影响。大脑皮层由众所周知的层组成，这些层是跨大脑区域连接的输入或输出的层，因此将fMRI信号定位到各个层将是破译人类脑电路的关键。然而，皮质微解剖学在各个层之间范围很大，引入了偏见，这些偏见被证明是为了混淆我们检测和将活性定位在层中的能力，因此会阻碍层状flaminar fMRI的解释和使用。我们的目的是表征和消除由于微解剖学的局部差异而导致的这些fMRI信号偏见，以解决fMRI的基本限制以及与神经元活动更准确相关的fMRI。我们将通过将人脑规范的组织学与先进的离体和体内成像相结合，从而开发出增强fMRI神经元特异性的框架 - 通过得出组织微结构和定量MRI的映射，然后纠正与组织微结构相关的FMRI信号偏见。候选人接受了物理和计算机科学的培训；具有高分辨率结构MRI的经验以及在体内和Ex Vivo MRI与组织学相关的经验；并寻求实验性神经科学的培训，以便成为该领域的独立研究人员。在修改阶段，她将开发一种物质内微观结构模型。使用来自Visual Cortex区域的离体数据。她将在体内测量血管密度，以绘制出fMRI信号偏置的额外来源，然后开发一个模型，以在体内预测皮质微观结构和fMRI响应的预测，并通过使用广泛的采集参数通过fMRI实验对其进行验证。为了实现这些目标，候选人（在经验丰富的导师，层状微型解剖学和fMRI的开拓者的指导下）将扩大她的知识，并在先进的超高现场fMRI获取和数据分析方面获得新技能。在此基础上，在独立阶段，她将将该模型应用于旨在验证偏置校正的层流fMINAR实验。该项目将为她的长期职业生涯目标做好准备，以建立一项研究计划，该研究计划在定量组织特性分析的帮助下，采用非侵入性功能成像技术，以研究人脑的电路。指导阶段将在马萨诸塞州综合医院，哈佛医学院的Athinoula A. Martinos生物医学成像中心进行，这是一个高度协作的环境，拥有最先进的成像设施和世界一流的专家，可用于心理/咨询。 K99奖将促进该项目所需的培训和研究组成部分，以帮助候选人成为独立的研究人员。