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”的中心目标是了解人类大脑回路的结构和功能。功能性磁共振成像（fMRI）具有实现这一目标的巨大潜力，然而，fMRI从根本上来说是一种间接测量神经元活动的方法——它通过测量局部神经元活动驱动的血流和氧合变化来评估大脑功能，并且还受到组织解剖结构（包括血管密度）的区域差异的影响。众所周知，大脑皮层由多个层组成，这些层作为大脑各区域连接的输入或输出，因此将fMRI信号定位到各个层将是破译人类大脑回路的关键。然而，皮层微观解剖结构在不同层间差异很大，这导致了一些偏差，这些偏差已经被证明会影响我们使用功能磁共振成像检测和定位层内活动的能力，从而阻碍了层流功能磁共振成像的解释和使用。我们的目标是表征和消除这些由于微观解剖学的局部差异而导致的fMRI信号偏差，以解决fMRI的这一基本限制，并更准确地将fMRI与神经元活动联系起来。我们将通过将人脑标本的组织学与先进的离体和体内成像相结合来实现这一目标，通过推导组织微结构和定量MRI之间的映射，然后纠正与组织微结构相关的fMRI信号偏差，开发一个增强fMRI神经元特异性的框架。候选人接受过物理和计算机科学方面的培训；具有高分辨率结构MRI的经验，以及将体内和离体MRI与组织学相关联的经验；并寻求实验神经科学方面的培训，以便成为该领域的独立研究人员。在指导阶段，她将利用视觉皮层区域的离体数据开发一个皮层内微观结构模型。她将测量体内血管密度，以绘制出fMRI信号偏差的额外来源，然后开发一个模型来预测体内皮层微观结构和fMRI反应，并通过使用广泛的采集参数进行fMRI实验来验证它。为了实现这些目标，候选人将在经验丰富的导师，层流显微解剖和功能磁共振成像先驱的指导下扩展她的知识，获得先进的超高场功能磁共振成像采集和数据分析的新技能。在此基础上，在独立阶段，她将把该模型应用于层流fMRI实验，以验证偏差校正。该项目将为候选人的长期职业目标做好准备，即建立一个研究项目，应用非侵入性功能成像技术，在定量组织特性分析的帮助下，研究人类大脑的电路。指导阶段将在哈佛医学院马萨诸塞州总医院的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备和世界一流的专家，可以进行指导/咨询。K99奖将促进该项目所需的培训和研究部分，以帮助候选人成为一名独立的研究人员。