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.

BRAIN Initiative的核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）有很大的潜力，以实现这一目标，然而，fMRI基本上是一个间接的神经元活动的测量，它评估大脑功能，通过测量的变化，血流和氧合驱动的局部神经元活动，也受到影响的组织解剖结构，包括血管密度的区域差异。大脑皮层由众所周知的层组成，这些层作为跨大脑区域连接的输入或输出，因此将功能磁共振成像信号定位到各个层将是破译人类大脑回路的关键。然而，皮质的显微解剖结构在各层之间变化很大，引入的偏见已被证明混淆了我们用fMRI检测和定位层内活动的能力，因此阻碍了层状fMRI的解释和使用。我们的目的是表征和消除这些fMRI信号的偏见，由于局部差异的显微解剖，以解决这个根本的限制，fMRI和更准确地将fMRI神经元活动。我们将实现这一目标，结合先进的离体和体内成像的人脑标本的组织学，以开发一个框架，通过组织微结构和定量MRI之间的映射，然后校正与组织微结构相关的fMRI信号偏差，以提高功能磁共振成像神经元特异性。候选人接受过物理学和计算机科学方面的培训;具有高分辨率结构MRI以及体内和体外MRI与组织学相关的经验;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，她将使用来自视觉皮层区域的离体数据开发皮质内微结构模型。她将在体内测量血管密度，以绘制出fMRI信号偏差的额外来源，然后开发一个模型，以获得皮质微观结构和fMRI反应的预测在体内，并通过使用广泛的采集参数的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，椎板显微解剖学和fMRI的先驱的指导下扩展她的知识，获得先进的超高场fMRI采集和数据分析的新技能。在此基础上，在独立阶段，她将应用该模型的层状功能磁共振成像实验设计，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，即建立一个应用非侵入性功能成像技术的研究项目，并借助定量组织特性分析来研究人脑的电路。指导阶段将在Athinoula A进行。Martinos生物医学成像中心，马萨诸塞州总医院，哈佛医学院，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，可提供指导/咨询。K99奖将促进该项目所需的培训和研究部分，以帮助候选人成为独立的研究人员。