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

项目总结/摘要 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）具有实现这一目标的巨大潜力，但fMRI 从根本上说，这是一种间接测量神经元活动的方法，它通过测量 血流和氧合的变化由局部神经元活动驱动，也受局部神经元活动的影响。 包括血管密度在内的组织解剖学差异。大脑皮层由多层结构组成- 作为大脑区域之间连接的输入或输出，因此定位功能磁共振成像信号， 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 戏剧性地跨层，引入偏见，已被证明混淆我们的能力，检测和 局部活动层内的功能磁共振成像，因此阻碍解释和使用层状功能磁共振成像。我们 目的是表征和消除这些由于显微解剖结构局部差异而引起的fMRI信号偏差， 解决了功能磁共振成像的这一基本局限性，并更准确地将功能磁共振成像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 开发一个框架来增强功能磁共振成像神经元的特异性--通过导出组织之间的映射， 微结构和定量MRI，然后校正与组织微结构相关的fMRI信号偏差。 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的经验， 将体内和体外MRI与组织学相关联;并寻求实验神经科学方面的培训， 成为该领域的独立研究者。在指导阶段，她将开发一个模型， 使用来自视觉皮层区域的离体数据的皮层内微结构。她会测量血管密度 在体内绘制出这个额外的fMRI信号偏差的来源，然后开发一个模型来预测皮质 微观结构和fMRI反应在体内，并通过fMRI实验验证它使用了广泛的 采集参数为了实现这些目标，候选人在经验丰富的导师的指导下， 层流显微解剖学和fMRI的先驱，将扩大她的知识，获得先进的超， 高场fMRI采集和数据分析。在此基础上，在独立阶段，她将应用该模型 旨在验证偏差校正的层状功能磁共振成像实验。该项目将准备候选人 她的长期职业目标是建立一个应用非侵入性功能成像的研究项目， 技术，借助定量组织特性分析，来研究人脑的电路。的 指导阶段将在Athinoula A进行。马萨诸塞州马蒂诺斯生物医学成像中心 总医院，哈佛医学院，一个高度协作的环境与国家的最先进的成像 设施和世界一流的专家提供指导/咨询。K99奖将促进所需的 该项目的培训和研究部分，以帮助候选人成为一名独立的研究人员。

Project Summary/Abstract 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.