权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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

基本信息

批准号：
10397243
负责人：
Anna I Blazejewska
金额：
$ 9.98万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-05-01 至 2022-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10397243
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 Feedback Functional Imaging Functional Magnetic Resonance Imaging General Hospitals Goals Gold 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 Weight area V1 area striata bioimaging brain circuitry career cerebral blood volume collaborative environment computer science density design experience experimental study extrastriate visual cortex histological specimens human data imaging facilities in vivo in vivo imaging indexing luminance medical schools monocular neuronal circuitry novel programs regional difference relating to nervous system response skills

项目摘要

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.

项目总结/文摘