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MICROSCOPIC FOUNDATION OF MULTIMODAL HUMAN IMAGING

多模态人体成像的微观基础

基本信息

批准号：
10220530
负责人：
ANDERS M DALE
金额：
$ 117.79万
依托单位：
BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-15 至 2022-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10220530
关键词：
Adoption Affect Animal Experimentation Animal Model Animals Automobile Driving Blood Vessels Blood flow Brain Cells Cerebrovascular Circulation Cerebrum Complex Computer Models Data Development Discipline Energy Metabolism Engineering Foundations Functional Magnetic Resonance Imaging Human Human Experimentation Image Imaging technology Institution Interneurons Knowledge Magnetoencephalography Measurement Metabolic Metabolism Methods Microscope Microscopic Modality Modeling Mus Neurons Neurosciences Pattern Physics Physiological Population Property Psychiatrist Psychologist Research Personnel Role Sensory Signal Transduction Somatosensory Cortex Technology Testing Time Translations Vasodilation Work base blood oxygen level dependent cell type computer framework computer science constriction cost dipole moment experimental study human imaging imaging genetics insight metabolic rate multimodality nano neuroimaging neuronal circuitry non-invasive imaging novel optical imaging optogenetics population based response simulation tool

项目摘要

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use noninvasive technologies. This is in contrast to animal models where a rich, detailed view on the cellular level brain function has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from human noninvasive signals. In the proposed project, we focus on the “Calibrated” Blood Oxygenation Level Dependent (BOLD) fMRI technology asking the questions: “Which aspects of the underlying neuronal activity can be reliably inferred from noninvasive cerebral blood flow (CBF) and Cerebral Metabolic Rate of O2 (CMRO2) observables?” and “What further information can be obtained from combining Calibrated BOLD with Magnetoencephalography (MEG)?” Our central hypothesis is that specific neuronal cell types have identifiable “signatures” in the way they drive changes in energy metabolism (CMRO2), blood flow (CBF) and contribute to macroscopic electrical signals (MEG current dipole dynamics). Because other factors may affect baseline flow and metabolism, our focus is on the evoked absolute CMRO2 and CBF changes associated with increased or decreased neuronal activity. We will perform parallel experiments in mice and humans to empirically connect the dots between the microscopic properties of brain's functional organization and their manifestation on the macroscopic level of noninvasive observables. Based on the experimental results, we will then develop a computational framework that will establish connections between scales and measurement modalities enabling robust estimation of the critical aspects of neuronal circuit activity from noninvasive measurements in humans. The proposed project will deliver a quantitative probe for neuronal activity of known cell types in human brain enabling a paradigm shift in human fMRI studies: from a simple mapping of fMRI signal change to the explicit estimation of the respective activity levels of specific neuronal cell types without confounding effects of the baseline state of flow and metabolism.

人脑的计算特性源于数十亿神经元之间复杂的相互作用