Understanding evoked and resting-state fMRI through multi scale imaging

通过多尺度成像了解诱发和静息态 fMRI

• 批准号: 9205912
• 负责人: R Todd Constable
• 金额: $ 107.32万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-16 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9205912
• 关键词: Animal Experiments; Animal Model; Animals; Area; Autistic Disorder; Bioinformatics; Biological; Biomedical Engineering; Blood flow; Brain; Brain imaging; Cells; Communication; Complement; Data; Data Analyses; Data Set; Development; Dimensions; Disease; Ensure; Equilibrium; Fingers; Fluorescence; Functional Magnetic Resonance Imaging; Gold; Human; Image; Imaging Device; Imaging Techniques; Knock-out; Label; Lesion; Link; Measures; Mental Depression; Metabolic; Methodology; Methods; Microscopic; Modality; Modeling; Molecular Biology; Motor; Mus; Names; Nature; Neuroglia; Neurological Models; Neurons; Physiological; Population; Post-Traumatic Stress Disorders; Property; Resolution; Rest; Rodent; Role; Scientist; Sensory; Signal Transduction; Source; System; Techniques; Testing; Therapeutic Intervention; Time; Transgenic Mice; Vibrissae; Work; animal data; base; blood oxygen level dependent; calcium indicator; cell type; cellular imaging; cognitive task; control theory; data modeling; design; excitatory neuron; genetic manipulation; graph theory; human data; human subject; improved; inhibitory neuron; insight; mouse model; multidisciplinary; network models; novel; novel strategies; optogenetics; predictive modeling; relating to nervous system; research study; response; spatiotemporal; temporal measurement; theories; two-photon

Project Summary This RFA is aimed at bringing together interdisciplinary teams to focus on novel, transformative and integrative efforts that will revolutionize our understanding of the biological and bioinformatics content of the data collected from non-invasive human functional brain imaging techniques. Our proposal does exactly this. We are a multidisciplinary team of scientists with combined expertise in optogenetics, two photon Ca2+ imaging, biomedical engineering, molecular biology, animal and human fMRI, network theory, data analysis and modeling. In this work, we will use a novel imaging device that combines mesoscopic imaging of genetically encoded Ca2+ indicators with very high (50m) spatial and high temporal (25ms) resolution across the entire cortex and simultaneous fMRI in transgenic mouse models. These animal experiments are designed to complement similar experiments in healthy human subjects. The results from the animal experiments will answer several long-standing questions about the source of the fMRI signal. Specifically, using imaging, we will quantify the contributions of different cell populations (excitatory neurons, inhibitory neurons, and glial cells) to the fMRI signal observed. We will be able to test and validate, for the first time, the application of graph theory approaches to the analysis of human fMRI data, and we will develop and test a new approach based on control theory for extracting more information from the fMRI signal. A powerful set of carefully controlled imaging experiments in mice will inform several aspects of analysis of human data. The human data will contain a test/retest component to ensure replication of the results and to allow predictive models to be built in one data set and tested in another. This work truly bridges scale and modalities and the simultaneous nature of the animal experiments will allow unprecedented clarity on the underlying source of the signal changes observed in fMRI. These animal studies are essential for providing new insights into the basis of human fMRI signals and data of this nature has not previously been available. The work in this proposal is novel in that it will directly inform measures of both evoked and spontaneous activity in terms of the underlying cell signal sources revealing the relative contributions of excitatory, inhibitory and glial cells to the fMRI signal. The implications of the work are multifaceted. This work will provide a platform for evaluating neurological models of disease. For example, mouse models of disease can be used to link to human data in diseases such as PTSD, depression, and autism, to name a few. It will also provide a firmer biological basis for understanding the node and network measures used in assessing the functional organization of the brain and will have important implications for the design of therapeutic interventions across a range of diseases.

项目概要 本次 RFA 旨在汇聚跨学科团队，专注于新颖、变革性和综合性的研究 这将彻底改变我们对所收集数据的生物和生物信息学内容的理解努力 我们的建议正是通过非侵入性人类功能性大脑成像技术来实现的。 多学科科学家团队结合光遗传学、双光子 Ca2+ 成像、 生物医学工程、分子生物学、动物和人类功能磁共振成像、网络理论、数据分析和 在这项工作中，我们将使用一种结合了遗传介观成像的新型成像设备。 编码的 Ca2+ 指示剂在整个过程中具有非常高 (50μm) 的空间和高时间 (25ms) 的分辨率 这些动物实验旨在研究转基因小鼠模型中的皮质和同步功能磁共振成像。 动物补体实验的结果将在健康人类受试者中进行类似的实验。 具体来说，我们使用成像来回答有关功能磁共振成像信号源的几个长期存在的问题。 将量化不同细胞群（兴奋性神经元、抑制性神经元和神经胶质细胞）的贡献 我们将能够首次测试和验证图的应用。 人类功能磁共振成像数据分析的理论方法，我们将开发和测试一种基于 用于从功能磁共振成像信号中提取更多信息的一组强大的精心控制的控制理论。 小鼠成像实验将为人类数据分析的几个方面提供信息。 包含测试/再测试组件，以确保结果的复制并允许内置预测模型 这项工作真正弥合了规模和模式以及同时性。 动物实验将使信号变化的根本来源变得前所未有的清晰 这些动物研究对于提供人类功能磁共振成像基础的新见解至关重要。 该提案中的工作的新颖之处在于它以前没有提供过这种性质的信号和数据。 将直接根据底层细胞信号来测量诱发和自发活动 揭示兴奋性细胞、抑制性细胞和神经胶质细胞对功能磁共振成像信号的相对贡献的来源。 这项工作的意义是多方面的。这项工作将为评估神经模型提供一个平台。 例如，小鼠疾病模型可用于链接到人类疾病数据，例如 仅举几例，它还将为理解创伤后应激障碍、抑郁症和自闭症提供更坚实的生物学基础。 用于评估大脑功能组织的节点和网络测量，并将具有 对一系列疾病的治疗干预措施的设计具有重要意义。