Contribution of ultralow frequency LFPs to functional MRI

超低频 LFP 对功能 MRI 的贡献

• 批准号: 10159972
• 负责人: Shella D Keilholz
• 金额: $ 34.04万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-20 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10159972
• 关键词: Anesthesia procedures; Anesthetics; Area; Astrocytes; Brain; Brain Diseases; Cell Nucleus; Clinical; Cognition; Cognitive; Coma; Conscious; Data; Disease; Exhibits; Frequencies; Functional Magnetic Resonance Imaging; Generations; Homologous Gene; Human; Imaging Techniques; Investigation; Knowledge; Laws; Link; Mediating; Mental disorders; Methods; Modeling; Multimodal Imaging; Neurons; Neurosciences; Pathway Analysis; Pattern; Periodicity; Play; Process; Rattus; Reproducibility; Research; Rest; Rodent; Role; Sensitivity and Specificity; Signal Transduction; Sleep; Source; Specificity; Structure; System; Time; Work; base; blood oxygen level dependent; cognitive process; experimental study; functional MRI scan; improved; information processing; insight; interest; locus ceruleus structure; multimodality; nervous system disorder; neural circuit; neurophysiology; neuroregulation; non-invasive imaging; potential biomarker; relating to nervous system; spatiotemporal

Resting state functional magnetic resonance imaging (rs-fMRI) contains a wealth of information about the large-scale structure of neural activity in the brain, an area that has been relatively unexplored. Rs-fMRI has provided some insight into the macroscopic organization of brain activity by identifying functional networks that are reproducible across subjects. The functional networks are often interpreted as if they represent time- varying interactions between areas of the type that would be expected to arise from cognitive processes, but the same network structure can be found in conditions where cognition is suppressed or absent (sleep, coma, and anesthesia). This persistent network structure is one of the lingering puzzles in rs-fMRI. Our previous work has shown that large-scale spatiotemporal quasi-periodic patterns (QPPs) of electrical activity can be isolated from the BOLD signal, allowing us to separate slow, semi-periodic modulations from the more localized aperiodic activity that is expected to arise from cognition and information processing. This led us to hypothesize that the QPPs account for a persistent background pattern of neuromodulation, over which time-varying contributions from cognition and information processing are superimposed. Our preliminary data indicates that QPPs arise from a different type of brain activity than the neural activity linked to information processing and cognition but still account for a substantial portion of the functional connectivity in the brain. In Aim 1 , we extend our previous work to investigate the neurophysiological sources that play a role in QPP generation using multimodal imaging in the rat. Our working model is that the QPPs arise from localized input from subcortical nuclei that then propagates across the cortex through the coordinated actions of neurons and astrocytes. In humans, the QPPs are most dominant in the default mode network (DMN), a critical structure implicated in numerous functions and altered in many disorders. Our preliminary data shows that QPPs account for a substantial portion of the connectivity in the DMN. In Aim 2, we will compare functional network metrics throughout the brain before and after the QPPs are removed by regression to determine how the presence of the infraslow modulation impacts standard analysis. Our final aim directly examines the hypothesis that QPPs account for background activity over which time- varying activity more relevant to cognition is superimposed. We will calculate the relative contribution of QPPs to the BOLD signal as a function of anesthetic depth in rats, where we expect their contribution to increase as anesthetic depth increases, and during tasks with varying difficulty in humans, where we expect their relative contribution to decrease as a function of increasing cognitive demand. Taken together, the work in this proposal will change the way we interpret rs-fMRI by allowing separate examination of two distinct components of brain activity that may both be of clinical interest.

静息状态功能磁共振成像(rs-fmri)包含了丰富的信息。 大脑中神经活动的大规模结构，这是一个相对未被探索的领域。RS-fMRI显示 通过识别功能网络，提供了对大脑活动的宏观组织的一些见解 可在不同受试者之间重现。功能网络通常被解释为好像它们代表时间- 认知过程中可能产生的不同类型的区域之间的相互作用，但 在认知受到抑制或缺失的情况下(睡眠、昏迷和 麻醉)。这种持久的网络结构是RS-fMRI中挥之不去的谜团之一。我们之前的工作是 结果表明，电活动的大尺度时空准周期模式(QPP)可以从 粗体信号，允许我们将慢的、半周期的调制与更局部化的非周期调制分开 预期从认知和信息处理中产生的活动。这导致我们假设， QPP解释了神经调节的持续背景模式，在这种模式下，随着时间的变化 认知和信息处理的贡献是叠加的。我们的初步数据显示 QPP来自不同类型的大脑活动，而不是与信息处理相关的神经活动 和认知，但仍占大脑功能连接的很大一部分。在目标1中，我们 扩展我们以前的工作，研究在QPP生成中起作用的神经生理学来源 大鼠的多模式成像。我们的工作模型是QPP来自皮质下的局部性输入 然后，通过神经元和星形胶质细胞的协调行动，细胞核在大脑皮层中传播。 在人类中，QPP在默认模式网络(DMN)中占主导地位，这是一种关键结构 牵涉到许多功能，并在许多紊乱中改变。我们的初步数据显示，QPP 占DMN中连接性的很大一部分。在目标2中，我们将比较功能网络 通过回归分析去除QPP前后整个大脑的指标，以确定 次流调制的存在会影响标准分析。 我们的最终目标直接检验QPP解释背景活动的假设，在这段时间内- 与认知更相关的不同活动叠加在一起。我们将计算QPP的相对贡献 对大鼠的BOLD信号作为麻醉深度的函数，我们预计它们的贡献将增加为 麻醉深度增加，在人类不同难度的任务中，我们预计他们的相对 作为认知需求增加的函数，对减少的贡献。综上所述，这项工作 该提案将改变我们解释RS-FMRI的方式，允许对两个不同的 可能同时具有临床意义的脑部活动成分。