Contribution of Ultra Low Frequency LFPs to Functional MRI

超低频 LFP 对功能 MRI 的贡献

• 批准号: 8546457
• 负责人: Shella D Keilholz
• 金额: $ 31.54万
• 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 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8546457
• 关键词: Affect; Anesthetics; Attention; Attention deficit hyperactivity disorder; Behavioral; Brain; Clinical; Coupled; Coupling; Data; Dexmedetomidine; Disease; Electroencephalography; Employee Strikes; Frequencies; Functional Magnetic Resonance Imaging; Goals; Human; Image; Individual; Isoflurane; Lead; Link; Location; Magnetic Resonance Imaging; Maps; Measures; Membrane Potentials; Methods; Network-based; Patients; Pattern; Performance; Physiological; Property; Protocols documentation; Rattus; Reaction Time; Reporting; Resolution; Rest; Rodent; Signal Transduction; Site; Spatial Distribution; Stimulus; Time; Variant; awake; base; blood oxygen level dependent; diagnosis evaluation; improved; insight; relating to nervous system; research study; slow potential; spatiotemporal; tool; vasomotion

DESCRIPTION (provided by applicant): Resting state MRI (rsMRI), based on fluctuations in the blood oxygenation level dependent (BOLD) signal, is increasingly used to map networks of spontaneous activity in the brain. The neural basis of these fluctuations is not well understood, with various studies reporting a link to low frequency power, high frequency power, modulation of spiking, and vasomotion. While the frequency range of the BOLD fluctuations is 0-0.1 Hz, previous studies have examined electrical activity in higher frequency bands (>1 Hz). It is known, however, that infra-slow oscillations (IFSOs; <1 Hz) exist in the brain and they have been linked to fluctuations in attentional control and reaction time in normal subjects and ADHD patients. We hypothesize that the BOLD fluctuations have a direct link to electrical fluctuations in the same frequency band, and that the modulation of higher frequencies by these slower oscillations leads to state-dependent relationships with the BOLD signal. 1. Determine the relationship between infra-slow potential fluctuations and activity in typical LFP bands (1-100 Hz). IFSOs and broadband local field potentials (LFPs) will be recorded from a network of cortical and subcortical sites to determine the spatial distribution of IFSOs and how they affect local activity. Simultaneous IFSO and intracellular recording will examine whether membrane potential changes are tied to low frequency oscillations. Different anesthetic states will modulate neural activity. 2. Characterize the contribution of IFSOs to the BOLD signal on a site-by-site and network basis. No studies have looked at the direct frequency correlates of the low frequency BOLD fluctuations. Preliminary data suggests that patterns of IFSOs can be mapped using MRI. Using a simultaneous recording/imaging protocol developed in our lab, we will obtain LFPs (broadband and infra-slow) and BOLD from sites selected from the network examined in aim 1. Correlation between LFPs and local BOLD signal will be performed to determine the largest contribution to BOLD fluctuations, while coherence between band-limited LFPs and BOLD correlation will be compared to identify the best predictors of BOLD correlation. 3. Examine the spatiotemporal dynamics of IFSOs and determine their link to quasi-periodic BOLD fluctuations. Preliminary data indicates that the time-lagged correlation between BOLD and IFSOs demonstrates a pattern of propagation along the cortex that is highly similar to the spatiotemporal dynamics previously observed with the BOLD signal. This aim will directly examine the link between BOLD and IFSO dynamics using the simultaneously-acquired multi-site data collected for aims 1 and 2. This project will provide unique insight into the network activity that underlies functional connectivity maps created with MRI and, if our hypothesis proves correct, will lead to a new way to map the spatiotemporal patterns of the infra-slow activity that modulates attention throughout the whole brain with resolution unobtainable with electroencephalography.

描述（由申请人提供）：静息状态MRI（rsMRI）基于血氧水平依赖（BOLD）信号的波动，越来越多地用于绘制大脑中自发活动的网络。这些波动的神经基础还不清楚，各种研究报告与低频功率，高频功率，尖峰调制和血管运动有关。虽然BOLD波动的频率范围是0-0.1 Hz，但以前的研究已经检查了更高频段（>1 Hz）的电活动。然而，众所周知，超慢振荡（IFSO; <1 Hz）存在于大脑中，并且它们与正常受试者和ADHD患者的注意力控制和反应时间的波动有关。我们假设，BOLD波动有一个直接的联系，在同一频带的电波动，和较高的频率调制这些较慢的振荡导致状态依赖关系的BOLD信号。1.确定亚慢电位波动与典型LFP频段（1-100 Hz）活动之间的关系。IFSO和宽带局部场电位（LFP）将从皮层和皮层下的网站网络记录，以确定IFSO的空间分布以及它们如何影响局部活动。同时IFSO和细胞内记录将检查膜电位变化是否与低频振荡有关。不同的麻醉状态将调节 神经活动2.在逐站点和网络的基础上描述IFSO对BOLD信号的贡献。没有研究着眼于低频BOLD波动的直接频率相关性。初步数据表明，IFSO的模式可以使用MRI进行映射。使用我们实验室开发的同步记录/成像协议，我们将从目标1中检查的网络中选择的站点获得LFP（宽带和超慢）和BOLD。将执行LFP与局部BOLD信号之间的相关性以确定对BOLD波动的最大贡献，而将比较带限LFP与BOLD相关性之间的相干性以识别BOLD相关性的最佳预测因子。3.检查IFSO的时空动态，并确定其与准周期BOLD波动的联系。初步数据表明，BOLD和IFSO之间的时滞相关性展示了一种沿皮层沿着传播的模式，该模式与先前用BOLD信号观察到的时空动态非常相似。这一目标将利用为目标1和2收集的多站点数据，直接审查BOLD与IFSO动态之间的联系。该项目将提供独特的洞察网络活动的基础功能连接地图创建与MRI，如果我们的假设被证明是正确的，将导致一种新的方式来映射时空模式的超慢活动，调节整个大脑的注意力与分辨率无法获得脑电图。