The role of brain arousal in resting-state functional MRI

大脑唤醒在静息态功能 MRI 中的作用

• 批准号: 10252780
• 负责人: Xiao Liu
• 金额: $ 34.93万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10252780
• 关键词: Affect; Area; Arousal; Base of the Brain; Behavior; Behavioral; Big Data; Brain; Brain Diseases; Cardiac; Clinical Research; Cognitive; Data; Data Analyses; Event; Functional Magnetic Resonance Imaging; Functional disorder; Future; Goals; Head; Human; Imaging Device; Individual Differences; Knowledge; Lead; Link; Maps; Measurement; Measures; Mediating; Motion; Motor; Neurosciences Research; Noise; Outcome; Patients; Physiological; Physiology; Population; Positioning Attribute; Public Health; Regulation; Research; Research Personnel; Research Project Grants; Rest; Risk; Role; Sensory; Signal Transduction; Time; Work; base; behavior measurement; connectome; experience; experimental study; functional magnetic resonance imaging/electroencephalography; imaging study; improved; innovation; insight; interest; neuroimaging; neurophysiology; novel; relating to nervous system; respiratory; spatiotemporal; tool; trait

Project Summary Resting-state functional magnetic resonance imaging (rsfMRI) is being widely used to measure functional connectivity and dynamics of large-scale brain networks in both healthy subjects and patient groups, despite the neural bases of rsfMRI-based connectivity/dynamics measures remain largely unclear. Converging evidence has suggested the contributions from arousal-related factors given large rsfMRI changes seen across distinct brain states, however, a systemic understanding of the role of arousal factors in rsfMRI research is missing. The lack of this knowledge hampers the correct interpretation and proper use of rsfMRI-based measures of brain connectivity and dynamics. To bridge this critical gap, the major goal of this application is to develop an arousal measure based on spatiotemporal fMRI dynamics and then use it to elucidate and control for the influences of the arousal on rsfMRI-based measures of brain connectivity and dynamics. The research objective will be achieved through three specific aims. Aim 1 is to map spatiotemporal fMRI dynamics associated with a recently discovered event of arousal modulation and utilize this information to improve fMRI-based arousal measure. The working hypothesis is that transient arousal modulations are associated with a specific sequence of fMRI activations, and this spatiotemporal dynamic can be utilized to greatly improve fMRI-based arousal measurements. Aim 2 is to assess the contribution of arousal-related fMRI changes to the relationship between rsfMRI connectivity and non-neuronal signals, including physiological signals and head motions. It is hypothesized that the arousal modulation mediates spurious relationships between rsfMRI connectivity and the non-neuronal noise. In Aim 3, the contributions of arousal factors to rsfMRI-based quantifications of brain dynamics and their correlations with behavioral measures will be assessed. The working hypothesis is that the arousal effects on rsfMRI dynamics can be decomposed into the “state” and “trait” effects that have preferential impacts on the sensory/motor brain areas and higher-order cognitive networks respectively. The arousal “trait” related to intrinsic individual difference in arousal regulation mediates a part of correlations between certain aspects of rsfMRI dynamics and human behavior. The proposed research is innovative because it will combine local experiments and big data analyses to systemically study the direct effect of arousal modulations on rsfMRI connectivity and dynamics, as well as indirect effects of mediating their correlations with physiology and behavior. It will also focus on spatiotemporal brain dynamics at transient arousal modulations and utilize this information for an fMRI-based arousal measure. The impact of this research is significant because a clear understanding of the effects of the arousal on rsfMRI-based connectivity/dynamics measures is critical for proper interpretation and correct use of these metrics. An accurate fMRI-based arousal measure is not only important for controlling the arousal effects and thus improve rsfMRI-based quantifications but also for future neuroimaging studies that are interested in the arousal and its role in various brain diseases.

项目摘要 静息态功能磁共振成像（rsfMRI）被广泛用于测量 健康受试者和患者群体中大规模脑网络的功能连接和动力学， 尽管基于rsfMRI的连接性/动力学测量的神经基础在很大程度上仍不清楚。会聚 有证据表明，觉醒相关因素的贡献给出了大的rsfMRI变化， 不同的大脑状态，然而，在rsfMRI研究中对唤醒因素的作用的系统理解是 失踪了缺乏这方面的知识阻碍了正确的解释和正确使用基于rsfMRI的 测量大脑的连通性和动力学。为了弥合这一关键差距，该应用程序的主要目标是 开发一种基于时空功能磁共振成像动力学的唤醒测量方法，然后用它来阐明和控制 唤醒对基于rsfMRI的大脑连接和动力学测量的影响。研究 将通过三个具体目标实现这一目标。目的1是映射时空fMRI动力学相关 与最近发现的唤醒调制事件，并利用这些信息来改善基于fMRI的 唤醒测量。工作假设是，短暂的唤醒调制与特定的 fMRI激活序列，这种时空动态可以用来大大提高基于fMRI的 唤醒测量。目的2是评估觉醒相关的fMRI改变对关系的贡献 rsfMRI连接和非神经元信号之间的关系，包括生理信号和头部运动。是 假设唤醒调制介导rsfMRI连接性和脑缺血之间的虚假关系， 非神经元噪声在目标3中，唤醒因素对基于rsfMRI的脑定量的贡献 将评估动力学及其与行为测量的相关性。工作假设是， 唤醒对rsfMRI动态的影响可以分解为具有优先性的“状态”和“特质”效应。 分别对感觉/运动脑区和高阶认知网络产生影响。唤醒“特质” 与唤醒调节中的内在个体差异有关， rsfMRI动力学和人类行为的方面。这项研究是创新的，因为它将联合收割机 局部实验和大数据分析，系统研究唤醒调制对rsfMRI的直接影响 连接和动态，以及介导其与生理和 行为它也将集中在时空脑动力学在瞬态唤醒调制和利用这一点 基于功能磁共振成像的唤醒测量的信息。这项研究的影响是重大的，因为一个明确的 了解觉醒对基于rsfMRI的连接/动力学测量的影响对于 正确解释和正确使用这些指标。一个准确的基于功能磁共振成像的唤醒测量不仅是 这对于控制唤醒效应并因此改善基于rsfMRI的定量以及未来的 神经影像学研究，对唤醒及其在各种脑部疾病中的作用感兴趣。