Biophysical Basis of Functional Connectivity by MRI

摘要/摘要 这是我们的项目“静息态连接的生物物理基础的磁共振成像”的第一次竞争性更新。 我们的目标是确定MRI(RsfMRI)静息状态波动的区域间相关性 来自大脑的信号可靠地测量大脑区域之间的功能连接(RsFC)，并建立 核磁共振数据如何与其他连接性指标相关联。这些目标与验证直接相关 以及解释人类对rsfMRI的应用。到目前为止进行的研究主要集中在介观方面。 在初级躯体感觉皮质(S1)明确定义的功能区内的尺度网络(100微米-10毫米) 在非人类灵长类动物中，我们可以高分辨率测量静息状态关联的空间模式 并用电生理信号和解剖示踪剂验证它们的解释。在下一阶段，我们 目的扩展这些研究以进一步确定rsFC测量的起源和意义。 大脑皮质呈层状结构，但对rsFC的层状分布知之甚少。在……里面 此外，rsfMRI相关性的强推论是否直接代表了功能连通性 超越了S1中子区域的细粒度级别，扩展到更宏观的维度 未被开发的。此外，最近对rsfmri相关性明显缓慢变化的研究表明，静息状态 状态本身表现出可能具有重要功能的动态变化。因此，我们提出三点建议 具体目标：[1]通过测量rsfMRI信号的连接模式来确定rsfc的起源 在S1、S2亚区、丘脑和相应对侧区的皮质层之间。我们 将在9.4T下使用振动触觉刺激获取fMRI数据，以确定功能不同的候选区域 双侧S1、S2和丘脑的激活，并测量体内和丘脑中体素之间的静息状态相关性 跨越这些区域的各层：[2]以测量选择性剥夺脊髓、丘脑、皮质的效果 以及rsfMRI上的大脑半球间输入，并演示它们与行为的关系：[3]以验证 用直接与定量比较的方法测量正常和无输入条件下的rsFC信号 颅内电生理学和组织学。我们将获得rsfMRI和侵入性多电极测量 以定量比较神经活动和解剖连接的不同指标。 我们将从猴脑获取9.4T的fMRI数据，以研究SI、SII和 丘脑。我们将使用创新的数学分析来量化静息状态关联中的变化 以及这些模式是否符合电生理相关性的缓慢变化。我们会 在相同的动物身上进行侵入性多通道微电极阵列测量，这样我们就可以 定量比较神经活动和解剖连接的不同度量。我们相信， 所提出的研究对于验证静息状态功能的神经基础具有相当重要的意义 连接测量，并对人类功能磁共振研究及其应用具有直接影响。

SUMMARY / ABSTRACT This is a 1st competitive renewal of our project “Biophysical Basis of Resting State Connectivity by MRI”. Our goals are to determine whether inter-regional correlations in resting state fluctuations of MRI (rsfMRI) signals from the brain reliably measure functional connectivity (rsFC) between brain regions, and to establish how MRI data correlate with other metrics of connectivity. These goals are directly relevant for the validation and interpretation of human applications of rsfMRI. Studies performed to date have focused on mesoscopic scale networks (100µm - 10mm) within a well defined functional region of primary somatosensory cortex (S1) in non-human primates, where we can measure spatial patterns of resting state correlations at high resolution and validate their interpretation with electrophysiological signals and anatomic tracers. In the next phase, we aim to expand these studies to further establish the origins and significance of rsFC measurements. Cerebral cortex exhibits a laminar structure, but the laminar distribution of rsFC is poorly understood. In addition, whether the strong inference that rsfMRI correlations directly represent and link functional connectivity extends beyond the fine-grained level of sub-regions in S1 to more macroscopic dimensions remains unexplored. Moreover, recent studies of apparent slow variations of rsfMRI correlations suggest that the resting state itself exhibits dynamic variations that may be of functional importance. We therefore propose three specific aims: [1] to identify the origins of rsFC by measuring the connectivity patterns of rsfMRI signals across and between cortical layers in sub-regions of S1, S2, thalamus and corresponding contralateral regions. We will acquire fMRI data at 9.4T using vibrotactile stimuli to identify functionally distinct candidate areas of activation in bilateral S1, S2, and thalamus, and measure resting state correlations between voxels within and across layers in these regions: [2] to measure the effects of selective deprivation of spinal, thalamic, cortical and inter-hemispheric inputs on rsfMRI and demonstrate their relationships to behavior: [3] to validate measurements of rsFC signals in normal and input-deprived conditions by direct comparisons with quantitative intracranial electrophysiology and histology. We will acquire rsfMRI and invasive multi-electrode measurements in the same animals to quantitatively compare different metrics of neural activity and anatomical connections. We will acquire fMRI data at 9.4T from monkey brain to study functionally distinct areas in SI, SII, and thalamus. We will use innovative mathematical analyses to quantify variations in resting state correlations across time and whether these patterns agree with slow variations in electrophysiological correlations. We will perform invasive multichannel microelectrode array measurements in the same animals so that we can quantitatively compare different metrics of neural activity and anatomical connections. We believe that the proposed studies have considerable importance for validating the neural basis of resting state functional connectivity measures, and have direct implications for human fMRI studies and their applications.