Understanding overlap in resting state fMRI networks at the single cell level: a cross-species approach

在单细胞水平上理解静息状态fMRI网络的重叠：跨物种 方法 摘要 静息状态功能连接性磁共振成像(RsfcMRI)是一种常用的内在性研究工具。 将大脑的功能组织成大规模的网络。多条不同的线路 调查表明，紧密相连的“枢纽”区域对于 认知和行为。然而，这些集线器中蜂窝电路的功能架构 地区是未知的。为了研究中枢区域的细胞基础，我们汇集了一个 跨学科研究团队，跨越物种和规模。我们一开始就是 总结人类跨物种功能磁共振成像分析的最新进展以表征 清醒猕猴rsfcMRI数据中网络重叠的个性化模式(AIM 1)。这使我们能够从中枢识别同一动物的记录感兴趣的区域 两个(或更多)网络在空间上重叠的区域，以及来自 分别只对其中一个网络做出重大贡献。然后我们问，是否在一个更好的 细胞尺度，在中枢区域的两个网络之间存在真正的神经耦合，或者 在rsfcMRI数据的分辨率上看起来空间重叠的网络实际上在空间上是重叠的 在更精细的尺度上交错而不是重叠(目标2)。最后，我们使用电生理学 记录以确定中枢区域的单个神经元是否整合了来自 两个重叠的网络(即耦合)，或者神经元是否动态切换其网络 随着时间的推移，从一个网络到另一个网络的忠诚(目标3)。这项提议的结果是 对人类rsfcmri数据建模和解释的重要意义。这辆R34 建议书提供了建立新协作和验证我们的方法的机会 跨物种。这些因素对于我们项目的下一阶段，即有针对性的大脑来说是必不可少的 电路项目R01提案，在该提案中，我们将在这条调查线上建立桥梁，以 研究中枢区域大脑回路的基本原理如何形成 心理过程的生物学基础。

Understanding overlap in resting state fMRI networks at the single cell level: a cross-species approach Abstract Resting state functional connectivity MRI (rsfcMRI) is a popular tool to investigate the intrinsic functional organization of the brain into large scale networks. Multiple different lines of investigation have pointed to the importance of densely interconnected `hub' regions for cognition and behavior. However, the functional architecture of cellular circuits in these hub regions is unknown. To study the cellular underpinnings of hub regions, we bring together an interdisciplinary research team to bridge across species and across scales. We start by generalizing recent advances in human fcMRI analyses across species to characterize individualized patterns of network overlap in rsfcMRI data from awake macaque monkeys (Aim 1). This allows us to identify regions of interest for recordings in this same animals from a hub region where two (or more) networks spatially overlap, and from two non-hub regions that strongly contribute to only one of the networks respectively. We then ask whether, at a finer cellular scale, there is true neural coupling between both networks in hub regions, or whether networks that appear spatially overlapping at the resolution of rsfcMRI data are in fact spatially interdigitated rather than overlapping at a finer scale (Aim 2). Lastly, we use electrophysiological recordings to determine whether individual neurons in hub regions integrate information from both overlapping networks (i.e. coupling), or whether neurons dynamically switch their network allegiance from one network to another over time (Aim 3). The outcomes of this proposal have important implications for the modeling and interpretation of human rsfcMRI data. This R34 proposal provides the opportunity to establish a new collaboration and validate our methodology across species. These factors are essential for the next stage of our project, a Targeted Brain Circuits Project R01 proposal, in which we will build on this line of investigation by bridging into behavior to study how fundamental principles of the brain circuits in hub regions form the biological basis of mental processes.