Department of Neurology and Neurosurgery, Montréal Neurological Institute, Montréal, QC H3A 2B4, Canada; Douglas Mental Health University Institute, Montréal, QC H4H 1R3, Canada.
Department of Neurology and Neurosurgery, Montréal Neurological Institute, Montréal, QC H3A 2B4, Canada; McConnell Brain Imaging Center, McGill University, Montréal, QC H3A 2B4, Canada.
Neuroimage. 2021 Aug 15;237:118149. doi: 10.1016/j.neuroimage.2021.118149. Epub 2021 May 12.
Neuronal variability patterns promote the formation and organization of neural circuits. Macroscale similarities in regional variability patterns may therefore be linked to the strength and topography of inter-regional functional connections. To assess this relationship, we used multi-echo resting-state fMRI and investigated macroscale connectivity-variability associations in 154 adult humans (86 women; mean age = 22yrs). We computed inter-regional measures of moment-to-moment BOLD signal variability and related them to inter-regional functional connectivity. Region pairs that showed stronger functional connectivity also showed similar BOLD signal variability patterns, independent of inter-regional distance and structural similarity. Connectivity-variability associations were predominant within all networks and followed a hierarchical spatial organization that separated sensory, motor and attention systems from limbic, default and frontoparietal control association networks. Results were replicated in a second held-out fMRI run. These findings suggest that macroscale BOLD signal variability is an organizational feature of large-scale functional networks, and shared inter-regional BOLD signal variability may underlie macroscale brain network dynamics.
神经元变异性模式促进了神经网络的形成和组织。因此，区域变异性模式的宏观相似性可能与区域间功能连接的强度和拓扑结构有关。为了评估这种关系，我们使用多回波静息态 fMRI 技术，在 154 名成年人（86 名女性；平均年龄 22 岁）中研究了宏观连接变异性的相关性。我们计算了区域间的局部场电位信号变异性的瞬间到瞬间的测量值，并将其与区域间的功能连接相关联。具有更强功能连接的区域对也表现出相似的 BOLD 信号变异性模式，而与区域间的距离和结构相似性无关。在所有网络中，连接变异性相关性都占主导地位，并遵循一种分层的空间组织，将感觉、运动和注意力系统与边缘、默认和额顶叶控制关联网络分开。在第二个独立的 fMRI 运行中复制了这些结果。这些发现表明，宏观的 BOLD 信号变异性是大尺度功能网络的组织特征，共享的区域间 BOLD 信号变异性可能是宏观大脑网络动态的基础。
