Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, United States of America.
PLoS Biol. 2019 Mar 25;17(3):e2007032. doi: 10.1371/journal.pbio.2007032. eCollection 2019 Mar.
Functional MRI (fMRI) studies have traditionally relied on intersubject normalization based on global brain morphology, which cannot establish proper functional correspondence between subjects due to substantial intersubject variability in functional organization. Here, we reliably identified a set of discrete, homologous functional regions in individuals to improve intersubject alignment of fMRI data. These functional regions demonstrated marked intersubject variability in size, position, and connectivity. We found that previously reported intersubject variability in functional connectivity maps could be partially explained by variability in size and position of the functional regions. Importantly, individual differences in network topography are associated with individual differences in task-evoked activations, suggesting that these individually specified regions may serve as the "localizer" to improve the alignment of task-fMRI data. We demonstrated that aligning task-fMRI data using the regions derived from resting state fMRI may lead to increased statistical power of task-fMRI analyses. In addition, resting state functional connectivity among these homologous regions is able to capture the idiosyncrasies of subjects and better predict fluid intelligence (gF) than connectivity measures derived from group-level brain atlases. Critically, we showed that not only the connectivity but also the size and position of functional regions are related to human behavior. Collectively, these findings suggest that identifying homologous functional regions across individuals can benefit a wide range of studies in the investigation of connectivity, task activation, and brain-behavior associations.
功能磁共振成像（fMRI）研究传统上依赖于基于大脑整体形态的受试者间归一化，由于功能组织在受试者间存在很大的可变性，因此无法在受试者间建立适当的功能对应关系。在这里，我们可靠地在个体中识别出一组离散的、同源的功能区域，以改善 fMRI 数据的受试者间配准。这些功能区域在大小、位置和连接性方面表现出显著的受试者间可变性。我们发现，先前报道的功能连接图中受试者间的可变性部分可以通过功能区域的大小和位置的可变性来解释。重要的是，网络拓扑结构的个体差异与任务诱发激活的个体差异相关，表明这些个体特定的区域可能作为“定位器”来改善任务 fMRI 数据的配准。我们证明，使用静息态 fMRI 中得到的区域对齐任务 fMRI 数据可以提高任务 fMRI 分析的统计功效。此外，这些同源区域之间的静息态功能连接能够捕捉到受试者的特质，并比从组水平脑图谱得出的连接测量更好地预测流体智力（gF）。至关重要的是，我们表明，不仅是连接性，而且功能区域的大小和位置与人类行为有关。总之，这些发现表明，在个体间识别同源功能区域可以有助于广泛的研究，包括连接、任务激活和脑行为关联的研究。
