Laumann Timothy O, Gordon Evan M, Adeyemo Babatunde, Snyder Abraham Z, Joo Sung Jun, Chen Mei-Yen, Gilmore Adrian W, McDermott Kathleen B, Nelson Steven M, Dosenbach Nico U F, Schlaggar Bradley L, Mumford Jeanette A, Poldrack Russell A, Petersen Steven E
Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
Neuron. 2015 Aug 5;87(3):657-70. doi: 10.1016/j.neuron.2015.06.037. Epub 2015 Jul 23.
Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected-considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individual's systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals. VIDEO ABSTRACT.
静息态功能磁共振成像(fMRI)能够在多个空间尺度上描述群体水平的脑功能组织。然而,跨个体平均可能会掩盖每个个体特有的脑组织结构模式。在此,我们对一名个体进行了长达一年多的反复测量,以表征其脑组织结构。我们报告了一种可重复且内部有效的个体特异性区域水平脑区划分,它与个体特异性任务激活相对应。如果收集到足够的数据(远多于通常采集的数据),就可以从这种脑区划分中得出高度收敛的相关网络估计值。值得注意的是,跨时段的个体内相关变异性在整个皮层呈现出异质性分布,集中在视觉和躯体运动区域,这与个体间变异性模式不同。此外,尽管该个体的系统水平组织与群体大致相似,但它表现出独特的拓扑特征。这些结果为研究皮层组织和功能的个体差异提供了基础,特别是对于特殊或罕见个体。视频摘要。