Individual Variability in Functional Connectivity Architecture of the Human Brain

被引:749
|
作者
Mueller, Sophia [1 ,2 ,3 ]
Wang, Danhong [1 ]
Fox, Michael D. [4 ]
Yeo, B. T. Thomas [1 ,5 ]
Sepulcre, Jorge [1 ,2 ,6 ,7 ]
Sabuncu, Mert R. [1 ]
Shafee, Rebecca [2 ]
Lu, Jie [8 ]
Liu, Hesheng [1 ]
机构
[1] Massachusetts Gen Hosp, Dept Radiol, Athinoula A Martinos Ctr Biomed Imaging, Charlestown, MA 02129 USA
[2] Harvard Univ, Ctr Brain Sci, Cambridge, MA 02138 USA
[3] Univ Munich, Inst Clin Radiol, D-81377 Munich, Germany
[4] Brigham & Womens Hosp, Massachusetts Gen Hosp, Dept Neurol, Boston, MA 02114 USA
[5] Duke NUS Grad Med Sch, Neurosci & Behav Disorders Program, Singapore 169857, Singapore
[6] Massachusetts Gen Hosp, Dept Radiol, Div Nucl Med & Mol Imaging, Boston, MA 02114 USA
[7] Harvard Univ, Sch Med, Boston, MA 02114 USA
[8] Capital Med Univ, Xuanwu Hosp, Dept Radiol, Beijing 100053, Peoples R China
关键词
SURFACE-BASED ANALYSIS; CEREBRAL-CORTEX; INTERSUBJECT VARIABILITY; GENETIC INFLUENCES; PREFRONTAL CORTEX; EVOLUTION; TOPOGRAPHY; ASYMMETRY; TALAIRACH; EXPANSION;
D O I
10.1016/j.neuron.2012.12.028
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here, we used repeated-measurement resting-state functional MRI to explore intersubject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Intersubject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging.
引用
收藏
页码:586 / 595
页数:10
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