Spatially constrained hierarchical parcellation of the brain with resting-state fMRI

被引:156
|
作者
Blumensath, Thomas [1 ,2 ]
Jbabdi, Saad [1 ]
Glasser, Matthew F. [3 ]
Van Essen, David C. [3 ]
Ugurbil, Kamil [4 ]
Behrens, Timothy E. J. [1 ,5 ]
Smith, Stephen M. [1 ]
机构
[1] Univ Oxford, FMRIB, Oxford, England
[2] Univ Southampton, ISVR Signal Proc & Control Grp, Southampton SO17 1BJ, Hants, England
[3] Washington Univ, Sch Med, Dept Anat & Neurobiol, St Louis, MO 63110 USA
[4] Univ Minnesota, CMRR, Minneapolis, MN 55455 USA
[5] Wellcome Trust Ctr Neuroimaging, London, England
基金
英国工程与自然科学研究理事会;
关键词
Resting state fMRI; Cortical parcellation; Connectomics; CORTEX; ORGANIZATION; NETWORKS;
D O I
10.1016/j.neuroimage.2013.03.024
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
We propose a novel computational strategy to partition the cerebral cortex into disjoint, spatially contiguous and functionally homogeneous parcels. The approach exploits spatial dependency in the fluctuations observed with functional Magnetic Resonance Imaging (fMRI) during rest. Single subject parcellations are derived in a two stage procedure in which a set of (similar to 1000 to 5000) stable seeds is grown into an initial detailed parcellation. This parcellation is then further clustered using a hierarchical approach that enforces spatial contiguity of the parcels. A major challenge is the objective evaluation and comparison of different parcellation strategies; here, we use a range of different measures. Our single subject approach allows a subject-specific parcellation of the cortex, which shows high scan-to-scan reproducibility and whose borders delineate clear changes in functional connectivity. Another important measure, on which our approach performs well, is the overlap of parcels with task fMRI derived clusters. Connectivity-derived parcellation borders are less well matched to borders derived from cortical myelination and from cytoarchitectonic atlases, but this may reflect inherent differences in the data. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:313 / 324
页数:12
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