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

机译:静止状态功能磁共振成像对大脑的空间约束分层分割

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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 (~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.
机译:我们提出了一种新颖的计算策略,将大脑皮层划分为不相交的,空间连续的和功能相同的包裹。该方法在休息期间利用功能性磁共振成像(fMRI)观察到的波动中利用了空间依赖性。单个主题的拆分过程分两个阶段进行,其中将一组(约1000到5000)稳定种子生长为初始的详细拆分。然后,使用可增强包裹空间连续性的分层方法进一步对这些包裹进行聚类。一个主要挑战是客观评估和比较不同包裹策略的情况;在这里,我们使用了一系列不同的措施。我们的单一主题方法允许特定主题的大脑皮层分割,从而显示出较高的扫描到扫描重现性,并且其边界勾勒出功能连接性的明显变化。我们的方法运行良好的另一个重要措施是包裹与任务fMRI派生的群集重叠。连接性派生的分割边界与皮质髓鞘化和细胞结构图谱的边界不太匹配,但这可能反映了数据的固有差异。

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