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Hierarchical organization of the functional brain identified using floating aggregation of functional signals

机译:使用浮动聚集的功能信号识别的功能性大脑的分层组织

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A novel method is proposed to parcellate the cerebral cortex into functionally homogenous regions at multiple scales with a hierarchical organization based on resting-state fMRI data. The cortical vertices are clustered according to inter-vertex functional similarity measures progressively at multiple spatial scales from fine to coarse by a procedure referred to as floating aggregation. The floating aggregation takes into consideration both the inter-regional functional similarity and the consistency of intra-regional functional homogeneity measures at every level of the resulting parcellation hierarchy. This aggregation procedure does not require to specify the number of regions for the parcellation, and could help identify proper spatial scales for the brain parcellation based on the overall region homogeneity changes across levels of the hierarchy. The experimental results on a resting-state fMRI dataset have demonstrated that the proposed method could not only obtain brain parcellation results with better functional homogeneity measures than state-of-the-art techniques, but also identify a hierarchical functional organization of the brain at multiple spatial scales.
机译:提出一种新的方法,用于将脑皮层对功能均匀区域进行将基于休息状态FMRI数据的分层组织的多个尺度对功能均匀区域。通过通过称为浮动聚合的过程逐渐地,根据顶点功能相似度逐渐逐渐逐渐群体聚类皮质顶点。浮动聚集考虑了区域间功能性相似性和区域内函数均匀性措施的跨区域功能相似性和一致性。该聚合过程不需要指定局部的区域数,并且可以帮助识别基于层次结构水平的整体区域均匀性变化的大脑局的适当空间尺度。休息状态FMRI数据集的实验结果表明,该方法不仅可以获得比最先进的技术更好的功能均匀度测量,还可以获得比最先进的技术,还可以在多个方面识别大脑的分层功能组织空间鳞片。

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