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The Brain Atlas Concordance Problem: Quantitative Comparison of Anatomical Parcellations

机译:脑图谱一致性问题:解剖碎片的定量比较

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摘要

Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at .
机译:许多神经科学报告都提到了大脑的离散宏观解剖区域,这些区域是根据大脑图集或切碎方案划定的。但是,目前,尚不存在用于划分皮层和皮层下结构或将标签分配给所得区域的广泛接受的标准,并且正在积极使用许多程序。先前调和神经解剖学术语的尝试在很大程度上是定性的,重点是叙词表的发展或术语之间的简单语义映射。在这里,我们采用根本不同的方法,将区域名称打折,然后将它们的定义作为空间实体进行比较,以期在由不同图集定义的解剖实体之间提供更精确的定量映射。我们开发了一个用于研究此脑图谱一致性问题的分析框架,并将这些方法应用于神经影像界使用的八种不同标记方法的比较。这些分析导致条件概率,该条件概率使能跨图集的区域之间的映射,这也为基于图的方法(用于提取区域集之间的高阶关系)和评估同一大脑的不同区域之间的全局相似性的过程提供了输入。在全球范围内,总体结果表明,可用的分割方案之间相当缺乏协调性,属于某些图集对的机会水平之内。在更细的层面上,这项研究揭示了在定义区域集之间的空间关系不是很明显。对于面临比较基于这些不同解剖模型的结果的挑战的研究人员而言,这些具有很高的潜在兴趣,尤其是在没有基于坐标的数据的情况下。揭示的空间重叠模式的复杂性指出了试图使用严格的定性和/或分类方法来调和解剖学单元和术语的问题。这项研究的详细结果可通过的交互式网站获得。

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