Independent components of human brain morphology.
Independent components of human brain morphology.
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DOI：
10.1016/j.neuroimage.2020.117546
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发表时间：
2021-02-01
期刊：
影响因子：
5.7
通讯作者：
Mota B
中科院分区：
文献类型：
--
作者：
Wang Y;Leiberg K;Ludwig T;Little B;Necus JH;Winston G;Vos SB;Tisi J;Duncan JS;Taylor PN;Mota B
脑形态学的定量化已经成为理解脑结构的重要基石。皮质形态的测量，如厚度和表面积，经常用于比较受试者组或纵向变化。然而，这些措施往往被视为相互独立。最近描述的缩放法，来自皮质折叠的统计物理模型，表明有三个常用的皮质形态测量之间的紧密协方差：皮质厚度，总表面积，和暴露的表面积。我们发现，假设独立的皮质形态的措施可以隐藏功能，并可能导致误解。使用的标度法，我们占皮质形态的措施之间的协方差，并获得新的独立措施的皮质形态。通过应用这些新的措施，我们表明，可以获得新的信息，在我们的例子中，我们表明，不同的形态学改变的基础上健康的老龄化相比，颞叶癫痫，即使在整个半球的粗糙水平。因此，我们提供了一个概念性的框架，在统计学上有效的和可解释的方式来表征皮质形态，基于理论推理的形状的皮质。
Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex.
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