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超越体积测量:利用分形维数考虑与年龄相关的脑形状复杂性变化。

Beyond volumetry: Considering age-related changes in brain shape complexity using fractal dimensionality.

作者信息

Madan Christopher R

机构信息

School of Psychology, University of Nottingham, Nottingham, UK.

出版信息

Aging Brain. 2021 May 28;1:100016. doi: 10.1016/j.nbas.2021.100016. eCollection 2021.

Abstract

Gray matter volume for cortical, subcortical, and ventricles all vary with age. However, these volumetric changes do not happen on their own, there are also age-related changes in cortical folding and other measures of brain shape. Fractal dimensionality has emerged as a more sensitive measure of brain structure, capturing both volumetric and shape-related differences. For subcortical structures it is readily apparent that segmented structures do not differ in volume in isolation-adjacent regions must also vary in shape. Fractal dimensionality here also appears to be more sensitive to these age-related differences than volume. Given these differences in structure are quite prominent in structure, caution should be used when examining comparisons across age in brain function measures, as standard normalisation methods are not robust enough to adjust for these inter-individual differences in cortical structure.

摘要

皮质、皮质下和脑室的灰质体积均随年龄变化。然而,这些体积变化并非孤立发生,皮质折叠和其他脑形态测量指标也存在与年龄相关的变化。分形维数已成为一种更敏感的脑结构测量指标,可捕捉体积和形状相关的差异。对于皮质下结构,很明显,孤立的分割结构在体积上并无差异——相邻区域的形状也必然会有所不同。此处的分形维数似乎也比体积对这些与年龄相关的差异更敏感。鉴于这些结构差异在结构中相当显著,在检查脑功能测量中的年龄比较时应谨慎,因为标准归一化方法不足以调整这些个体间皮质结构差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ffc3/9997150/defea215edba/gr1.jpg

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