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Linear and curvilinear correlations of brain gray matter volume and density with age using voxel‐based morphometry with the Akaike information criterion in 291 healthy children

机译:使用基于体素的形态计量学和Akaike信息标准的291名健康儿童脑灰质体积和密度与年龄的线性和曲线相关性

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摘要

We examined linear and curvilinear correlations of gray matter volume and density in cortical and subcortical gray matter with age using magnetic resonance images (MRI) in a large number of healthy children. We applied voxel‐based morphometry (VBM) and region‐of‐interest (ROI) analyses with the Akaike information criterion (AIC), which was used to determine the best‐fit model by selecting which predictor terms should be included. We collected data on brain structural MRI in 291 healthy children aged 5–18 years. Structural MRI data were segmented and normalized using a custom template by applying the diffeomorphic anatomical registration using exponentiated lie algebra (DARTEL) procedure. Next, we analyzed the correlations of gray matter volume and density with age in VBM with AIC by estimating linear, quadratic, and cubic polynomial functions. Several regions such as the prefrontal cortex, the precentral gyrus, and cerebellum showed significant linear or curvilinear correlations between gray matter volume and age on an increasing trajectory, and between gray matter density and age on a decreasing trajectory in VBM and ROI analyses with AIC. Because the trajectory of gray matter volume and density with age suggests the progress of brain maturation, our results may contribute to clarifying brain maturation in healthy children from the viewpoint of brain structure. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.
机译:我们使用磁共振图像(MRI)在许多健康儿童中检查了皮质和皮质下灰质中灰质体积和密度与年龄之间的线性和曲线相关性。我们使用了基于体素的形态计量学(VBM)和感兴趣区域(ROI)分析以及Akaike信息标准(AIC),该标准用于通过选择应包含哪些预测变量来确定最佳拟合模型。我们收集了291名5-18岁健康儿童的大脑结构MRI数据。通过使用指数幂代数(DARTEL)程序应用微形解剖配准,使用定制模板对结构MRI数据进行分割和归一化。接下来,我们通过估计线性,二次和三次多项式函数,分析了带有AIC的VBM中灰质体积和密度与年龄的相关性。在用AIC进行的VBM和ROI分析中,前额叶皮层,中枢回和小脑等几个区域在增加的轨迹上显示灰质数量与年龄之间的线性或曲线相关性,而在下降的轨迹上显示灰质密度与年龄之间的线性或曲线显着线性关系。由于灰质体积和密度随年龄的变化轨迹表明了大脑成熟的进展,因此我们的结果可能有助于从大脑结构的角度阐明健康儿童的大脑成熟。嗡嗡声脑图,2013年。©2012 Wiley Periodicals,Inc.

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