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Predicting Language Lateralization from Gray Matter

机译:从灰色问题预测语言横向化

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摘要

It has long been predicted that the degree to which language is lateralized to the left or right hemisphere might be reflected in the underlying brain anatomy. We investigated this relationship on a voxel-by-voxel basis across the whole brain using structural and functional magnetic resonance images from 86 healthy participants. Structural images were converted to gray matter probability images, and language activation was assessed during naming and semantic decision. All images were spatially normalized to the same symmetrical template, and lateralization images were generated by subtracting right from left hemisphere signal at each voxel. We show that the degree to which language was left or right lateralized was positively correlated with the degree to which gray matter density was lateralized. Post hoc analyses revealed a general relationship between gray matter probability and blood oxygenation level-dependent signal. This is the first demonstration that structural brain scans can be used to predict language lateralization on a voxel-by-voxel basis in the normal healthy brain.
机译:长期以来,人们一直在预测语言在左侧或右侧半球的偏斜程度可能会反映在基础的大脑解剖结构中。我们使用来自86位健康参与者的结构和功能磁共振图像,在整个大脑中逐个像素地研究了这种关系。将结构图像转换为灰质概率图像,并在命名和语义决策过程中评估语言激活。所有图像在空间上均归一化为相同的对称模板,并且通过从每个体素的左半球信号中减去右信号来生成横向图像。我们表明,语言被左或右偏斜的程度与灰质密度被偏斜的程度呈正相关。事后分析揭示了灰质几率与血液氧合水平依赖性信号之间的一般关系。这是结构健康的大脑扫描可用于在正常健康的大脑中逐个像素地预测语言偏侧化的第一个证明。

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