Predicting Language Lateralization from Gray Matter
Predicting Language Lateralization from Gray Matter
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DOI：
10.1523/jneurosci.1680-09.2009
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发表时间：
2009-10-28
影响因子：
5.3
通讯作者：
Price, Cathy J.
中科院分区：
文献类型：
--
作者：
Josse, Goulven;Kherif, Ferath;Price, Cathy J.
长期以来，人们一直预测，语言向左半球或右半球偏侧的程度可能反映在潜在的大脑解剖结构中。我们利用86名健康参与者的结构和功能磁共振图像，在逐体素的基础上研究了整个大脑的这种关系。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。所有图像在空间上归一化为相同的对称模板，并通过在每个体素上减去左半球信号来生成侧化图像。我们发现，语言左右侧化的程度与灰质密度侧化的程度呈正相关。事后分析揭示了灰质概率与血氧水平依赖信号之间的一般关系。这是第一次证明大脑结构扫描可以用来预测正常健康大脑中逐体素的语言偏侧化。
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.