College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, China.
Neuroimage. 2012 Jul 16;61(4):931-40. doi: 10.1016/j.neuroimage.2012.03.080. Epub 2012 Apr 3.
There has been growing interest recently in the use of multivariate pattern analysis (MVPA) to decode information from high-dimensional neuroimaging data. The present study employed a support vector machine-based MVPA approach to identify the complex patterns of sex differences in brain structure and resting-state function. We also aimed to assess the role of anatomy on functional sex differences during rest. One hundred and forty healthy young Chinese adults (70 men and 70 women) underwent structural and resting-state functional MRI scans. Gray matter density and regional homogeneity (ReHo) were used to map brain structure and resting-state function, respectively. After combining these two feature vectors into one union-vector, a pattern classifier was designed using principal component analysis and linear support vector machine to identify brain areas that had distinct characteristics between the groups. We found that: (1) male and female brains were different with a mean classification accuracy of 89%; (2) sex differences in gray matter density were widely distributed in the brain, notably in the occipital lobe and the cerebellum; (3) men primarily showed higher ReHo in their right hemispheres and women tended to show greater ReHo in their left hemispheres; (4) about 50% of brain areas with functional sex differences exhibited significant positive correlations between gray matter density and ReHo. Our results suggest that sex is an important factor that account for interindividual variability in the healthy brain.
最近，人们对使用多元模式分析（MVPA）来解码高维神经影像学数据中的信息越来越感兴趣。本研究采用基于支持向量机的 MVPA 方法，来识别大脑结构和静息状态功能性别差异的复杂模式。我们还旨在评估解剖结构在静息状态下对功能性别差异的作用。140 名健康的中国年轻人（70 名男性和 70 名女性）接受了结构和静息状态功能磁共振成像扫描。使用灰质密度和局部一致性（ReHo）分别映射大脑结构和静息状态功能。将这两个特征向量组合成一个联合向量后，使用主成分分析和线性支持向量机设计模式分类器，以识别组间具有明显特征的大脑区域。我们发现：（1）男性和女性的大脑存在差异，平均分类准确率为 89%；（2）灰质密度的性别差异广泛分布于大脑中，特别是在枕叶和小脑；（3）男性主要在右半球表现出更高的 ReHo，而女性则倾向于在左半球表现出更高的 ReHo；（4）约 50%具有功能性别差异的大脑区域的灰质密度与 ReHo 之间存在显著的正相关。我们的研究结果表明，性别是解释健康大脑个体间变异性的一个重要因素。
