Satterthwaite Theodore D, Wolf Daniel H, Roalf David R, Ruparel Kosha, Erus Guray, Vandekar Simon, Gennatas Efstathios D, Elliott Mark A, Smith Alex, Hakonarson Hakon, Verma Ragini, Davatzikos Christos, Gur Raquel E, Gur Ruben C
Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Department of Radiology, Perelman Scholl of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Cereb Cortex. 2015 Sep;25(9):2383-94. doi: 10.1093/cercor/bhu036. Epub 2014 Mar 18.
Sex differences in human cognition are marked, but little is known regarding their neural origins. Here, in a sample of 674 human participants ages 9-22, we demonstrate that sex differences in cognitive profiles are related to multivariate patterns of resting-state functional connectivity MRI (rsfc-MRI). Males outperformed females on motor and spatial cognitive tasks; females were faster in tasks of emotion identification and nonverbal reasoning. Sex differences were also prominent in the rsfc-MRI data at multiple scales of analysis, with males displaying more between-module connectivity, while females demonstrated more within-module connectivity. Multivariate pattern analysis using support vector machines classified subject sex on the basis of their cognitive profile with 63% accuracy (P < 0.001), but was more accurate using functional connectivity data (71% accuracy; P < 0.001). Moreover, the degree to which a given participant's cognitive profile was "male" or "female" was significantly related to the masculinity or femininity of their pattern of brain connectivity (P = 2.3 × 10(-7)). This relationship was present even when considering males and female separately. Taken together, these results demonstrate for the first time that sex differences in patterns of cognition are in part represented on a neural level through divergent patterns of brain connectivity.
人类认知中的性别差异很明显,但关于其神经起源却知之甚少。在此,在一个由674名9至22岁人类参与者组成的样本中,我们证明认知特征的性别差异与静息态功能连接磁共振成像(rsfc-MRI)的多变量模式有关。男性在运动和空间认知任务上的表现优于女性;女性在情绪识别和非语言推理任务中速度更快。在多个分析尺度的rsfc-MRI数据中,性别差异也很显著,男性表现出更多的模块间连接,而女性则表现出更多的模块内连接。使用支持向量机的多变量模式分析根据参与者的认知特征对其性别进行分类,准确率为63%(P < 0.001),但使用功能连接数据时准确率更高(71%;P < 0.001)。此外,特定参与者的认知特征为“男性化”或“女性化”的程度与他们大脑连接模式的男性化或女性化显著相关(P = 2.3 × 10(-7))。即使分别考虑男性和女性,这种关系也存在。综上所述,这些结果首次证明认知模式中的性别差异部分通过大脑连接的不同模式在神经层面上得以体现。