Linked Sex Differences in Cognition and Functional Connectivity in Youth
Linked Sex Differences in Cognition and Functional Connectivity in Youth
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DOI：
10.1093/cercor/bhu036
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发表时间：
2015-09-01
期刊：
影响因子：
3.7
通讯作者：
Gur, Ruben C.
中科院分区：
文献类型：
--
作者：
Satterthwaite, Theodore D.;Wolf, Daniel H.;Gur, Ruben C.
人类认知的性别差异是显著的，但对其神经起源知之甚少。在这项研究中，我们以674名年龄在9-22岁之间的人类参与者为样本，证明了认知特征的性别差异与静息状态功能连接MRI （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，性别差异也很突出，男性表现出更多的模块间连通性，而女性表现出更多的模块内连通性。使用支持向量机进行多变量模式分析，根据受试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更准确（准确率为71%，P < 0.001）。此外，给定参与者的认知特征是“男性”或“女性”的程度与其大脑连接模式的男性化或女性化显著相关（P = 2.3x10(-7)）。即使将男性和女性分开考虑，这种关系也存在。综上所述，这些结果首次表明，认知模式的性别差异在一定程度上是通过大脑连接的不同模式在神经层面上表现出来的。
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 = 2.3x10(-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.