Abstract
A large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants’ sex can be classified based on spatially specific resting state (RS) brain connectivity, using 2 samples from the Human Connectome Project (n1 = 434, n2 = 310) and 1 fully independent sample from the 1000BRAINS study (n = 941). The classifier, which was trained on 1 sample and tested on the other 2, was able to reliably classify sex, both within sample and across independent samples, differing both with respect to imaging parameters and sample characteristics. Brain regions displaying highest sex classification accuracies were mainly located along the cingulate cortex, medial and lateral frontal cortex, temporoparietal regions, insula, and precuneus. These areas were stable across samples and match well with previously described sex differences in functional brain organization. While our data show a clear link between sex and regionally specific brain connectivity, they do not support a clear-cut dimorphism in functional brain organization that is driven by sex alone.
Highlights
A large amount of brain imaging research has focused on delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization
Our results show that sex classification based on resting state (RS) fMRI data is possible with high accuracies, which are significantly different from chance across more or less the whole brain
The results show that classification can be reliably extended to independent samples, differing both with respect to imaging parameters and sample characteristics
Summary
A large amount of brain imaging research has focused on delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. With respect to brain structure, some literature (Joel et al 2015) even argues that any particular brain might comprise certain features that are statistically more typical of females and others which are more typical for males. In that sense, these authors suggested (Joel et al 2015) that most brains are comprised of “mosaics” of features, some more common in females, some more common
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