000863624 001__ 863624 000863624 005__ 20220930130214.0 000863624 0247_ $$2doi$$a10.1093/cercor/bhz129 000863624 0247_ $$2ISSN$$a1047-3211 000863624 0247_ $$2ISSN$$a1460-2199 000863624 0247_ $$2Handle$$a2128/24591 000863624 0247_ $$2altmetric$$aaltmetric:62849496 000863624 0247_ $$2pmid$$apmid:31251328 000863624 0247_ $$2WOS$$aWOS:000530440700031 000863624 037__ $$aFZJ-2019-03635 000863624 082__ $$a610 000863624 1001_ $$0P:(DE-Juel1)172811$$aWeis, Susanne$$b0$$eCorresponding author$$ufzj 000863624 245__ $$aSex Classification by Resting State Brain Connectivity 000863624 260__ $$aOxford$$bOxford Univ. Press$$c2020 000863624 3367_ $$2DRIVER$$aarticle 000863624 3367_ $$2DataCite$$aOutput Types/Journal article 000863624 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1585044339_4655 000863624 3367_ $$2BibTeX$$aARTICLE 000863624 3367_ $$2ORCID$$aJOURNAL_ARTICLE 000863624 3367_ $$00$$2EndNote$$aJournal Article 000863624 500__ $$aThe Deutsche Forschungsgemeinschaft (EI 816/11-1), TheNational Institute of Mental Health (R01-MH074457); TheHelmholtz Portfolio Theme “Supercomputing and Modeling forthe Human Brain”; The European Union [Horizon 2020 Researchand Innovation Programme under grant agreement no. 720270(HBP SGA1) 785907 (HBP SGA2)]; Singapore National ResearchFoundation [fellowship (class of 2017) to B.T.T.Y.].APC & Rechnung ergänzt 10.07.19 000863624 520__ $$aA 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. 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