000904415 001__ 904415 000904415 005__ 20220131120426.0 000904415 0247_ $$2doi$$a10.1080/17588928.2020.1867084 000904415 0247_ $$2ISSN$$a1758-8928 000904415 0247_ $$2ISSN$$a1758-8936 000904415 0247_ $$2Handle$$a2128/29991 000904415 0247_ $$2pmid$$a33406985 000904415 0247_ $$2WOS$$aWOS:000605657900001 000904415 037__ $$aFZJ-2021-05985 000904415 082__ $$a610 000904415 1001_ $$0P:(DE-Juel1)176497$$aWiersch, Lisa$$b0$$ufzj 000904415 245__ $$aSex differences in the brain: More than just male or female 000904415 260__ $$aHove$$bPsychology Press$$c2021 000904415 3367_ $$2DRIVER$$aarticle 000904415 3367_ $$2DataCite$$aOutput Types/Journal article 000904415 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1641562076_18961 000904415 3367_ $$2BibTeX$$aARTICLE 000904415 3367_ $$2ORCID$$aJOURNAL_ARTICLE 000904415 3367_ $$00$$2EndNote$$aJournal Article 000904415 520__ $$aSex differences in the brain are widely studied, but results are often inconsistent and it is assumed that many negative findings are not even being reported. The lack of consistent findings might be based on the highly questionable assumption of a clear-cut sexual dimorphism in brain structure and function, that underlies commonly used group comparisons between males and females. Without having to rely on this assumption, state of the art statistical learning methods based on large neuroimaging data sets might offer the tools necessary to disentangle the complex pattern of sex-related variations in brain structure and organization. 000904415 536__ $$0G:(DE-HGF)POF4-5251$$a5251 - Multilevel Brain Organization and Variability (POF4-525)$$cPOF4-525$$fPOF IV$$x0 000904415 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de 000904415 7001_ $$0P:(DE-Juel1)172811$$aWeis, Susanne$$b1$$eCorresponding author 000904415 773__ $$0PERI:(DE-600)2542443-9$$a10.1080/17588928.2020.1867084$$gVol. 12, no. 3-4, p. 187 - 188$$n3-4$$p187 - 188$$tCognitive neuroscience$$v12$$x1758-8928$$y2021 000904415 8564_ $$uhttps://juser.fz-juelich.de/record/904415/files/PCNS_A_1867084-1.pdf$$yRestricted 000904415 8564_ $$uhttps://juser.fz-juelich.de/record/904415/files/submission_commentary_cogneurosci20.pdf$$yOpenAccess 000904415 909CO $$ooai:juser.fz-juelich.de:904415$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire 000904415 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176497$$aForschungszentrum Jülich$$b0$$kFZJ 000904415 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)172811$$aForschungszentrum Jülich$$b1$$kFZJ 000904415 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5251$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0 000904415 9141_ $$y2021 000904415 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bCOGN NEUROSCI-UK : 2019$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess 000904415 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-02-04 000904415 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2021-02-04 000904415 920__ $$lyes 000904415 9201_ $$0I:(DE-Juel1)INM-7-20090406$$kINM-7$$lGehirn & Verhalten$$x0 000904415 980__ $$ajournal 000904415 980__ $$aVDB 000904415 980__ $$aUNRESTRICTED 000904415 980__ $$aI:(DE-Juel1)INM-7-20090406 000904415 9801_ $$aFullTexts