On average, men and women differ in brain structure and behavior, raising the possibility of a link between sex differences in brain and behavior. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study (n = 1,040) and Human Connectome Project (n = 1,113), we obtained data-driven measures of individual differences along a male–female dimension for brain and behavior based on average sex differences in brain structure and behavior, respectively. We found a weak association between these brain and behavioral differences, driven by brain size. These brain and behavioral differences were moderately heritable. Our findings suggest that behavioral sex differences are, to some extent, related to sex differences in brain structure but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously.
AdamsD. C.Otarola-CastilloE. (2013). geomorph: an R package for the collection and analysis of geometric morphometric shape data. Methods in Ecology and Evolution, 4(4), 393–399. https://doi.org/10.1111/2041-210X.12035
2.
AndersonN. E.HarenskiK. A.HarenskiC. L.KoenigsM. R.DecetyJ.CalhounV. D.KiehlK. A. (2019). Machine learning of brain gray matter differentiates sex in a large forensic sample. Human Brain Mapping, 40(5), 1496–1506. https://doi.org/10.1002/hbm.24462
3.
ArcherJ. (2019). The reality and evolutionary significance of human psychological sex differences. Biological Reviews, 94, 1381–1415. https://doi.org/10.1111/brv.12507
4.
BokerS.NealeM.MaesH.WildeM.SpiegelM.BrickT.SpiesJ.EstabrookR.KennyS.BatesT.MehtaP.FoxJ. (2011). OpenMx: An open source extended structural equation modeling framework. Psychometrika, 76(2), 306–317. https://doi.org/10.1007/s11336-010-9200-6
5.
BrunerE.de la CuétaraJ. M.ColomR.Martin-LoechesM. (2012). Gender-based differences in the shape of the human corpus callosum are associated with allometric variations. Journal of Anatomy, 220(4), 417–421. https://doi.org/10.1111/j.1469-7580.2012.01476.x
6.
ChekroudA. M.WardE. J.RosenbergM. D.HolmesA. J. (2016). Patterns in the human brain mosaic discriminate males from females. Proceedings of the National Academy of Sciences, USA, 113(14), Article E1968. https://doi.org/10.1073/pnas.1523888113
7.
Couvy-DuchesneB.StrikeL. T.ZhangF.HoltzY.ZhengZ.KemperK. E.YengoL.ColliotO.WrightM. J.WrayN. R.YangJ.VisscherP. M. (2020). A unified framework for association and prediction from vertex-wise grey-matter structure. Human Brain Mapping, 41(14), 4062–4076. https://doi.org/10.1002/hbm.25109
8.
de JongL. W.VidalJ.-S.ForsbergL. E.ZijdenbosA. P.HaightT., Alzheimer’s Disease Neuroimaging Initiative, SigurdssonS.GudnasonV.van BuchemM. A.LaunerL. J. (2017). Allometric scaling of brain regions to intra-cranial volume: An epidemiological MRI study. Human Brain Mapping, 38(1), 151–164. https://doi.org/10.1002/hbm.23351
9.
Del GiudiceM.LippaR. A.PutsD. A.BaileyD. H.BaileyJ. M.SchmittD. P. (2016). Joel et al.’s method systematically fails to detect large, consistent sex differences. Proceedings of the National Academy of Sciences, USA, 113(14), Article E1965. https://doi.org/10.1073/pnas.1525534113
10.
De VriesG. J. (2004). Minireview: Sex differences in adult and developing brains: Compensation, compensation, compensation. Endocrinology, 145(3), 1063–1068. https://doi.org/10.1210/en.2003-1504
EaglyA. H.WoodW. (2013). The nature–nurture debates: 25 years of challenges in understanding the psychology of gender. Perspectives on Psychological Science, 8(3), 340–357. https://doi.org/10.1177/1745691613484767
FristonK. J.HolmesA. P.PolineJ. B.GrasbyP. J.WilliamsS. C. R.FrackowiakR. S. J.TurnerR. (1995). Analysis of fMRI time-series revisited. NeuroImage, 2(1), 45–53. https://doi.org/10.1006/nimg.1995.1007
15.
GillespieN. A.HendersA. K.DavenportT. A.HermensD. F.WrightM. J.MartinN. G.HickieI. B. (2013). The Brisbane Longitudinal Twin Study: Pathways to Cannabis Use, Abuse, and Dependence project—current status, preliminary results, and future directions. Twin Research and Human Genetics, 16(1), 21–33. https://doi.org/10.1017/thg.2012.111
16.
GlasserM. F.SotiropoulosS. N.WilsonJ. A.CoalsonT. S.FischlB.AnderssonJ. L.XuJ.JbabdiS.WebsterM.PolimeniJ. R.Van EssenD. C.JenkinsonM., & WU-Minn HCP Consortium. (2013). The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage, 80, 105–124. https://doi.org/10.1016/j.neuroimage.2013.04.127
17.
GoriounovaN. A.MansvelderH. D. (2019). Genes, cells and brain areas of intelligence. Frontiers in Human Neuroscience, 13, Article 44. https://doi.org/10.3389/fnhum.2019.00044
18.
GurR. E.GurR. C. (2016). Sex differences in brain and behavior in adolescence: Findings from the Philadelphia Neurodevelopmental Cohort. Neuroscience & Biobehavioral Reviews, 70, 159–170. https://doi.org/10.1016/j.neubiorev.2016.07.035
19.
JahanshadN.AganjI.LengletC.JoshiA.JinY.BaryshevaM.McMahonK. L.de ZubicarayG. I.MartinN. G.WrightM. J.TogaA. W.SapiroG.ThompsonP. M. (2011, March30–April2). Sex differences in the human connectome: 4-tesla high angular resolution diffusion imaging (HARDI) tractography in 234 young adult twins [Paper presentation]. 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Chicago, IL, United States.
JoelD.PersicoA.SalhovM.BermanZ.OligschlägerS.MeilijsonI.AverbuchA. (2018). Analysis of human brain structure reveals that the brain “types” typical of males are also typical of females, and vice versa. Frontiers in Human Neuroscience, 12, Article 399. https://doi.org/10.3389/fnhum.2018.00399
22.
KimH. J.KimN.KimS.HongS.ParkK.LimS.ParkJ.-M.NaB.ChaeY.LeeJ.YeoS.ChoeI.-H.ChoS.-Y.ChoG. (2012). Sex differences in amygdala subregions: Evidence from subregional shape analysis. NeuroImage, 60(4), 2054–2061. https://doi.org/10.1016/j.neuroimage.2012.02.025
23.
LotzeM.DominM.GerlachF. H.GaserC.LuedersE.SchmidtC. O.NeumannN. (2019). Novel findings from 2,838 adult brains on sex differences in gray matter brain volume. Scientific Reports, 9(1), Article 1671. https://doi.org/10.1038/s41598-018-38239-2
24.
MillerK. L.Alfaro-AlmagroF.BangerterN. K.ThomasD. L.YacoubE.XuJ.BartschA. J.JbabdiS.SotiropoulosS. N.AnderssonJ. L. R.GriffantiL.DouaudG.OkellT. W.WealeP.DragonuI.GarrattS.HudsonS.CollinsR.JenkinsonM.. . . SmithS. M. (2016). Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nature Neuroscience, 19(11), 1523–1536. https://doi.org/10.1038/nn.4393
25.
OuJ.XieL.LiX.ZhuD.TerryD. P.PuenteA. N.JiangR.ChenY.WangL.ShenD.ZhangJ.MillerL. S.LiuT. (2015). Atomic connectomics signatures for characterization and differentiation of mild cognitive impairment. Brain Imaging and Behavior, 9(4), 663–677. https://doi.org/10.1007/s11682-014-9320-1
26.
PearseR. V.Young-PearseT. L. (2019). Lost in translational biology: Understanding sex differences to inform studies of diseases of the nervous system. Brain Research, 1722, Article 146352. https://doi.org/10.1016/j.brainres.2019.146352
27.
PhillipsO. R.OnopaA. K.HsuV.OllilaH. M.HillaryR. P.HallmayerJ.GotlibI. H.TaylorJ.MackeyL.SinghM. K. (2019). Beyond a binary classification of sex: An examination of brain sex differentiation, psychopathology, and genotype. Journal of the American Academy of Child & Adolescent Psychiatry, 58(8), 787–798. https://doi.org/10.1016/j.jaac.2018.09.425
28.
R Core Team. (2018). R: A language and environment for statistical computing (Version 3.4.4) [Computer software]. http://www.r-project.org/
29.
RenteríaM. E.HansellN. K.StrikeL. T.McMahonK. L.de ZubicarayG. I.HickieI. B.ThompsonP. M.MartinN. G.MedlandS. E.WrightM. J. (2014). Genetic architecture of subcortical brain regions: Common and region-specific genetic contributions. Genes, Brain, and Behavior, 13(8), 821–830. https://doi.org/10.1111/gbb.12177
30.
RitchieS. J.CoxS. R.ShenX.LombardoM. V.ReusL. M.AllozaC.HarrisM. A.AldersonH. L.HunterS.NeilsonE.LiewaldD. C. M.AuyeungB.WhalleyH. C.LawrieS. M.GaleC. R.BastinM. E.McIntoshA. M.DearyI. J. (2018). Sex differences in the adult human brain: Evidence from 5216 UK Biobank participants. Cerebral Cortex, 28(8), 2959–2975. https://doi.org/10.1093/cercor/bhy109
31.
RobinX.TurckN.HainardA.TibertiN.LisacekF.SanchezJ.-C.MüllerM. (2011). pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics, 12, Article 77. https://doi.org/10.1186/1471-2105-12-77
32.
RobinsonG. K. (1991). That BLUP is a good thing: The estimation of random effects. Statistical Science, 6(1), 15–32. https://doi.org/10.1214/ss/1177011926
33.
RuigrokA. N.Salimi-KhorshidiG.LaiM.-C.Baron-CohenS.LombardoM. V.TaitR. J.SucklingJ. (2014). A meta-analysis of sex differences in human brain structure. Neuroscience & Biobehavioral Reviews, 39, 34–50. https://doi.org/10.1016/j.neubiorev.2013.12.004
34.
TournierJ.-D.SmithR. E.RaffeltD.TabbaraR.DhollanderT.PietschM.ChristiaensD.JeurissenB.YehC.-H.ConnellyA. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 202, Article 116137. https://doi.org/10.1016/j.neuroimage.2019.116137
35.
ToussaintN.SoupletJ. C.FillardP. (2007). MedINRIA: Medical image navigation and research tool by INRIA. In Proceedings of MICCAI’07 Workshop on interaction in medical image analysis and visualization. The Medical Image Computing and Computer Assisted Intervention Society.
36.
TunçB.SolmazB.ParkerD.SatterthwaiteT. D.ElliottM. A.CalkinsM. E.RuparelK.GurR. E.GurR. C.VermaR. (2016). Establishing a link between sex-related differences in the structural connectome and behaviour. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1688), Article 20150111. https://doi.org/10.1098/rstb.2015.0111
van EijkL.HansellN. K.StrikeL. T.Couvy-DuchesneB.de ZubicarayG. I.ThompsonP. M.McMahonK. L.ZietschB. P.WrightM. J. (2020). Region-specific sex differences in the hippocampus. NeuroImage, 215, Article 116781. https://doi.org/10.1016/j.neuroimage.2020.116781
39.
Van EssenD. C.UgurbilK.AuerbachE.BarchD.BehrensT. E. J.BucholzR.ChangA.ChenL.CorbettaM.CurtissS. W.Della PennaS.FeinbergD.GlasserM. F.HarelN.HeathA. C.Larson-PriorL.MarcusD.MichalareasG.MoellerS., . . . WU-Minn HCP Consortium. (2012). The Human Connectome Project: A data acquisition perspective. NeuroImage, 62(4), 2222–2231. https://doi.org/10.1016/j.neuroimage.2012.02.018
40.
VenablesW. N.RipleyB. D. (2002). Modern applied statistics with S (4th ed). Springer.
41.
VerweijK. J.MosingM. A.UllenF.MadisonG. (2016). Individual differences in personality masculinity-femininity: Examining the effects of genes, environment, and prenatal hormone transfer. Twin Research and Human Genetics, 19(2), 87–96. https://doi.org/10.1017/thg.2016.8
42.
WainschteinP.JainD. P.YengoL.ZhengZ.CupplesL. A.ShadyabA. H.McKnightB.ShoemakerB. M.MitchellB. D.PsatyB. M.KooperbergC.RodenD.DarbarD.ArnettD. K.ReganE. A.BoerwinkleE.RotterJ. I.AllisonM. A.McDonaldM.-L. N.. . . VisscherP. M. (2021). Recovery of trait heritability from whole genome sequence data. bioRxiv. https://doi.org/10.1101/588020
43.
WrightM. J.MartinN. G. (2004). Brisbane Adolescent Twin Study: Outline of study methods and research projects. Australian Journal of Psychology, 56(2), 65–78. https://doi.org/10.1080/00049530410001734865
44.
XinJ.ZhangY.TangY.YangY. (2019). Brain differences between men and women: Evidence from deep learning. Frontiers in Neuroscience, 13, Article 185. https://doi.org/10.3389/fnins.2019.00185
ZhuD.LiK.GuoL.JiangX.ZhangT.ZhangD.ChenH.DengF.FaracoC.JinC.WeeC.-Y.YuanY.LvP.YinY.HuX.DuanL.HuX.HanJ.WangL.. . . LiuT. (2013). DICCCOL: Dense individualized and common connectivity-based cortical landmarks. Cerebral Cortex, 23(4), 786–800. https://doi.org/10.1093/cercor/bhs072
47.
ZhuD.ZhanL.FaskowitzJ.DaianuM.JahanshadN.de ZubicarayG. I.McMahonK. L.MartinN. G.WrightM. J.ThompsonP. M. (2015). Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins. In Proceedings of the IEEE 12th International Symposium on Biomedical Imaging (pp. 1167–1171). https://doi.org/10.1109/ISBI.2015.7164080
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
