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Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants
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Abstract
Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44-77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.
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“Sex-related differences in brain structure and function have been consistently reported across large-scale neuroimaging studies, involving both global and regional measures such as total brain volume, cortical thickness, white matter microstructure, and functional connectivity [29,30,31,32].”
From Benchmarking Multimodal Deep Fusion Strategies for Heterogeneous Neuroimaging and Cognitive Data Using a Controlled Sex Classification Task (2026) · cites this paper as [31]
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“As sex differences exist in brain morphology,33”
From Sex Differences in the Association of Global Amyloid and Regional Tau Deposition Measured by Positron Emission Tomography in Clinically Normal Older Adults (2019) · cites this paper as [33]
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“Memory impairment is similarly found among patients with Cushing disease and Cushing syndrome (694).”
From Congenital Adrenal Hyperplasia—Current Insights in Pathophysiology, Diagnostics, and Management (2022) · cites this paper as [694]
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BackgroundImage processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank
Alfaro‐Almagro, F., Jenkinson, M., Bangerter, N. K., Andersson, J., Griffanti, L., Douaud, G., Sotiropoulos, S. N., Jbabdi, S., Hernández-Fernández, M., Vallée, E., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.10.034 · Cited by 1,564 · cited 1×
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MethodThe social brain in psychiatric and neurological disorders
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ResultSex beyond the genitalia: the human brain mosaic
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“A fuller understanding of morphological and functional differences between the brains of the human sexes might provide insight into why the observed prevalence of some psychiatric disorders differs substantially by sex (Rutter et al. 2003), and would assist in explaining several behavioral sex differences (Zell et al.”
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“2009; Reinhold and Engqvist 2013), or other protective factors that might “buffer” females from potential deleterious consequences of rare genetic mutations (Jacquemont et al. 2014; Robinson et al. 2013).”
BackgroundAccelerated microstructure imaging via Convex Optimization (AMICO) from diffusion MRI data
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BackgroundExamining and interpreting the female protective effect against autistic behavior
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“It is known that ASD females typically require a higher burden of rare, deleterious de novo mutations compared to males with ASD [47], and this effect extends into the general population when examining autistic traits in typically-developing individuals [48].”
BackgroundUK Biobank: Current status and what it means for epidemiology
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“Data on many thousands of further MRI scans (to a maximum sample of 100,000 with MRI data) will be available from UK Biobank in the coming months and years, in addition to more complex cognitive testing batteries and genotypic data.”
BackgroundMethodInfluentialGur, R. C., Richard, J., Calkins, M. E., Chiavacci, R., Hansen, J. A., Bilker, W. B., Loughead, J., Connolly, J. J., Qiu, H., Mentch, F. D., et al. (2012) · Neuropsychology · doi:10.1037/a0026712 · Cited by 507 · cited 1×
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BackgroundAgeing and brain white matter structure in 3,513 UK Biobank participants
Cox, S. R., Ritchie, S. J., Tucker-Drob, E. M., Liewald, D. C., Hagenaars, S. P., Davies, G., Wardlaw, J. M., Gale, C. R., Bastin, M. E., & Deary, I. J. (2016) · Nature Communications · doi:10.1038/ncomms13629 · Cited by 487 · cited 3×
“Other diffusion and NODDI measures of white matter microstructure such as radial and axial diffusivity and intracellular volume fraction (Cox et al. 2016), cortical measures such as regional gyrification (Gregory et al.”
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Evaluating gender similarities and differences using metasynthesis.
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“2003), and would assist in explaining several behavioral sex differences (Zell et al. 2015; Gur and Gur 2017).”
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“For example, rates of Alzheimer’s Disease are higher in females than males, prompting a recent call for the prioritisation of biomedical research into sex differences [13].”
BackgroundDiffusion tensor imaging of the brain: review of clinical applications
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“Studies that have attempted to quantify sex differences in white matter microstructure with diffusion tensor MRI —which uses information about the movement of water molecules through the brain’s white matter tracts to produce measures such as fractional anisotropy (FA), which has been linked to variation in cognitive…”
BackgroundMother's curse: the effect of mtDNA on individual fitness and population viability
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“This complexity is deepened by phenomena such as genomic imprinting (where the expression profiles of certain genes differs according to whether they were inherited paternally or maternally, which has been hypothesized to contribute to the aforementioned sex-biased nature of some psychiatric disorders; Dulac and Chris…”
BackgroundChanges in Thickness and Surface Area of the Human Cortex and Their Relationship with Intelligence
Schnack, H. G., van Haren, N. E. M., Brouwer, R. M., Evans, A. C., Durston, S., Boomsma, D. I., Kahn, R. S., & Pol, H. E. H. (2014) · Cerebral Cortex · doi:10.1093/cercor/bht357 · Cited by 407
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“Following gradient distortion correction, and further correction for head movement and eddy currents, BEDPOSTx was used to model within-voxel multi-fiber tract orientation, followed by probabilistic tractography (with crossing fiber modeling) using PROBTRACKx (Behrens et al. 2003, 2007; Jbabdi et al. 2012).”
MethodGender effects on cortical thickness and the influence of scaling
Eileen Luders, A., Narr, K. L., Thompson, P. M., Rex, D., Woods, R. P., DeLuca, H., Jäncke, L., & Toga, A. W. (2005) · Human Brain Mapping · doi:10.1002/hbm.20187 · Cited by 355 · cited 1×
“[27-29]), though our greater statistical power allowed us to find smaller differences in thickness across the cortex.”
BackgroundMETASTROKE Consortium, I. C. F. B. P. G., Hagenaars, S. P., SpiroMeta Consortium, CHARGE Consortium Pulmonary Group, C. C. A. A. L. G., Harris, S. E., Davies, G., Hill, W. D., Liewald, D. C. M., Ritchie, S. J., Marioni, R. E., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.225 · Cited by 350 · cited 1×
“Although the tests—particularly verbal-numerical reasoning—have some external validity (Hagenaars et al. 2016), the above issues mean that the cogni-”
BackgroundSelf-citationSex differences in Alzheimer's disease and other dementias
Mazure, C. M., & Swendsen, J. (2016) · The Lancet Neurology · doi:10.1016/s1474-4422(16)00067-3 · Cited by 350 · cited 4×
“For example, rates of Alzheimer’s Disease are higher in females than males, prompting a recent call for the prioritisation of biomedical research into sex differences [13].”
BackgroundInfluentialPietschnig, J., Penke, L., Wicherts, J. M., Zeiler, M., & Voracek, M. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.09.017 · Cited by 316
Brain white matter tract integrity as a neural foundation for general intelligence
Penke, L., Maniega, S. M., Bastin, M. E., Hernández, M. C. V., Murray, C. L., Royle, N. A., Starr, J. M., Wardlaw, J. M., & Deary, I. J. (2012) · Molecular Psychiatry · doi:10.1038/mp.2012.66 · Cited by 303 · cited 1×
“linking white matter microstructure to cognitive processing speed (Penke et al. 2012; Bennett and Madden 2014), white matter microstructural measures only mediated a small proportion of the sex difference in reaction time (this may have been due to weaknesses in this cognitive measure; see below).”
BackgroundSelf-citationFetal Testosterone Influences Sexually Dimorphic Gray Matter in the Human Brain
Lombardo, M. V., Ashwin, E., Auyeung, B., Chakrabarti, B., Taylor, K., Hackett, G., Bullmore, E. T., & Baron-Cohen, S. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.4389-11.2012 · Cited by 302
Self-citationGennatas, E. D., Avants, B. B., Wolf, D. H., Satterthwaite, T. D., Ruparel, K., Ciric, R., Hakonarson, H., Gur, R. E., & Gur, R. C. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3550-16.2017 · Cited by 302 · cited 3×
“2008; note that the insula showing the largest sex difference is consistent with a recent large-scale study of children and adolescents (Gennatas et al. 2017)—it appears this region retains its substantial sex difference into later life), but also areas such as the right fusiform gyrus.”
BackgroundResultEnlarged Perivascular Spaces and Cerebral Small Vessel Disease
Potter, G. M., Doubal, F. N., Jackson, C. A., Chappell, F. M., Sudlow, C. L., Dennis, M. S., & Wardlaw, J. M. (2015) · International Journal of Stroke · doi:10.1111/ijs.12054 · Cited by 296 · cited 1×
“2015) and enlarged perivascular spaces (Potter et al. 2015) may show interesting patterns of sex differences both across the population, and in how they relate to healthy behavioral variation as well as disease states.”
BackgroundDawson, G., Ashman, S. B., & Carver, L. J. (2000) · Development and Psychopathology · doi:10.1017/s0954579400004089 · Cited by 268 · cited 1×
“development (Dawson et al. 2000) was beyond the scope of our research and our dataset.”
BackgroundRippon, G., Jordan-Young, R. M., Kaiser, A., & Fine, C. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00650 · Cited by 266 · cited 1×
“The issue of adjusting for overall brain size in analyses of sex differences (Rippon et al. 2014) was addressed in each of our macrostructural analyses.”
BackgroundPrevalence of sexual dimorphism in mammalian phenotypic traits
Karp, N. A., Mason, J., Beaudet, A. L., Benjamini, Y., Bower, L., Braun, R. E., Brown, S. D. M., Chesler, E. J., Dickinson, M. E., Flenniken, A. M., et al. (2017) · Nature Communications · doi:10.1038/ncomms15475 · Cited by 257 · cited 1×
“It has been noted by several researchers that the potential influences of sex are underexplored in neuroscientific research (Beery and Zucker 2011; Cahill 2006, 2017; Karp et al. 2017).”
BackgroundLyall, D. M., Cullen, B., Allerhand, M. H., Smıth, D. J., Mackay, D., Evans, J. J., Anderson, J. J., Fawns‐Ritchie, C., McIntosh, A. M., Deary, I. J., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154222 · Cited by 247 · cited 1×
“The cognitive measures were relatively psychometrically poor compared to a full IQ assessment: the verbalnumerical reasoning had only 13 items, and the reaction time test had only 4 trials that counted towards the final score (see [59] for analyses of their reliability).”
MethodSelf-citationOlds, T., Tomkinson, G. R., Léger, L., & Cazorla, G. (2006) · Journal of Sports Sciences · doi:10.1080/02640410500432193 · Cited by 241 · cited 1×
“2013), and a range of physical traits such as athletic performance (Olds et al. 2006), and both birth and adult weight (Lehre et al.”
BackgroundSex differences in normal age trajectories of functional brain networks
Scheinost, D., Finn, E. S., Tokoglu, F., Shen, X., Papademetris, X., Hampson, M., & Constable, R. T. (2014) · Human Brain Mapping · doi:10.1002/hbm.22720 · Cited by 240 · cited 1×
“As has been noted (Scheinost et al. 2015), a better characterization of broad patterns, including sex differences, in relatively novel measures such as functional connectivity (and in the NODDI parameters described above) is of importance to establish a “baseline” upon which future studies of normal versus abnormal fu…”
BackgroundSelf-citationBeyond differences in means: robust graphical methods to compare two groups in neuroscience
Rousselet, G. A., Pernet, C. R., & Wilcox, R. R. (2017) · European Journal of Neuroscience · doi:10.1111/ejn.13610 · Cited by 225 · cited 1×
“This was confirmed by computing shift functions (Rousselet et al. 2017) for each overall and subcortical brain structure, illustrated in Figure S2a for the raw values and Figure S2b for the values cor-”
MethodGur, R. E., & Gur, R. C. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.07.035 · Cited by 211
Global Sex Differences in Test Score Variability
Machin, S. J., & Tuomas Pekkarinen, Y. (2008) · Science · doi:10.1126/science.1162573 · Cited by 211
Definition and characterization of an extended social-affective default network
Amft, M., Bzdok, D., Laird, A. R., Fox, P. T., Schilbach, L., & Eickhoff, S. B. (2015) · Brain Structure and Function · doi:10.1007/s00429-013-0698-0 · Cited by 208
de Groot, M., Vernooij, M. W., Klein, S., Ikram, M. A., Vos, F. M., Smith, S. M., Niessen, W. J., & Andersson, J. L. R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.015 · Cited by 205
Brain size, sex, and the aging brain
Jäncke, L., Mérillat, S., Liem, F., & Hänggi, J. (2014) · Human Brain Mapping · doi:10.1002/hbm.22619 · Cited by 204 · cited 1×
“2017) or somewhat limited in the number of brain measures they report (Jäncke et al. 2015).”
BackgroundGender Differences in White Matter Microstructure
Kanaan, R., Allin, M. P. G., Picchioni, M., Barker, G. J., Daly, E., Shergill, S. S., Woolley, J., & McGuire, P. K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0038272 · Cited by 204 · cited 2×
“Whereas previous work has found some white matter regions where fractional anisotropy was higher for females (Kanaan et al. 2012; Dunst et al. 2014), we found that males”
BackgroundSex Differences in Variability in General Intelligence: A New Look at the Old Question
Johnson, W., Carothers, A. D., & Deary, I. J. (2008) · Perspectives on Psychological Science · doi:10.1111/j.1745-6924.2008.00096.x · Cited by 202 · cited 1×
“this context has been cognitive ability: almost universally, studies have found that males show greater variance in this trait (Deary et al. 2007a; Johnson et al. 2008; Lakin 2013; though see Iliescu et al. 2016).”
BackgroundSelf-citationThe human hippocampus is not sexually-dimorphic: Meta-analysis of structural MRI volumes
Tan, A., Ma, W., Vira, A., Marwha, D., & Eliot, L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.08.050 · Cited by 180 · cited 1×
“With regard to the hippocampus, however, we found results consistent with another recent meta-analysis (Tan et al. 2016): there were no longer significant sex differences after adjustment for total brain volume (this was also the case for the thalamus and caudate).”
ResultTang, Y., Hojatkashani, C., Dinov, I. D., Sun, B., Fan, L., Lin, X., Qi, H., Hua, X., Liu, S., & Toga, A. W. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.111 · Cited by 177 · cited 1×
“We first adjusted all variables for age and ethnicity (both of which may have been associated with differences in brain measures; Cox et al. 2016; Isamah et al. 2010; Tang et al. 2010).”
MethodComplementarity of sex differences in brain and behavior: From laterality to multimodal neuroimaging
Gur, R. C., & Gur, R. E. (2016) · Journal of Neuroscience Research · doi:10.1002/jnr.23830 · Cited by 165
Explaining the sex difference in dyslexia
Arnett, A. B., Pennington, B. F., Peterson, R. L., Willcutt, E. G., DeFries, J. C., & Olson, R. K. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12691 · Cited by 162
Wierenga, L. M., Sexton, J. A., Laake, P., Giedd, J. N., Tamnes, C. K., & the Pediatric Imaging, N. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx154 · Cited by 152 · cited 2×
“To our knowledge, only two prior studies have explicitly examined sex differences in the variability of brain structure (Wierenga et al. 2017; Lange et al. 1997), and no studies have done so in”
BackgroundVariability of human brain structure size: ages 4–20 years
Lange, N., Giedd, J. N., Xavier Castellanos, F., Vaituzis, A. C., & Rapoport, J. L. (1997) · Psychiatry Research: Neuroimaging · doi:10.1016/s0925-4927(96)03054-5 · Cited by 134 · cited 1×
“To our knowledge, only two prior studies have explicitly examined sex differences in the variability of brain structure (Wierenga et al. 2017; Lange et al. 1997), and no studies have done so in”
BackgroundMeta-analysis reveals a lack of sexual dimorphism in human amygdala volume
Marwha, D., Halari, M., & Eliot, L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.021 · Cited by 127 · cited 1×
“A recent meta-analysis of sex differences in amygdala volume (Marwha et al. 2016) found that, although males showed larger raw volume, after correction for total brain volume there was no longer an appreciable sex difference.”
BackgroundKarama, S., Bastin, M. E., Murray, C. L., Royle, N. A., Penke, L., Maniega, S. M., Gow, A. J., Corley, J., Hernández, M. V., Lewis, J. D., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.64 · Cited by 127
Self-citationLehre, A., Lehre, K. P., Laake, P., & Danbolt, N. C. (2008) · Developmental Psychobiology · doi:10.1002/dev.20358 · Cited by 127 · cited 1×
“2006), and both birth and adult weight (Lehre et al. 2009a).”
BackgroundImpact of Sex and Gonadal Steroids on Neonatal Brain Structure
Knickmeyer, R. C., Wang, J., Zhu, H., Geng, X., Woolson, S., Hamer, R. M., Konneker, T., Styner, M., & Gilmore, J. H. (2014) · Cerebral Cortex · doi:10.1093/cercor/bht125 · Cited by 109 · cited 1×
“[35]), though this does not imply that the pattern of adult differences we observed is necessarily the same as is found in”
ResultRegional Variations in Brain Gyrification Are Associated with General Cognitive Ability in Humans
Gregory, M. D., Kippenhan, J. S., Dickinson, D., Carrasco, J., Mattay, V. S., Weinberger, D. R., & Berman, K. F. (2016) · Current Biology · doi:10.1016/j.cub.2016.03.021 · Cited by 101 · cited 1×
“2016), cortical measures such as regional gyrification (Gregory et al. 2016) and grey matter density (Ruigrok et al.”
BackgroundPower-up: A Reanalysis of 'Power Failure' in Neuroscience Using Mixture Modeling
Nord, C. L., Valton, V., Wood, J., & Roiser, J. P. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3592-16.2017 · Cited by 91 · cited 2×
“Given the surfeit of small-n studies in neuroscience (Button et al. 2013; Nord et al. 2017), it is of great importance to test hypotheses in large, well-powered samples, especially given that many neural sex differences are modest in size (Joel et al.”
BackgroundGender consistency and difference in healthy adults revealed by cortical thickness
Lv, B., Li, J., He, H., Li, M., Zhao, M., Ai, L., Yan, F., Xian, J., & Wang, Z. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.020 · Cited by 91 · cited 1×
“Our finding that raw cortical thickness was greater for females—a finding with a smaller mean effect than the one in the opposite direction for volume or surface area—is consistent with a number of previous, smaller studies (e.g., Luders et al. 2006; Sowell et al. 2007; Lv et al. 2010; van Velsen et al. 2013; though n…”
ResultDeary, I. J., Paul Irwing, B., Der, G., & Bates, T. C. (2006) · Intelligence · doi:10.1016/j.intell.2006.09.003 · Cited by 90 · cited 1×
“this context has been cognitive ability: almost universally, studies have found that males show greater variance in this trait (Deary et al. 2007a; Johnson et al. 2008; Lakin 2013; though see Iliescu et al. 2016).”
BackgroundSelf-citationBrain cortical thickness in the general elderly population: The Rotterdam Scan Study
van Velsen, E. F. S., Vernooij, M. W., Vrooman, H. A., van der Lugt, A., Breteler, M. M. B., Albert Hofman, D., Niessen, W. J., & Ikram, M. A. (2013) · Neuroscience Letters · doi:10.1016/j.neulet.2013.06.063 · Cited by 89
Gobinath, A. R., Choleris, E., & Galea, L. A. M. (2017) · Journal of Neuroscience Research · doi:10.1002/jnr.23872 · Cited by 87 · cited 1×
“Females also show a higher prevalence of major depressive disorder (Rutter et al. 2003; Gobinath et al. 2017), whereas males display higher rates of disorders such as autism spectrum disorder (Baron-Cohen et al.”
BackgroundTHE VARIABILITY IS IN THE SEX CHROMOSOMES
Reinhold, K., & Engqvist, L. (2013) · Evolution · doi:10.1111/evo.12224 · Cited by 82 · cited 1×
“One potential candidate to explain greater male variability across multiple phenotypes is the hypothesized “female-protective” mechanism involving effects of the X chromosome (Craig et al. 2009; Johnson et al. 2009; Reinhold and Engqvist 2013), or other protective factors that might “buffer” females from potential del…”
BackgroundSex differences in the IQ-white matter microstructure relationship: A DTI study
Dunst, B., Benedek, M., Koschutnig, K., Jauk, E., & Neubauer, A. C. (2014) · Brain and Cognition · doi:10.1016/j.bandc.2014.08.006 · Cited by 73 · cited 2×
“Whereas previous work has found some white matter regions where fractional anisotropy was higher for females (Kanaan et al. 2012; Dunst et al. 2014), we found that males”
BackgroundIliescu, D., Ilie, A., Ispas, D., Dobrean, A., & Clinciu, A. I. (2016) · Intelligence · doi:10.1016/j.intell.2016.06.007 · Cited by 68 · cited 1×
“The best-studied human phenotype in this context has been cognitive ability: almost universally, studies have found that males show greater variance in this trait ([6,18,39], though see [40]).”
BackgroundDo men vary more than women in personality? A study in 51 cultures
Borkenau, P., McCrae, R. R., & Terracciano, A. (2012) · Journal of Research in Personality · doi:10.1016/j.jrp.2012.12.001 · Cited by 67 · cited 1×
“2009a, 2009b), other psychological characteristics such as personality (Borkenau et al. 2013), and a range of physical traits such as athletic performance (Olds et al.”
BackgroundSex differences in mouse cortical thickness are independent of the complement of sex chromosomes
Markham, J. A., Jurgens, H. A., Auger, C. J., Vries, G. J. D., Arnold, A. P., & Juraska, J. M. (2003) · Neuroscience · doi:10.1016/s0306-4522(02)00554-7 · Cited by 63 · cited 1×
“the animal literature found greater cortical thickness in male mice (Markham et al. 2003); however, this study had a small sample size and by necessity used very different methods from ours: further comparison of sex differences in the brains across”
MethodIsamah, N., Faison, W. E., Payne, M. E., MacFall, J. R., Steffens, D. C., Beyer, J. L., Krishnan, K. R., & Taylor, W. D. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013642 · Cited by 60 · cited 1×
“We first adjusted all variables for age and ethnicity (both of which may have been associated with differences in brain measures; Cox et al. 2016; Isamah et al. 2010; Tang et al. 2010).”
MethodBrain cortical characteristics of lifetime cognitive ageing
Cox, S. R., Bastin, M. E., Ritchie, S. J., Dickie, D. A., Liewald, D., Maniega, S. M., Redmond, P. H., Royle, N. A., Pattie, A., Hernández, M. V., et al. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1505-0 · Cited by 59
Self-citationDykiert, D., Galé, C. R., & Deary, I. J. (2008) · Intelligence · doi:10.1016/j.intell.2008.06.002 · Cited by 59 · cited 1×
“This may be due to problems of sample representativeness (see [57]), or due to the tests tapping specific cognitive skills rather than general ability [58].”
BackgroundSelf-citationHow distinct Arp2/3 complex variants regulate actin filament assembly
Rottner, K., & Stradal, T. E. B. (2015) · Nature Cell Biology · doi:10.1038/ncb3293 · Cited by 59
A Role for the X Chromosome in Sex Differences in Variability in General Intelligence?
Johnson, W., Carothers, A. D., & Deary, I. J. (2009) · Perspectives on Psychological Science · doi:10.1111/j.1745-6924.2009.01168.x · Cited by 57 · cited 1×
“One potential candidate to explain greater male variability across multiple phenotypes is the hypothesized “female-protective” mechanism involving effects of the X chromosome (Craig et al. 2009; Johnson et al. 2009; Reinhold and Engqvist 2013), or other protective factors that might “buffer” females from potential del…”
BackgroundSelf-citationLakin, J. M. (2013) · Intelligence · doi:10.1016/j.intell.2013.04.004 · Cited by 55
Sex differences in brain volume are related to specific skills, not to general intelligence
Burgaleta, M., Head, K., Álvarez‐Linera, J., Martínez, K., Escorial, S., Haier, R. J., & Colom, R. (2011) · Intelligence · doi:10.1016/j.intell.2011.10.006 · Cited by 55 · cited 1×
“2009), or due to the tests tapping specific cognitive skills rather than general ability (Burgaleta et al. 2012).”
BackgroundCahill, L. F. (2016) · Journal of Neuroscience Research · doi:10.1002/jnr.23972 · Cited by 51 · cited 1×
“fields, such as neuroscience, the potential effects of sex are not always considered [10-12].”
BackgroundHandbook of Frontal Lobe Assessment (DRAFT)
MacPherson, S. E., Sala, S. D., Cox, S. R., Girardi, A., & Iveson, M. H. (2015) · Oxford University Press eBooks · doi:10.1093/med:psych/9780199669523.001.0001 · Cited by 40
Self-citationMaeda, Y., & Yoon, S. Y. (2012) · Educational Psychology Review · doi:10.1007/s10648-012-9215-x · Cited by 39 · cited 1×
“For instance, performance on mental rotation tasks (Maeda and Yoon 2013) and physical aggression (Archer 2004) are on average higher in males, whereas self-reported interest in people versus things (Su et al.”
BackgroundZhang, T., Casanova, R., Resnick, S. M., Manson, J. E., Baker, L. D., Padual, C. B., Kuller, L. H., Bryan, R. N., Espeland, M. A., & Davatzikos, C. A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0150834 · Cited by 32 · cited 1×
“(Zhang et al. 2016), effects which may themselves change with increasing age.”
BackgroundPatterns of cortical degeneration in an elderly cohort with cerebral small vessel disease
Reid, A., van Norden, A. G. W., de Laat, K. F., van Oudheusden, L. J. B., Zwiers, M. P., Evans, A. C., de Leeuw, F., & Kötter, R. (2010) · Human Brain Mapping · doi:10.1002/hbm.20994 · Cited by 31 · cited 1×
“Our finding that raw cortical thickness was greater for females—a finding with a smaller mean effect than the one in the opposite direction for volume or surface area—is consistent with a number of previous, smaller studies (e.g., Luders et al. 2006; Sowell et al. 2007; Lv et al. 2010; van Velsen et al. 2013; though n…”
ResultHandbook of Frontal Lobe Assessment
MacPherson, S. E., Sala, S. D., Cox, S. R., Girardi, A., & Iveson, M. H. (2015) · Cited by 27
Self-citationGender and the 2003 Quality Reform in higher education in Norway
Lehre, A., Hansen, A., & Laake, P. (2009) · Higher Education · doi:10.1007/s10734-009-9211-3 · Cited by 10 · cited 1×
“This has also been found to be the case for academic achievement test results (a potential consequence of intelligence differences [8,41,42]), other psychological characteristics such as personality [7], and a range of physical traits such as athletic performance [43], and both birth and adult weight [8].”
BackgroundCraig, I., Haworth, C. M. A., & Plomin, R. J. (2009) · Perspectives on Psychological Science · doi:10.1111/j.1745-6924.2009.01170.x · Cited by 8 · cited 1×
“Since males carry only one X chromosome, this effect cannot occur, increasing the likelihood of the allele being expressed in males, and thus increasing the variation in the phenotype linked to that allele [44,46].”
BackgroundGenomic Imprinting in the Adult and Developing Brain
Dulac, C. G., & Christopher, G. (2012) · Research and perspectives in endocrine interactions · doi:10.1007/978-3-642-33721-5_3 · Cited by 2 · cited 1×
“This complexity is deepened by phenomena such as genomic imprinting (where the expression profiles of certain genes differs according to whether they were inherited paternally or maternally, which has been hypothesized to contribute to the aforementioned sex-biased nature of some psychiatric disorders; Dulac and Chris…”
Background
Research works printed but not linked: 2
- Fine, 2017, Testosterone Rex: unmaking the myths of our gendered minds
- Maeda, 2013, Ed Psychol Rev, 69
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Metadata
- Authors
- Ritchie, S. J., Cox, S. R., Shen, X., Lombardo, M. V., Reus, L. M., Alloza, C., Harris, M. A., Alderson, H. L., Hunter, S., Neilson, E., Liewald, D. C. M., Auyeung, B., Whalley, H. C., Lawrie, S. M., Gale, C. R., Bastin, M. E., McIntosh, A. M., & Deary, I. J.
- Affiliations
- University of Edinburgh (GB)
- University of Cambridge (GB)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
- Queen Margaret Hospital (GB)
- NHS Lothian (GB)
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Corresponding author
- Ritchie, Stuart J
- ORCID
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-05-16
- Volume
- 28
- Issue
- 8
- Pages
- 2959-2975
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- PMC
- PMC6041980
- OpenAlex
- W2952574438
- Cited by
- 855
- References
- 125
- Citations by year
- 2026: 75 · 2025: 86 · 2024: 101 · 2023: 110 · 2022: 105 · 2021: 130 · 2020: 138 · 2019: 68 · 2018: 35
- FWCI
- 88.29
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cerebral Cortex (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- ePrints Soton (University of Southampton) (acceptedVersion)
- Pure Amsterdam UMC (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- CCACE (MR/K026992/1)
- MRC (MR/M013111/1)
- Dementias Platform UK (MR/L015382/1)
- STRADL (104036/Z/14/Z)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Sex and Gender in Healthcare
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- sex differences, adult human brain, brain structure, brain function, brain volume, cortical thickness, white matter fractional anisotropy, functional connectome, default mode network, sensorimotor cortex, UK Biobank
- MeSH terms
- Adult, Aged, Brain, Brain Mapping, Female, United Kingdom, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Oxygen, Rest, Sex Characteristics, Biological Specimen Banks, Community Health Planning, Connectome, White Matter
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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