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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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“…quantitative, in which the distribution differs between the two sexes but largely overlaps, as is the case with height or brain volume (Maney, 2016; Ritchie et al., 2018), as well as many physiological traits such as stress (Bangasser & Wicks, 2017), opioid sensitivity (Averitt, Eidson, Doyle, &…”
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“assessed sex differences in one DTI metric (FA) and one NODDI metric (OD), among other non-dMRI measures, and similarly supported the existence of significant white matter differences between men and women for a range of tracts (Ritchie et al., 2018).”
InfluentialWierenga, L. M., Bos, M. G. N., van Rossenberg, F., & Crone, E. A. (2019) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01375 · Cited by 83
When your brain looks older than expected: combined lifestyle risk and BrainAGE
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Biological Sex: A Potential Moderator of Physical Activity Efficacy on Brain Health
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“Aligning with this finding, the UK Biobank study reported that across 2,750 female and 2,466 male participants between the age of 44–77 years, a significantly stronger connectivity in the default mode network was observed in females compared to males (Ritchie et al., 2018), for which the same findings were reported in…”
ResultRegion-specific sex differences in the hippocampus
van Eijk, L., Hansell, N. K., Strike, L. T., Couvy‐Duchesne, B., de Zubicaray, G. I., Thompson, P. M., McMahon, K. L., Zietsch, B. P., & Wright, M. J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116781 · Cited by 77
“Regional brain volumes also show size differences in this direction, but these findings are inconsistent once intracranial or total brain volume is used as a correction factor (Kaczkurkin et al., 2019; Ritchie et al., 2018).”
Sex/gender differences in cognitive abilities
Kheloui, S., Jacmin-Park, S., Larocque, O., Kerr, P., Rossi, M., Cartier, L., & Juster, R.-P. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105333 · Cited by 78
Harrison, L. M., Noble, D. W. A., & Jennions, M. D. (2021) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/brv.12818 · Cited by 79
Zhang, X., Liang, M., Qin, W., Wan, B., Yu, C., & Ming, D. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00244 · Cited by 71
“…that different part of the prefrontal cortex may be involved differently in females and males during certain cognitive-motor control tasks (Rubia et al., 2013; Koch et al., 2007), which may explain the present finding that, for the FCs between prefrontal areas and SMA/cerebellum, some…”
BackgroundX-chromosome regulation and sex differences in brain anatomy
Raznahan, A., & Distèche, C. M. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.10.024 · Cited by 69
“scale studies(Lotze et al., 2019; Ritchie et al., 2018; Ruigrok et al., 2014), but also showed that the spatial patterning of these sex-differences was highly consistent within and between different neuroimaging datasets (Figure 5).”
InfluentialMartin, A. K., Huang, J., Hunold, A., & Meinzer, M. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.10.005 · Cited by 67
“A recent large study (N= 5216) identified greater connectivity in females in the default mode network (DMN) which includes the mPFC (Ritchie, 2017).”
BackgroundInfluentialLee, J. J., McGue, M. K., Iacono, W. G., Michael, A. M., & Chabris, C. F. (2019) · Intelligence · doi:10.1016/j.intell.2019.01.011 · Cited by 71
“These differences are consistent with those observed in a recent study of a larger sample (Ritchie et al., 2018).”
Associations of cigarette smoking with gray and white matter in the UK Biobank
Gray, J. C., Thompson, M. F., Benca‐Bachman, C. E., Owens, M. M., Murphy, M. A., & Palmer, R. H. C. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0630-2 · Cited by 70
Sex Differences in Variability of Brain Structure Across the Lifespan
Forde, N. J., Jeyachandra, J., Joseph, M. J. E., Jacobs, G. R., Dickie, E. W., Satterthwaite, T. D., Shinohara, R. T., Ameis, S. H., & Voineskos, A. N. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa123 · Cited by 66
Udeh-Momoh, C., & Watermeyer, T. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101459 · Cited by 67
Sex-specific impact of prenatal androgens on social brain default mode subsystems
Lombardo, M. V., Bonnie Auyeung, B., Pramparo, T., Quartier, A., Courraud, J., Holt, R., Waldman, J., Ruigrok, A. N. V., Mooney, N., Bethlehem, R. A. I., et al. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0198-y · Cited by 67
“Two large independent studies on adults utilizing the 1000 Functional Connectomes or UK Biobank datasets now replicably show that default mode connectivity is subtly on-average stronger in females than in males [49, 50].”
BackgroundResultSelf-citationKoppelmans, V., Silvester, B., & Duff, K. M. (2022) · Journal of Alzheimer s Disease Reports · doi:10.3233/adr-210065 · Cited by 66
The Complex Relationships between Sex and the Brain
Joel, D., Garcı́a-Falgueras, A., & Swaab, D. F. (2019) · The Neuroscientist · doi:10.1177/1073858419867298 · Cited by 66
Cho, J., Noh, Y., Kim, S., Sohn, J., Noh, J., Kim, W., Cho, S.-K., Seo, H., Seo, G., Lee, S., et al. (2020) · Environmental Health Perspectives · doi:10.1289/ehp7133 · Cited by 64
“Considering possible sex differences in cortical thickness and volume (Ritchie et al. 2018), we additionally investigated sex-specific associations between air pollutant concentrations and ROI-based brainMRI markers.”
BackgroundJockwitz, C., & Caspers, S. (2021) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-021-02520-7 · Cited by 72
“Sex differences in RSFC of the aged brain have been reported repeatedly, such that females show higher connectivity within the DMN, while males show higher RSFC for the somatomotor network [66, 83, 95].”
BackgroundZhou, X., Wu, R., Zeng, Y., Qi, Z., Ferraro, S., Xu, L., Zheng, X., Li, J., Fu, M., Yao, S., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-03880-1 · Cited by 66
“28 , we focused on biological variables, i.e., sex and age 9,10,29 – 32 .”
MethodResultVisual Information Processing in Young and Older Adults
Ebaid, D., & Crewther, S. G. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00116 · Cited by 65
“Though there is currently very little robust evidence to suggest gender-differences in cognitive performance in any age-group psychophysically and in neuroimaging (see Hill et al., 2014; Reed et al., 2017; Ritchie et al., 2018), future research may benefit from including an even spread of genders within their study wh…”
BackgroundSex is a defining feature of neuroimaging phenotypes in major brain disorders
Salminen, L. E., Tubi, M. A., Bright, J. K., Thomopoulos, S. I., Wieand, A., & Thompson, P. M. (2021) · Human Brain Mapping · doi:10.1002/hbm.25438 · Cited by 61
Interactions Between Age, Sex, Menopause, and Brain Structure at Midlife: A UK Biobank Study
Than, S., Moran, C., Beare, R. J., Vincent, A. J., Collyer, T. A., Wang, W., Callisaya, M. L., Thomson, R. J., Phan, T. G., Fornito, A., et al. (2020) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaa847 · Cited by 61
Hofmann, S., Beyer, F., Lapuschkin, S., Goltermann, O., Loeffler, M., Müller, K., Villringer, A., Samek, W., & Witte, A. V. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119504 · Cited by 67
Ryali, S., Zhang, Y., Angeles, C. D. L., Supekar, K., & Menon, V. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2310012121 · Cited by 71
“While the striatum has not been a primary focus of investigations into sex - specific differences in the functional organization of the human brain, there is a considerable evidence for sexual dimorphism in its anatomy (20, 29).”
InfluentialMaglanoc, L. A., Kaufmann, T., Jonassen, R., Hilland, E., Beck, D., Landrø, N. I., & Westlye, L. T. (2019) · Human Brain Mapping · doi:10.1002/hbm.24802 · Cited by 59
Brain network interactions in transgender individuals with gender incongruence
Uribe, C., Junqué, C., Gómez‐Gil, E., Abós, A., Mueller, S. C., & Guillamón, A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116613 · Cited by 60
Sex-specific Behavioral Features of Rodent Models of Autism Spectrum Disorder
Jeon, S. J., Gonzales, E. L., Mabunga, D. F. N., Valencia, S. T., Kim, D. G., Kim, Y., Adil, K. J., Shin, D., Park, D., & Shin, C. Y. (2018) · Experimental Neurobiology · doi:10.5607/en.2018.27.5.321 · Cited by 67
Holm, M. C., Leonardsen, E. H., Beck, D., Dahl, A., Kjelkenes, R., de Lange, A. G., & Westlye, L. T. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101220 · Cited by 59
“Although some sex-differences in brain structure are well replicated, such as a larger total brain volume in males, there are many inconsistent findings regarding sex-differences in brain morphology at large (Lenroot and Giedd, 2010; Ritchie et al., 2018).”
Why and How to Account for Sex and Gender in Brain and Behavioral Research
Eliot, L., Beery, A. K., Jacobs, E. G., LeBlanc, H. F., Maney, D. L., & McCarthy, M. M. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0020-23.2023 · Cited by 68
“For studies exploring regional brain differences between males and females, it is therefore necessary to control for total brain volume (TBV) or intracranial volume (ICV), which largely eliminates regional volume differences in humans (Jäncke et al., 2015 ; Ritchie et al., 2018).”
BackgroundIndividual variation underlying brain age estimates in typical development
Ball, G., Kelly, C. E., Beare, R. J., & Seal, M. L. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118036 · Cited by 62
Individual differences in developmental plasticity: A role for early androgens?
Giudice, M. D., Barrett, E. S., Belsky, J., Hartman, S., Martel, M. M., Sangenstedt, S., & Kuzawa, C. W. (2018) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2018.02.025 · Cited by 59
Kroll, D. S., Feldman, D. E., Biesecker, C. L., McPherson, K. L., Manza, P., Joseph, P. V., Volkow, N. D., & Wang, G. (2020) · Nutrients · doi:10.3390/nu12071942 · Cited by 63
“(2019) controlled for total brain volume or intracranial volume; recent studies have shown that when these measures are accounted for, many regional sex/gender differences disappear [29,30].”
BackgroundZhao, S., Wang, G., Yan, T., Xiang, J., Yu, X., Li, H., & Wang, B. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa335 · Cited by 56
Comprehensive evaluation of harmonization on functional brain imaging for multisite data-fusion
Wang, Y., Chen, X., & Yan, C. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120089 · Cited by 57
Sex differences in ability tilt in the right tail of cognitive abilities: A 35-year examination
Wai, J., Hodges, J., & Makel, M. C. (2018) · Intelligence · doi:10.1016/j.intell.2018.02.003 · Cited by 56
Sex Hormones and Gender Role Relate to Gray Matter Volumes in Sexually Dimorphic Brain Areas
Pletzer, B. A. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00592 · Cited by 55
Evidence for distinct biodevelopmental influences on male sexual orientation
Swift‐Gallant, A., Coome, L. A., Aitken, M., Monks, D. A., & VanderLaan, D. P. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1809920116 · Cited by 54
Sex Differences in Functional Brain Networks for Language
Xu, M., Liang, X., Ou, J., Li, H., Luo, Y., & Tan, L. H. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz184 · Cited by 54
Sex differences in brain modular organization in chronic pain
Fauchon, C., David Meunier, A., Rogachov, A., Hemington, K. S., Cheng, J. C., Bosma, R. L., Osborne, N. R., Kim, J. A., Hung, P. S.-P., Inman, R. D., et al. (2020) · Pain · doi:10.1097/j.pain.0000000000002104 · Cited by 57
“Interestingly, in our results, there were sex differences in functional connectivity (i.e., PC and WMD) of the DMN; findings in this network of interest has also been reported in several large cohort studies comparing male’s and female’s brain [5,77,88,91].”
Koenig, J., Abler, B., Agartz, I., Åkerstedt, T., Andreassen, O. A., Anthony, M., Bär, K., Bertsch, K., Brown, R. C., Brunner, R. M., et al. (2020) · Psychophysiology · doi:10.1111/psyp.13688 · Cited by 53
“More recently, the largest single-sample study drawing on data from the UK Biobank (n = 5,216) showed that although adult males have larger cortical and subcortical volumes—except the right insula—adult females showed greater CT in 47 out of 68 ROI investigated (Ritchie et al., 2018).”
Ma, D., Popuri, K., Bhalla, M., Sangha, O., Lu, D., Cao, J., Jacova, C., Wang, L., Beg, M. F., & Initiative, A. D. N. (2018) · Human Brain Mapping · doi:10.1002/hbm.24463 · Cited by 53
“Sex is also an important source of demographic-related variation in TIV and volumes of brain structures (Gur et al., 1991; Perlaki et al., 2014; Ritchie et al., 2018).”
BackgroundThe Superficial White Matter in Autism and Its Role in Connectivity Anomalies and Symptom Severity
Hong, S., Hyung, B., Paquola, C., & Bernhardt, B. C. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy321 · Cited by 53
“Models corrected for “Sex” and “Age” given their effects on brain morphology and diffusion properties (Phillips et al. 2013; Ritchie et al. 2018), “Site” to account for systematic differences in acquisition parameters, and average root-meansquare displacement of each DWI volume compared with the previous one as an ind…”
Result
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
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