Cited by 855Sex and Gender in HealthcareAdvanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies

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Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

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Ritchie, Stuart J, Cox, Simon R, Shen, Xueyi, Lombardo, Michael V, Reus, Lianne M, Alloza, Clara, Harris, Mathew A, Alderson, Helen L, Hunter, Stuart, Neilson, Emma, Liewald, David C M, Auyeung, Bonnie, Whalley, Heather C, Lawrie, Stephen M, Gale, Catharine R, Bastin, Mark E, McIntosh, Andrew M, Deary, Ian J·2018·Cerebral Cortex

DOI 10.1093/cercor/bhy109PMC PMC6041980

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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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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324 · cited 1×
“2007), according to the Desikan– Killiany atlas (Desikan et al. 2006).”
Method
Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888 · cited 1×
“The following preprocessing procedures were applied: motion correction using MCFLIRT (Jenkinson et al. 2002), grand-mean intensity normalization using a single multiplicative factor, high-pass temporal filtering with a Gaussian-weighted least-squares straight line fitting (sigma was set as 50.”
Method
The descent of man and selection in relation to sex
チャールス, ダ., & 茂穂, 田. (1907) · Tokyo Jinrui Gakkai zasshi · doi:10.1537/ase1887.22.495 · Cited by 10,909
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
Power failure: why small sample size undermines the reliability of neuroscience
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3475 · Cited by 7,641 · 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.”
Background
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628 · cited 1×
“2001, 2007a, 2007b) and FAST (Zhang et al. 2001), yielding cerebrospinal fluid (CSF), grey and white matter volumes.”
Background
How do you feel — now? The anterior insula and human awareness
(Bud) Craig, A. D. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2555 · Cited by 6,657
Measuring the thickness of the human cerebral cortex from magnetic resonance images
Fischl, B. R., & Dale, A. M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200033797 · Cited by 5,995
A New Initiative on Precision Medicine
Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202

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Titelei/Inhaltsverzeichnis
Herker, S. (2022) · Nomos Verlagsgesellschaft mbH & Co. KG eBooks · doi:10.5771/9783748932512-1 · Cited by 2
NBS-Predict: An easy-to-use toolbox for connectome-based machine learningPreprint
Serin, E., Vaidya, N., Walter, H., & Kruschwitz, J. (2023) · doi:10.31219/osf.io/cfm7j · Cited by 2
Sexual selection and sex differences in brain and cognition
Geary, D. C. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-820480-1.00032-2 · Cited by 2
Sex differences in deep brain shape and asymmetry persist across schizophrenia and healthy individuals: A meta-analysis from the ENIGMA-Schizophrenia Working GroupPreprint
Cimmino, D. B., Zabriskie, B. N., Luke, S. G., Gutman, B. A., Isaev, D., Alpert, K. I., Glahn, D. C., Rodrigue, A., Kelly, S., Pearlson, G. D., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.24.619733 · Cited by 2
“…work also has strong alignment with our findings, in a single-site study of 5,216 participants, greater volume of the amygdala, caudate, pallidum, putamen, and thalamus was observed in males compared to females, but with females showing greater volume in the accumbens (Ritchie et al., 2018).”
Result
No effect of additional education on long-term brain structure – a preregistered natural experiment in thousands of individualsPreprint
Judd, N., & Kievit, R. (2024) · eLife · doi:10.7554/elife.101526.1 · Cited by 2
Brain Size: To Adjust or Not Adjust? It’s Not a Matter of If, but HowPreprint
Brzezinski-Rittner, A., Moqadam, R., Zeighami, Y., & Dadar, M. (2025) · medRxiv · doi:10.1101/2025.09.21.25336298 · Cited by 2
“…subcortical brain regions appear to have significantly larger volumes in males than in females, females present with greater overall cortical thickness, and the effect of these differences decrease, or reveal different patterns when the analyses appropriately account for intracranial volume 19,20 .”
Brain Morphometry Differences Across Sexes Revealed Through Explainable Artificial Intelligence: A Human Connectome Project Young Adult Study
Camastra, C., Pelagi, A., Quattrone, A., & Sarica, A. (2025) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-82487-6_17 · Cited by 1
Happiness across Cultures and Genders
Kim‐Prieto, C., Heye, M., & Mangino, K. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.038 · Cited by 1
Women’s Leadership across Cultures
Reichard, R. J., Trainor, L. L., Jensen, K. L., & Macias‐Alonso, I. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.026 · Cited by 1
The Impact of Gender-affirming Hormone Therapy on Anatomic Structures of the Brain Among Transgender Individuals
O’Leary, K. B., & Garcia-Altieri, M. A. (2022) · Journal of Psychiatric Practice · doi:10.1097/pra.0000000000000633 · Cited by 1
Bleiberecht für Opfer von Hasskriminalität
Herker, S. (2022) · Nomos Verlagsgesellschaft mbH & Co. KG eBooks · doi:10.5771/9783748932512 · Cited by 1
Entorhinal Cortex Functional Connectivity during Item Long-Term Memory and the Role of Sex
Spets, D. S., & Slotnick, S. D. (2023) · Brain Sciences · doi:10.3390/brainsci13030446 · Cited by 1
“Resting-state studies have identified greater functional connectivity in sensorimotor, visual, and anterior lateral prefrontal regions for males than for females and greater functional connectivity within the default mode network for females than for males [9].”
Background
Sex differences in normal fetal regional brain apparent diffusion coefficient changes assessed by in utero DWI
Ren, J., Zhu, M., & Dong, S. (2024) · Frontiers in Pediatrics · doi:10.3389/fped.2024.1354475 · Cited by 1
Facial approximation of a skull with signs of tertiary syphilis found in the Skriðuklaustur monastery (Iceland, 15th-16th century AD)
Moraes, C. A. D. C., Varotto, E., Habicht, M. E., Sìneo, L., & Galassi, F. M. (2024) · Digital Applications in Archaeology and Cultural Heritage · doi:10.1016/j.daach.2024.e00362 · Cited by 1
Analysis of functional connectivity changes from childhood to old age: A study using HCP-D, HCP-YA, and HCP-A datasets
Wang, Y., Li, S., He, J., Peng, L., Wang, Q., Zou, X., Tudorascu, D., Schaeffer, D. J., Schaeffer, L. K. H., Szczupak, D., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag_a_00503 · Cited by 1
“…brain networks are well-documented in the literature ( Jockwitz & Caspers, 2021), with studies highlighting that women typically exhibit higher FC within the DMN ( Ju et al., 2023; Ritchie et al., 2018), while men show stronger FC within the SMN ( Stumme et al., 2020; Zonneveld et al., 2019).”
Connectomics modeling of regional networks of white-matter fractional anisotropy to predict the severity of young adult drinking
Li, Y., Li, G., Yang, L., Yan, Y., Zhang, N., Gao, M., Hao, D., Ye-Lin, Y., & Li, C.-S. R. (2025) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims-24-2131 · Cited by 1
Mid-Sagittal MRI Morphometry of the Corpus Callosum in High-Altitude Tibetan Populations: A Novel Quantitative Approach Using Circularity and Eccentricity
Zeng, K., Wu, H., Zhao, G.-X., Wang, Z.-F., Su, M.-R., Zhang, Z.-Y., Wang, Y., & Zhong, H. (2025) · Journal of Craniofacial Surgery · doi:10.1097/scs.0000000000011496 · Cited by 1
Genetic and environmental contributions to ReHo and fALFF in early adolescence vary across brain regions
Strike, L. T., McMahon, K. L., Medland, S. E., & de Zubicaray, G. I. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf143 · Cited by 1
Predicting brain volumes from anthropometric and demographic features: insights from UK biobank neuroimaging data
Nazarzadeh, K., Eickhoff, S. B., Antonopoulos, G., Hensel, L., Tscherpel, C., Komeyer, V., Raimondo, F., Grefkes, C., & Patil, K. R. (2026) · Brain Structure and Function · doi:10.1007/s00429-025-03070-9 · Cited by 1
Male Sex, Masculinization, Sexual Orientation, and Gynephilia Synergistically Predict Increased Sexual Jealousy
Kennair, L. E. O., Bendixen, M., & Schmitt, D. P. (2025) · Archives of Sexual Behavior · doi:10.1007/s10508-025-03225-z · Cited by 1
“…such as male sexual jealousy are reliably influenced by genetic, hormonal, and neurological differences between women and men (Ngun et al., 2011; Ritchie et al., 2018; Ruigrok et al., 2014; Trabzuni et al., 2013), this in no way implies dimorphic and completely non-overlapping “female brains”…”
Preliminary assessment of age- and sex-related differences in brain volume using Quantib™ brain quantification: a study in a Vietnamese cohort
Vu, D. L., Do, T. P. L., Nguyen, K. V., Nguyen, H. A., Nguyen, Q. A., Le, V. K., Trang, N. N., Võ, H. K., Nguyen, V. H., Nguyen, C. T., et al. (2025) · Frontiers in Neurology · doi:10.3389/fneur.2025.1552559 · Cited by 1
Beyond the Binary: When to Lump and When to Split in Sex Differences Research
Meltzer, A. L., & Hammock, E. A. D. (2025) · Archives of Sexual Behavior · doi:10.1007/s10508-025-03324-x · Cited by 1
Brain Sex: Differences That Do Not Differentiate
Baxendale, S. (2025) · Archives of Sexual Behavior · doi:10.1007/s10508-025-03306-z · Cited by 1
“Although group differences in brain volumes between males and females have been reliably reported in large-scale studies (Flint et al., 2020; Guillamon et al., 2016; Luders et al., 2009; Ritchie et al., 2018; Ruigrok et al., 2014), there is considerable overlap between the sexes.”
Intergenerational neuroimaging’s present and future: Considering sex as a biological variable to enhance knowledge of brain development through parent–offspring similarity
Matsudaira, I. Y., & Yamaguchi, R. (2025) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2025.101635 · Cited by 1
“…trajectories of each brain metric, readers are referred to other relevant empirical studies and review articles (Brain Development Cooperative Group, 2012; Cao et al., 2017; Lawrence et al., 2023; Lebel and Deoni, 2018; Raznahan et al., 2011; Ritchie et al., 2018; Wierenga et al., 2014a, 2014b).”
Sex differences in dynamic and static measures of brain integration derived from resting-state functional magnetic resonance imaging
Fang, X., Schwemmer, O., Hogan, A., & Marxen, M. (2026) · Biology of Sex Differences · doi:10.1186/s13293-026-00891-z · Cited by 1
“Moreover, stronger FC within the default mode network and reduced FC in sensorimotor cortices during rest have been reported in females [12, 13].”
Intracranial volume variation in Chinchorro mummies: a comparative study with pre-hispanic farmers and contemporary Chilean populations
Rojas-Costa, G. M., Silva-Pinto, V., Valenzuela-Sánchez, Y., de la Iglesia-Vayá, M., Molina‐Mateo, J., Salazar‐García, D. C., Valdes-Sosa, P. A., & Gálvez, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-25186-y · Cited by 1
CSF estrogens’ relationships to neuroinflammatory markers and brain networks in middle-aged and older black and white women
Hu, W. T., Butts, B., Misiura, M. B., Verble, D. D., Swatson, E., Park, C., Watson, J., Hammerschlag, B. L., Nayyar, A., Korrapati, N., et al. (2025) · Journal of Neuroinflammation · doi:10.1186/s12974-025-03657-3 · Cited by 3
“These are consistent with differences seen between men and women in the UK Biobank [83].”
The P300 response in hearing sciences: Mechanisms, measurement, and clinical use
Kurt, B., Yüksel, M., & Skarzynski, P. H. (2025) · Hearing Balance and Communication · doi:10.4103/hbc.hbc_30_25 · Cited by 1
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Halbertsma, H. N., Haykal, S., Willis, H., Bridge, H., Jansonius, N., & Cornelissen, F. W. (2026) · Brain Communications · doi:10.1093/braincomms/fcag023 · Cited by 1
“This adjustment was applied to both datasets, given previously reported sex differences in intracranial volume 39 even though the correlation between intracranial and fibre-bundle cross-section reached significance only in dataset 2 ( r = 0.36, P = 0.02) and not in dataset 1 ( r = 0.33, P = 0.13).”
Influential
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“…that human males have larger total brain volumes (approximately 10% larger) and higher gray and white matter volumes, particularly in regions like the amygdala, while human females have relatively larger cortical areas linked to language and emotion (Ruigrok et al., 2014 ; Ritchie et al., 2018).”
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DiPentima, A. R., Lyday, R. G., Laurienti, P. J., & Dagenbach, D. (2026) · Brain Imaging and Behavior · doi:10.1007/s11682-026-01070-9 · Cited by 1
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Zhang, F., Rushmore, J., Li, Y., Karayumak, S. C., Song, Y., Cai, W., Westin, C., Levitt, J. J., Makris, N., Yogesh Rathi, A., et al. (2026) · NeuroImage Clinical · doi:10.1016/j.nicl.2026.103979 · Cited by 1
“…Hasan et al., 2009; Herlin et al., 2024; Kitamura et al., 2011; Lebel et al., 2010; Lei et al., 2016; Liu et al., 2010; Liu et al., 2011; Nordahl et al., 2015; Oh et al., 2007; Ritchie et al., 2018; Thiebaut de Schotten et al., 2011; Wang et al., 2014; Wheelock et al., 2021; Zhang et al., 2014).”
Influential
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García-Navarra, S., Solares, L., & Mendez, M. (2026) · Behavioural Brain Research · doi:10.1016/j.bbr.2026.116227 · Cited by 2
A comparative assessment of age- and gender-related variations in brain morphometry using linear and volumetric MRI analysis
Gupta, S. K., & Rastogi, R. (2026) · BMC Medical Imaging · doi:10.1186/s12880-026-02283-6 · Cited by 1
Sex differences in activations to the sight of faces, scenes, body parts and tools in visual and non-visual cortical regions leading to the human hippocampus
Zhang, R.-H., Rolls, E. T., & Feng, J.-F. (2026) · Biology of Sex Differences · doi:10.1186/s13293-026-00933-6 · Cited by 1
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Yang, Y., Tao, L., Zhao, R., Bai, R., Liu, S., Zhang, G., Li, S., Xu, X., Cheng, Y., & Xu, J. (2026) · Lupus Science & Medicine · doi:10.1136/lupus-2026-002032 · Cited by 1
“These MRI-based imaging findings highlight the diverse patterns of brain structural”
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Wierenga, L. M., Zabihi, M., van Drunen, L., van der Meulen, M., Achterberg, M., Rutherford, S., Marquand, A. F., & Crone, E. A. (2026) · Behavioural Brain Research · doi:10.1016/j.bbr.2026.116350 · Cited by 1
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Zhang, D., Kwon, E., Danesh-Meyer, H. V., & Schierding, W. S. (2026) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.67.8.34 · Cited by 1
Gender and Adolescent Development across Cultures
Qu, Y., Zhang, S., Kalindi, S. C., Yang, B., & Wang, Q. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.010 · Cited by 1
Sex and Gender in Psychopathology
Lefler, E. K., & Hartung, C. M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.043 · Cited by 1
[A review on the application of UK Biobank in neuroimaging].
Lin, L., Xiong, M., & Wu, S. (2021) · PubMed Central · doi:10.7507/1001-5515.202012059 · Cited by 2
A Stereological Study of the Three Types of Ganglia of Male, Female, and Undifferentiated Scrobicularia plana (Bivalvia)
Tantiwisawaruji, S., Rocha, M. J., Silva, A., Pardal, M. Â., Kovitvadhi, U., & Rocha, E. (2022) · Animals · doi:10.3390/ani12172248 · Cited by 2
“As mentioned, the total volume of the entire nervous system organs and the number of neural cells are parameters found to differ in males and females and vertebrates and invertebrates [12,13,16].”
Background
A Gender-Based Point of View in Pediatric Neurology
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“Two studies underlined how assigned males at birth show a greater variance in the hippocampus, pallidum and putamen compared to assigned females at birth [21,31].”
Background
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Matos, K. D., Cury, C., Chougar, L., Strike, L. T., Rolland, T., Riche, M., Hemforth, L., Martin, A., Banaschewski, T., Bokde, A. L. W., et al. (2023) · Brain Structure and Function · doi:10.1007/s00429-023-02663-6 · Cited by 1
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Biggins, K., & Tubbs, R. S. (2023) · Springer eBooks · doi:10.1007/978-3-031-38114-0_37 · Cited by 1
An MRI Study of Morphology, Asymmetry, and Sex Differences of Inferior Precentral Sulcus
Zhao, X., Wang, Y., Wu, X., & Liu, S. (2024) · Brain Topography · doi:10.1007/s10548-024-01035-5 · Cited by 1
“On the other hand, adult females are characterized by a thicker and denser cortex (Raz et al. 1997; Cosgrove et al. 2007; Ritchie et al. 2018; Luders et al. 2005).”
Background
Exploring dynamical whole-brain models in high-dimensional parameter spaces
Wischnewski, K. J., Jarre, F., Eickhoff, S. B., & Popovych, O. V. (2025) · PLoS ONE · doi:10.1371/journal.pone.0322983 · Cited by 1
Clinical validation pipeline of a deep learning model for segmenting and quantifying intracranial and ventricular volumes on computed tomography
Pinto, B. G. G., Olegário, T. M. M., Silva, P. V. A., Ferracioli, G. M., Paulo, A. J. M., Schumacher, K., Cunha, M. T., Lee, H. M. H., Rodrigues, M. A. S., Kitamura, F., et al. (2026) · Scientific Reports · doi:10.1038/s41598-026-49678-7 · Cited by 1
“…metrics may be attributed to variations in the size of the segmented structures, as female ventricles are typically smaller, confirmed by both DeepCTE3D-generated and GT masks 54–58 and that Hausdorff distance, which is less sensitive to object size, showed no significant sex-related differences.”
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“Zudem können individuelle Einaussfaktoren wie Alter, Geschlecht und Persönlichkeitsprole einen Einauss auf zahlreiche Entitäten der Bildgebung haben [76, 77, 78, 79].”
Decoding Sex Differences in the Brain, One Worm at a Time
Wang, C. (2018) · Gender and the Genome · doi:10.1177/2470289718789306 · Cited by 1
“2(3) 76-80 a The Author(s) 2018 Article reuse guidelines: sagepub.”
cInvestigation of Brain Volume and Brain Regions’ Fractal Dimension in Healthy and ADHD Children: A Structural MRI Study
Dezhsetan, M., Saviz, S. M., Towhidkhah, F., Baghdadi, G., & Rahimi, S. (2019) · National and International Iranian Conference on Biomedical Engineering (ICBME) · doi:10.1109/icbme49163.2019.9030407 · Cited by 1
“ADHD subjects had smaller brain volume, which is consistent with the outcomes of previous studies [10, 11].”
Result
Sex Differences in the Brain: Divergent Results from Traditional Machine Learning and Convolutional Networks
Brueggeman, L., Thomas, T., Koomar, T., Hoskins, B., & Michaelson, J. J. (2020) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098402 · Cited by 1
“These traditional methods have had some success in detecting sex differences, especially when the study is well-powered [3].”
Background
Sex, Gender, and Intelligence
Halpern, D. F., Flores-Mendoza, C. E., & Rindermann, H. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.014 · Cited by 2
Habilidades cognitivas e desempenho nos testes de ordenação temporal em idosos
Rabelo, M. B., Lopes, M. D. S., Corona, A. P., de Carvalho, J. F., & de Araújo, R. P. C. (2020) · Audiology - Communication Research · doi:10.1590/2317-6431-2019-2272 · Cited by 1
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Tamnes, C. K., & Mills, K. L. (2020) · The MIT Press eBooks · doi:10.7551/mitpress/11442.003.0006 · Cited by 2
Stochastic encoding of graphs in deep learning allows for complex analysis of gender classification in resting-state and task functional brain networks from the UK BiobankPreprint
Leming, M., & Suckling, J. (2020) · arXiv.org · doi:10.48550/arxiv.2002.10936 · Cited by 2
“Details of the acquisition parameters are given elsewhere [45].”
Background
Distribution of facial resemblance in romantic couples suggests both positive and negative assortative processes influence human mate choicePreprint
Holzleitner, I. J., O’Shea, K. J., Fasolt, V., Lee, A. J., DeBruine, L. M., & Jones, B. C. (2019) · doi:10.31234/osf.io/pw5c2 · Cited by 1
Big data approaches to identifying sex differences in long-term memory
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The Brain Is Globally Symmetric: An Analysis of Intra and Interhemispheric Symmetry of Subcortical Structures in the Aging Human BrainPreprint
Gómez‐Ramírez, J., & González-Rosa, J. J. (2021) · Research Square · doi:10.21203/rs.3.rs-267371/v1 · Cited by 1
Sex vs Gender: A Biological Location for Gender, not Sex.Preprint
Woodhill, B. M., & Samuels, C. A. (2021) · doi:10.33774/coe-2020-k7gt1-v3 · Cited by 1
“The frontoparietal region related to the own body perception shows sex differences (Uribe et al., 2020; Ritchie et al. 2018).”
Imaging structural brain development in childhood and adolescencePreprint
Tamnes, C. K., & Mills, K. L. (2020) · doi:10.31234/osf.io/u58pf · Cited by 1
The Use of MRI for Sternocleidomastoid Muscle Volume Measurement and its Association with Internal Carotid Artery Velocity in a Healthy Cohort
Gill, S. K. (2019) · YorkSpace (York University) · Cited by 1
Gene, the Sexual Brain, and Cognition: Machine-Predicted Brain Sex Score Explains Individual Differences in Cognitive Development and Genetic Influence.Preprint
Kim, G., Joo, Y. Y., Ahn, G., Wang, H., Moon, S., Kim, H., Ahn, W., & Cha, J. (2021) · doi:10.31219/osf.io/5x9hb · Cited by 1
NBS-Predict: An easy-to-use toolbox for connectome-based machine learningPreprint
Serin, E., Vaidya, N., Walter, H., & Kruschwitz, J. (2022) · doi:10.31219/osf.io/4ghpm · Cited by 1
The link between autism and sex-specific neuroanatomy, and associated cognition and gene expressionPreprint
Floris, D. L., Peng, H., Warrier, V., Lombardo, M. V., Pretzsch, C. M., Moreau, C. A., Tsompanidis, A., Gong, W., Mennes, M., Llera, A., et al. (2022) · medRxiv · doi:10.1101/2022.03.18.22272409 · Cited by 1
“…are in line with the up-to-date notion that there is no strict sexual dimorphism in human neuroanatomy (64, 65), but brains exhibit a ‘multimorphic’ mosaic of male-/female-like features (66, 67) which can reliably distinguish males from females with above-chance to high accuracy (66, 68, 69).”
BackgroundSelf-citation
Sex differences in ability tilt in the right tail of cognitive abilities: A 35-year examinationPreprint
Wai, J., & Makel, M. C. (2017) · doi:10.31234/osf.io/rwgpy · Cited by 1
Sex vs Gender: Are We there Yet? A Biological Location for Gender, not Sex.Preprint
Tannett, B. (2020) · doi:10.33774/coe-2020-k7gt1 · Cited by 1
“The pre-frontal cortex (PFC) is involved in the generation of dimorphic behaviours and with its subcortical connections in the limbic system, the PFC is a neurological structure heavily involved in the social brain (Ritchie et al., 2018; Pavlova, 2017; Reber & Tranel, 2017; Guillamon et al., 2016).”
Modeling brain sex in the limbic system as phenotype for female-prevalent mental disordersPreprint
Bon, G. M., Kraft, D., Comasco, E., Derntl, B., & Kaufmann, T. (2023) · medRxiv · doi:10.1101/2023.08.17.23294165 · Cited by 1
Situating the oxytocin receptor gene polymorphisms in the context of structural and connectome-level substrates and association with endogenous oxytocinPreprint
Kaya, K., Önal, D., Kartal, Y., Budak, M. T., Karabulut, E., Oğuz, K. K., & Pehli̇vanoğlu, B. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.24.554569 · Cited by 1
“These findings are in line with previous studies indicating higher cSA and cortical volumes in men and higher WM tract complexity in women [Chen et al., 2012; Gur et al., 1999; Ritchie et al., 2018].”
Result
Assessing White Matter Engagement in Brain Networks through Functional and Structural Connectivity MappingPreprint
Li, M., Schilling, K. G., Ding, Z., & Gore, J. C. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.04.574259 · Cited by 1
“These disparities are in line with existing research that underscores sex-specific patterns in brain connectivity, such as enhanced connectivity within the Default Mode Network (DMN) observed in females 55,56 , with cingulum playing a pivotal role in linking key DMN components.”
Result
Sex/gender associated mechanisms in the (human) brain: Sex hormones, sex chromosomes, and social-cultural gender factors
Wierenga, L. M., & Beck, D. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-820480-1.00173-x · Cited by 1
Interplay between Sex and Disease Burden in Huntington’s Disease: Clinical and Neuroimaging PerspectivesPreprint
Yao, J., Grayson Feng, B. S., Guowen Shao, M. S., Mendizabal, A., Telesca, D., Fang, K., Ibragimova, L., Shoaib, J., Morrison, M. A., & Lupo, J. (2024) · medRxiv · doi:10.1101/2024.10.31.24315900 · Cited by 1
“We found similar caudate volume and smaller putamen volume in female HD gene carriers compared to males after adjusting for intracranial volumes at lower disease burden, aligning with existing literature in healthy individuals 29–32 .”
Result
The progression of sex differences in brain networks across the lifespanPreprint
Huang, K., Jamison, K. W., Jacobs, E. G., Miolane, N., & Kuceyeski, A. F. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.30.702608 · Cited by 5
“Sex differences in brain and behavior are not static; previous work has shown varied effects over the key developmental stages of puberty, reproductive maturity, and aging 13;18;20 .”
Attenuation of typical sex differences in the time-resolved functional connectivity of the fusiform gyrus in autismPreprint
Floris, D. L., Saccaro, L. F., Delavari, F., Strzelczyk, D., Vieira, B. H., Elleaume, C., Pretzsch, C. M., Ecker, C., Banaschewski, T., Holt, R., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-10317780/v1 · Cited by 1
Benchmarking Multimodal Deep Fusion Strategies for Heterogeneous Neuroimaging and Cognitive Data Using a Controlled Sex Classification Task
Camastra, C., Pelagi, A., Quattrone, A., & Sarica, A. (2026) · Brain Sciences · doi:10.3390/brainsci16040405 · Cited by 1
Sex Differences in the Human Brain
Franks, D. D. (2018) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780190299323.013.6
Characterization of Brain Cortical Morphology Using Localized Topology-Encoding GraphsPreprint
Maghsadhagh, S., Shamsi, M., Eklund, A., & Behjat, H. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1810.10339
“Variations in the cortical morphology of male and female subjects has been suggested in many studies, see for example [15].”
O desenvolvimento do pensamento espacial e a cognição incorporada: novas perspectivas para o ensino de ciências e matemática
Oliva, E. N. D. O. (2018) · doi:10.11606/d.81.2018.tde-16072018-134552
Improving reliability in clinical neuroimaging: a study in transgender personsPreprint
Khorashad, B. S., Khazai, B., Talaeı, A., Acar, F., Hudson, A. R., Borji, N., Saberi, H., Aminzadeh, B., & Mueller, S. C. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/861864
Enhanced prediction of cognitive function using aging-sensitive networks within the human structural connectomePreprint
Madole, J. W., Ritchie, S. J., Cox, S. R., Buchanan, C. R., Hernández, M. V., Maniega, S. M., Wardlaw, J. M., Harris, M. A., Bastin, M. E., Deary, I. J., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.13.875559
Self-citation
Neuroimaging Research in Women’s Mental Health: Current Research and Emerging Trends in Women and Transgender Women’s Psychiatry and Mental Health
Minuzzi, L., Schneider, M. A., & Syan, S. K. (2020) · Springer eBooks · doi:10.1007/978-3-030-29081-8_22
Occupational Health Psychology and Women in Asian Contexts
Siu, O. L., Wang, H., & Pagon, M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.027
Sex vs Gender: Are We there Yet? A Biological Location for Gender, not Sex.Preprint
Tannett, B. (2020) · doi:10.33774/coe-2020-k7gt1-v2
Sex-biased gene expression in rhesus macaque and human brainsPreprint
DeCasien, A. R., Sherwood, C. C., & Higham, J. P. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.17.208785
“Sexual dimorphism often extends to behavior and cognition, implicating sex differences in neuroanatomy and/or brain gene expression (Mitchell 1980; Jacobs 1996; Knickmeyer et al. 2009; Jazin and Cahill 2010; Ruigrok et al. 2014; Ritchie et al. 2018; c.f. Joel et al. 2015).”
Background
Women and Psychotherapy
Duan, C., & Grazioso, M. D. P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.044
The Psychology of Women in Entrepreneurship
Chan, E. T., Tang, P. M., & Chen, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.025
Sex, Gender, and Sexuality
Byers, E. S., & Blair, K. L. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.005
Understanding Women’s Antisocial and Criminal Behavior
Zhong, H., & Ryder, J. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.034
Gender and Women’s Sexual and Reproductive Health
Hindin, M. J., & OlaOlorun, F. M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.040
Three Ways that Aging Affects Women Differently from Men
Chen, A. X., Tsang, V. H. L., Wong, T. K., Fung, H. H.-L., & Ayalon, L. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.012
Work–Family Interface and Crossover Effects
Rajadhyaksha, U. A., & Başkurt, A. B. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.028 · Cited by 1
The Contents and Discontents of the Nature–Nurture Debate
Gangestad, S. W., & Chang, L. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.004
Sex Differences on the Brain
Grabowska, A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.006
Women under Pressure
Eagle, G. T., Ayers, S., Mkone, C., & Moroke, M. S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.039
Physical Health
Parton, C., Ussher, J. M., Perz, J., & Rubin, L. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.041
Contextualizing the Many Faces of Domestic Violence
Nduna, M., Mkwananzi, S., Wekwete, N. N., & Makongoza, M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.030
International and Intersectional Perspectives on the Psychology of Women
Cheung, F. M., & Halpern, D. F. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.002

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: Ritchie, Stuart J
Shen, Xueyi
Lombardo, Michael V
Reus, Lianne M
Alloza, Clara
Harris, Mathew A
Neilson, Emma
Liewald, David C M
Whalley, Heather C
Lawrie, Stephen M
Bastin, Mark E
McIntosh, Andrew M
Deary, Ian J
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
DOI: 10.1093/cercor/bhy109
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: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
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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Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

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