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Sex differences in the structural connectome of the human brain
Open accessAbstract
Significance: Sex differences are of high scientific and societal interest because of their prominence in behavior of humans and nonhuman species. This work is highly significant because it studies a very large population of 949 youths (8–22 y, 428 males and 521 females) using the diffusion-based structural connectome of the brain, identifying novel sex differences. The results establish that male brains are optimized for intrahemispheric and female brains for interhemispheric communication. The developmental trajectories of males and females separate at a young age, demonstrating wide differences during adolescence and adulthood. The observations suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.
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“The number of streamlines (NOS) is one widely used measure to quantify the connectivity strength (Hagmann et al., 2008b; Ingalhalikar et al., 2014; Roberts et al., 2016; Sporns et al., 2005; van Dellen et al., 2018).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Ingalhalikar et al., 2014
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The most popular scalar value for connectivity matrix analysis is the NOS (Hagmann et al., 2008b; Ingalhalikar et al., 2014; Roberts et al., 2016; Sporns et al., 2005; van Dellen et al., 2018), where higher values are considered to indicate stronger connectivity between pairs of gray matter regions.”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Ingalhalikar et al., 2014
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“In a study of 37 young adults with CAH, alterations in grey matter structure, including the middle frontal gyrus and the parietal and superior occipital cortex were found in CAH patients compared to controls (696).”
From Congenital Adrenal Hyperplasia—Current Insights in Pathophysiology, Diagnostics, and Management (2022) · cites this paper as [696]
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“These regions play a role in visuospatial working memory and patients performed worse in visuospatial working memory tasks.”
From Congenital Adrenal Hyperplasia—Current Insights in Pathophysiology, Diagnostics, and Management (2022) · cites this paper as [696]
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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
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910
Nonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256
Cortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147
MR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173
Diffusion tensor imaging: Concepts and applications
Le Bihan, D., Mangin, J., Poupon, C., Clark, C. A., Pappata, S., Molko, N., & Chabriat, H. (2001) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.1076 · Cited by 3,547
Characterization and propagation of uncertainty in diffusion-weighted MR imaging
Behrens, T. E. J., Woolrich, M. W., Jenkinson, M., Johansen‐Berg, H., Nunes, R. G., Clare, S., Matthews, P. M., Brady, J. M., & Smith, S. M. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10609 · Cited by 3,038
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Chung, M. K., Das, S. R., & Ombao, H. (2023) · Foundations of Data Science · doi:10.3934/fods.2023013 · Cited by 11
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Rigon, A., Voss, M. W., Turkstra, L. S., Mutlu, B., & Duff, M. C. (2018) · Social Neuroscience · doi:10.1080/17470919.2018.1489302 · Cited by 8
Ben‐Soussan, T. D., & Glicksohn, J. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00071 · Cited by 8
Çeri, V., Özer, Ü., Layık, M. E., & İz, F. B. A. (2018) · Van Medical Journal · doi:10.5505/vtd.2018.80557 · Cited by 8
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Feng, Y., Yan, W., Wang, J., Song, J., Zeng, Q., & Zhao, C. (2020) · Neuroscience · doi:10.1016/j.neuroscience.2020.03.049 · Cited by 8
Golden, C. E. M., Yee, Y., Wang, V. X., Harony‐Nicolas, H., Hof, P. R., Lerch, J. P., & Buxbaum, J. D. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00943-x · Cited by 8
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Martínez, K., & Colom, R. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108635462.005 · Cited by 8
Kaiser, M. (2020) · The MIT Press eBooks · doi:10.7551/mitpress/11980.001.0001 · Cited by 25
Chen, T., Li, Z., Cui, J., Huang, J., Irish, M., Wang, Y., & Chan, R. C. K. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00694-x · Cited by 8
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Litwińczuk, M. C., Muhlert, N., Trujillo‐Barreto, N. J., & Woollams, A. M. (2024) · Human Brain Mapping · doi:10.1002/hbm.26592 · Cited by 7
Gaznick, N., Bechara, A., & Tranel, D. (2014) · Journal of Clinical and Experimental Neuropsychology · doi:10.1080/13803395.2014.915012 · Cited by 8
Águila, D. A., Abad, F. J., & Colom, R. (2018) · Personality and Individual Differences · doi:10.1016/j.paid.2018.09.043 · Cited by 8
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Xu, C., Sun, G., Liang, R., & Xu, X. (2021) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2021.3094555 · Cited by 8
Stark, R., & Gibb, R. L. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-804036-2.00014-5 · Cited by 8
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Inui, K., Takeuchi, N., Bayasgalan, B., Shingaki, M., Sugiyama, S., Taniguchi, T., Nishihara, M., Watanabe, T., Suzuki, D., Motomura, E., et al. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1378619 · Cited by 7
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Maggio, M. G., Benenati, A., Impellizzeri, F., Rizzo, A., Barbera, M., Cannavò, A., Gregoli, V., Morone, G., Chirico, F., Quartarone, A., et al. (2024) · Brain Sciences · doi:10.3390/brainsci14121227 · Cited by 7
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Mozafari, A. R., & Xu, X. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.029 · Cited by 7
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Zorrilla, I., López-Zurbano, S., Cano, A. I., & González-Pinto, A. M. (2014) · Springer eBooks · doi:10.1007/978-3-319-05870-2_27 · Cited by 6
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Self-citation
Metadata
- Authors
- Ingalhalikar, M., Smith, A., Parker, D., Satterthwaite, T. D., Elliott, M. A., Ruparel, K., Hakonarson, H., Gur, R. E., Gur, R. C., & Verma, R.
- Affiliations
- Section of Biomedical Image Analysis and
- University of Pennsylvania (US)
- Center for Magnetic Resonance and Optical Imaging, Department of Radiology, and
- Children's Hospital of Philadelphia (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2013-12-02
- Volume
- 111
- Issue
- 2
- Pages
- 823-828
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3896179
- OpenAlex
- W2009872283
- Cited by
- 1,223
- References
- 55
- Citations by year
- 2026: 69 · 2025: 91 · 2024: 95 · 2023: 95 · 2022: 77 · 2021: 111 · 2020: 147 · 2019: 101 · 2018: 112 · 2017: 89 · 2016: 97 · 2015: 70 · 2014: 66 · 2013: 2
- FWCI
- 60.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Brain and Behavior Research Foundation (K23MH098130)
- National Institute of Mental Health (RC2MH089983, MH079938, MH089983, K23MH098130, R01MH079938, MH089924, RC2MH089924, MH092862, R01MH092862)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- sex differences, structural connectome, brain connectivity, brain development, diffusion tensor imaging, cerebellar connections, interhemispheric connectivity, network modularity, transitivity, adolescents, youth
- MeSH terms
- Adolescent, Brain, Child, Female, Humans, Male, Sex Characteristics, Linear Models, Young Adult, Diffusion Tensor Imaging, Connectome
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