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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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Zhou, L., Kong, J., Li, X., & Ren, Q. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105067 · Cited by 51
Jahanshad, N., & Thompson, P. M. (2016) · Journal of Neuroscience Research · doi:10.1002/jnr.23919 · Cited by 55
Gender effects on auditory P300: A systematic review
Mėlynytė, S., Wang, G., & Griškova-Bulanova, I. (2018) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2018.08.009 · Cited by 51
System-level matching of structural and functional connectomes in the human brain
Osmanlıoğlu, Y., Tunç, B., Parker, D., Elliott, M. A., Baum, G. L., Ćirić, R., Satterthwaite, T. D., Gur, R. E., Gur, R. C., & Verma, R. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.064 · Cited by 51
Self-citationThe adverse effect of gradient nonlinearities on diffusion MRI: From voxels to group studies
Mesri, H. Y., Dávid, S., Viergever, M. A., & Leemans, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116127 · Cited by 51
Whole Brain and Cranial Size Adjustments in Volumetric Brain Analyses of Sex- and Age-Related Trends
Kijonka, M., Borys, D., Psiuk-Maksymowicz, K., Gorczewski, K., Wojcieszek, P., Kossowski, B., Marchewka, A., Świerniak, A., Sokol, M. B., & Bobek‐Billewicz, B. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00278 · Cited by 50
Sex differences in the human reward system: convergent behavioral, autonomic and neural evidence
Warthen, K., Boyse-Peacor, A., Jones, K. G., Sanford, B., Love, T., & Mickey, B. J. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa104 · Cited by 50
Zekelman, L., Zhang, F., Makris, N., He, J., Chen, Y., Xue, T., Liera, D., Drane, D. L., Yogesh Rathi, A., Golby, A. J., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118739 · Cited by 51
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Benedetto, M. G. D., Landi, P., Mencacci, C., & Cattaneo, A. (2024) · Neuropsychobiology · doi:10.1159/000531588 · Cited by 55
Lafta, M. S., Mwinyi, J., Affatato, O., Rukh, G., Dang, J., Andersson, G., & Schiöth, H. B. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1340108 · Cited by 58
Graph Theoretical Analysis Reveals: Women’s Brains Are Better Connected than Men’s
Szalkai, B., Varga, B., & Grolmusz, V. I. (2015) · PLoS ONE · doi:10.1371/journal.pone.0130045 · Cited by 50
Roalf, D. R., Gur, R. E., Verma, R., Parker, W. A., Quarmley, M., Ruparel, K., & Gur, R. C. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.09.026 · Cited by 50
Self-citationSex Influences on the Brain: An Issue Whose Time Has Come
Cahill, L. F., & Aswad, D. W. (2015) · Neuron · doi:10.1016/j.neuron.2015.11.021 · Cited by 50
Shiino, A., Chen, Y., Tanigaki, K., Yamada, A., Vigers, P. N., Watanabe, T., Tooyama, I., & Akiguchi, I. (2017) · Scientific Reports · doi:10.1038/srep39818 · Cited by 48
Navarra‐Ventura, G., Fernández‐Gonzalo, S., Turón, M., Pousa, E., Palao, D. J., Cardoner, N., & Jódar, M. (2017) · The Canadian Journal of Psychiatry · doi:10.1177/0706743717746661 · Cited by 50
Gu, Y., Peng, S., Li, Y., Gao, L., & Dong, Y. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102619 · Cited by 52
Xu, C., Li, C., Wu, H., Wu, Y., Hu, S., Zhu, Y., Zhang, W., Wang, L., Zhu, S., Liu, J., et al. (2015) · BioMed Research International · doi:10.1155/2015/183074 · Cited by 49
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Hsu, M. Y.-T., & Cheng, J. M.-S. (2018) · European Journal of Marketing · doi:10.1108/ejm-12-2016-0866 · Cited by 50
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Verriotis, M., Jones, L., Whitehead, K., Laudiano‐Dray, M. P., Panayotidis, I., Patel, H., Meek, J. H., Lorenzo Fabrizi, D., & Fitzgerald, M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.030 · Cited by 49
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Braga, J., Samir, C., Risser, L., Dumoncel, J., Descouens, D., Thackeray, F., Balaresque, P. L., Oettlé, A. C., Loubes, J.-M., & Fradi, A. (2019) · Scientific Reports · doi:10.1038/s41598-019-47433-9 · Cited by 49
Tunç, B., Yankowitz, L., Parker, D., Alappatt, J. A., Pandey, J., Schultz, R., & Verma, R. (2019) · Molecular Autism · doi:10.1186/s13229-019-0301-5 · Cited by 47
Self-citationSakakibara, E., Homae, F., Kawasaki, S., Nishimura, Y., Takizawa, R., Koike, S., Kinoshita, A., Sakurada, H., Yamagishi, M., Nishimura, F., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.011 · Cited by 48
Research Updates in Neuroimaging Studies of Children Who Stutter
Chang, S. (2014) · Seminars in Speech and Language · doi:10.1055/s-0034-1382151 · Cited by 50
Zhou, Y., Tao, L., Qian, Z., Wu, J., Liu, H., Yu, Y., Song, J., Wang, S., & Sun, J. (2016) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-015-1330-y · Cited by 48
Developmental neurogenetics and multimodal neuroimaging of sex differences in autism
Chen, C., & Horn, J. D. V. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-015-9504-3 · Cited by 55
Iseger, T. A., Korgaonkar, M. S., Kenemans, J. L., Grieve, S. M., Baeken, C., Fitzgerald, P. B., & Arns, M. (2017) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2017.02.002 · Cited by 48
Sato, M. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2020.107404 · Cited by 52
Predicting Biological Gender and Intelligence From fMRI via Dynamic Functional Connectivity
Sen, B., & Parhi, K. K. (2020) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2020.3011363 · Cited by 46
Spalek, K., Fastenrath, M., Ackermann, S., Auschra, B., Coynel, D., Frey, J. N., Gschwind, L., Hartmann, F., van der Maarel, N., Papassotiropoulos, A., et al. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.2384-14.2015 · Cited by 49
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Goldstone, A., Mayhew, S. D., Przeździk, I., Wilson, R. S., Hale, J. R., & Bagshaw, A. P. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2016.00285 · Cited by 44
Tyan, Y., Liao, J., Shen, C., Lin, Y.-C., & Weng, J. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.05.014 · Cited by 63
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Szameitat, A. J., Hamaida, Y., Tulley, R. S., Saylık, R., & Otermans, P. C. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140371 · Cited by 45
Just Like a Circus: The Public Consumption of Sex Differences
Maney, D. L. (2014) · Current topics in behavioral neurosciences · doi:10.1007/7854_2014_339 · Cited by 50
Lawrence, E. L., Fassola, I., Werner, I., Leclercq, C., & Valero‐Cuevas, F. J. (2014) · Frontiers in Neurology · doi:10.3389/fneur.2014.00053 · Cited by 45
Massey, S. C., Whitmire, P., Doyle, T. E., Ippolito, J. E., Mrugała, M. M., Hu, L., Canoll, P., Anderson, A. R. A., Wilson, M. A., Fitzpatrick, S. M., et al. (2020) · Cancer Letters · doi:10.1016/j.canlet.2020.07.030 · Cited by 47
Sanchis‐Segura, C., Aguirre, N., Cruz-Gómez, Á. J., Félix, S., & Forn, C. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119343 · Cited by 48
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Dhamala, E., Ooi, L. Q. R., Chen, J., Ricard, J. A., Berkeley, E., Chopra, S., Qu, Y. L., Zhang, X.-H., Lawhead, C., Yeo, B. T. T., et al. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.03.025 · Cited by 43
Andrei Irimia, A., Torgerson, C. M., Goh, S.-Y. M., & Horn, J. D. V. (2014) · Brain Imaging and Behavior · doi:10.1007/s11682-014-9321-0 · Cited by 44
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Funes, C. M., Lavretsky, H., Ercoli, L. M., Cyr, N. S., & Siddarth, P. (2017) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2017.06.012 · Cited by 49
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Rácz, F. S., Stylianou, O., Mukli, P., & Eke, A. (2018) · Frontiers in Physiology · doi:10.3389/fphys.2018.01704 · Cited by 49
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Nebli, A., & Rekik, I. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00123-6 · Cited by 44
Sex differences in cognitive processing: An integrative review of electrophysiological findings
Ramos‐Loyo, J., González‐Garrido, A. A., Llamas-Alonso, L. A., & Sequeira, H. (2022) · Biological Psychology · doi:10.1016/j.biopsycho.2022.108370 · Cited by 44
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Dhamala, E., Bassett, D. S., Yeo, B. T. T., & Holmes, A. J. (2024) · Science Advances · doi:10.1126/sciadv.adn4202 · Cited by 44
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Knight, M. J., McCann, B., Tsivos, D., Dillon, S., Coulthard, E. J., & Kauppinen, R. A. (2016) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/15/5587 · Cited by 44
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LaClair, M., Febo, M., Nephew, B. C., Gervais, N. J., Poirier, G. L., Workman, K. P., Chumachenko, S. Y., Payne, L., Moore, M. C., King, J. A., et al. (2019) · eNeuro · doi:10.1523/eneuro.0154-19.2019 · Cited by 42
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de Lacy, N., McCauley, E., Kutz, J. N., & Calhoun, V. D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116116 · Cited by 42
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Kurth, F., Thompson, P. M., & Eileen Luders, A. (2017) · Cortex · doi:10.1016/j.cortex.2017.11.017 · Cited by 42
Chiesa, P. A., Cavedo, E., Grothe, M. J., Houot, M., Teipel, S. J., Potier, M., Habert, M., Lista, S., Dubois, B., Hampel, H. J., et al. (2018) · Radiology · doi:10.1148/radiol.2018180268 · Cited by 40
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Ryan, L. V. (2016) · Journal of Business Ethics · doi:10.1007/s10551-016-3110-1 · Cited by 42
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Tadić, B., Andjelković, M., & Melnik, R. (2019) · Scientific Reports · doi:10.1038/s41598-019-48568-5 · Cited by 43
Wang, Y., Wu, H., & Sun, Z. S. (2019) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2019.100798 · Cited by 48
Studholme, C., Kroenke, C. D., & Dighe, M. (2020) · Nature Communications · doi:10.1038/s41467-020-16763-y · Cited by 45
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De Asis-Cruz, J., Andersen, N., Kapse, K., Khrisnamurthy, D., Quistorff, J., Lopez, C., Vezina, G., & Limperopoulos, C. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhaa410 · Cited by 40
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Gao, M., Wong, N. M. L., Lin, C., Huang, C., Liu, H., Toh, C., Wu, C. W., Tsai, Y., Lee, S.-H., & Lee, T. M. C. (2023) · Nature Mental Health · doi:10.1038/s44220-022-00007-7 · Cited by 43
Civier, O., Kronfeld-Duenias, V., Amir, O., Ezrati-Vinacour, R., & Ben‐Shachar, M. (2015) · Brain and Language · doi:10.1016/j.bandl.2015.01.012 · Cited by 45
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Glezerman, M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1524418113 · Cited by 40
Morgan, C. P., & Bale, T. L. (2017) · Biology of Sex Differences · doi:10.1186/s13293-017-0149-3 · Cited by 42
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Kerepesi, C., Szalkai, B., Varga, B., & Grolmusz, V. I. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158680 · Cited by 38
Seligowski, A. V., Harnett, N. G., Merker, J. B., & Ressler, K. J. (2019) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2019.12.006 · Cited by 39
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Zhang, F., Wu, W., Ning, L., McAnulty, G. B., Waber, D. P., Gagoski, B. A., Sarill, K., Hamoda, H. M., Song, Y., Cai, W., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.006 · Cited by 35
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Rhee, J., & Mehta, R. K. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00455 · Cited by 37
Kozhemiako, N., Nunes, A. S., Vakorin, V. A., Iarocci, G., Ribary, U., & Doesburg, S. M. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa109 · Cited by 33
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Mathew, J., Masson, G. S., & Danion, F. (2020) · Scientific Reports · doi:10.1038/s41598-020-68069-0 · Cited by 37
Rechtman, E., Curtin, P. C. P., Papazaharias, D. M., Renzetti, S., Cagna, G., Peli, M., Levin‐Schwartz, Y., Placidi, D., Smith, D. R., Lucchini, R. G., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01041-8 · Cited by 37
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Lyall, A. E., Savadjiev, P., Shenton, M. E., & Kubicki, M. R. (2016) · Journal of Neuroimaging in Psychiatry and Neurology · doi:10.17756/jnpn.2016-003 · Cited by 37
Reed, J. L., Gallagher, N. M., Sullivan, M. E., Callicott, J. H., & Green, A. E. (2017) · Brain and Cognition · doi:10.1016/j.bandc.2017.01.001 · Cited by 38
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Lind, K. E., Gutierrez, E. J., Yamamoto, D. J., Regner, M. F., McKee, S. A., & Tanabe, J. (2017) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2016.12.019 · Cited by 36
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Wang, B., Zhan, Q., Yan, T., Imtiaz, S., Xiang, J., Niu, Y., Liu, M., Wang, G., Cao, R., & Li, D. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz027 · Cited by 37
Leroux, E., Delcroix, N., & Dollfus, S. (2015) · Schizophrenia Research · doi:10.1016/j.schres.2015.03.028 · Cited by 38
Vanicek, T., Hahn, A., Traub‐Weidinger, T., Hilger, E., Spies, M., Wadsak, W., Lanzenberger, R. R., Pataraia, E., & Asenbaum-Nan, S. (2016) · Scientific Reports · doi:10.1038/srep28513 · Cited by 35
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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
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.
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