Age-Related Effects and Sex Differences in Gray Matter Density, Volume, Mass, and Cortical Thickness from Childhood to Young Adulthood
Open accessAbstract
Developmental structural neuroimaging studies in humans have long described decreases in gray matter volume (GMV) and cortical thickness (CT) during adolescence. Gray matter density (GMD), a measure often assumed to be highly related to volume, has not been systematically investigated in development. We used T1 imaging data collected on the Philadelphia Neurodevelopmental Cohort to study age-related effects and sex differences in four regional gray matter measures in 1189 youths ranging in age from 8 to 23 years. Custom T1 segmentation and a novel high-resolution gray matter parcellation were used to extract GMD, GMV, gray matter mass (GMM; defined as GMD × GMV), and CT from 1625 brain regions. Nonlinear models revealed that each modality exhibits unique age-related effects and sex differences. While GMV and CT generally decrease with age, GMD increases and shows the strongest age-related effects, while GMM shows a slight decline overall. Females have lower GMV but higher GMD than males throughout the brain. Our findings suggest that GMD is a prime phenotype for the assessment of brain development and likely cognition and that periadolescent gray matter loss may be less pronounced than previously thought. This work highlights the need for combined quantitative histological MRI studies. SIGNIFICANCE STATEMENT This study demonstrates that different MRI-derived gray matter measures show distinct age and sex effects and should not be considered equivalent but complementary. It is shown for the first time that gray matter density increases from childhood to young adulthood, in contrast with gray matter volume and cortical thickness, and that females, who are known to have lower gray matter volume than males, have higher density throughout the brain. A custom preprocessing pipeline and a novel high-resolution parcellation were created to analyze brain scans of 1189 youths collected as part of the Philadelphia Neurodevelopmental Cohort. A clear understanding of normal structural brain development is essential for the examination of brain–behavior relationships, the study of brain disease, and, ultimately, clinical applications of neuroimaging.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Women have lower gray matter volume.
“Women also appear to have lower gray matter volume,50”
From Sex differences in cognitive decline among US adults (2021) · cites this paper as [50]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319 · see citing works
Wood, S. N. (2010) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.1467-9868.2010.00749.x · Cited by 7,538 · see citing works
N4ITK: Improved N3 Bias Correction
Tustison, N. J., Avants, B., Cook, P. A., Zheng, Y., Egan, A., Yushkevich, P. A., & Gee, J. C. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2010.2046908 · Cited by 6,119 · see citing works
Self-citationAvants, B., Epstein, C. L., Grossman, M., & Gee, J. C. (2007) · Medical Image Analysis · doi:10.1016/j.media.2007.06.004 · Cited by 5,618 · see citing works
Self-citationDynamic mapping of human cortical development during childhood through early adulthood
Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., Nugent, T. F., Herman, D. H., Clasen, L. S., Toga, A. W., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0402680101 · Cited by 5,604 · cited 3× · see citing works
“Several developmental neuroimaging studies have described modest decreases in gray matter during adolescence using measures derived from gray matter volume and cortical thickness (Sowell et al., 2003, 2004; Gogtay et al., 2004; Shaw et al., 2008; Brain Development Cooperative Group, 2012).”
BackgroundMethodResultInfluentialA multi-modal parcellation of human cerebral cortex
Glasser, M. F., Coalson, T. S., Robinson, E. C., Hacker, C. D., Harwell, J., Yacoub, E., Ugurbil, K., Andersson, J., Beckmann, C. F., Jenkinson, M., et al. (2016) · Nature · doi:10.1038/nature18933 · Cited by 5,111 · see citing works
NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain
Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.072 · Cited by 3,288 · see citing works
Neurodegenerative Diseases Target Large-Scale Human Brain Networks
Seeley, W. W., Crawford, R. K., Zhou, J., Miller, B. L., & Greicius, M. D. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.024 · Cited by 2,350 · see citing works
Mapping cortical change across the human life span
Sowell, E. R., Peterson, B. S., Thompson, P. M., Welcome, S. E., Henkenius, A. L., & Toga, A. W. (2003) · Nature Neuroscience · doi:10.1038/nn1008 · Cited by 2,328 · see citing works
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration
Klein, A., Andersson, J., Ardekani, B. A., Ashburner, J., Avants, B., Chiang, M.-C., Christensen, G. E., Collins, D. L., Gee, J., Hellier, P., et al. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.037 · Cited by 2,227 · see citing works
Self-citationThe basics of brain development
Stiles, J., & Jernigan, T. L. (2010) · Neuropsychology Review · doi:10.1007/s11065-010-9148-4 · Cited by 2,009 · see citing works
Neurodevelopmental Trajectories of the Human Cerebral Cortex
Shaw, P., Kabani, N. J., Lerch, J. P., Eckstrand, K., Lenroot, R., Gogtay, N., Greenstein, D., Clasen, L., Evans, A., Rapoport, J. L., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.5309-07.2008 · Cited by 1,644 · see citing works
A Structural MRI Study of Human Brain Development from Birth to 2 Years
Knickmeyer, R. C., Gouttard, S., Kang, C., Evans, D., Wilber, K., Smith, J. K., Hamer, R. M., Lin, W., Gerig, G., & Gilmore, J. H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.3479-08.2008 · Cited by 1,151 · see citing works
The Science of Sex Differences in Science and Mathematics
Halpern, D. F., Benbow, C. P., Geary, D. C., Gur, R. C., Hyde, J. S., & Gernsbacher, M. A. (2007) · Gothic.net · doi:10.1111/j.1529-1006.2007.00032.x · Cited by 1,141 · see citing works
Self-citationGur, R. C., Turetsky, B. I., Matsui, M., Yan, M., Bilker, W., Hughett, P., & Gur, R. E. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-10-04065.1999 · Cited by 909 · see citing works
Self-citationRaznahan, A., Shaw, P., Lalonde, F., Stockman, M., Wallace, G. L., Greenstein, D., Clasen, L., Gogtay, N., & Giedd, J. N. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.0054-11.2011 · Cited by 712 · see citing works
Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements
Tustison, N. J., Cook, P. A., Klein, A., Song, G., Das, S. R., Duda, J. T., Kandel, B. M., van Strien, N., Stone, J. R., Gee, J. C., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.05.044 · Cited by 670 · see citing works
Self-citationMyelin and iron concentration in the human brain: a quantitative study of MRI contrast
Stüber, C., Morawski, M., Schäfer, A., Labadie, C., Wähnert, M., Leuze, C., Streicher, M., Barapatre, N., Reimann, K., Geyer, S., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.02.026 · Cited by 635 · see citing works
Mapping Changes in the Human Cortex throughout the Span of Life
Sowell, E. R., Thompson, P. M., & Toga, A. W. (2004) · The Neuroscientist · doi:10.1177/1073858404263960 · Cited by 572 · see citing works
An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data
Avants, B., Tustison, N. J., Wu, J., Cook, P. A., & Gee, J. C. (2011) · Neuroinformatics · doi:10.1007/s12021-011-9109-y · Cited by 559 · see citing works
Self-citationMCDANIEL, M. (2005) · Intelligence · doi:10.1016/j.intell.2004.11.005 · Cited by 527 · see citing works
Neuroimaging of the Philadelphia Neurodevelopmental Cohort
Satterthwaite, T. D., Elliott, M. A., Ruparel, K., Loughead, J., Prabhakaran, K., Calkins, M. E., Hopson, R., Jackson, C., Keefe, J., Riley, M., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.07.064 · Cited by 504 · see citing works
Self-citationOn p-values for smooth components of an extended generalized additive model
Wood, S. N. (2012) · Biometrika · doi:10.1093/biomet/ass048 · Cited by 415 · see citing works
Network-level structural covariance in the developing brain
Zielinski, B. A., Gennatas, E. D., Zhou, J., & Seeley, W. W. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1003109107 · Cited by 405 · see citing works
Self-citationBrain Development Cooperative Group (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr018 · Cited by 372 · see citing works
Age-related Volumetric Changes of Brain Gray and White Matter in Healthy Infants and Children
Matsuzawa, J. (2001) · Cerebral Cortex · doi:10.1093/cercor/11.4.335 · Cited by 315 · see citing works
Grydeland, H., Walhovd, K. B., Tamnes, C. K., Westlye, L. T., & Fjell, A. M. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.2811-13.2013 · Cited by 290 · see citing works
Evaluation of volume-based and surface-based brain image registration methods
Klein, A., Ghosh, S. S., Avants, B., Yeo, B. T. T., Fischl, B., Ardekani, B., Gee, J. C., Mann, J. J., & Parsey, R. V. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.091 · Cited by 255 · see citing works
Self-citationNieuwenhuys, R. (2012) · Brain Structure and Function · doi:10.1007/s00429-012-0460-z · Cited by 252 · see citing works
Registration based cortical thickness measurement
Das, S. R., Avants, B., Grossman, M., & Gee, J. C. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.016 · Cited by 246 · see citing works
Self-citationGur, R. E., & Gur, R. (2016) · Neuroscience and Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.07.035 · Cited by 203 · see citing works
Self-citationSavalia, N. K., Agres, P. F., Chan, M. Y., Feczko, E., Kennedy, K. M., & Wig, G. S. (2016) · Human Brain Mapping · doi:10.1002/hbm.23397 · Cited by 167 · see citing works
Motion Artifact in Magnetic Resonance Imaging: Implications for Automated Analysis
Blumenthal, J. D., Zijdenbos, A. P., Molloy, E. A., & Giedd, J. N. (2002) · NeuroImage · doi:10.1006/nimg.2002.1076 · Cited by 137 · see citing works
Bakhshi, K., & Chance, S. A. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.06.028 · Cited by 128 · see citing works
Gray Matter Alterations in Schizophrenia High-Risk Youth and Early-Onset Schizophrenia
Brent, B. K., Thermenos, H. W., Keshavan, M. S., & Seidman, L. J. (2013) · Child and Adolescent Psychiatric Clinics of North America · doi:10.1016/j.chc.2013.06.003 · Cited by 112 · see citing works
Shao, N., Yang, J., Li, J., & Shang, H. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00063 · Cited by 45 · see citing works
Neocortical maturation during adolescence: Change in neuronal soma dimension
Rabinowicz, T., Petétot, J. M.-C., Khoury, J. C., & de Courten‐Myers, G. M. (2008) · Brain and Cognition · doi:10.1016/j.bandc.2008.08.005 · Cited by 15 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Harmonization of cortical thickness measurements across scanners and sites
Fortin, J.-P., Cullen, N., Sheline, Y. I., Taylor, W. D., Aselcioglu, I., Cook, P. A., Adams, P., Cooper, C., Fava, M., McGrath, P. J., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.024 · Cited by 1,580 · see citing works
Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants
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., et al. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy109 · Cited by 855 · see citing works
Sex differences in cognitive decline among US adults
Levine, D. A., Gross, A. L., Briceño, E. M., Tilton, N., Giordani, B. J., Sussman, J. B., Hayward, R. A., Burke, J. F., Hingtgen, S., Elkind, M. S. V., et al. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.0169 · Cited by 440 · see citing works
Linked dimensions of psychopathology and connectivity in functional brain networks
Xia, C. H., Ma, Z., Ciric, R., Gu, S., Betzel, R. F., Kaczkurkin, A. N., Calkins, M. E., Cook, P. A., García de la Garza, A., Vandekar, S. N., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05317-y · Cited by 437 · see citing works
Self-citationQuantitative Assessment of Structural Image Quality
Rosen, A. F. G., Roalf, D., Ruparel, K., Blake, J., Seelaus, K., Villa, L., Ciric, R., Cook, P. A., Davatzikos, C., Elliott, M., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.059 · Cited by 443 · see citing works
Self-citationSex differences in the developing brain: insights from multimodal neuroimaging
Kaczkurkin, A. N., Raznahan, A., & Satterthwaite, T. D. (2019) · Neuropsychopharmacology · doi:10.1038/s41386-018-0111-z · Cited by 403 · see citing works
Self-citationEliot, L., Ahmed, A., Khan, H., & Patel, J. Y. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.02.026 · Cited by 351 · see citing works
Zou, L., Zheng, J., Miao, C., McKeown, M. J., & Wang, Z. J. (2017) · IEEE Access · doi:10.1109/access.2017.2762703 · Cited by 313 · see citing works
Gur, R. E., Moore, T. M., Rosen, A. F. G., Barzilay, R., Roalf, D. R., Calkins, M. E., Ruparel, K., Scott, J. C., Almasy, L., Satterthwaite, T. D., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.0943 · Cited by 239 · see citing works
Self-citationLiu, S., Seidlitz, J., Blumenthal, J. D., CLASEN, L. S., & Raznahan, A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1919091117 · Cited by 221 · see citing works
Bedford, S. A., Park, M. T. M., Devenyi, G. A., Tullo, S., Germann, J., Patel, R., Anagnostou, E. A., Baron‐Cohen, S., Bullmore, E. T., Chura, L. R., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0420-6 · Cited by 181 · see citing works
Persistent metabolic youth in the aging female brain
Goyal, M. S., Blazey, T., Su, Y., Couture, L. E., Durbin, T. J., Bateman, R. J., Benzinger, T. L. S., Morris, J. C., Raichle, M. E., & Vlassenko, A. G. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1815917116 · Cited by 178 · see citing works
Norbom, L. B., Ferschmann, L., Parker, N., Agartz, I., Andreassen, O. A., Paus, T., Westlye, L. T., & Tamnes, C. K. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102109 · Cited by 122 · see citing works
Patient-Tailored, Connectivity-Based Forecasts of Spreading Brain Atrophy
Brown, J. A., Deng, J., Neuhaus, J. M., Sible, I. J., Sias, A. C., Lee, S. E., Kornak, J., Marx, G. A., Karydas, A. M., Spina, S., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.08.037 · Cited by 112 · see citing works
Pitfalls in brain age analyses
Butler, E. R., Chen, A. A., Ramadan, R., Le, T. T., Ruparel, K., Moore, T. M., Satterthwaite, T. D., Zhang, F., Shou, H., Gur, R. C., et al. (2021) · Human Brain Mapping · doi:10.1002/hbm.25533 · Cited by 117 · see citing works
Self-citationStructural brain correlates of cognitive function in schizophrenia: A meta-analysis
Khalil, M., Hollander, P., Raucher‐Chéné, D., Lepage, M., & Lavigne, K. M. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.11.034 · Cited by 100 · see citing works
Walsh, M. J. M., Wallace, G. L., Gallegos, S. M., & Braden, B. B. (2021) · NeuroImage: Clinical · doi:10.1016/j.nicl.2021.102719 · Cited by 97 · see citing works
Weighted Stochastic Block Models of the Human Connectome across the Life Span
Faskowitz, J., Yan, X., Zuo, X., & Sporns, O. (2018) · Scientific Reports · doi:10.1038/s41598-018-31202-1 · Cited by 94 · see citing works
Mapping Human Laryngeal Motor Cortex during Vocalization
Eichert, N., Papp, D., Mars, R. B., & Watkins, K. E. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa182 · Cited by 89 · see citing works
Larsen, B., Sydnor, V. J., Keller, A. S., Yeo, B. T. T., & Satterthwaite, T. D. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.07.007 · Cited by 90 · see citing works
Self-citationLarsen, B., Cui, Z., Adebimpe, A., Pines, A., Alexander-Bloch, A., Bertolero, M., Calkins, M. E., Gur, R. E., Gur, R. C., Mahadevan, A. S., et al. (2022) · Science Advances · doi:10.1126/sciadv.abj8750 · Cited by 80 · see citing works
Self-citationCharting brain growth in tandem with brain templates at school age.
Dong, H.-M., Castellanos, F. X., Yang, N., Zhang, Z., Zhou, Q., He, Y., Zhang, L., Xu, T., Holmes, A., Yeo, B. T. T., et al. (2020) · Science Bulletin · doi:10.1016/j.scib.2020.07.027 · Cited by 72 · see citing works
Unbiased age‐specific structural brain atlases for Chinese pediatric population
Zhao, T.-D., Liao, X.-H., Fonov, V. S., Wang, Q., Men, W.-W., Wang, Y.-P., Qin, S., Tan, S.-P., Gao, J.-H., Evans, A. C., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.006 · Cited by 71 · see citing works
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 · see citing works
The Age of Reason: Functional Brain Network Development during Childhood
Tooley, U. A., Park, A. T., Leonard, J., Boroshok, A. L., McDermott, C. L., Tisdall, M. D., Bassett, D. S., & Mackey, A. P. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.0511-22.2022 · Cited by 74 · see citing works
Obstructive sleep apnea and cortical thickness in females and males
Macey, P. M., Haris, N., Kumar, R., Thomas, M. A., Woo, M. A., & Harper, R. M. (2018) · PLoS ONE · doi:10.1371/journal.pone.0193854 · Cited by 70 · see citing works
What has sex got to do with it? The role of hormones in the transgender brain
Nguyen, H. B., Loughead, J., Lipner, E., Hantsoo, L. V., Kornfield, S. L., & Epperson, C. N. (2018) · Neuropsychopharmacology · doi:10.1038/s41386-018-0140-7 · Cited by 69 · see citing works
Zhou, 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 60 · see citing works
Cumplido‐Mayoral, I., García-Prat, M., Operto, G., Falcón, C., Shekari, M., Cacciaglia, R., Milà‐Alomà, M., Lorenzini, L., Ingala, S., Wink, A. M., et al. (2023) · eLife · doi:10.7554/elife.81067 · Cited by 68 · see citing works
The Speed of Development of Adolescent Brain Age Depends on Sex and Is Genetically Determined
Brouwer, R. M., Schutte, J., Janssen, R. J., Boomsma, D. I., Pol, H. E. H., & Schnack, H. G. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa296 · Cited by 63 · see citing works
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 63 · see citing works
Sex differences in the neurochemistry of frontal cortex: Impact of early life stress
Perry, C. J., Campbell, E. J., Drummond, K. D., Lum, J. S., & Kim, J. H. (2020) · Journal of Neurochemistry · doi:10.1111/jnc.15208 · Cited by 58 · see citing works
Individual 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 58 · see citing works
Popovic, D., Ruef, A., Dwyer, D., Antonucci, L. A., Eder, J., Sanfelici, R., Kambeitz‐Ilankovic, L., Oztuerk, O. F., Dong, M. S., Paul, R., et al. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.05.020 · Cited by 59 · see citing works
Ge, R., Torres, I. J., Brown, J. J., Gregory, E., McLellan, E., Downar, J. H., Blumberger, D. M., Daskalakis, Z. J., Lam, R. W. M., & Vila‐Rodriguez, F. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.04.096 · Cited by 56 · see citing works
Volumetric gray matter measures of amygdala and accumbens in childhood overweight/obesity
Perlaki, G., Molnár, D., Smeets, P. A. M., Ahrens, W., Wolters, M., Eiben, G., Lissner, L., Erhard, P., van Meer, F., Herrmann, M., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0205331 · Cited by 55 · see citing works
García, J. M. P., Suárez‐Suárez, S., Doallo, S., & Cadaveira, F. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104637 · Cited by 51 · see citing works
Bas‐Hoogendam, J. M., van Steenbergen, H., Tissier, R., Houwing‐Duistermaat, J. J., Westenberg, P. M., & van der Wee, N. J. A. (2018) · EBioMedicine · doi:10.1016/j.ebiom.2018.08.048 · Cited by 50 · see citing works
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 62 · see citing works
Truelove-Hill, M., Erus, G., Bashyam, V. M., Varol, E., Sako, C., Gur, R., Gur, R. E., Koutsouleris, N., Zhuo, C., Fan, Y., et al. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.2092-19.2019 · Cited by 45 · see citing works
Self-citationLi, Y., Sethi, S. K., Zhang, C., Miao, Y., Yerramsetty, K. K., Palutla, V. K., Gharabaghi, S., Wang, C., He, N., Cheng, J., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.607705 · Cited by 48 · see citing works
Modabbernia, A., Reichenberg, A., Ing, A., Moser, D., Doucet, G., Artiges, E., Banaschewski, T., Barker, G., Becker, A., Bokde, A. L. W., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0757-x · Cited by 47 · see citing works
Sato, M. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2020.107404 · Cited by 43 · see citing works
Assessment of conditioned fear extinction in male and female adolescent rats
Perry, C. J., Ganella, D. E., Nguyen, L. D., Du, X., Drummond, K. D., Whittle, S., Pang, T. Y., & Kim, J. H. (2020) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2020.104670 · Cited by 47 · see citing works
Chen, D., Strang, J. F., Kolbuck, V. D., Rosenthal, S. M., Wallen, K., Waber, D. P., Steinberg, L. D., Sisk, C. L., ROSS, J. L., Paus, T., et al. (2020) · Transgender Health · doi:10.1089/trgh.2020.0006 · Cited by 47 · see citing works
Improving Individual Brain Age Prediction Using an Ensemble Deep Learning Framework
Kuo, C.-Y., Tai, T., Lee, P., Tseng, C.-W., Chen, C.-Y., Chen, L., Lee, C.-K., Chou, K., See, S. C. W., & Lin, C. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.626677 · Cited by 45 · see citing works
Tapia‐Serrano, M. Á., García‐Hermoso, A., Sevil‐Serrano, J., Sánchez‐Oliva, D., & Miguel, P. A. S. (2021) · Journal of science and medicine in sport · doi:10.1016/j.jsams.2021.09.005 · Cited by 47 · see citing works
Cannabis use in youth is associated with limited alterations in brain structure
Scott, J. C., Rosen, A. F. G., Moore, T. M., Roalf, D. R., Satterthwaite, T. D., Calkins, M. E., Ruparel, K., Gur, R. E., & Gur, R. C. (2019) · Neuropsychopharmacology · doi:10.1038/s41386-019-0347-2 · Cited by 44 · see citing works
Self-citationLiloia, D., Zamfira, D. A., Tanaka, M., Manuello, J., Crocetta, A., Keller, R., Cozzolino, M., Duca, S., Cauda, F., & Costa, T. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105791 · Cited by 44 · see citing works
Dynamic gray matter volume changes in pediatric multiple sclerosis
Meo, E. D., Meani, A., Moiola, L., Ghezzi, A., Veggiotti, P., Filippi, M., & Rocca, M. A. (2019) · Neurology · doi:10.1212/wnl.0000000000007267 · Cited by 41 · see citing works
Qiu, L., Yan, H., Zhu, R., Yan, J., Yuan, H., Han, Y., Yue, W., Tian, L., & Zhang, D. (2018) · BMC Psychiatry · doi:10.1186/s12888-018-1806-8 · Cited by 37 · see citing works
León, J. J., Sánchez-Kuhn, A., Fernández‐Martín, P., Páez-Pérez, M. A., Thomas, C., Datta, A., Sánchez-Santed, F., & Flores, P. (2020) · Behavioural Brain Research · doi:10.1016/j.bbr.2020.112485 · Cited by 40 · see citing works
Belov, V., Erwin-Grabner, T., Aghajani, M., Aleman, A., Amod, A. R., Başgöze, Z., Benedetti, F., Besteher, B., Bülow, R., Ching, C. R. K., et al. (2024) · Scientific Reports · doi:10.1038/s41598-023-47934-8 · Cited by 39 · see citing works
Chow, H. M., Garnett, E. O., Li, H., Etchell, A. C., Sepulcre, J., Drayna, D. T., Chugani, D. C., & Chang, S. (2020) · Neurobiology of Language · doi:10.1162/nol_a_00017 · Cited by 36 · see citing works
The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students
Tsuchida, A., Laurent, A., Crivello, F., Petit, L., Joliot, M., Pepe, A., Beguedou, N., Gueye, M.-F., Verrecchia, V., Nozais, V., et al. (2021) · Brain Structure and Function · doi:10.1007/s00429-021-02334-4 · Cited by 29 · see citing works
Qu, G., Zhou, Z., Calhoun, V. D., Zhang, A., & Wang, Y. (2025) · Medical Image Analysis · doi:10.1016/j.media.2025.103570 · Cited by 35 · see citing works
Thomas, C., Ghodratitoostani, I., Delbem, A. C. B., Ali, A., & Datta, A. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856898 · Cited by 37 · see citing works
Morphometrical Brain Markers of Sex Difference
Brennan, D. J., Wu, T., & Fan, J. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab037 · Cited by 33 · see citing works
Canales-Rodríguez, E. J., Alonso-Lana, S., Verdolini, N., Sarró, S., Feria‐Raposo, I., Montoro, I., Garcia‐Ruiz, B., Jiménez, E., Varo, C., Albacete, À., et al. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.06.002 · Cited by 32 · see citing works
Walter, A. E., Wilkes, J. R., Arnett, P. A., Miller, S. J., Sebastianelli, W. J., Seidenberg, P. H., & Slobounov, S. (2021) · Brain Imaging and Behavior · doi:10.1007/s11682-021-00489-6 · Cited by 33 · see citing works
Wadsley, M. G., & Ihssen, N. (2023) · Brain Sciences · doi:10.3390/brainsci13050787 · Cited by 34 · see citing works
Burrowes, S. A. B., Rhodes, C. S., Meeker, T. J., Greenspan, J. D., Gullapalli, R. P., & Seminowicz, D. A. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00095-7 · Cited by 32 · see citing works
Statsenko, Y. A., Habuza, T., Smetanina, D., Simiyu, G. L., Uzianbaeva, L., Gorkom, K., Zaki, N., Charykova, I., Koteesh, J. A., Almansoori, T. M., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.713680 · Cited by 31 · see citing works
A systematic comparison of VBM pipelines and their application to age prediction
Antonopoulos, G., More, S., Raimondo, F., Eickhoff, S. B., Hoffstaedter, F., & Patil, K. R. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120292 · Cited by 30 · see citing works
How does hormonal contraception affect the developing human adolescent brain?
Cahill, L. F. (2018) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.06.015 · Cited by 31 · see citing works
Ibrahim, K., Kalvin, C. B., Li, F., He, G. S., Pelphrey, K. A., McCarthy, G., & Sukhodolsky, D. G. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100884 · Cited by 32 · see citing works
Raine, P. J., & Rao, H. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00659-0 · Cited by 30 · see citing works
Ma, Q., Wang, H., Rolls, E. T., Xiang, S., Li, J., Li, Y., Zhou, Q., Cheng, W., & Li, F. R. (2022) · BMC Medicine · doi:10.1186/s12916-022-02627-3 · Cited by 30 · see citing works
Wang, S., Yang, C., Zhao, Y., Lai, H., Zhang, L., & Gong, Q. (2019) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-019-01421-6 · Cited by 28 · see citing works
Gur, R. C., Butler, E. R., Moore, T. M., Rosen, A. F. G., Ruparel, K., Satterthwaite, T. D., Roalf, D. R., Gennatas, E. D., Bilker, W. B., Shinohara, R. T., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa282 · Cited by 27 · see citing works
Self-citationNormative cerebral cortical thickness for human visual areas
Alvarez, I., Parker, A. J., & Bridge, H. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116057 · Cited by 28 · see citing works
Shifting brain circuits in pain chronicity
Youssef, A. M., Azqueta‐Gavaldon, M., Silva, K. E., Barakat, N., Lopez, N., Mahmud, F., Lebel, A., Sethna, N. F., Zurakowski, D., Simons, L. E., et al. (2019) · Human Brain Mapping · doi:10.1002/hbm.24709 · Cited by 27 · see citing works
Lv, Q., Yan, M., Shen, X., Wu, J., Yu, W., Yan, S., Yang, F., Zeljic, K., Shi, Y., Zhou, Z., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa229 · Cited by 28 · see citing works
Sex and Sleep Disruption as Contributing Factors in Alzheimer’s Disease
Johnson, C. E., Duncan, M. J., & Murphy, M. P. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230527 · Cited by 34 · see citing works
Yang, D., Ha, S. G., Ryoo, E., Choi, J. Y., & Kim, H. J. (2019) · Resuscitation · doi:10.1016/j.resuscitation.2019.01.033 · Cited by 27 · see citing works
Cortical morphometry in anorexia nervosa: An out‐of‐sample replication study
Leppänen, J., Sedgewick, F., Cardi, V., Treasure, J. L., & Tchanturia, K. (2019) · European Eating Disorders Review · doi:10.1002/erv.2686 · Cited by 25 · see citing works
Dennis, E., Caeyenberghs, K., Asarnow, R., Babikian, T., Bartnik-Olson, B. L., Bigler, E., Figaji, A., Giza, C., Goodrich-Hunsaker, N. J., Hodges, C., et al. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00363-x · Cited by 19 · see citing works
Brain structure changes associated with sexual orientation
Votinov, M., Goerlich, K. S., Puiu, A. A., Smith, E. S., Nickl‐Jockschat, T., Derntl, B., & Habel, U. (2021) · Scientific Reports · doi:10.1038/s41598-021-84496-z · Cited by 26 · see citing works
Prenatal Programming of Neurodevelopment: Structural and Functional Changes
Demers, C. H., Aran, Ö., Glynn, L. M., & Davis, E. P. (2021) · Springer eBooks · doi:10.1007/978-3-030-60159-1_9 · Cited by 25 · see citing works
Relationship between Lipoprotein (a) and cognitive function – Results from the Berlin Aging Study II
Rohr, F., Bucholtz, N., Toepfer, S., Norman, K., Spira, D., Steinhagen‐Thiessen, E., Lill, C. M., Bertram, L., Demuth, I., Buchmann, N., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-66783-3 · Cited by 25 · see citing works
Skorska, M. N., Chavez, S., Devenyi, G. A., Patel, R., Thurston, L. T., Lai, M., Zucker, K. J., Chakravarty, M. M., Lobaugh, N. J., & VanderLaan, D. P. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10020345 · Cited by 25 · see citing works
Sexual Dimorphism in Brain Development: Influence on Affective Disorders
López-Ojeda, W., & Hurley, R. A. (2021) · Journal of Neuropsychiatry · doi:10.1176/appi.neuropsych.20100269 · Cited by 24 · see citing works
Lin, H.-M., Chang, Y.-T., Chen, M.-H., Liu, S.-T., Chen, B.-S., Li, L., Lee, C.-Y., Sue, Y.-R., Sung, T.-M., Sun, C.-K., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192316277 · Cited by 26 · see citing works
Measures of Brain Connectivity and Cognition by Sex in US Children
Tomasi, D. G., & Volkow, N. D. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.0157 · Cited by 25 · see citing works
Complexity of Sex Differences and Their Impact on Alzheimer’s Disease
Kadlecová, M., Freude, K., & Haukedal, H. (2023) · Biomedicines · doi:10.3390/biomedicines11051261 · Cited by 26 · see citing works
Wu, J., & Tang, X. (2019) · Neuroinformatics · doi:10.1007/s12021-019-09438-7 · Cited by 25 · see citing works
Haapala, E. A., Haapala, H. L., Syväoja, H., Tammelin, T. H., Finni, T., & Kiuru, N. (2020) · Journal of Sport and Health Science · doi:10.1016/j.jshs.2019.07.003 · Cited by 24 · see citing works
Sung, D., Park, B., Kim, S.-Y., Kim, B.-N., Park, S., Jung, K.-I., Kim, J., & Park, M.-H. (2020) · Scientific Reports · doi:10.1038/s41598-020-60692-1 · Cited by 24 · see citing works
Prospective Study of Gray Matter Atrophy Following Pediatric Mild Traumatic Brain Injury
Mayer, A. R., Meier, T. B., Dodd, A. B., Stephenson, D. D., Robertson‐Benta, C. R., Ling, J. M., Reddy, S. P., Zotev, V. S., Vakamudi, K., Campbell, R. A., et al. (2022) · Neurology · doi:10.1212/wnl.0000000000201470 · Cited by 23 · see citing works
Kim, J., Jung, Y., Barcus, R. A., Bachevalier, J., Sánchez, M. M., Nader, M. A., & Whitlow, C. T. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa015 · Cited by 23 · see citing works
Sex effects on cortical morphological networks in healthy young adults
Ge, R., Liu, X., Long, D., Frangou, S., & Vila‐Rodriguez, F. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117945 · Cited by 19 · see citing works
Chen, Y., Chaudhary, S., Wang, W., & Li, C.-S. R. (2021) · Addiction Neuroscience · doi:10.1016/j.addicn.2021.100003 · Cited by 22 · see citing works
Linli, Z., Rolls, E. T., Zhao, W. D., Kang, J., Feng, J., & Guo, S. (2022) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2022.110698 · Cited by 21 · see citing works
Pan, N., Yang, C., Suo, X., Shekara, A., Hu, S., Gong, Q., & Wang, S. (2023) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-023-02231-7 · Cited by 23 · see citing works
Relating sex-bias in human cortical and hippocampal microstructure to sex hormones
Küchenhoff, S., Bayrak, Ş., Zsido, R. G., Saberi, A., Bernhardt, B. C., Weis, S., Schaare, H. L., Sacher, J., Eickhoff, S. B., & Valk, S. L. (2024) · Nature Communications · doi:10.1038/s41467-024-51459-7 · Cited by 30 · see citing works
Shafiei, G., Esper, N., Hoffmann, M., Ai, L., Chen, A. A., Cluce, J., Covitz, S., Giavasis, S., Lane, C., Mehta, K., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.08.026 · Cited by 10 · see citing works
Self-citationBrain MR Image Classification for ADHD Diagnosis Using Deep Neural Networks
Abdolmaleki, S., & Abadeh, M. S. (2020) · Iranian Conference on Machine Vision and Image Processing · doi:10.1109/mvip49855.2020.9116877 · Cited by 21 · see citing works
Rosales, E. G., Baumgärtner, T., & Knoch, D. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119664 · Cited by 21 · see citing works
Ross, M. C., Dvorak, D., Sartin‐Tarm, A., Botsford, C., Cogswell, I. E., Hoffstetter, A., Putnam, O., Schomaker, C. M., Smith, P., Stalsberg, A., et al. (2021) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2021.111297 · Cited by 18 · see citing works
Yang, D., Ryoo, E., & Kim, H. J. (2019) · Frontiers in Pediatrics · doi:10.3389/fped.2019.00223 · Cited by 20 · see citing works
- Authors
- Gennatas, E. D., Avants, B. B., Wolf, D. H., Satterthwaite, T. D., Ruparel, K., Ciric, R., Hakonarson, H., Gur, R. E., & Gur, R. C.
- Affiliations
- University of Pennsylvania (US)
- Children's Hospital of Philadelphia (US)
- ORCID
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2017-04-21
- Volume
- 37
- Issue
- 20
- Pages
- 5065-5073
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC5444192
- OpenAlex
- W2605712228
- Cited by
- 302
- References
- 37
- Citations by year
- 2026: 23 · 2025: 28 · 2024: 34 · 2023: 37 · 2022: 38 · 2021: 51 · 2020: 38 · 2019: 35 · 2018: 14 · 2017: 4
- FWCI
- 19.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01mh107235-03, MH-089983, MH-096891, MH107235)
- National Institute of Mental Health (RC2MH089983, P50MH096891, R01-MH-107235)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- gray matter density, gray matter volume, cortical thickness, brain development, sex differences, age-related changes, adolescence, Philadelphia Neurodevelopmental Cohort, structural MRI
- MeSH terms
- Adolescent, Aging, Brain, Child, Female, Humans, Magnetic Resonance Imaging, Male, Organ Size, Sensitivity and Specificity, Sex Characteristics, Reproducibility of Results, Young Adult, Connectome, Gray 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 ›
Are you an author, or do you see a problem with this page? Request a review