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Patterns of Coordinated Anatomical Change in Human Cortical Development: A Longitudinal Neuroimaging Study of Maturational Coupling
Open accessAbstract
SUMMARY Understanding of human structural brain development has rapidly advanced in recent years, but remains fundamentally “localizational” in nature. Here, we use 376 longitudinally acquired structural brain scans from 108 typically developing adolescents to conduct the first study of coordinated anatomical change within the developing cortex. Correlation in rates of anatomical change was regionally heterogeneous, with fronto-temporal association cortices showing the strongest and most widespread maturational coupling with other cortical areas, and lower-order sensory cortices showing the least. Canonical cortical systems with rich structural and functional interconnectivity showed significantly elevated maturational coupling. Evidence for sexually dimorphic maturational coupling was found within a frontopolar-centered prefrontal system involved in complex decision-making. By providing the first link between cortical connectivity and the coordination of cortical development, we reveal a hitherto unseen property of healthy brain maturation, which may represent a target for neurodevelopmental disease processes, and a substrate for sexually dimorphic behavior in adolescence.
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Citations
Cites
A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
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
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
Dynamic 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 2×
“This re-representation of repeat sMRI measures of brain anatomy as person-specific maps of anatomical change enabled us to interrelate the diverse maturational tempos that exist within the growing cortical sheet (Gogtay et al., 2004; Shaw et al., 2008) by asking how interindividual differences in rate of change at one…”
Self-citationConsistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
Why do many psychiatric disorders emerge during adolescence?
Paus, T., Keshavan, M., & Giedd, J. N. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2513 · Cited by 3,123
Self-citationFunctional-anatomic fractionation of the brain’s default network
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010) · Neuron · doi:10.1016/j.neuron.2010.02.005 · Cited by 2,767
Changes in grey matter induced by training
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004) · Nature · doi:10.1038/427311a · Cited by 2,373
Intrinsic functional architecture in the anaesthetized monkey brain
Vincent, J. L., Patel, G. H., Fox, M. D., Snyder, A. Z., Baker, J. T., Van Essen, D. C., Zempel, J. M., Snyder, L. H., Corbetta, M., & Raichle, M. E. (2007) · Nature · doi:10.1038/nature05758 · Cited by 1,786
Cited by
Adolescence: A foundation for future health
Sawyer, S. M., Afifi, R. A., Bearinger, L. H., Blakemore, S.-J., Dick, B., Ezeh, A. C., & Patton, G. C. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60072-5 · Cited by 2,635
Semple, B. D., Blomgren, K., Gimlin, K., Ferriero, D. M., & Noble-Haeusslein, L. J. (2013) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2013.04.001 · Cited by 2,132
Plasticity in gray and white: neuroimaging changes in brain structure during learning
Zatorre, R. J., Fields, R. D., & Johansen-Berg, H. (2012) · Nature Neuroscience · doi:10.1038/nn.3045 · Cited by 1,685
Imaging structural co-variance between human brain regions
Alexander-Bloch, A., Giedd, J. N., & Bullmore, E. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3465 · Cited by 1,064
Self-citationOn testing for spatial correspondence between maps of human brain structure and function
Alexander-Bloch, A. F., Shou, H., Liu, S., Satterthwaite, T. D., Glahn, D. C., Shinohara, R. T., Vandekar, S. N., & Raznahan, A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.05.070 · Cited by 947
Self-citationAdolescence as a neurobiological critical period for the development of higher-order cognition
Larsen, B., & Luna, B. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.09.005 · Cited by 853
Decision-making in the adolescent brain
Blakemore, S.-J., & Robbins, T. W. (2012) · Nature Neuroscience · doi:10.1038/nn.3177 · Cited by 711
Networks of anatomical covariance
Evans, A. C. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.054 · Cited by 429
Brain development and aging: Overlapping and unique patterns of change
Tamnes, C. K., Walhovd, K. B., Dale, A. M., Østby, Y., Grydeland, H., Richardson, G., Westlye, L. T., Roddey, J. C., Hagler, D. J., Due-Tønnessen, P., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.039 · Cited by 287
Shaw, P., Malek, M., Watson, B., Greenstein, D., de Rossi, P., & Sharp, W. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.04.007 · Cited by 303
Self-citationDumontheil, I. (2014) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2014.07.009 · Cited by 293
Paulus, M. P., Squeglia, L. M., Bagot, K., Jacobus, J., Kuplicki, R., Breslin, F. J., Bodurka, J., Morris, A. S., Thompson, W. K., Bartsch, H., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.040 · Cited by 254
Pfefferbaum, A., Rohlfing, T., Rosenbloom, M. J., Chu, W., Colrain, I. M., & Sullivan, E. V. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.008 · Cited by 256
Normative brain size variation and brain shape diversity in humans
Reardon, P. K., Seidlitz, J., Vandekar, S., Liu, S., Patel, R., Park, M. T. M., Alexander-Bloch, A., Clasen, L. S., Blumenthal, J. D., Lalonde, F. M., et al. (2018) · Science · doi:10.1126/science.aar2578 · Cited by 255
Self-citationDevelopmental Changes in Organization of Structural Brain Networks
Khundrakpam, B. S., Reid, A., Brauer, J., Carbonell, F., Lewis, J., Ameis, S., Karama, S., Lee, J., Chen, Z., Das, S., et al. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs187 · Cited by 234
Development of Human Brain Structural Networks Through Infancy and Childhood
Huang, H., Shu, N., Mishra, V., Jeon, T., Chalak, L., Wang, Z. J., Rollins, N., Gong, G., Cheng, H., Peng, Y., et al. (2015) · Cerebral Cortex · doi:10.1093/cercor/bht335 · Cited by 223
Vértes, P. E., & Bullmore, E. T. (2015) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12365 · Cited by 197
Structural and Maturational Covariance in Early Childhood Brain Development
Geng, X., Li, G., Lu, Z., Gao, W., Wang, L., Shen, D., Zhu, H., & Gilmore, J. H. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw022 · Cited by 175
Structural brain development: A review of methodological approaches and best practices
(2017) · doi:10.1016/j.dcn.2017.11.008 · Cited by 124
Adolescent nicotine induces persisting changes in development of neural connectivity.
Smith, R. F., McDonald, C. G., Bergstrom, H. C., Ehlinger, D. G., & Brielmaier, J. M. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.05.019 · Cited by 120
Brain connectivity in normally developing children and adolescents
Khundrakpam, B. S., Lewis, J. D., Zhao, L., Chouinard-Decorte, F., & Evans, A. C. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.03.062 · Cited by 91
Richmond, S., Johnson, K. A., Seal, M. L., Allen, N. B., & Whittle, S. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.08.024 · Cited by 70
Development of cortical anatomical properties from early childhood to early adulthood
Nie, J., Li, G., & Shen, D. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.021 · Cited by 70
Lee, N. R., Wallace, G. L., Raznahan, A., Clasen, L. S., & Giedd, J. N. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00496 · Cited by 30
“A (s) Age Z-score M 12.23 114.28 28.50 −0.06 14.92 0.00 SD 1.80 12.08 10.66 0.91 9.08 1.00 Range 9–14 86–147 10–61 −1.76–2.82 0–48 −1.93–3.82 www.frontiersin.org July 2014 | Volume 5 | Article 496 | 3 Time (Trails B–”
BackgroundMethodInfluentialSelf-citationFunctional neuroanatomy of interoceptive processing in children and adolescents: a pilot study
Klabunde, M., Juszczak, H., Jordan, T., Baker, J. M., Bruno, J., Carrion, V., & Reiss, A. L. (2019) · Scientific Reports · doi:10.1038/s41598-019-52776-4 · Cited by 29
Jiang, L., Zhang, T., Lv, F., Li, S., Liu, H., Zhang, Z., & Luo, T. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00010 · Cited by 13
Metadata
- Authors
- Raznahan, A., Lerch, J. P., Lee, N., Greenstein, D., Wallace, G. L., Stockman, M., Clasen, L., Shaw, P. W., & Giedd, J. N.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2011-12
- Volume
- 72
- Issue
- 5
- Pages
- 873-884
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W1990300831
- Cited by
- 305
- References
- 29
- FWCI
- 9.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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