The DOI matches its Crossref record; 67 of the 68 references it cites were found in a registry or an index.
Structural and Maturational Covariance in Early Childhood Brain Development
Open accessAbstract
Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development.
Overview
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
Verification
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?
In the citing paper
“These trends are consistent with the presence of basic somatosensory and visual functions at birth, and help contextualize findings that primary sensory regions are generally the first cortical areas to reach plateaus or peaks in growth (Geng et al., 2016; Gilmore et al., 2012; Lyall et al., 2015; Scott et al., 2015).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Geng et al., 2016
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881
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
Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.015 · Cited by 11,314
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.018 · Cited by 7,429
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
Synaptic Activity and the Construction of Cortical Circuits
Katz, L. C., & Shatz, C. J. (1996) · Science · doi:10.1126/science.274.5290.1133 · Cited by 3,048
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
Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems
Fox, M. D., Corbetta, M., Snyder, A. Z., Vincent, J. L., & Raichle, M. E. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0604187103 · Cited by 2,101
Research works printed but not linked: 1
- 10.2307/2408955 · DOI
Cited by
Sorted by citations
Imaging structural and functional brain development in early childhood
Gilmore, J. H., Knickmeyer, R. C., & Gao, W. (2018) · Nature Reviews Neuroscience · doi:10.1038/nrn.2018.1 · Cited by 1,013
Self-citationMakropoulos, A., Robinson, E. C., Schuh, A., Wright, R., Fitzgibbon, S. P., Božek, J., Counsell, S. J., Steinweg, J. K., Vecchiato, K., Passerat‐Palmbach, J., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.054 · Cited by 571
Grayson, D. S., & Fair, D. A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.079 · Cited by 411
Eliot, L., Ahmed, A., Khan, H., & Patel, J. Y. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.02.026 · Cited by 379
Adolescent Tuning of Association Cortex in Human Structural Brain Networks
Váša, F., Seidlitz, J., Romero-García, R., Whitaker, K. J., Rosenthal, G., Vértes, P. E., Shinn, M., Alexander‐Bloch, A. F., Fonagy, P., Dolan, R. J., et al. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx249 · Cited by 358
Developmental connectomics from infancy through early childhood
Cao, M., Huang, H., & He, Y. (2017) · Trends in Neurosciences · doi:10.1016/j.tins.2017.06.003 · Cited by 284
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
Linking interindividual variability in brain structure to behaviour
Genon, S., Eickhoff, S. B., & Masouleh, S. K. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00584-7 · Cited by 193
Canetto, S. S., & Chen, J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.042 · Cited by 194
Computational neuroanatomy of baby brains: A review
Li, G., Wang, L., Yap, P., Wang, F., Wu, Z., Meng, Y., Dong, P., Kim, J., Shi, F., Rekik, I., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.042 · Cited by 172
Self-citationRapid infant prefrontal cortex development and sensitivity to early environmental experience
Hodel, A. S. (2018) · Developmental Review · doi:10.1016/j.dr.2018.02.003 · Cited by 177
Sex differences in functional connectivity during fetal brain development
Wheelock, M. D., Hect, J. L., Hernandez-Andrade, E., Hassan, S. S., Romero, R., Eggebrecht, A. T., & Thomason, M. E. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100632 · Cited by 126
Developmental topography of cortical thickness during infancy
Wang, F., Lian, C., Wu, Z., Zhang, H., Li, T., Meng, Y., Wang, L., Lin, W., Shen, D. G., & Li, G. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1821523116 · Cited by 122
Self-citationManwell, L. A., Tadros, M., Ciccarelli, T. M., & Eikelboom, R. (2022) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2101028 · Cited by 122
Infant social interactions and brain development: A systematic review
Ilyka, D., Johnson, M. H., & Lloyd‐Fox, S. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.09.001 · Cited by 150
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 93
Infant and Child MRI: A Review of Scanning Procedures
Copeland, A., Silver, E. A., Korja, R., Lehtola, S. J., Merisaari, H., Saukko, E., Sinisalo, S., Saunavaara, J. P., Lähdesmäki, T., Parkkola, R. K., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.666020 · Cited by 92
Lebenberg, J., Mangin, J.-F., Thirion, B., Poupon, C., Hertz-Pannier, L., Leroy, F., Adibpour, P., Dehaene-Lambertz, G., & Dubois, J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.07.022 · Cited by 65
Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain
Fenchel, D., Dimitrova, R., Seidlitz, J., Robinson, E. C., Batalle, D., Hutter, J., Christiaens, D., Pietsch, M., Brandon, J., Hughes, E. J., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa150 · Cited by 71
Petanjek, Z., Sedmak, D., Džaja, D., Hladnik, A., Rašin, M. R., & Milošević, N. J. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00122 · Cited by 67
Luo, N., Jing Sui (Beijing Normal University), my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Abrol, A., Chen, J., Turner, J. A., Damaraju, E., Fu, Z., Fan, L., Lin, D., Zhuo, C., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa127 · Cited by 48
Structural insight into the individual variability architecture of the functional brain connectome
Sun, L., Liang, X., Duan, D., Liu, J., Chen, Y., Wang, X., Liao, X., Xia, M., Zhao, T., & Yong He, A. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119387 · Cited by 48
Default Mode Network Maturation and Environmental Adversities During Childhood
Rebello, K., Moura, L. M., Pinaya, W. H. L., Rohde, L. A., & Sato, J. R. (2018) · Chronic Stress · doi:10.1177/2470547018808295 · Cited by 46
Vijayakumar, N., Ball, G., Seal, M. L., Mundy, L. K., Whittle, S., & Silk, T. J. (2021) · Scientific Reports · doi:10.1038/s41598-021-88918-w · Cited by 46
A systematic review of physical–digital play technology and developmentally relevant child behaviour
Torres, P. E., Ulrich, P., Cucuiat, V., Cukurova, M., la Presa, M. C. F. D., Luckin, R., Carr, A., Dylan, T., Durrant, A. C., Vines, J., et al. (2021) · International Journal of Child-Computer Interaction · doi:10.1016/j.ijcci.2021.100323 · Cited by 83
Fine-grained functional parcellation maps of the infant cerebral cortex
Wang, F., Zhang, H., Wu, Z., Hu, D., Zhou, Z., Girault, J. B., Wang, L., Lin, W., & Li, G. (2023) · eLife · doi:10.7554/elife.75401 · Cited by 46
Self-citationVanes, L. D., Hadaya, L., Kanel, D., Falconer, S., Ball, G., Batallé, D., Counsell, S. J., Edwards, A. D., & Nosarti, C. (2021) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2021.05.002 · Cited by 40
Multi-task prediction of infant cognitive scores from longitudinal incomplete neuroimaging data
Adeli, E., Meng, Y., Li, G., Lin, W., & Shen, D. G. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.052 · Cited by 39
Self-citationBrain Development and Physical Aggression
Eliot, L. (2021) · Current Anthropology · doi:10.1086/711705 · Cited by 44
Smith, S. M., Duff, E. P., Groves, A. R., Nichols, T. E., Jbabdi, S., Westlye, L. T., Tamnes, C. K., Engvig, A., Walhovd, K. B., Fjell, A. M., et al. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.2912-18.2019 · Cited by 39
Aboud, K. S., Huo, Y., Kang, H., Ealey, A., Resnick, S. M., Landman, B. A., & Cutting, L. E. (2018) · Human Brain Mapping · doi:10.1002/hbm.24359 · Cited by 34
Mixed-Effect Time-Varying Network Model and Application in Brain Connectivity Analysis
Zhang, J., Sun, W. W., & Li, L. (2019) · Journal of the American Statistical Association · doi:10.1080/01621459.2019.1677242 · Cited by 34
The emergence of long-range language network structural covariance and language abilities
Qi, T., Schaadt, G., Cafiero, R., Bräuer, J., Skeide, M. A., & Friederici, A. D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.02.014 · Cited by 31
Dissecting human cortical similarity networks across the lifespan
Liang, X., Sun, L., Xia, M., Zhao, T., Gong, G., Li, Q., Liao, X., Cui, Z., Duan, D., Pang, C., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.06.018 · Cited by 34
Wang, L., Li, G., Adeli, E., Liu, M., Wu, Z., Meng, Y., Lin, W., & Shen, D. G. (2018) · Human Brain Mapping · doi:10.1002/hbm.24027 · Cited by 28
Self-citationWoodburn, M., Bricken, C. L., Wu, Z., Li, G., Wang, L., Lin, W., Sheridan, M. A., & Cohen, J. R. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118232 · Cited by 32
Self-citationLiu, M., Lepage, C., Kim, S. Y., Jeon, S., Kim, S. H., Simon, J. P., Tanaka, N., Yuan, S., Islam, T., Peng, B., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.650082 · Cited by 25
(2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374 · Cited by 30
Sun, L., Zhang, D., Lian, C., Wang, L., Wu, Z., Shao, W., Lin, W., Shen, D. G., & Li, G. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.037 · Cited by 26
Self-citationCulture in Mind – An Enactivist Account
Hutto, D. D., Gallagher, S., Ilundáin‐Agurruza, J., & Hipólito, I. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.009 · Cited by 29
Brain age prediction and deviations from normative trajectories in the neonatal connectome
Sun, H., Mehta, S., Khaitova, M., Cheng, B., Hao, X., Spann, M. N., & Scheinost, D. (2024) · Nature Communications · doi:10.1038/s41467-024-54657-5 · Cited by 27
Hippocampus co-atrophy pattern in dementia deviates from covariance patterns across the lifespan.
Plachti, A., Kharabian, S., Eickhoff, S., Maleki-Balajoo, S., Hoffstaedter, F., Varikuti, D., Jockwitz, C., Caspers, S., Amunts, K., & Genon, S. (2020) · Brain : a journal of neurology · doi:10.1093/brain/awaa222 · Cited by 24
Sex differences in resting state functional connectivity across the first two years of life
Fenske, S. J., Liu, J., Chen, H., Diniz, M. A., Stephens, R. L., Cornea, E. A., Gilmore, J. H., & Gao, W. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101235 · Cited by 22
Self-citationThe Cambridge Handbook of the International Psychology of Women
Cheung, F. M., & Halpern, D. F. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716 · Cited by 24
Xu, F., Liu, M., Kim, S. Y., Ge, X., Zhang, Z., Tang, Y., Lin, X., Toga, A. W., Liu, S., & Kim, H. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab123 · Cited by 19
Lammertink, F., van den Heuvel, M. P., Hermans, E. J., Dudink, J., Tataranno, M. L., Benders, M. J. N. L., & Vinkers, C. H. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02019-4 · Cited by 24
Disrupted Topological Patterns of Large-Scale Network in Conduct Disorder
Jiang, Y., Liu, W., Ming, Q., Gao, Y., Ma, R., Zhang, X., Situ, W., Wang, X., Yao, S., & Huang, B. (2016) · Scientific Reports · doi:10.1038/srep37053 · Cited by 20
Can we predict subject‐specific dynamic cortical thickness maps during infancy from birth?
Meng, Y., Li, G., Rekik, I., Zhang, H., Gao, Y., Lin, W., & Shen, D. G. (2017) · Human Brain Mapping · doi:10.1002/hbm.23555 · Cited by 19
Self-citationGendron, M., Mesquita, B., & Barrett, L. F. (2020) · Culture, Mind, and Brain · doi:10.1017/9781108695374.010 · Cited by 20
Wang, Y., Zhu, D., Zhao, L., Wang, X., Zhang, Z., Hu, B., Wu, D., & Zheng, W. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120660 · Cited by 17
Surface-constrained volumetric registration for the early developing brain
Ahmad, S., Wu, Z., Li, G., Wang, L., Lin, W., Yap, P., & Shen, D. G. (2019) · Medical Image Analysis · doi:10.1016/j.media.2019.101540 · Cited by 14
Self-citationGraff, K., Tansey, R. C., Rai, S., Ip, A., Rohr, C. S., Dimond, D., Dewey, D., & Bray, S. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119367 · Cited by 14
Li, S., Bai, R., Yang, Y., Zhao, R., Upreti, B., Wang, X., Liu, S., Cheng, Y., & Xu, J. (2022) · Arthritis Research & Therapy · doi:10.1186/s13075-022-02954-z · Cited by 14
Wilson, S., Cromb, D., Bonthrone, A. F., Uus, A. U., Price, A. N., Egloff, A. M., van Poppel, M. P. M., Steinweg, J. K., Pushparajah, K., Simpson, J. M., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.124.035880 · Cited by 15
Phenotype Network and Brain Structural Covariance Network of Major Depression
Yun, J., & Kim, Y. (2021) · Advances in experimental medicine and biology · doi:10.1007/978-981-33-6044-0_1 · Cited by 12
Feng, Y.-X., Collignon, O., Maurer, D. M., Yao, K., & Gao, X. (2021) · Frontiers in Medicine · doi:10.3389/fmed.2021.752021 · Cited by 11
Sato, J. R., Biazoli, C. E., Salum, G. A., Gadelha, A., Crossley, N. A., Vieira, G., Zugman, A., Picon, F. A., Pan, P. M., Hoexter, M. Q., et al. (2018) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-018-1240-y · Cited by 12
Wong, W. I., & VanderLaan, D. P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.009 · Cited by 12
Song, J., Li, J., Chen, L., Lu, X., Zheng, S., Yang, Y., Cao, B., Weng, Y., Chen, Q., Ding, J., et al. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00378-4 · Cited by 11
Brain templates for Chinese babies from newborn to three months of age
Geng, X., Chan, P. H. Y., Lam, H. S., Chu, C. W., & Wong, P. C. M. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120536 · Cited by 10
Self-citationThe Not So Subtle and Status Quo Maintaining Nature of Everyday Sexism
Vescio, T. K., & Kosakowska‐Berezecka, N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.019 · Cited by 10
Li, J., Wang, Q., Li, K., Li, Y., & Guo, X. (2023) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.28984 · Cited by 9
Phenotype Network and Brain Structural Covariance Network of Anxiety
Yun, J., & Kim, Y. (2020) · Advances in experimental medicine and biology · doi:10.1007/978-981-32-9705-0_2 · Cited by 9
Neuroanthropological Perspectives on Culture, Mind, and Brain
Lende, D. H., & Downey, G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.014 · Cited by 10
The Impact of Gender and Culture in Consumer Behavior
Ng, S., Bharti, M., & Faust, N. T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.021 · Cited by 9
Developmental pattern of individual morphometric similarity network in the human fetal brain
Zhao, R., Sun, C., Xu, X., Zhao, Z., Li, M., Chen, R., Shen, Y., Pan, Y., Zhang, S., Wang, G., et al. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120410 · Cited by 8
Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout
Yang, Y., Cheng, Y., Wang, X., Upreti, B., Cui, R., Liu, S., Shan, B., Yu, H., Luo, C., & Xu, J. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.662497 · Cited by 7
Functional brain activity is highly associated with cortical myelination in neonates
Huang, Z., Gao, W., Wu, Z., Li, G., & Nie, J. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac321 · Cited by 9
Self-citationCultural Influences on Body Image and Body Esteem
Sotiriou, E. G., & Awad, G. H. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.018 · Cited by 8
Mutual Constitution of Culture and the Mind
Kitayama, S., & Yu, Q. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.006 · Cited by 9
Neural signatures of STEM learning and interest in youth
Candela-Leal, M. O., Alanis-Espinosa, M., Murrieta-González, J., Lozoya-Santos, J. D. J., & Ramírez-Moreno, M. A. (2025) · Acta Psychologica · doi:10.1016/j.actpsy.2025.104949 · Cited by 7
Kirmayer, L. J., Worthman, C. M., & Kitayama, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.028 · Cited by 8
Structural networking of the developing brain: from maturation to neurosurgical implications
BENEDICTIS, A. D., Rossi‐Espagnet, M. C., Palma, L. D., Sarubbo, S., & Marras, C. E. (2023) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2023.1242757 · Cited by 11
Neurodiversity as a Conceptual Lens and Topic of Cross-Cultural Study
Cascio, M. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.027 · Cited by 7
Mozafari, A. R., & Xu, X. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.029 · Cited by 7
Gondová, A., Neumane, S., Arichi, T., & Dubois, J. (2025) · Human Brain Mapping · doi:10.1002/hbm.70186 · Cited by 8
Kirmayer, L. J., Gómez-Carrillo, A., Langlois‐Thérien, T., Ramstead, M. J. D., & Gold, I. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.012 · Cited by 6
Cultural Priming Effects and the Human Brain
Han, S., & Northoff, G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.011 · Cited by 5
Kirmayer, L. J., Worthman, C. M., & Kitayama, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.002 · Cited by 6
Koss, M. P., Hansen, M., Anderson, E. J., Bach, M. H., & Bramsen, R. H. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.035 · Cited by 5
Ritual and Religion as Social Technologies of Cooperation
Kavanagh, C. M., Jong, J., & Whitehouse, H. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.016 · Cited by 7
The Cultural Brain as Historical Artifact
Boddice, R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.018 · Cited by 6
Multimodal MRI analysis of COVID-19 effects on pediatric brain
Peng, T., Zhang, C., Xie, P., Lin, Y., Zhang, L., Lan, Z., Yang, M., Huang, X., Liu, J., & Cheng, G. (2025) · Scientific Reports · doi:10.1038/s41598-025-96191-4 · Cited by 4
Systematic Review and Meta‐Analyses Reveal no Gender Difference in Neonatal Social Perception
Karson, L., Minhas, H., Dhesi, M., Davies, J., Patel, J. Y., & Eliot, L. (2025) · Social Development · doi:10.1111/sode.12790 · Cited by 5
No sex difference in maturation of brain morphology during the perinatal period
Sheng, Y., Wang, Y., Wang, X., Zhang, Z., Zhu, D., & Zheng, W. (2024) · Brain Structure and Function · doi:10.1007/s00429-024-02828-x · Cited by 4
Top ten discoveries of the year: Neurodevelopmental disorders
Dierssen, M. (2020) · Free Neuropathology · doi:10.17879/freeneuropathology-2020-2672 · Cited by 4
At the Crossroads of Women’s Experience
Pang, J. S., & Baumann, N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.015 · Cited by 4
The Reward of Musical Emotions and Expectations
Gold, B. P., & Zatorre, R. J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.021 · Cited by 4
Simulation-based inference of developmental EEG maturation with the spectral graph model
Bernardo, D., Xie, X., Verma, P., Kim, J., Liu, V., Numis, A. L., Wu, Y., Glass, H. C., Yap, P., Nagarajan, S. S., et al. (2024) · Communications Physics · doi:10.1038/s42005-024-01748-w · Cited by 4
Sex/Gender Differences in the Brain and their Relationship to Behavior
Eliot, L. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.007 · Cited by 4
Fertility, Childbirth, and Parenting
Macleod, C. I., & Morison, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.011 · Cited by 5
Wang, R., Liu, J., Li, J., Ma, X., Fu, C., Zhang, H., Luo, L., Ning, G., Liao, Y., Jia, F., et al. (2025) · Brain and Behavior · doi:10.1002/brb3.70905 · Cited by 3
Xia, J., Wang, F., Meng, Y., Wu, Z., Wang, L., Lin, W., Zhang, C., Shen, D. G., & Li, G. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.07.006 · Cited by 3
Self-citationLeung, S. A., & Cinamon, R. G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.024 · Cited by 4
Understanding Gender Inequality in Poverty and Social Exclusion through a Psychological Lens
Zhang, M. F., & Gordon, D. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.033 · Cited by 3
Worthman, C. M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108695374.007 · Cited by 3
The genetics of spatiotemporal variation in cortical thickness in youth
Schmitt, J. E., Alexander‐Bloch, A. F., Seidlitz, J., Raznahan, A., & Neale, M. C. (2024) · Communications Biology · doi:10.1038/s42003-024-06956-2 · Cited by 3
Evolutionary Roots of Women’s Aggression
Davis, A. C., Vaillancourt, T., & Archer, J. E. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108561716.022 · Cited by 4
Connectome and graph analysis of the developing brain
Cao, M., & Yong He, A. (2021) · Advances in magnetic resonance technology and applications · doi:10.1016/b978-0-12-816633-8.00021-1 · Cited by 3
Metadata
- Authors
- Geng, X., Li, G., Lu, Z., Gao, W., Wang, L., Shen, D., Zhu, H., & Gilmore, J. H.
- Affiliations
- University of Hong Kong (HK)
- University of North Carolina at Chapel Hill (US)
- Korea University (KR)
- Corresponding author
- Geng, Xiujuan
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-02-13
- Volume
- 27
- Issue
- 3
- Pages
- bhw022
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- PMC
- PMC6059236
- OpenAlex
- W2324745214
- Cited by
- 175
- References
- 68
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 12 · 2023: 9 · 2022: 10 · 2021: 15 · 2020: 84 · 2019: 10 · 2018: 13 · 2017: 5 · 2016: 1
- FWCI
- 6.15
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cerebral Cortex (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- UNC Libraries
- Funders
- NIH
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- structural covariance networks, early childhood brain development, cortical maturation, default mode network, dorsal attention network, sensorimotor network, functional connectivity, longitudinal neuroimaging
- MeSH terms
- Brain, Child Development, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Magnetic Resonance Imaging, Male, Neural Pathways, Organ Size, Sex Characteristics
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