The DOI matches its Crossref record; 63 of the 65 references it cites were found in a registry or an index.
A Structural MRI Study of Human Brain Development from Birth to 2 Years
Open accessAbstract
Brain development in the first 2 years after birth is extremely dynamic and likely plays an important role in neurodevelopmental disorders, including autism and schizophrenia. Knowledge regarding this period is currently quite limited. We studied structural brain development in healthy subjects from birth to 2. Ninety-eight children received structural MRI scans on a Siemens head-only 3T scanner with magnetization prepared rapid gradient echo T1-weighted, and turbo spin echo, dual-echo (proton density and T2 weighted) sequences: 84 children at 2–4 weeks, 35 at 1 year and 26 at 2 years of age. Tissue segmentation was accomplished using a novel automated approach. Lateral ventricle, caudate, and hippocampal volumes were also determined. Total brain volume increased 101% in the first year, with a 15% increase in the second. The majority of hemispheric growth was accounted for by gray matter, which increased 149% in the first year; hemispheric white matter volume increased by only 11%. Cerebellum volume increased 240% in the first year. Lateral ventricle volume increased 280% in the first year, with a small decrease in the second. The caudate increased 19% and the hippocampus 13% from age 1 to age 2. There was robust growth of the human brain in the first two years of life, driven mainly by gray matter growth. In contrast, white matter growth was much slower. Cerebellum volume also increased substantially in the first year of life. These results suggest the structural underpinnings of cognitive and motor development in early childhood, as well as the potential pathogenesis of neurodevelopmental disorders.
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
“doubling in volume during the first year and reaching 80–90% of adult volume by age 3 (Courchesne et al., 2000; Knickmeyer et al., 2008).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Knickmeyer et al., 2008
In the citing paper
“Recently, however, imaging studies in early childhood have begun to illuminate the extremely rapid pace of postnatal structural and functional brain development3–6.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [3]
In the citing paper
“Brain volume is about 35% of adult volume 2–3 weeks after birth after birth13, doubles from term size in the first year of life and increases an additional 15% in the second to about 80% of adult size3.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [3]
In the citing paper
“From birth to age 1, cortical grey-matter volume increases 108–149%, whereas white matter increases by about 11%; from age 1 to age 2 years, grey matter increases 14–19%, whereas white matter increases by 19%3.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [3]
In the citing paper
“Lateral ventricle volume increases by over 100% in year 1, but subsequently decreases by 7–24% in the second year of life3, 10, 19.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [3]
In the citing paper
“Grey and white matter have different growth trajectories soon after birth, with rapid development of grey-matter volume compared to white-matter volume, which increases much more gradually15,3.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [3]
In the citing paper
“In general, studies suggest a complex pattern of development that varies based on anatomical location and cortical metric.”
From Quantifying cortical development in typically developing toddlers and young children, 1–6 years of age (2017) · cites this paper as Knickmeyer et al., 2008
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
Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.015 · Cited by 8,868
Self-citationBrain development during childhood and adolescence: a longitudinal MRI study
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., Zijdenbos, A., Paus, T., Evans, A. C., & Rapoport, J. L. (1999) · Nature Neuroscience · doi:10.1038/13158 · Cited by 5,552
The cerebellar cognitive affective syndrome
Schmahmann, J. (1998) · Brain · doi:10.1093/brain/121.4.561 · Cited by 3,230
Synaptic density in human frontal cortex —Developmental changes and effects of aging
Peter R., H. (1979) · Brain Research · doi:10.1016/0006-8993(79)90349-4 · Cited by 2,645
Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging
Lenroot, R. K., & Giedd, J. N. (2006) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2006.06.001 · Cited by 1,863
(1967) · Medical Entomology and Zoology · Cited by 1,713
Unusual brain growth patterns in early life in patients with autistic disorder: An MRI study
Courchesne, E., Karns, C. M., Davis, H. R., Ziccardi, R., Carper, R. A., Tigue, Z. D., Chisum, H. J., Moses, P., Pierce, K., Lord, C., et al. (2001) · Neurology · doi:10.1212/wnl.57.2.245 · Cited by 1,487
Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children
Sowell, E. R., Thompson, P. M., Leonard, C. M., Welcome, S. E., Kan, E., & Toga, A. W. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.1798-04.2004 · Cited by 1,481
Pfefferbaum, A., Mathalon, D. H., Sullivan, E. V., Rawles, J. M., Zipursky, R. B., & Lim, K. O. (1994) · Archives of Neurology · doi:10.1001/archneur.1994.00540210046012 · Cited by 1,363
Schizophrenia as a Disorder of Neurodevelopment
Lewis, D. A., & Levitt, P. (2002) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.25.112701.142754 · Cited by 1,163
Research works printed but not linked: 2
- 10.1080/02770930290056541 · DOI
- Sampaio RC Truwit CL (2001) in Handbook of developmental cognitive neuroscience, Myelination in the developing brain, eds Nelson CA Luciana M (MIT, Cambridge, MA), pp 35–44.
Cited by
Sorted by citations
Items 501–600 of 1,000
Early development of the functional brain network in newborns
Nazari, R., & Salehi, M. (2023) · Brain Structure and Function · doi:10.1007/s00429-023-02681-4 · Cited by 16
Early-Life Circumstances and Racial Disparities in Cognition Among Older Adults in the US
Lin, Z., Ye, J., Allore, H. G., Gill, T. M., & Chen, X. (2024) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2024.1132 · Cited by 15
Mongerson, C. R., Jennings, R. W., Zurakowski, D., & Bajic, D. (2019) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2019.09.005 · Cited by 15
Clinical and Preclinical Evidence for Adverse Neurodevelopment after Postnatal Zika Virus Infection
Raper, J., & Chahroudi, A. (2021) · Tropical Medicine and Infectious Disease · doi:10.3390/tropicalmed6010010 · Cited by 16
Buffet‐Bataillon, S., Bellanger, A., Boudry, G., Gangneux, J., Yverneau, M., Beuchée, A., Blat, S., & Huërou‐Luron, I. L. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.676622 · Cited by 17
Hoang, D.-H., Diep, G., Tran, M., & Le, N. (2022) · ACM Symposium on Applied Computing · doi:10.1145/3477314.3507112 · Cited by 15
The Theories of Cognitive Development
Ramesh, S. (2022) · Springer eBooks · doi:10.1007/978-3-031-12666-6_4 · Cited by 15
Che, D., Li, J., Fu, L., Pi, L., Rong, X., Wang, Y., Xu, Y., Huang, P., Chu, M., & Gu, X. (2018) · Infection and Drug Resistance · doi:10.2147/idr.s174140 · Cited by 15
The Perfect Storm: Mapping the Life Course Trajectories of Serial Killers
Reid, S., Katan, A., Ellithy, A., Stua, R. D., & Denisov, E. V. (2019) · International Journal of Offender Therapy and Comparative Criminology · doi:10.1177/0306624x19838683 · Cited by 18
Short, S. J., Willoughby, M. T., Camerota, M., Stephens, R. L., Steiner, R. J., Styner, M. A., & Gilmore, J. H. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01955-0 · Cited by 16
Self-citationCriticizing Montessori’s Method of Early Childhood Education using Islamic Psychology Perspective
Gumiandari, S., Nafi’a, I., & Jamaluddin, D. (2019) · Jurnal Pendidikan Islam · doi:10.15575/jpi.v5i2.5835 · Cited by 15
Miller, D. J., Lackey, E. P., Hackett, T. A., & Kaas, J. H. (2013) · The Journal of Comparative Neurology · doi:10.1002/cne.23379 · Cited by 15
Murphy, V. A., Shen, M. D., Kim, S. H., Cornea, E. A., Styner, M. A., & Gilmore, J. H. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.03.008 · Cited by 14
Self-citationErnährungsarmut bei Kindern – Ursachen, Folgen, COVID-19
Biesalski, H. K. (2021) · Aktuelle Ernährungsmedizin · doi:10.1055/a-1553-3202 · Cited by 15
Motion Robust MR Fingerprinting Scan to Image Neonates With Prenatal Opioid Exposure
Ma, D., Badve, C. A., Sun, J., Hu, S., Wang, X., Chen, Y., Nayate, A. P., Wien, M. A., Martin, D., Singer, L. T., et al. (2023) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.28907 · Cited by 14
A light in the darkness: Early phases of development and the emergence of cognition
Cainelli, E., Stramucci, G., & Bisiacchi, P. S. (2025) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2025.101527 · Cited by 16
Projection Regression Models for Multivariate Imaging Phenotype
Lin, J.-A., Hongtu Zhu, B., Knickmeyer, R. C., Styner, M. A., Gilmore, J. H., & Ibrahim, J. G. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21658 · Cited by 14
Self-citationDell’Acqua, F., Khan, W., Gottlieb, N., Giampietro, V., Ginestet, C. E., Bouls, D., Newhouse, S., Dobson, R., Banaschewski, T., Barker, G. J., et al. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-140519 · Cited by 14
The Brain Basis of Comorbidity in Neurodevelopmental Disorders
Licari, M. K., Finlay‐jones, A. L., Reynolds, J. E., Alvares, G. A., Spittle, A. J., Downs, J. A., Whitehouse, A., Leonard, H., Evans, K. L., & Varcin, K. J. (2019) · Current Developmental Disorders Reports · doi:10.1007/s40474-019-0156-7 · Cited by 19
Dijkshoorn, A. B. C., Turk, E., Hortensius, L. M., van der Aa, N. E., Hoebeek, F. E., Groenendaal, F., Benders, M. J. N. L., & Dudink, J. (2020) · Scientific Reports · doi:10.1038/s41598-020-62078-9 · Cited by 14
García‐Alba, J., Rubio-Valdehita, S., Sánchez, M. J., García, A. I. M., Esteba‐Castillo, S., & Gómez-Caminero, M. (2020) · International Journal of Developmental Disabilities · doi:10.1080/20473869.2020.1764242 · Cited by 15
Primary repair of esophageal atresia is followed by multiple diagnostic and surgical procedures.
van Hoorn, C. E., de Graaff, J. C., Vlot, J., Wijnen, R. M. H., Stolker, R. J., & Schnater, J. M. (2021) · Journal of Pediatric Surgery · doi:10.1016/j.jpedsurg.2021.06.004 · Cited by 14
A new framework for analyzing white matter maturation in early brain development
Prastawa, M. W., Sadeghi, N., Gilmore, J. H., Lin, W., & Gerig, G. (2010) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2010.5490404 · Cited by 14
Self-citationMatas, E., Bock, J., & Braun, K. (2016) · Psychopathology · doi:10.1159/000448055 · Cited by 14
“What” and “where” was when? Memory for the temporal order of episodic events in children
Scarf, D., Boden, H., Labuschagne, L. G., Gross, J., & Hayne, H. (2017) · Developmental Psychobiology · doi:10.1002/dev.21553 · Cited by 14
Hoare, J., Heany, S. J., Fouché, J., Phillips, N. J., Joska, J. A., Myer, L., Zar, H. J., & Stein, D. J. (2019) · Journal of NeuroVirology · doi:10.1007/s13365-018-0712-7 · Cited by 14
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-citationA voxel-wise assessment of growth differences in infants developing autism spectrum disorder
de la Parra, A. C., Lewis, J. D., Fonov, V., Botteron, K. N., McKinstry, R. C., Gerig, G., Pruett, J. R., Dager, S. R., Elison, J. T., Styner, M. A., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102551 · Cited by 14
Self-citationBrain size growth in Australopithecus
Cofran, Z. (2019) · Journal of Human Evolution · doi:10.1016/j.jhevol.2019.02.006 · Cited by 17
Infant Emotion Development and Temperament
Aktar, E., & Pérez‐Edgar, K. E. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108351959.026 · Cited by 17
Longitudinal development of the cerebellum in human infants during the first 800 days
Wang, Y., Chen, L., Wu, Z., Li, T., Sun, Y., Cheng, J., Hongtu Zhu, B., Lin, W., Wang, L., Huang, W., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112281 · Cited by 13
Self-citationGriffiths-King, D., WOOD, A. G., & Novák, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-42414-5 · Cited by 13
The infant gut microbiome and cognitive development in malnutrition
Shennon, I., Wilson, B. C., Behling, A. H., Portlock, T., Haque, R., Forrester, T., Nelson, C. A., & O'Sullivan, J. M. (2024) · Clinical Nutrition · doi:10.1016/j.clnu.2024.03.029 · Cited by 14
Zhou, X., Azimi, M., Handin, N., Riselli, A. M., Vora, B., Chun, E., Dang, Z., Huang, E. J., Yee, S. W., Artursson, P., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-31224-6 · Cited by 13
Human Brain Evolution: Ontogeny and Phylogeny
Neubauer, S. (2014) · Springer series in bio-/neuroinformatics · doi:10.1007/978-3-319-08500-5_5 · Cited by 13
Fiber-driven resolution enhancement of diffusion-weighted images
Yap, P., An, H., Chen, Y., & Shen, D. G. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.016 · Cited by 13
Qiu, W., Chen, Y., Kishimoto, J., de Ribaupierre, S., Chiu, B. C. Y., Fenster, A., Menon, B. K., & Yuan, J. Y. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2643635 · Cited by 13
Hou, B., Kang, G., Zhang, N., & Liu, K. (2019) · Cognitive Computation · doi:10.1007/s12559-019-09645-z · Cited by 13
Longitudinal brain atlases of early developing cynomolgus macaques from birth to 48 months of age
Zhong, T., Wei, J., Wu, K., Chen, L., Zhao, F., Pei, Y., Wang, Y., Zhang, H., Wu, Z., Huang, Y., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118799 · Cited by 13
Hofstee, M., van der Velde, B., Huijding, J., Endendijk, J. J., Kemner, C., & Deković, M. (2022) · Infant Behavior and Development · doi:10.1016/j.infbeh.2022.101769 · Cited by 14
Neurodevelopment among children exposed to HIV and uninfected in sub‐Saharan Africa
Bulterys, M. A., Njuguna, I. N., Mahy, M. I., Gulaid, L., Powis, K. M., Wedderburn, C. J., & John-Stewart, G. C. (2023) · Journal of the International AIDS Society · doi:10.1002/jia2.26159 · Cited by 13
Chalifour, B., Holzhausen, E. A., Lim, J. J., Yeo, E. N., Shen, N., Jones, D. P., Peterson, B. S., Goran, M. I., Liang, D., & Alderete, T. L. (2023) · npj Metabolic Health and Disease · doi:10.1038/s44324-023-00001-2 · Cited by 13
Benavente‐Fernández, I., Rodríguez-Zafra, E., León-Martínez, J., Jiménez‐Gómez, G., Ruiz‐González, E., Fernández-Colina, R. C., Lechuga-Sancho, A. M., & Lubián‐López, S. P. (2018) · Radiology · doi:10.1148/radiol.2018171956 · Cited by 13
Kim, H., Kim, Y.-T., Song, E.-S., Yoon, B. C., Choi, Y. H., Kim, K., & Kim, D. (2018) · Journal of neurosurgery · doi:10.3171/2018.5.jns172711 · Cited by 13
Torres, E. R., Tumey, T. A., Dean, D., Kassahun‐Yimer, W., Lopez-Lambert, E., & Hitchcock, M. (2020) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2020.103551 · Cited by 13
White matter development in infants at risk for schizophrenia
Ahn, S. J., Cornea, E. A., Murphy, V. A., Styner, M. A., Jarskog, L. F., & Gilmore, J. H. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.05.039 · Cited by 13
Self-citationSecondhand smoke’s effects on brain development: ADHD and associated behaviors in children
El‐Beeh, M. E. (2023) · Journal of Umm Al-Qura University for Applied Sciences · doi:10.1007/s43994-023-00065-2 · Cited by 12
Mao, W., Chen, Y., He, Z., Wang, Z., Xiao, Z., Sun, Y., He, L., Zhou, J., Guo, W., Ma, C., et al. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3355020 · Cited by 12
Development and Maturation of the Human Brain, from Infancy to Adolescence
Paus, T. (2024) · Current topics in behavioral neurosciences · doi:10.1007/7854_2024_514 · Cited by 13
Machine-learning based prediction of future outcome using multimodal MRI during early childhood
Ouyang, M., Whitehead, M. T., Mohapatra, S., Zhu, T., & Huang, H. (2024) · Seminars in Fetal and Neonatal Medicine · doi:10.1016/j.siny.2024.101561 · Cited by 12
Measuring and interpreting individual differences in fetal, infant, and toddler neurodevelopment
Olson, H. A., Camacho, M. C., Abdurokhmonova, G., Ahmad, S., Chen, E. M., Chung, H., Lorenzo, R. D., Dineen, Á. T., Ganz, M., Licandro, R., et al. (2025) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2025.101539 · Cited by 14
Using Modern Attachment Theory to Guide Clinical Assessments of Early Attachment Relationships
Schore, A. N., & Newton, R. P. (2012) · Springer eBooks · doi:10.1007/978-1-4614-4848-8_4 · Cited by 12
SPReM: Sparse Projection Regression Model For High-Dimensional Linear Regression
Sun, Q., Hongtu Zhu, B., Liu, Y., & Ibrahim, J. G. (2015) · Journal of the American Statistical Association · doi:10.1080/01621459.2014.892008 · Cited by 12
Cauley, K. A., Hu, Y., Och, J., Yorks, P. J., & Fielden, S. W. (2018) · American Journal of Neuroradiology · doi:10.3174/ajnr.a5559 · Cited by 12
Emergence of Groupwise Registration in MR Brain Study
Guorong Wu, A., Jia, H., Wang, Q., Shi, F., Yap, P., & Shen, D. G. (2012) · CRC Press eBooks · doi:10.1201/b12941-5 · Cited by 12
Blum, S., Mack, J. T., Weise, V., Kopp, M., Asselmann, E., Martini, J., & Garthus‐Niegel, S. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.886347 · Cited by 12
Effect of Dietary Complex Lipids on the Biosynthesis of Piglet Brain Gangliosides
dos Reis, M. M., Bermingham, E. N., Reis, M. G., Deb‐Choudhury, S., MacGibbon, A. K. H., Fong, B., McJarrow, P., Bibiloni, R., Bassett, S. A., & Roy, N. C. (2016) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.5b05211 · Cited by 12
Novel insights from quantitative imaging of the developing cerebellum
Allin, M. P. G. (2016) · Seminars in Fetal and Neonatal Medicine · doi:10.1016/j.siny.2016.06.003 · Cited by 12
Cirillo, C., & Francis, K. (2016) · Advances in Neonatal Care · doi:10.1097/anc.0000000000000330 · Cited by 12
Cockayne syndrome: a diffusion tensor imaging and volumetric study
Koob, M., Rousseau, F., Laugel, V., Meyer, N., Armspach, J., Girard, N. J., & Dietemann, J. (2016) · British Journal of Radiology · doi:10.1259/bjr.20151033 · Cited by 12
Neocortical Development in Brain of Young Children—A Stereological Study
Kjær, M., Fabricius, K., Sigaard, R. K., & Pakkenberg, B. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw314 · Cited by 12
Hanford, L. C., Schmithorst, V. J., Panigrahy, A., Lee, V., Ridley, J., Bonar, L. K., Versace, A., Hipwell, A. E., & Phillips, M. L. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01968 · Cited by 13
Age-specific optimization of T1-weighted brain MRI throughout infancy
Zhang, H., Lai, C., Liu, R., Liu, T., Niu, W., Oishi, K., Zhang, Y., & Wu, D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.075 · Cited by 12
Household food insecurity and preschool suspension/expulsion in the United States
Jackson, D. B., & Testa, A. M. (2020) · Preventive Medicine · doi:10.1016/j.ypmed.2020.106283 · Cited by 12
Variation of the slope of the tentorium during childhood
Rehder, R., Yang, E., & Cohen, A. R. (2015) · Child s Nervous System · doi:10.1007/s00381-015-2899-8 · Cited by 12
Wade, M., Madigan, S. L., Akbari, E. M., & Jenkins, J. M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00354 · Cited by 18
Schore, A. N. (2015) · Children Australia · doi:10.1017/cha.2015.13 · Cited by 12
Blodgett, J. M., Kuh, D. J., Hardy, R., Davis, D. H. J., & Cooper, R. (2018) · The Journals of Gerontology Series A · doi:10.1093/gerona/gly275 · Cited by 12
Baby Open Brains: An open-source dataset of infant brain segmentations
Feczko, E., Stoyell, S. M., Moore, L. A., Alexopoulos, D., Bagonis, M., Barrett, K., Bower, B., Cavender, A. C., Chamberlain, T. A., Conan, G., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-05404-y · Cited by 13
Bompard, L., Xu, S., Styner, M., Paniagua, B., Ahn, M., Yuan, Y., Jewells, V., Gao, W., Shen, D., Zhu, H., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0108306 · Cited by 11
“[1] showed a similar pattern of growth but with a different growth rate; the LV size increased by 280% in year 1 and 28% in year 2.”
BackgroundSelf-citationNiu, Y., Camacho, M. C., Schilling, K. G., & Humphreys, K. L. (2025) · Brain Structure and Function · doi:10.1007/s00429-025-03007-2 · Cited by 11
Two axes of white matter development
Luo, A. C., Meisler, S. L., Sydnor, V. J., Alexander‐Bloch, A. F., Bagautdinova, J., Barch, D. M., Bassett, D. S., Davatzikos, C. A., Franco, A. R., Goldsmith, J., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-68714-8 · Cited by 11
Eichner, C., Berger, P., Klein, C. C., & Friederici, A. D. (2024) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2024.102602 · Cited by 11
Lyons‐Ruth, K., Chasson, M., Khoury, J. E., & Ahtam, B. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105746 · Cited by 11
The importance of sleep for the developing brain
Riggins, T., Ratliff, E. L., Horger, M. N., & Spencer, R. M. C. (2024) · Current Sleep Medicine Reports · doi:10.1007/s40675-024-00307-7 · Cited by 12
Ottino‐González, J., Rivas‐Fernández, M. Á., Esaian, S., Rajagopalan, V., Bouhrara, M., Goran, M. I., & Adise, S. (2025) · Pediatric Research · doi:10.1038/s41390-025-04086-x · Cited by 11
Advanced nanotherapies to promote neuroregeneration in the injured newborn brain
Arteaga, O., Mikrogeorgiou, A., Kannan, S., & Ferriero, D. M. (2019) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2019.10.005 · Cited by 10
Evidence for Attentional Phenotypes in Infancy and Their Role in Visual Cognitive Performance
Ross‐Sheehy, S., Reynolds, E., & Eschman, B. (2020) · Brain Sciences · doi:10.3390/brainsci10090605 · Cited by 11
Cross-Cultural Perspectives on Parent–Infant Interactions
Bornstein, M. H., & Esposito, G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108351959.029 · Cited by 12
Darki, F., Nyström, P., McAlonan, G. M., Bölte, S., & Falck‐Ytter, T. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab069 · Cited by 11
Li, J., & Menon, N. (2020) · The Journal of Development Studies · doi:10.1080/00220388.2021.1969009 · Cited by 11
Integrated structural and functional atlases of Asian children from infancy to childhood
Zhu, J., Zhang, H., Chong, Y. S., Shek, L. P., Gluckman, P. D., Meaney, M. J., Fortier, M. V., & Qiu, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118716 · Cited by 11
(Un)common space in infant neuroimaging studies: A systematic review of infant templates
Dufford, A. J., Hahn, C. A., Peterson, H., Gini, S., Mehta, S., Alfano, A., & Scheinost, D. (2022) · Human Brain Mapping · doi:10.1002/hbm.25816 · Cited by 11
Gaillard, L., Tjaberinga, M. C., Dremmen, M. H. G., Mathijssen, I. M. J., & Vrooman, H. A. (2024) · Journal of Anatomy · doi:10.1111/joa.14028 · Cited by 11
A Bayesian approach to the creation of a study-customized neonatal brain atlas
Zhang, Y., Chang, L., Ceritoglu, C., Skranes, J. S., Ernst, T., Mori, S., Miller, M. I., & Oishi, K. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.001 · Cited by 11
Minor Fetal Sonographic Findings in Autism Spectrum Disorder
Gamliel, M., Ebstein, R. P., Yirmiya, N., & Mankuta, D. (2012) · Obstetrical & Gynecological Survey · doi:10.1097/ogx.0b013e31824bb5d6 · Cited by 11
zhong, J., Chen, D. Q., Walker, M., Waspe, A. C., Looi, T., Piorkowska, K., Drake, J. M., & Hodaie, M. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00092 · Cited by 11
Kim, J. C., Wang, L., Shen, D. G., & Lin, W. (2016) · Scientific Reports · doi:10.1038/srep37666 · Cited by 11
Self-citationBoos, V., Tietze, A., Berger, F. F., & Bührer, C. (2019) · Pediatric Critical Care Medicine · doi:10.1097/pcc.0000000000001878 · Cited by 11
Individual variation in longitudinal postnatal development of the primate brain
Ball, G., & Seal, M. (2018) · Brain Structure and Function · doi:10.1007/s00429-019-01829-5 · Cited by 12
Cruz, G. B., Vasquez, M. A., Cabañas, E., Joseph, J. N., Skeen, J. C., Lynch, K. P., Ahmed, I., Khairi, E. B., Bonitto, J. R., Clarke, E. G., et al. (2022) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-93337-1_43 · Cited by 11
Increased cerebellar volume in the early stage of fucosidosis: a case control study
Kau, T., Karlo, C. A., Güngör, T., Prietsch, V., Kellenberger, C. J., Scheer, I., & Boltshauser, E. (2011) · Neuroradiology · doi:10.1007/s00234-011-0855-1 · Cited by 11
Dong, P., Guo, Y., Shen, D. G., & Guorong Wu, A. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-28194-0_23 · Cited by 11
Wu, Y., Guorong Wu, A., Wang, L., Munsell, B. C., Wang, Q., Lin, W., Feng, Q., Chen, W., & Shen, D. G. (2015) · Medical Physics · doi:10.1118/1.4922393 · Cited by 11
Self-citationSong, L., Peng, Y., Ouyang, M., Peng, Q., Feng, L., Sotardi, S. T., Yu, Q., Kang, H., Sindabizera, K., Liu, S., et al. (2024) · Human Brain Mapping · doi:10.1002/hbm.26695 · Cited by 10
Comparative analysis of brain age prediction using structural and diffusion MRIs in neonates
Fang, Z., Pan, N., Liu, S., Li, H., Pan, M., Zhang, J., Li, Z., Liu, M., & Ge, X. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120815 · Cited by 10
Chauvet, L., Charton, E., Lemaire, M., Huërou‐Luron, I. L., & Deglaire, A. (2025) · Frontiers in Nutrition · doi:10.3389/fnut.2025.1635919 · Cited by 10
Fractal analysis of brain shape formation predicts age and genetic similarity in human newborns
Krohn, S., Romanello, A., von Schwanenflug, N., Rasmussen, J. M., Buß, C., Valk, S. L., Madan, C. R., & Finke, C. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02107-w · Cited by 10
Nisari, M., Ertekın, T., Özçelik, Ö., Çınar, Ş., Doğanay, S., & Acer, N. (2012) · Surgical and Radiologic Anatomy · doi:10.1007/s00276-012-0971-6 · Cited by 10
Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation
Sun, Y., Gao, K., Niu, S., Lin, W., Li, G., Wang, L., & The UNC/UMN Baby Connectome Project Consortium (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59861-7_67 · Cited by 10
Self-citation
Metadata
- Authors
- Knickmeyer, R. C., Gouttard, S., Kang, C., Evans, D., Wilber, K., Smith, J. K., Hamer, R. M., Lin, W., Gerig, G., & Gilmore, J. H.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- University of Utah (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2008-11-19
- Volume
- 28
- Issue
- 47
- Pages
- 12176-12182
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC2884385
- OpenAlex
- W2018077021
- Cited by
- 1,151
- References
- 65
- Citations by year
- 2026: 67 · 2025: 82 · 2024: 85 · 2023: 79 · 2022: 71 · 2021: 99 · 2020: 112 · 2019: 80 · 2018: 75 · 2017: 58 · 2016: 55 · 2015: 61 · 2014: 57 · 2013: 44 · 2012: 46
- FWCI
- 23.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institutes of Health (UL1TR000454)
- National Institute of Mental Health (HD053000, MH064065, T32MH019111, P50MH064065, MH019111)
- National Center for Research Resources (UL1RR025008)
- National Center for Advancing Translational Sciences
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD053000, #HD03110, HD053000, P30HD003110, HD-40127, T32HD040127)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Fetal and Pediatric Neurological Disorders
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- brain development, early childhood, cerebellum, lateral ventricle, caudate nucleus, hippocampus, total brain volume, neurodevelopmental disorders, autism spectrum disorder, schizophrenia
- MeSH terms
- Age Factors, Brain, Brain Mapping, Child, Preschool, Female, Humans, Image Processing, Computer-Assisted, Infant, Infant, Newborn, Magnetic Resonance Imaging, Male, Pregnancy
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