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Spatial Patterns, Longitudinal Development, and Hemispheric Asymmetries of Cortical Thickness in Infants from Birth to 2 Years of Age
Open accessAbstract
Cortical thickness (CT) is related to normal development and neurodevelopmental disorders. It remains largely unclear how the characteristic patterns of CT evolve in the first 2 years. In this paper, we systematically characterized for the first time the detailed vertex-wise patterns of spatial distribution, longitudinal development, and hemispheric asymmetries of CT at 0, 1, and 2 years of age, via surface-based analysis of 219 longitudinal magnetic resonance images from 73 infants. Despite the dynamic increase of CT in the first year and the little change of CT in the second year, we found that the overall spatial distribution of thin and thick cortices was largely present at birth, and evolved only modestly during the first 2 years. Specifically, the precentral gyrus, postcentral gyrus, occipital cortex, and superior parietal region had thin cortices, whereas the prefrontal, lateral temporal, insula, and inferior parietal regions had thick cortices. We revealed that in the first year thin cortices exhibited low growth rates of CT, whereas thick cortices exhibited high growth rates. We also found that gyri were thicker than sulci, and that the anterior bank of the central sulcus was thicker than the posterior bank. Moreover, we showed rightward hemispheric asymmetries of CT in the lateral temporal and posterior insula regions at birth, which shrank gradually in the first 2 years, and also leftward asymmetries in the medial prefrontal, paracentral, and anterior cingulate cortices, which expanded substantially during this period. This study provides the first comprehensive picture of early patterns and evolution of CT during infancy.
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“Regional heterogeneity of cortical thickness observed in adults is well established at birth and persists through age 2 years into adulthood4,26.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [26]
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Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Cortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147
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
SMITH, S., & NICHOLS, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.061 · Cited by 5,250
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.668698 · Cited by 4,731
Microstructure of a spatial map in the entorhinal cortex
Hafting, T., Fyhn, M., Molden, S., Moser, M.-B., & Moser, E. I. (2005) · Nature · doi:10.1038/nature03721 · Cited by 4,068
Specification of Cerebral Cortical Areas
Rakic, P. (1988) · Science · doi:10.1126/science.3291116 · Cited by 3,127
(1909) · Cited by 2,575
Thinning of the Cerebral Cortex in Aging
Salat, D. H. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh032 · Cited by 1,851
Attention-deficit/hyperactivity disorder is characterized by a delay in cortical maturation
Shaw, P., Eckstrand, K., Sharp, W., Blumenthal, J., Lerch, J. P., Greenstein, D., Clasen, L., Evans, A., Giedd, J., & Rapoport, J. L. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0707741104 · Cited by 1,819
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Self-citationSydnor, V. J., Larsen, B., Bassett, D. S., Alexander‐Bloch, A. F., Fair, D. A., Liston, C. M., Mackey, A. P., Milham, M. P., Pines, A. R., Roalf, D. R., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.06.016 · Cited by 750
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Self-citationRemer, J., Croteau-Chonka, E., Dean, D. C., D’Arpino, S., Dirks, H., Whiley, D., & Deoni, S. C. L. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.010 · Cited by 152
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Hines, M., Spencer, D., Kung, K. T., Browne, W. V., Constantinescu, M., & Noorderhaven, R. M. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2016.02.008 · Cited by 74
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Hu, D., Zhang, H., Wu, Z., Wang, F., Wang, L., Smith, J. K., Lin, W., Li, G., & Shen, D. G. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.3013825 · Cited by 68
Self-citationConejero, Á., Guerra, S., Abundis‐Gutiérrez, A., & Rueda, M. R. (2018) · Developmental Science · doi:10.1111/desc.12494 · Cited by 62
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Qi, T., Schaadt, G., & Friederici, A. (2019) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2019.100704 · Cited by 7
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Frew, S., Samara, A., Shearer, H., Eilbott, J. A., & Vanderwal, T. (2022) · PLoS ONE · doi:10.1371/journal.pone.0265112 · Cited by 39
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Self-citationDuan, D., Xia, S., Rekik, I., Meng, Y., Wu, Z., Wang, L., Lin, W., Gilmore, J. H., Shen, D. G., & Li, G. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.041 · Cited by 40
Self-citationMulti-task prediction of infant cognitive scores from longitudinal incomplete neuroimaging data
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Self-citationMapping hemispheric asymmetries of the macaque cerebral cortex during early brain development
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Self-citationAnatomo-functional correlates of auditory development in infancy
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Self-citationvan der Plas, E. A. A., Noakes, L. S., Butcher, D. T., Weksberg, R., Galin-Corini, L., Wanstall, E. A., Te, P., Hopf, L., Guger, S., Spiegler, B. J., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102428 · Cited by 23
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Salminen, L. E., Wilcox, R. R., Zhu, A. H., Riedel, B. C., Ching, C. R. K., Rashid, F. M., Thomopoulos, S. I., Saremi, A., Harrison, M. B., Ragothaman, A., et al. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz060 · Cited by 16
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Fu, X., & Richards, J. E. (2021) · Neurophotonics · doi:10.1117/1.nph.8.3.035003 · Cited by 14
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Mihailov, A., Padula, M. C., Scariati, E., Schaer, M., Schneider, M., & D, S. E. M. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.01.031 · Cited by 10
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Metadata
- Authors
- Li, G., Lin, W., Gilmore, J. H., & Shen, D.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Korea University (KR)
- Venue
- Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2015-06-17
- Volume
- 35
- Issue
- 24
- Pages
- 9150-9162
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC4469740
- OpenAlex
- W1489066826
- Cited by
- 164
- References
- 78
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 11 · 2023: 18 · 2022: 12 · 2021: 22 · 2020: 44 · 2019: 11 · 2018: 17 · 2017: 12 · 2016: 7 · 2015: 2
- FWCI
- 12.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Neuroscience (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institute on Aging (R01AG041721, AG041721)
- National Institute of Mental Health (MH100217, MH088520, U01MH070890, RC1MH088520, MH064065, R01MH100217, MH070890, P50MH064065, R01MH070890)
- National Institute of Neurological Disorders and Stroke (NS055754, R01NS055754)
- National Institute of Biomedical Imaging and Bioengineering (EB006733, EB009634, R03EB008760, EB008374, R01EB008374, EB008760, R01EB009634, R01EB006733)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD053000, HD053000)
- 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
- cortical thickness, infant brain development, hemispheric lateralization, central sulcus, lateral temporal cortex, posterior insula, prefrontal cortex, anterior cingulate cortex, first two years of life
- MeSH terms
- Brain Mapping, Cerebral Cortex, Child Development, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Functional Laterality, Longitudinal Studies, Magnetic Resonance Imaging, Male
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