The DOI matches its Crossref record; 85 of the 86 references it cites were found in a registry or an index.
Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping
Open accessAbstract
The elaboration of the myelinated white matter is essential for normal neurodevelopment, establishing and mediating rapid communication pathways throughout the brain. These pathways facilitate the synchronized communication required for higher order behavioral and cognitive functioning. Altered neural messaging (or 'disconnectivity') arising from abnormal white matter and myelin development may underlie a number of neurodevelopmental psychiatric disorders. Despite the vital role myelin plays, few imaging studies have specifically examined its maturation throughout early infancy and childhood. Thus, direct investigations of the relationship(s) between evolving behavioral and cognitive functions and the myelination of the supporting neural systems have been sparse. Further, without knowledge of the 'normative' developmental time-course, identification of early abnormalities associated with developmental disorders remains challenging. In this work, we examined the use of longitudinal (T(1)) and transverse (T(2)) relaxation time mapping, and myelin water fraction (MWF) imaging to investigate white matter and myelin development in 153 healthy male and female children, 3 months through 60 months in age. Optimized age-specific acquisition protocols were developed using the DESPOT and mcDESPOT imaging techniques; and mean T(1), T(2) and MWF trajectories were determined for frontal, temporal, occipital, parietal and cerebellar white matter, and genu, body and splenium of the corpus callosum. MWF results provided a spatio-temporal pattern in-line with prior histological studies of myelination. Comparison of T(1), T(2) and MWF measurements demonstrates dissimilar sensitivity to tissue changes associated with neurodevelopment, with each providing differential but complementary information.
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
“Males also show increased global gyrification at 2 years of age compared with females (adjusting for total brain volume)”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [127]
In the citing paper
“local or regional gyrification index is similar between males and females at each age127.”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [127]
In the citing paper
“but not at 0 or 1 year of age”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [127]
In the citing paper
“this strategy of template creation mirrors our prior work that has been shown to successfully create structural and quantitative MRI templates of the pediatric brain (Deoni et al., 2012, Dean et al., 2014).”
From Quantifying cortical development in typically developing toddlers and young children, 1–6 years of age (2017) · cites this paper as Deoni et al., 2012
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
Avants, B., Epstein, C. L., Grossman, M., & Gee, J. C. (2007) · Medical Image Analysis · doi:10.1016/j.media.2007.06.004 · Cited by 5,876
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,628
The Human Connectome Project: A data acquisition perspective
Essen, D. C. V., Uǧurbil, K., Auerbach, E. J., Barch, D. M., Behrens, T. E. J., Bucholz, R. D., Chang, A., Chen, L., Corbetta, M., Curtiss, S. W., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.018 · Cited by 2,638
Mullen Scales of Early Learning
Bradley‐Johnson, S. (1997) · Psychology in the Schools · doi:10.1002/(sici)1520-6807(199710)34:4 · Cited by 2,329
Unbiased average age-appropriate atlases for pediatric studies
Fonov, V., Evans, A. C., Botteron, K., Almli, C. R., McKinstry, R. C., & Collins, D. L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.033 · Cited by 2,290
Regional Development of the Brain in Early Life
(1968) · Archives of Disease in Childhood · doi:10.1136/adc.43.229.388 · Cited by 2,107
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
Behavioral manifestations of autism in the first year of life
Zwaigenbaum, L., Bryson, S., Rogers, T., Roberts, W., Brian, J., & Szatmari, P. (2005) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2004.05.001 · Cited by 1,602
Intellectual ability and cortical development in children and adolescents
Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Evans, A., Rapoport, J., & Giedd, J. (2006) · Nature · doi:10.1038/nature04513 · Cited by 1,543
Flagged first, then by citations
1 of the 86 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 101–200 of 389
McCray, G., McCoy, D. C., Kariger, P. K., Janus, M., Black, M. M., Chang, S. M., Tofail, F., Eekhout, I. E., Waldman, M. R., van Buuren, S., et al. (2023) · BMJ Global Health · doi:10.1136/bmjgh-2022-009827 · Cited by 54
The Infant Orienting With Attention Task: Assessing the Neural Basis of Spatial Attention in Infancy
Ross‐Sheehy, S., Schneegans, S., & Spencer, J. P. (2015) · Infancy · doi:10.1111/infa.12087 · Cited by 54
Gabard-Durnam, L. J., O’Muircheartaigh, J., Dirks, H., Dean, D., Tottenham, N., & Deoni, S. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.06.004 · Cited by 54
Self-citationInflammation, Cognition, and White Matter in Older Adults: An Examination by Race
Boots, E. A., Castellanos, K. J., Zhan, L., Barnes, L. L., Tussing-Humphreys, L. M., Deoni, S., & Lamar, M. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.553998 · Cited by 50
Self-citationIncorporation of nonzero echo times in the SPGR and bSSFP signal models used in mcDESPOT
Bouhrara, M., & Spencer, R. G. S. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25984 · Cited by 50
Chen, Z., Zhang, H. G., Yushkevich, P. A., Liu, M., & Beaulieu, C. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00009 · Cited by 52
Development of Structural and Functional Connectivity
Dubois, J., Kostović, I., & Judas, M. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00360-2 · Cited by 55
Mechanisms of T2* anisotropy and gradient echo myelin water imaging
Lee, J., Nam, Y., Choi, J. Y., Kim, E. Y., Oh, S., & Kim, D. (2016) · NMR in Biomedicine · doi:10.1002/nbm.3513 · Cited by 49
Howell, B., McMurray, M. S., Guzman, D., Nair, G., Shi, Y., McCormack, K. M., Hu, X. P., Styner, M. A., & Sánchez, M. M. (2016) · Social Neuroscience · doi:10.1080/17470919.2016.1200481 · Cited by 48
Quantification of myelin in children using multiparametric quantitative MRI: a pilot study
Kim, H. G., Moon, W., Han, J., & Choi, J. (2017) · Neuroradiology · doi:10.1007/s00234-017-1889-9 · Cited by 36
Deoni, S., O’Muircheartaigh, J., Ljungberg, E., Huentelman, M., & Williams, S. (2022) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29273 · Cited by 47
Self-citationFranchini, M., Armstrong, V. L., Schaer, M., & Smith, I. M. (2018) · Child Neuropsychology · doi:10.1080/09297049.2018.1490706 · Cited by 52
Cerebral blood flow increases across early childhood
Paniukov, D., Lebel, R. M., Giesbrecht, G. F., & Lebel, C. A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116224 · Cited by 52
An open resource for transdiagnostic research in pediatric mental health and learning disordersPreprint
Alexander, L. M., Escalera, J., Ai, L., Andreotti, C., Febre, K., Mangone, A., Potler, N. V., Langer, N., Alexander, A., Kovacs, M., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/149369 · Cited by 55
Jensen, S. K. G., Pangelinan, M., Björnholm, L., Klasnja, A., Leemans, A., Drakesmith, M., Evans, C. J., Barker, E. D., & Paus, T. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.10.033 · Cited by 44
Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies
Korom, M., Camacho, M. C., Filippi, C. A., Licandro, R., Moore, L. A., Dufford, A. J., Zöllei, L., Graham, A. M., Spann, M. N., Howell, B., et al. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.101055 · Cited by 49
Cesarean Delivery Impacts Infant Brain Development
Deoni, S., Adams, S. H., Li, X., Badger, T. M., Pivik, R. T., Glasier, C. M., Ramakrishnaiah, R. H., Rowell, A. C., & Ou, X. (2018) · American Journal of Neuroradiology · doi:10.3174/ajnr.a5887 · Cited by 47
Self-citationDai, X., Hadjipantelis, P. Z., Wang, J., Deoni, S., & Müller, H. (2019) · Human Brain Mapping · doi:10.1002/hbm.24690 · Cited by 41
Self-citationMercer, J., Erickson‐Owens, D. A., Deoni, S., Dean, D., Tucker, R. J., Parker, A. B., Joelson, S., Mercer, E. N., Collins, J. A., & Padbury, J. F. (2020) · American Journal of Perinatology · doi:10.1055/s-0040-1714258 · Cited by 43
Self-citationSHANK3 deficiency leads to myelin defects in the central and peripheral nervous system
Malara, M., Lutz, A.-K., Incearap, B., Bauer, H. F., Cursano, S., Volbracht, K., Lerner, J. J., Pandey, R., Delling, J. P., Ioannidis, V., et al. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04400-4 · Cited by 49
Eminian, S., Hajdu, S. D., Meuli, R. A., Maeder, P. P., & Hagmann, P. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198250 · Cited by 43
Longitudinal Study of White Matter Development and Outcomes in Children Born Very Preterm
Young, J. M., Morgan, B. R., Whyte, H. E. A., Lee, W., Smith, M. L., Raybaud, C., Shroff, M. M., Sled, J. G., & Taylor, M. J. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw221 · Cited by 41
Dubois, J., Adibpour, P., Poupon, C., Hertz-Pannier, L., & Dehaene-Lambertz, G. (2016) · Brain Plasticity · doi:10.3233/bpl-160031 · Cited by 40
Faulkner, M. E., Gong, Z., Guo, A., Laporte, J. P., Bae, J., & Bouhrara, M. (2024) · Journal of Neurochemistry · doi:10.1111/jnc.16170 · Cited by 39
Bouhrara, M., Kim, R. W., Khattar, N., Qian, W., Bergeron, C. M., Melvin, D. L., Zukley, L. M., Ferrucci, L., Resnick, S. M., & Spencer, R. G. S. (2021) · Human Brain Mapping · doi:10.1002/hbm.25372 · Cited by 36
Magnetic resonance fingerprinting: an overview
Tippareddy, C., Zhao, W., Sunshine, J. L., Griswold, M. A., Ma, D., & Badve, C. A. (2021) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-021-05384-2 · Cited by 38
Morin, E. L., Howell, B. R., Feczko, E., Earl, E., Pincus, M., Reding, K., Kovacs-Balint, Z. A., Meyer, J. S., Styner, M., Fair, D., et al. (2020) · Development and Psychopathology · doi:10.1017/s0954579420001133 · Cited by 37
Posterior–Anterior Brain Maturation Reflected in Perceptual, Motor and Cognitive Performance
Gerván, P., Soltész, P., Rosta‐Filep, O., Berencsi, A., & Kovács, I. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00674 · Cited by 37
Low-frequency variation in TP53 has large effects on head circumference and intracranial volume
Haworth, S. J., Shapland, C. Y., Hayward, C., Prins, B. P., Felix, J. F., Medina‐Gómez, C., Rivadeneira, F., Wang, C. A., Ahluwalia, T. S., Vrijheid, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-018-07863-x · Cited by 35
Insights into the Brain: Neuroimaging of Brain Development and Maturation
Lyall, A. E., Savadjiev, P., Shenton, M. E., & Kubicki, M. R. (2016) · Journal of Neuroimaging in Psychiatry and Neurology · doi:10.17756/jnpn.2016-003 · Cited by 37
Human white matter myelinates faster in utero than ex utero
Grotheer, M., Bloom, D., Kruper, J., Richie-Halford, A., Zika, S., González, V. A. A., Yeatman, J. D., Kalanit Grill-spector, A., & Rokem, A. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2303491120 · Cited by 37
Using Deep Convolutional Neural Networks for Neonatal Brain Image Segmentation
Ding, Y., Acosta, R., Enguix, V., Suffren, S., Ortmann, J., Luck, D., Dolz, J., & Lodygensky, G. A. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00207 · Cited by 34
White matter alterations in young children with prenatal alcohol exposure
Kar, P., Reynolds, J. E., Grohs, M. N., Gibbard, W. B., McMorris, C. A., Tortorelli, C., & Lebel, C. A. (2021) · Developmental Neurobiology · doi:10.1002/dneu.22821 · Cited by 34
Fetal and neonatal neuroimaging
Counsell, S. J., Arichi, T., Arulkumaran, S., & Rutherford, M. (2019) · Handbook of clinical neurology · doi:10.1016/b978-0-444-64029-1.00004-7 · Cited by 33
Rubinski, A., Franzmeier, N., Dewenter, A., Luan, Y., Smith, R. A., Strandberg, O. T., Ossenkoppele, R., Dichgans, M., Hansson, O., Ewers, M., et al. (2022) · Alzheimer s Research & Therapy · doi:10.1186/s13195-022-01074-9 · Cited by 41
Remer, J., Dean, D. C., Chen, K., Reiman, R. A., Huentelman, M. J., Reiman, E. M., & Deoni, S. C. L. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117243 · Cited by 33
Self-citationLanguage Exposure and Brain Myelination in Early Development
Fibla, L., Forbes, S. H., McCarthy, J., Mee, K., Magnotta, V. A., Deoni, S., Cameron, D., & Spencer, J. P. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.1034-22.2023 · Cited by 33
Self-citationA simple sleep EEG marker in childhood predicts brain myelin 3.5 years later
LeBourgeois, M. K., Dean, D., Deoni, S., Kohler, M., & Kurth, S. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.072 · Cited by 34
Self-citationBlock, R. I., Magnotta, V. A., Bayman, E. O., Choi, J. Y. J., Thomas, J., & Kimble, K. K. (2017) · Anesthesiology · doi:10.1097/aln.0000000000001808 · Cited by 33
Cognitive Training in Young Patients With Traumatic Brain Injury: A Fixel-Based Analysis
Verhelst, H., Giraldo, D. L., Linden, C. V., Vingerhoets, G., Jeurissen, B., & Caeyenberghs, K. (2019) · Neurorehabilitation and neural repair · doi:10.1177/1545968319868720 · Cited by 32
Schneider, N., Greenstreet, E., & Deoni, S. (2021) · Child Development · doi:10.1111/cdev.13649 · Cited by 31
Self-citationThe Development of Appetite: Tracking and Age-Related Differences in Appetitive Traits in Childhood
Jansen, E., Thapaliya, G., Beauchemin, J., D’Sa, V. A., Deoni, S., & Carnell, S. (2023) · Nutrients · doi:10.3390/nu15061377 · Cited by 32
Self-citationIndividual differences in human brain development
Brown, T. T. (2016) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1389 · Cited by 32
Rapid multicomponent relaxometry in steady state with correction of magnetization transfer effects
Liu, F., Block, W. F., Kijowski, R., & Samsonov, A. A. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25672 · Cited by 31
Bruckert, L., Shpanskaya, K. S., McKenna, E. S., Borchers, L. R., Yablonski, M., Blecher, T., Ben‐Shachar, M., Travis, K. E., Feldman, H. M., & Yeom, K. W. (2019) · The Cerebellum · doi:10.1007/s12311-018-1003-9 · Cited by 27
Lee, H., Nam, Y., Lee, H., Hsu, J.-J., Henry, R. G., & Kim, D. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.058 · Cited by 30
Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder
Dean, D., Travers, B. G., Adluru, N., Tromp, D., Destiche, D. J., Samsin, D., Prigge, M. B. D., Zielinski, B. A., Fletcher, P. T., Anderson, J. S., et al. (2016) · Brain Connectivity · doi:10.1089/brain.2015.0385 · Cited by 30
Self-citationWiggermann, V., Vavasour, I. M., Kolind, S., MacKay, A. L., Helms, G., & Rauscher, A. (2020) · NMR in Biomedicine · doi:10.1002/nbm.4277 · Cited by 28
The Cambridge Handbook of Infant Development
Lockman, J. J., Hertz, D., Tamis-LeMonda, C. S., Brain, B. C., Context..........................................., Rey, J., Falck-Ytter, T., Jones, E., Maurer, D., Cirelli, L., et al. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108351959 · Cited by 31
Howell, B., Ahn, M., Shi, Y., Godfrey, J. R., Hu, X. P., Hongtu Zhu, B., Styner, M. A., & Sánchez, M. M. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.013 · Cited by 31
Liao, Y., Coelho, S., Chen, J., Ades‐Aron, B., Pang, M., Stepanov, V., Osorio, R. S., Shepherd, T. M., Lui, Y. W., Novikov, D. S., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00102 · Cited by 29
So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging
Lee, J., Ji, S., & Oh, S. (2024) · Magnetic Resonance in Medical Sciences · doi:10.2463/mrms.rev.2024-0001 · Cited by 28
Quantitative T1 mapping of the normal brain from early infancy to adulthood
Gräfe, D., Frahm, J., Merkenschlager, A., Voit, D., & Hirsch, W. (2020) · Pediatric Radiology · doi:10.1007/s00247-020-04842-7 · Cited by 28
Early postnatal myelin content estimate of white matter via T1w/T2w ratio
Lee, K., Cherel, M., Budin, F., Gilmore, J. H., Consing, K. N. Z., Rasmussen, J. M., Wadhwa, P. D., Entringer, S., Glasser, M. F., Essen, D. C. V., et al. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2082198 · Cited by 28
Longo, C. A., Fried, P. A., Cameron, I. G. M., & Smith, A. (2013) · Neurotoxicology and Teratology · doi:10.1016/j.ntt.2013.05.007 · Cited by 29
Four Pillars of the Montessori Method and Their Support by Current Neuroscience
Catherine, L., Javier, B., & Francisco, G. (2020) · Mind, Brain, and Education · doi:10.1111/mbe.12262 · Cited by 27
Novel 3D magnetic resonance fingerprinting radiomics in adult brain tumors: a feasibility study
Tippareddy, C., Onyewadume, L., Sloan, A. E., Wang, G.-M., Patil, N. T., Hu, S., Barnholtz‐Sloan, J. S., Boyacıoğlu, R., Gulani, V., Sunshine, J. L., et al. (2022) · European Radiology · doi:10.1007/s00330-022-09067-w · Cited by 27
Weber, A. M., Zhang, Y., Kames, C., & Rauscher, A. (2019) · NMR in Biomedicine · doi:10.1002/nbm.4222 · Cited by 25
Hierarchical Complexity of the Macro-Scale Neonatal Brain
Blesa, M., Galdi, P., Cox, S. R., Sullivan, G., Stoye, D. Q., Lamb, G. J., Quigley, A. J., Thrippleton, M. J., Escudero, J., Bastin, M. E., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa345 · Cited by 28
Trajectories of brain white matter development in young children with prenatal alcohol exposure
Kar, P., Reynolds, J. E., Gibbard, W. B., McMorris, C. A., Tortorelli, C., & Lebel, C. A. (2022) · Human Brain Mapping · doi:10.1002/hbm.25944 · Cited by 25
Kulikova, S. P., Hertz‐Pannier, L., Dehaene‐Lambertz, G., Poupon, C., & Dubois, J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0163143 · Cited by 26
Fil, J. E., Joung, S., Hayes, C. A., & Dilger, R. N. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.649536 · Cited by 25
White matter microstructural abnormalities in children with severe congenital hypothyroidism
Cooper, H. E., Kaden, E., Halliday, L. F., Bamiou, D., Mankad, K., Peters, C. J., & Clark, C. A. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101980 · Cited by 26
The Development of Multisensory Attention Skills
Bahrick, L. E., Lickliter, R., & Todd, J. T. T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108351959.011 · Cited by 27
Trajectory of Long-Term Outcome in Severe Pediatric Diffuse Axonal Injury: An Exploratory Study
Lang, S., Kilbaugh, T. J., Friess, S. H., Sotardi, S. T., Kim, C. T., Mazandi, V. M., Zhang, B., Storm, P. B., Heuer, G. G., Tucker, A. M., et al. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.704576 · Cited by 24
Multivariate analyses applied to fetal, neonatal and pediatric MRI of neurodevelopmental disorders
Levman, J. E. D., & Takahashi, E. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.09.017 · Cited by 25
Uematsu, A., Hata, J., Komaki, Y., Seki, F., Yamada, C., Okahara, N., Kurotaki, Y., Sasaki, E., & Okano, H. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.028 · Cited by 24
Brain myelination at 7 months of age predicts later language development
Corrigan, N. M., Yarnykh, V. L., Huber, E., Zhao, T. C., & Kuhl, P. K. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119641 · Cited by 25
Exploring the role of white matter connectivity in cortex maturation
Friedrichs‐Maeder, C., Griffa, A., Schneider, J., Hüppi, P. S., Truttmann, A. C., & Hagmann, P. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177466 · Cited by 25
Charvet, C. J. (2021) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2020.2987 · Cited by 22
Quantitative MRI in leukodystrophies
Stellingwerff, M. D., Pouwels, P. J. W., Roosendaal, S. D., Barkhof, F., & van der Knaap, M. S. (2023) · NeuroImage Clinical · doi:10.1016/j.nicl.2023.103427 · Cited by 23
Sex differences of brain and their implications for personalized therapy
Rezzani, R., Franco, C., & Rodella, L. F. (2019) · Pharmacological Research · doi:10.1016/j.phrs.2019.01.030 · Cited by 24
Jang, H., Carl, M., Ma, Y.-J., Searleman, A. C., Jerban, S., Chang, E., Corey-Bloom, J., & Du, J. (2020) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims.2020.04.13 · Cited by 20
Kühne, F., Neumann, W., Hofmann, P., Marques, J. P., Kaindl, A. M., & Tietze, A. (2021) · Pediatric Radiology · doi:10.1007/s00247-021-05109-5 · Cited by 22
Mallott, J. M., Palacios, E. M., Maruta, J., Ghajar, J., & Mukherjee, P. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00518 · Cited by 22
Myelination may be impaired in neonates following birth asphyxia
Olivieri, B., Rampakakis, E., Gilbert, G., Fezoua, A., & Wintermark, P. (2021) · NeuroImage: Clinical · doi:10.1016/j.nicl.2021.102678 · Cited by 19
Cerebral blood flow and cognitive outcome after pediatric stroke in the middle cerebral artery
Steiner, L., Federspiel, A., Jaros, J., Slavova, N., Wiest, R., Steinlin, M. I., Grunt, S., & Everts, R. (2021) · Scientific Reports · doi:10.1038/s41598-021-98309-w · Cited by 20
Chen, G., Fu, S., Chen, P., Zhong, S., Chen, F., Qian, L., Luo, Z., Pan, Y., Tang, G., Jia, Y., et al. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.12.111 · Cited by 20
Gabucio, L. M. C., Collado, L. T., de la Hera, M. G., Fernández‐Somoano, A., Tardón, A., Júlvez, J., Sunyer, J., Rebagliato, M., Murcia, M., Ibarluzea, J. M., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph191912123 · Cited by 21
On the emergence of autism: neuroimaging findings from birth to preschool
Wolff, J. J., & Piven, J. (2013) · Neuropsychiatry · doi:10.2217/npy.13.11 · Cited by 19
Spader, H. S., Dean, D., LaFrance, W. C., Jr., Raukar, N. P., Cosgrove, G. R., Eyerly‐Webb, S. A., Ellermeier, A., Correia, S., Deoni, S., & Rogg, J. M. (2018) · Journal of neurosurgery · doi:10.3171/2017.12.jns171597 · Cited by 20
Self-citationBrain Myelin Water Fraction and Diffusion Tensor Imaging Atlases for 9‐10 Year‐Old Children
Morris, S. R., Holmes, R. D., Dvorak, A. V., Liu, H., Yoo, Y., Vavasour, I. M., Mazabel, S., Mädler, B., Kolind, S., Li, D. K. B., et al. (2020) · Journal of Neuroimaging · doi:10.1111/jon.12689 · Cited by 20
Magnetic Resonance Fingerprinting
Badve, C. A., & Ma, D. (2023) · Springer eBooks · doi:10.1007/978-3-031-10909-6_53 · Cited by 20
Multivariate characterization of white matter heterogeneity in autism spectrum disorder
Dean, D., LANGE, N. D., Travers, B. G., Prigge, M. B. D., Matsunami, N., Kellett, K. A., Freeman, A., Kane, K. L., Adluru, N., Tromp, D., et al. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.01.002 · Cited by 23
Self-citationRasmussen, J. M., Kruggel, F., Gilmore, J. H., Styner, M. A., Entringer, S., Consing, K. N. Z., Potkin, S. G., Wadhwa, P. D., & Buß, C. (2016) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2016.12.004 · Cited by 18
Association between breastfeeding during infancy and white matter microstructure in early childhood
Kar, P., Reynolds, J. E., Grohs, M. N., Bell, R. C., Jarman, M., Dewey, D., & Lebel, C. A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118084 · Cited by 19
Why monkeys do not get multiple sclerosis (spontaneously)
Bove, R. M. (2018) · Evolution Medicine and Public Health · doi:10.1093/emph/eoy002 · Cited by 19
Early Life Stress: a Key Link between Childhood Adversity and Risk of Attempting Suicide.
Raleva, M. (2018) · PubMed · Cited by 18
Dvorak, A. V., Ljungberg, E., Vavasour, I. M., Lee, L. E., Abel, S., Li, D. K. B., Traboulsee, A. L., MacKay, A. L., & Kolind, S. (2021) · Scientific Reports · doi:10.1038/s41598-020-80585-7 · Cited by 21
Sleurs, C., Lemiere, J., Radwan, A., Verly, M., Elens, I., Renard, M., Jacobs, S. A., Sunaert, S. G., Deprez, S., & Uyttebroeck, A. (2019) · Pediatric Blood & Cancer · doi:10.1002/pbc.27893 · Cited by 17
Age-dynamic networks and functional correlation for early white matter myelination
Dai, X., Müller, H., Wang, J.-L., & Deoni, S. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1785-z · Cited by 17
Self-citationBrandes-Aitken, A. N., Metser, M., Braren, S. H., Vogel, S. C., & Brito, N. H. (2023) · Infant Behavior and Development · doi:10.1016/j.infbeh.2022.101807 · Cited by 16
Rajhans, P., Mainardi, F., Austin, S., Sprenger, N., Deoni, S., Hauser, J., & Schneider, N. (2023) · Nutrients · doi:10.3390/nu15214624 · Cited by 16
Self-citationDecoding Brain Development and Aging
Hagiwara, A., Kamio, S., Kikuta, J., Nakaya, M., Uchida, W., Fujita, S., Stikov, N., Akasahi, T., Wada, A., Kamagata, K., et al. (2024) · Investigative Radiology · doi:10.1097/rli.0000000000001120 · Cited by 18
White matter trajectories over the lifespan
Conte, S., Zimmerman, D., & Richards, J. E. (2024) · PLoS ONE · doi:10.1371/journal.pone.0301520 · Cited by 17
Deoni, S., Beauchemin, J., D’Sa, V. A., Bonham, K., & Klepac‐Ceraj, V. (2025) · Brain Structure and Function · doi:10.1007/s00429-025-02907-7 · Cited by 15
Self-citationDiffusion effects in myelin sheath free induction decay
Kurz, F. T., Buschle, L. R., Hahn, A., Jende, J. M. E., Bendszus, M., Heiland, S., & Ziener, C. H. (2018) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2018.10.001 · Cited by 15
Wier, R., Aleksonis, H. A., Pearson, M. M., Cannistraci, C. J., Anderson, A. W., Kuttesch, J. F., Compas, B. E., & Hoskinson, K. R. (2019) · Journal of Neuro-Oncology · doi:10.1007/s11060-019-03180-5 · Cited by 15
Lamar, M., Zhou, X. J., Charlton, R. A., Dean, D., Little, D. M., & Deoni, S. (2013) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2013.08.001 · Cited by 16
Self-citationInherent spatial structure in myelin water fraction maps
Baumeister, T. R., Kolind, S., MacKay, A. L., & McKeown, M. J. (2019) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2019.09.012 · Cited by 15
Metadata
- Authors
- Deoni, S. C. L., Dean, D. C., O'Muircheartaigh, J., Dirks, H., & Jerskey, B. A.
- Affiliations
- Brown University (US)
- Corresponding author
- Deoni, Sean C.L.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-11
- Volume
- 63
- Issue
- 3
- Pages
- 1038-1053
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3711836
- OpenAlex
- W2131940336
- Cited by
- 390
- References
- 86
- Citations by year
- 2026: 18 · 2025: 28 · 2024: 25 · 2023: 32 · 2022: 27 · 2021: 36 · 2020: 64 · 2019: 32 · 2018: 27 · 2017: 27 · 2016: 25 · 2015: 21 · 2014: 14 · 2013: 12 · 2012: 2
- FWCI
- 11.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- National Institutes of Mental Health (R01 MH087510)
- Sir Henry Wellcome Postdoctoral Fellowship (No 096195)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › NMR spectroscopy and applications
- Keywords
- white matter development, myelination, myelin water fraction, T1 relaxation time, T2 relaxation time, corpus callosum, brain development, infancy, early childhood, despots, cerebellum
- MeSH terms
- Brain, Brain Mapping, Child, Preschool, Female, Humans, Infant, Male, Myelin Sheath, Neurogenesis
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