Abstract
Diffusion-weighted imaging studies have repeatedly shown that white matter correlates with reading throughout development. However, the neurobiological interpretation of this relationship is constrained by the limited microstructural specificity of diffusion imaging. A critical component of white matter microstructure is myelin, which can be investigated noninvasively using MRI. Here, we examined the link between myelin water fraction (MWF) and reading ability in 10-year-old children (n = 69). To better understand this relationship, we additionally investigated how these two variables relate to fractional anisotropy (FA; a common index of diffusion-weighted imaging). Our analysis revealed that lower MWF coheres with better reading scores in left-hemispheric tracts relevant for reading. While we replicated previous reports on a positive relationship between FA and MWF, we did not find any evidence for an association between reading and FA. Together, these findings contrast previous research suggesting that poor reading abilities might be rooted in lower myelination and emphasize the need for further longitudinal research to understand how this relationship evolves throughout reading development. Altogether, this study contributes important insights into the role of myelin-related processes in the relationship between reading and white matter structure.
This is a preview of subscription content, log in via an institution to check access.
Data availability
The conditions of our ethics approval do not permit public archiving of anonymised study data, since consent had only been obtained for the participation in the study, and not to share data with third parties. Researchers seeking access to the study data should contact the last author (maaike.vandermosten@kuleuven.be) explaining the purpose of their request. In accordance with the EU general data protection regulation (GDPR), data will be released to requestors upon the following conditions: consent of the representative of the minor and a formal agreement between parties. Please note that the MRI data cannot be shared under any circumstance, as MRI data are person-specific and therefore cannot be considered anonymous.
Notes
Information on dyslexia status is available but not reported in Table 1 for two main reasons: 1) reading is treated as a continuous measure and 2) it is difficult to make a dichotomous classification because dyslexia status was determined using different criteria for the children participating in the longitudinal study compared to the children recruited later.
References
Avants BB, Tustison NJ, Song G et al (2011) A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 54:2033–2044. https://doi.org/10.1016/j.neuroimage.2010.09.025
Bates D, Mächler M, Bolker BM, Walker SC (2015) Fitting linear mixed-effects models using lme4. J Stat Softw. https://doi.org/10.18637/jss.v067.i01
Beaulieu C (2009) The biological basis of diffusion anisotropy. In: Johansen-Berg H, Behrens TEJ (eds) Diffusion MRI: from quantitative measurement to in vivo neuroanatomy. Academic Press Elsevier, London, pp 105–127
Beaulieu C, Yip E, Low PB et al (2020) Myelin water imaging demonstrates lower brain myelination in children and adolescents with poor reading ability. Front Hum Neurosci 14:1–12. https://doi.org/10.3389/fnhum.2020.568395
Bells S, Cercignani M, Deoni S, Assaf Y (2011) “Tractometry”—comprehensive multi-modal quantitative assessment of white matter along specific tracts. Proc Int Soc Magnet Reson Med 19:678
Ben-Shachar M, Dougherty RF, Wandell BA (2007) White matter pathways in reading. Curr Opin Neurobiol 17(2):258–270. https://doi.org/10.1016/j.conb.2007.03.006
Billiet T, Vandenbulcke M, Mädler B et al (2015) Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI. Neurobiol Aging 36:2107–2121. https://doi.org/10.1016/j.neurobiolaging.2015.02.029
Boudreau B, Poulin C (2009) An examination of the validity of the Family Affluence Scale II (FAS II) in a general adolescent population of Canada. Soc Indic Res 94:29–42. https://doi.org/10.1007/s11205-008-9334-4
Brus BT, Voeten MJM (1979) Eén-minuut-test: Vorm A en B : verantwoording en handleiding : schoolvorderingstest voor de technische leesvaardigheid, bestemd voor het tweede tot en met het zesde leerjaar van het basisonderwijs. Berkhout, Nijmegen
Christodoulou JA, Murtagh J, Cyr A et al (2016) Relation of white-matter microstructure to reading ability and disability in beginning readers. Neuropsychology 31:508–515
De Santis S, Drakesmith M, Bells S et al (2014) Why diffusion tensor MRI does well only some of the time: Variance and covariance of white matter tissue microstructure attributes in the living human brain. Neuroimage 89:35–44. https://doi.org/10.1016/j.neuroimage.2013.12.003
Dudal P (1997) Leerlingvolgsysteem VCLB (CSBO). Spelling: Toetsen 1-2-3. Basisboek en kopieerbundel. Garant, Leuven
Eluvathingal TJ, Hasan KM, Larry K et al (2007) Quantitative diffusion tensor tractography of association and projection fibers in normally developing children and adolescents. Cereb Cortex 17:2760–2768
Friedrich P, Fraenz C, Schlüter C et al (2020) The relationship between axon density, myelination, and fractional anisotropy in the human corpus callosum. Cereb Cortex 30:2042–2056. https://doi.org/10.1093/cercor/bhz221
Geeraert BL, Lebel RM, Lebel C (2019) A multiparametric analysis of white matter maturation during late childhood and adolescence. Hum Brain Mapp 40:4345–4356. https://doi.org/10.1002/hbm.24706
Grotheer M, Zhen Z, Lerma-Usabiaga G, Grill-Spector K (2019) Separate lanes for adding and reading in the white matter highways of the human brain. Nat Commun 10(1):3675. https://doi.org/10.1038/s41467-019-11424-1
Jones DK, Knösche TR, Turner R (2013) White matter integrity, fiber count, and other fallacies: the do’s and don’ts of diffusion. Neuroimage 73:239–254. https://doi.org/10.1016/j.neuroimage.2012.06.081
Kaller MS, Lazari A, Blanco-Duque C et al (2017) Myelin plasticity and behaviour—connecting the dots. Curr Opin Neurobiol 47:86–92. https://doi.org/10.1016/j.conb.2017.09.014
Klingberg T, Hedehus M, Temple E et al (2000) Microstructure of temporo-parietal white matter as a basis for reading ability. Neuron 25:493–500. https://doi.org/10.1016/S0896-6273(00)80911-3
Kraft I, Schreiber J, Cafiero R et al (2016) Predicting early signs of dyslexia at a preliterate age by combining behavioral assessment with structural MRI. Neuroimage 143:378–386. https://doi.org/10.1016/j.neuroimage.2016.09.004
Kuznetsova A, Brockhoff PB, Christensen RHB (2017) lmerTest package: tests in linear mixed effects models. J Stat Softw 82:1–26
Laule C, Leung E, Li DKB et al (2006) Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology. Mult Scler 12:747–753. https://doi.org/10.1177/1352458506070928
Lebel C, Beaulieu C (2009) Lateralization of the arcuate fasciculus from childhood to adulthood and its relation to cognitive abilities in children. Hum Brain Mapp 30:3563–3573. https://doi.org/10.1002/hbm.20779
Lebel C, Beaulieu C (2011) Longitudinal development of human brain wiring continues from childhood into adulthood. J Neurosci 31:10937–10947. https://doi.org/10.1523/JNEUROSCI.5302-10.2011
Lebel C, Shaywitz B, Holahan J et al (2013) Diffusion tensor imaging correlates of reading ability in dysfluent and non-impaired readers. Brain Lang 125:215–222. https://doi.org/10.1016/j.bandl.2012.10.009
Leemans A, Jeurissen B, Sijbers J, Jones DK (2009) ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. Proc Int Soc Magnet Resonance Med 17:3537
MacKay AL, Laule C (2016) Magnetic resonance of myelin water: an in vivo marker for myelin. Brain Plasticity 2:71–91. https://doi.org/10.3233/BPL-160033
Mädler B, Drabycz SA, Kolind SH et al (2008) Is diffusion anisotropy an accurate monitor of myelination? Correlation of multicomponent T2 relaxation and diffusion tensor anisotropy in human brain. Magn Reson Imaging 26:874–888. https://doi.org/10.1016/j.mri.2008.01.047
Meisler SL, Gabrieli JDE (2022) A large-scale investigation of white matter microstructural associations with reading ability. Neuroimage 249:118909
Moore GRW, Leung E, MacKay AL et al (2000) A pathology-MRI study of the short-T2 component in formalin-fixed multiple sclerosis brain. Neurology 55:1506–1510. https://doi.org/10.1212/WNL.55.10.1506
Moreau D, Stonyer JE, McKay NS, Waldie KE (2018) No evidence for systematic white matter correlates of dyslexia: an activation likelihood estimation meta-analysis. Brain Res 1683:36–47
Morris SR, Holmes RD, Dvorak AV et al (2020) Brain myelin water fraction and diffusion tensor imaging atlases for 9–10 year-old children. J Neuroimag 30:150–160. https://doi.org/10.1111/jon.12689
Nakagawa S, Schielzeth H (2013) A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol 4:133–142. https://doi.org/10.1111/j.2041-210x.2012.00261.x
Odegard TN, Farris EA, Ring J et al (2009) Brain connectivity in non-reading impaired children and children diagnosed with developmental dyslexia. Neuropsychologia 47:1972–1977
Prasloski T, Rauscher A, MacKay AL et al (2012) Rapid whole cerebrum myelin water imaging using a 3D GRASE sequence. Neuroimage 63:533–539. https://doi.org/10.1016/j.neuroimage.2012.06.064
R Core Team (2020) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
Raven JC, Court JH, Raven J (1984) Manual for Raven’s progressive matrices and vocabulary scales. Lewis, London
Skeide MA, Bazin PL, Trampel R et al (2018) Hypermyelination of the left auditory cortex in developmental dyslexia. Neurology 90:e492–e497. https://doi.org/10.1212/WNL.0000000000004931
van Atteveldt N, Vandermosten M, Weeda W, Bonte M (2021) How to capture developmental brain dynamics: gaps and solutions. NPJ Sci Learn. https://doi.org/10.1038/s41539-021-00088-6
Van Den Bos KP, Spelberg H, Scheepsma A, De Vries J (1994) De Klepel. Vorm A en B. Een test voor de leesvaardigheid van pseudowoorden. Verantwoording, handleiding, diagnostiek en behandeling. Berkhout, Nijmegen, The Netherlands
Van Der Auwera S, Vandermosten M, Wouters J et al (2021) A three-time point longitudinal investigation of the arcuate fasciculus throughout reading acquisition in children developing dyslexia. Neuroimage 237:118087
Vanderauwera J, Wouters J, Vandermosten M, Ghesquière P (2017) Early dynamics of white matter deficits in children developing dyslexia. Dev Cogn Neurosci 27:69–77. https://doi.org/10.1016/j.dcn.2017.08.003
Vanderauwera J, Vos AD, Forkel SJ et al (2018) Neural organization of ventral white matter tracts parallels the initial steps of reading development: a DTI tractography study. Brain Lang 183:32–40. https://doi.org/10.1016/j.bandl.2018.05.007
Vandermosten M, Boets B, Wouters J, Ghesquière P (2012) A qualitative and quantitative review of diffusion tensor imaging studies in reading and dyslexia. Neurosci Biobehav Rev 36:1532–1552. https://doi.org/10.1016/j.neubiorev.2012.04.002
Vandermosten M, Boets B, Poelmans H et al (2012a) A tractography study in dyslexia: neuroanatomic correlates of orthographic, phonological and speech processing. Brain 135:935–948. https://doi.org/10.1093/brain/awr363
Vandermosten M, Vanderauwera J, Theys C et al (2015) A DTI tractography study in pre-readers at risk for dyslexia. Dev Cogn Neurosci 14:8–15. https://doi.org/10.1016/j.dcn.2015.05.006
Walton M, Dewey D, Lebel C (2018) Brain white matter structure and language ability in preschool-aged children. Brain Lang 176:19–25. https://doi.org/10.1016/j.bandl.2017.10.008
Wandell BA, Yeatman JD (2013) Biological development of reading circuits. Curr Opin Neurobiol 23:261–268. https://doi.org/10.1038/jid.2014.371
Wang R, Benner T, Sorensen AG, Wedeen VJ (2007) Diffusion toolkit: a software package for diffusion imaging data processing and tractography. In: Proc intl soc mag reson med, pp 3720
Whittall KP, MacKay AL (1989) Quantitative interpretation of NMR relaxation data. J Magnet Resonance 84:134–152. https://doi.org/10.1016/0022-2364(89)90011-5
Whittall KP, Mackay AL, Graeb DA et al (1997) In vivo measurement ofT2 distributions and water contents in normal human brain. Magn Reson Med 37:34–43. https://doi.org/10.1002/mrm.1910370107
Yeatman J, Dougherty RF, Rykhlevskaia E et al (2011) Anatomical properties of the arcuate fasciculus predict phonological and reading skills in children. J Cogn Neurosci 23:3304–3317. https://doi.org/10.1162/jocn
Yeatman JD, Dougherty RF, Ben-Shachar M, Wandell BA (2012) Development of white matter and reading skills. Proc Natl Acad Sci USA. https://doi.org/10.1073/pnas.1206792109
Zhang M, Chen C, Xue G et al (2014) Language-general and -specific white matter microstructural bases for reading. Neuroimage 98:435–441. https://doi.org/10.1016/j.neuroimage.2014.04.080
Zuk J, Yu X, Sanfilippo J et al (2021) White matter in infancy is prospectively associated with language outcomes in kindergarten. Dev Cogn Neurosci. https://doi.org/10.1016/j.dcn.2021.100973
Acknowledgements
We would like to thank Caroline Beelen, Thanh Vân Phan and all the DYSCO colleagues and student assistants for participant selection and data collection. We are grateful to all families, children and schools for their participation in this research.
Funding
This work was supported by the European Union H2020 MSCA-ITN-2014-ETN Programme, Advancing brain research in children’s developmental neurocognitive disorders-project (ChildBrain, #641652), and the Research Council of KU Leuven (C14/17/046). J.V. was a postdoctoral fellow of the Research Foundation Flanders (12T4818N).
Author information
Authors and Affiliations
Contributions
ME and MV designed this study. ME conducted the data processing, data visualization, statistical analysis and drafted the manuscript. TB provided software for image processing, contributed to the methodology and revised the manuscript. JW, PG, JV and MV revised the manuscript, were involved in conceptualization, data curation, project administration, funding acquisition and supervised the project. All authors read and approved the final version of this manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethics approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Medical Ethical Committee of the Leuven University Hospital (B322201214607).
Consent to participate
Written informed consent was obtained from the parents/guardians of the children participating in this study. Verbal assent was obtained from the children before participation.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Economou, M., Billiet, T., Wouters, J. et al. Myelin water fraction in relation to fractional anisotropy and reading in 10-year-old children. Brain Struct Funct 227, 2209–2217 (2022). https://doi.org/10.1007/s00429-022-02486-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00429-022-02486-x