Abstract
The home language and literacy environment (HLLE) in infancy has been associated with subsequent pre-literacy skill development and HLLE at preschool-age has been shown to correlate with white matter organization in tracts that subserve pre-reading and reading skills. Furthermore, childhood socioeconomic status (SES) has been linked with both HLLE and white matter organization. It is important to understand whether the relationships between environmental factors such as HLLE and SES and white matter organization can be detected as early as infancy, as this period is characterized by rapid brain development that may make white matter pathways particularly susceptible to these early experiences. Here, we hypothesized that HLLE (1) relates to white matter organization in pre-reading and reading-related tracts in infants, and (2) mediates a link between SES and white matter organization. To test these hypotheses, infants (mean age: 8.6 ± 2.3 months, N = 38) underwent diffusion-weighted imaging MRI during natural sleep. Image processing was performed with an infant-specific pipeline and fractional anisotropy (FA) was estimated from the arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF) bilaterally using the baby automated fiber quantification method. HLLE was measured with the Reading subscale of the StimQ (StimQ-Reading) and SES was measured with years of maternal education. Self-reported maternal reading ability was also quantified and applied to our statistical models as a proxy for confounding genetic effects. StimQ-Reading positively correlated with FA in left AF and to maternal education, but did not mediate the relationship between them. Taken together, these findings underscore the importance of considering HLLE from the start of life and may inform novel prevention and intervention strategies to support develo** infants during a period of heightened brain plasticity.
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Data availability
Due to Institutional Review Board regulations at Boston Children’s Hospital at the time of consent, our data cannot presently be uploaded to a permanent third-party archive. However, data sharing can be initiated through a Data Usage Agreement upon request. Additionally, code used for analyzing the data may be found at https://github.com/TeddyTuresky/diffusionHLLE2021.
References
Andersson JLR, Graham MS, Drobnjak I, Zhang H, Filippini N, Bastiani M (2017) Towards a comprehensive framework for movement and distortion correction of diffusion MR images: within volume movement. Neuroimage 152:450–466. https://doi.org/10.1016/j.neuroimage.2017.02.085
Andersson JLR, Skare S, Ashburner J (2003) How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. Neuroimage 20:870–888. https://doi.org/10.1016/S1053-8119(03)00336-7
Andersson JLR, Sotiropoulos SN (2016) An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 125:1063–1078. https://doi.org/10.1016/j.neuroimage.2015.10.019
Bastiani M, Andersson JLR, Cordero-grande L, Murgasova M, Hutter J, Price AN, Makropoulos A, Fitzgibbon SP, Hughes E, Rueckert D, Victor S, Rutherford M, Edwards AD, Smith SM, Tournier J, Hajnal JV, Jbabdi S, Sotiropoulos SN (2019) Automated processing pipeline for neonatal diffusion MRI in the develo** human connectome project. Neuroimage 185:750–763
Betancourt LM, Avants B, Farah MJ, Brodsky NL, Wu J, Ashtari M, Hurt H (2016) Effect of socioeconomic status (SES) disparity on neural development in female African-American infants at age 1 month. Dev Sci 19:947–956. https://doi.org/10.1111/desc.12344
Black JM, Tanaka H, Stanley L, Nagamine M, Zakerani N, Thurston A, Kesler S, Hulme C, Lyytinen H, Glover GH, Serrone C, Raman MM, Reiss AL, Hoeft F (2012) Maternal history of reading difficulty is associated with reduced language-related gray matter in beginning readers. Neuroimage 59:3021–3032. https://doi.org/10.1016/j.neuroimage.2011.10.024
Brito NH, Fifer WP, Myers MM, Elliott AJ, Noble KG (2016) Associations among family socioeconomic status, EEG power at birth, and cognitive skills during infancy. Dev Cogn Neurosci 19:144–151. https://doi.org/10.1016/j.dcn.2016.03.004
Brito NH, Noble KG (2014) Socioeconomic status and structural brain development. Front Neurosci 8:1–12. https://doi.org/10.3389/fnins.2014.00276
Burgess SR, Hecht SA, Christopher J (2002) Relations of the home literacy environment (HLE) to the development of reading-related abilities: a one–year longitudinal study. Read Res Q 37:408–426
Bus AG, Van IJzendoorn MH, Pellegrini AD (1995) Joint book reading makes for success in learning to read: a meta-analysis on intergenerational transmission of literacy. Rev Educ Res 65:1–21. https://doi.org/10.3102/00346543065001001
Catani M, Dawson MS (2017) Language Processing, development and evolution, Conn’s translational neuroscience. Elsevier Inc, Academic Press. https://doi.org/10.1016/B978-0-12-802381-5.00049-X
Catani M, Jones DK, Ffytche DH (2005) Perisylvian language networks of the human brain. Ann Neurol 57:8–16. https://doi.org/10.1002/ana.20319
Christian K, Morrison FJ, Bryant FB (1998) Predicting kindergarten academic skills: Interactions among child care, maternal education, and family literacy environments. Early Child Res Q 13:501–521. https://doi.org/10.1016/S0885-2006(99)80054-4
Cordero-Grande L, Christiaens D, Hutter J, Price AN, Hajnal JV (2019) Complex diffusion-weighted image estimation via matrix recovery under general noise models. Neuroimage 200:391–404. https://doi.org/10.1016/j.neuroimage.2019.06.039
Davison K, Zuk J, Mullin L, Ozernov-Palchik O, Norton E, Gabrieli J, Yu X, Gaab N (2022) Examining the relationship between shared book reading at home, white matter organization in kindergarten, and subsequent language and reading abilities: a longitudinal investigation. J Cogn Neurosci (Accepted)
Demir-Lira ÖE, Applebaum LR, Goldin-Meadow S, Levine SC (2019) Parents’ early book reading to children: relation to children’s later language and literacy outcomes controlling for other parent language input. Dev Sci 22:e12764. https://doi.org/10.1111/desc.12764
de Jong PF, van der Leij A (1999) Specific contributions of phonological abilities to early reading acquisition: results from a Dutch latent variable longitudinal study. J Educ Psychol 91:450–476
Dhollander T, Raffelt D, Connelly A (2016) Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image. ISMRM Workshop on Breaking the Barriers of Diffusion MRI. https://mrtrix.readthedocs.io/en/dev/reference/commands/dwi2response.html
Duff FJ, Reen G, Plunkett K, Nation K (2015) Do infant vocabulary skills predict school-age language and literacy outcomes? J Child Psychol Psychiatry 56:848–856
Eden GF, Olulade OA, Evans TM, Krafnick AJ, Alkire DR (2016) Developmental dyslexia. In: Hickok G, Small S (eds) Neurobiology of Language. Oxford, UK, Elsevier
Farah MJ (2017) The neuroscience of socioeconomic status: correlates, causes, and consequences. Neuron 96:56–71. https://doi.org/10.1016/j.neuron.2017.08.034
Foster MA, Lambert R, Abbott-shim M, Mccarty F, Franze S (2005) A model of home learning environment and social risk factors in relation to children’s emergent literacy and social outcomes. Early Chil 20:13–36. https://doi.org/10.1016/j.ecresq.2005.01.006
Friend A, DeFries J, Olson R, Pennington B, Harlaar N, Byrne B, Samuelsson S, Willcutt E, Wadsworth S, Corley R, Keenan J (2009) Heritability of high reading ability and its interaction with parental education. Behav Genet 39:427–436. https://doi.org/10.1007/s10519-009-9263-2.Heritability
Friend A, Defries JC, Olson RK (2008) Parental education moderates genetic influences on reading disability: research article. Psychol Sci 19:1124–1130. https://doi.org/10.1111/j.1467-9280.2008.02213.x
Frijters JC, Barron RW, Brunello M (2000) Direct and mediated influences of home literacy and literacy interest on prereaders ’ oral vocabulary and early written language skill. J Educ Psychol 92:466–477
Geng X, Gouttard S, Sharma A, Gu H, Styner M, Lin W, Gerig G, Gilmore JH (2012) NeuroImage quantitative tract-based white matter development from birth to age 2 years. Neuroimage 61:542–557. https://doi.org/10.1016/j.neuroimage.2012.03.057
Georgiou GK, Parrila R, Papadopoulos TC (2008) Predictors of word decoding and reading fluency across languages varying in orthographic consistency. J Educ Psychol 100:566–580. https://doi.org/10.1037/0022-0663.100.3.566
Grotheer M, Rosenke M, Wu H, Kular H, Querdasi FR, Natu VS, Yeatman JD, Grill-Spector K (2022) White matter myelination during early infancy is linked to spatial gradients and myelin content at birth. Nat Commun 13:1–12. https://doi.org/10.1038/s41467-022-28326-4
Gratton C, Nelson SM, Gordon EM (2022) Brain-behavior correlations: two paths toward reliability. Neuron 110(9):1446–1449. https://doi.org/10.1016/j.neuron.2022.04.018
Gullick MM, Booth JR (2015) The direct segment of the arcuate fasciculus is predictive of longitudinal reading change. Dev Cogn Neurosci 13:68–74. https://doi.org/10.1016/j.dcn.2015.05.002
Gullick MM, Demir-lira E, Booth JR (2016) Reading skill–fractional anisotropy relationships in visuospatial tracts diverge depending on socioeconomic status. Dev Sci 19:673–685. https://doi.org/10.1111/desc.12428
Hamilton L, Hayiou-Thomas M, Hulme C, Snowling M (2016) The home literacy environment as a predictor of the early literacy development of children at family-risk of dysle. Sci Stud Read 20:401–419
Hanson JL, Chandra A, Wolfe BL, Pollak SD (2011) Association between income and the hippocampus. PLoS ONE 6:1–8. https://doi.org/10.1371/journal.pone.0018712
Hart SA, Little C, van Bergen E (2021) Nurture might be nature: cautionary tales and proposed solutions. npj Sci. Learn 6:1–12. https://doi.org/10.1038/s41539-020-00079-z
Hoeft F, McCandliss BD, Black JM, Gantman A, Zakerani N, Hulme C, Lyytinen H, Whitfield-Gabrieli S, Glover GH, Reiss AL, Gabrieli JDE (2011) Neural systems predicting long-term outcome in dyslexia. Proc Natl Acad Sci 108:361–366. https://doi.org/10.1073/pnas.1008950108
Hoff E (2003) The specificity of environmental influence: socioeconomic status affects early vocabulary development via maternal speech. Child Dev 74:1368–1378. https://doi.org/10.1111/1467-8624.00612
Hutton JS, Dudley J, Horowitz-Kraus T, DeWitt T, Holland SK (2020) Associations between home literacy environment, brain white matter integrity and cognitive abilities in preschool-age children. Acta Paediatr 109:1376–1386
Hutton JS, Horowitz-Kraus T, Mendelsohn AL, DeWitt T, Holland SK (2015) Home reading environment and brain activation in preschool children listening to stories. Pediatrics 136:466–478. https://doi.org/10.1542/peds.2015-0359
Hutton JS, Phelan K, Horowitz-Kraus T, Dudley J, Altaye M, DeWitt T, Holland SK (2017) Shared reading quality and brain activation during story listening in preschool-age children. J Pediatr 191:204-211.e1. https://doi.org/10.1016/j.jpeds.2017.08.037
Ivanova MV, Zhong A, Turken A, Baldo JV, Dronkers NF (2021) Functional contributions of the arcuate fasciculus to language processing. Front Hum Neurosci 15:1–15. https://doi.org/10.3389/fnhum.2021.672665
Jednorog K, Altarelli I, Monzalvo K, Fluss J, Dubois J, Billard C, Dehaene-Lambertz G, Ramus F (2012) The influence of socioeconomic status on children’s brain structure. PLoS ONE 7:1–9. https://doi.org/10.1371/journal.pone.0042486
Jeurissen B, Tournier JD, Dhollander T, Connelly A, Sijbers J (2014) Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. Neuroimage 103:411–426. https://doi.org/10.1016/j.neuroimage.2014.07.061
Karrass J, Braungart-Rieker JM (2005) Effects of shared parent-infant book reading on early language acquisition. J Appl Dev Psychol 26:133–148. https://doi.org/10.1016/j.appdev.2004.12.003
King LS, Camacho MC, Montez DF, Humphreys KL, Gotlib IH (2021) Naturalistic language input is associated with resting-state functional connectivity in infancy. J Neurosci 41:424–434. https://doi.org/10.1523/JNEUROSCI.0779-20.2020
Küntay AC, Ahtam B (2004) Effect of maternal education on Turkish mothers’ styles of reminiscing with their children. Türk Psikol Derg 19:19–31
Laakso M, Poikkeus A, Lyytinen P (1999) Shared reading interaction in families with and without genetic risk for dyslexia: implications for toddlers’ language development. Infant Child Dev 8:179–195
Langer N, Peysakhovich B, Zuk J, Drottar M, Sliva DD, Smith S, Becker BLC, Grant PE, Gaab N (2017) White matter alterations in infants at risk for developmental dyslexia. Cereb Cortex 27:1027–1036. https://doi.org/10.1093/cercor/bhv281
Lawson GM, Duda JT, Avants BB, Wu J, Farah MJ (2013) Associations between children’s socioeconomic status and prefrontal cortical thickness. Dev Sci 16:641–652. https://doi.org/10.1111/desc.12096.Associations
Lebel C, Deoni S (2018) NeuroImage the development of brain white matter microstructure. Neuroimage 182:207–218. https://doi.org/10.1016/j.neuroimage.2017.12.097
Lefly DL, Pennington BF (2000) Reliability and validity of the adult reading history questionnaire. J Learn Disabil 33:286–296. https://doi.org/10.1177/002221940003300306
Levy BA, Gong Z, Hessels S, Evans MA, Jared D (2006) Understanding print: early reading development and the contributions of home literacy experiences. J Exp Child Psychol 93:63–93. https://doi.org/10.1016/j.jecp.2005.07.003
Luby J, Belden A, Botteron K, Marrus N, Harms MP, Babb C, Nishino T, Barch D (2013) The effects of poverty on childhood brain development: the mediating effect of caregiving and stressful life events. JAMA Pediatr 167:1135–1142. https://doi.org/10.1001/jamapediatrics.2013.3139
Malin JL, Cabrera NJ, Rowe ML (2014) Low-income minority mothers’ and fathers’ reading and children’s interest: longitudinal contributions to children’s receptive vocabulary skills. Early Child Res Q 29:425–432. https://doi.org/10.1016/j.ecresq.2014.04.010
Marek S, Tervo-Clemmens B, Calabro FJ, Montez DF, Kay BP, Hatoum AS, Donohue MR, Foran W, Miller RL, Hendrickson TJ, Malone SM, Kandala S, Feczko E, Miranda-Dominguez O, Graham AM, Earl EA, Perrone AJ, Cordova M, Doyle O, Moore LA, Conan GM, Uriarte J, Snider K, Lynch BJ, Wilgenbusch JC, Pengo T, Tam A, Chen J, Newbold DJ, Zheng A, Seider NA, Van AN, Metoki A, Chauvin RJ, Laumann TO, Greene DJ, Petersen SE, Garavan H, Thompson WK, Nichols TE, Yeo BTT, Barch DM, Luna B, Fair DA, Dosenbach NUF (2022) Reproducible brain-wide association studies require thousands of individuals. Nat 603:654–660. https://doi.org/10.1038/s41586-022-04492-9
McDermott CL, Seidlitz J, Nadig XA, Liu S, Clasen LS, Blumenthal JD, Reardon PK, Franc X, Greenstein D, Patel XR, Chakravarty MM, Lerch JP, Raznahan XA (2019) Longitudinally map** childhood socioeconomic status associations with cortical and subcortical morphology. J Neurosci 39:1365–1373
Merz E, Maskus E, Melvin S, He X, Noble K (2020) Socioeconomic disparities in language input are associated with children’s language-related brain structure and reading skills. Child Dev 91:846–860
Merz EC, Tottenham N, Noble KG (2018) Socioeconomic status, amygdala volume, and internalizing symptoms in children and adolescents. J Clin Child Adolesc Psychol 47:312–323. https://doi.org/10.1080/15374416.2017.1326122
Muhinyi A, Rowe ML (2019) Shared reading with preverbal infants and later language development. J Appl Dev Psychol 64:1–11. https://doi.org/10.1016/j.appdev.2019.101053
National Early Literacy Panel (2008) Develo** Early Literacy. National Institute for Literacy, Federal Agency, Washington, D.C
Nelson CA, Gabard-durnam LJ (2020) Early adversity and critical periods: neurodevelopmental consequences of violating the expectable environment. Trends Neurosci 43:133–143
Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15:1–25. https://doi.org/10.1002/hbm.1058
Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, Akshoomoff N, Amaral DG, Bloss CS, Libiger O, Schork NJ, Murray SS, Casey BJ, Chang L, Ernst TM, Frazier JA, Gruen JR, Kennedy DN, Van Zijl P, Mostofsky S, Kaufmann WE, Kenet T, Dale AM, Jernigan TL, Sowell ER (2015) Family income, parental education and brain structure in children and adolescents. Nat Neurosci 18:773–778. https://doi.org/10.1038/nn.3983
Noble KG, Houston SM, Kan E, Sowell ER (2012) Neural correlates of socioeconomic status in the develo** human brain. Dev Sci 15:516–527. https://doi.org/10.1111/j.1467-7687.2012.01147.x
Odegard TN, Farris EA, Washington JA (2022) Exploring boundary conditions of the listening comprehension-reading comprehension discrepancy index. Ann Dyslexia 72:301–323. https://doi.org/10.1007/s11881-021-00250-0
Ozernov-Palchik O, Norton ES, Wang Y, Beach SD, Zuk J, Wolf M, Gabrieli JDE, Gaab N (2018) The relationship between socioeconomic status and white matter microstructure in pre-reading children: a longitudinal investigation. Hum Brain Mapp 40:741–754. https://doi.org/10.1002/hbm.24407
Payne AC, Whitehurst G, Angell AL (1994) The role of home literacy environment in the development of language ability in preschool children from low-income families. Early Child Res Q 9:427–440
Pietsch M, Christiaens D, Hutter J, Cordero-Grande L, Price AN, Hughes E, Edwards AD, Hajnal JV, Counsell SJ, Tournier JD (2019) A framework for multi-component analysis of diffusion MRI data over the neonatal period. Neuroimage 186:321–337. https://doi.org/10.1016/j.neuroimage.2018.10.060
Powers SJ, Wang Y, Beach SD, Sideridis GD, Gaab N (2016) Examining the relationship between home literacy environment and neural correlates of phonological processing in beginning readers with and without a familial risk for dyslexia: an fMRI study. Ann Dyslexia 66:337–360. https://doi.org/10.1007/s11881-016-0134-2
Puglisi M, Hulme C, Hamilton L, Snowling M (2017) The home literacy environment is a correlate, but perhaps not a cause, of variations in children’s language and literacy development. Sci Stud Read 21:498–514
Raschle N, Zuk J, Ortiz-Mantilla S, Sliva DD, Franceschi A, Grant PE, Benasich AA, Gaab N (2012) Pediatric neuroimaging in early childhood and infancy: challenges and practical guidelines. Ann N Y Acad Sci 1252:43–50. https://doi.org/10.1111/j.1749-6632.2012.06457.x
Reynolds JE, Grohs MN, Dewey D, Lebel C (2019) NeuroImage global and regional white matter development in early childhood. Neuroimage 196:49–58. https://doi.org/10.1016/j.neuroimage.2019.04.004
Romeo RR, Segaran J, Leonard JA, Robinson ST, West MR, Mackey AP, Yendiki A, Rowe ML, Gabrieli JDE (2018) Language exposure relates to structural neural connectivity in childhood. J Neurosci 38:7870–7877. https://doi.org/10.1523/jneurosci.0484-18.2018
Sanfilippo J, Ness M, Petscher Y, Rappaport L, Zuckerman B, Gaab N (2020) Reintroducing dyslexia: early identification and implications for pediatric practice. Pediatrics 146:e20193046. https://doi.org/10.1542/peds.2019-3046
Scarborough H (1998) Early identification of children at risk for reading disabilities. In: Shapiro B, Accardo P, Capute A (eds) Specific reading disability: a view of the spectrum. York Press, Timonium, pp 75–119. https://doi.org/10.1177/027112149201200206
Scarborough H, Dobrich W (1994) On the efficacy of reading and preschoolers. Dev Rev 14:245–302
Schatschneider C, Fletcher JM, Francis DJ, Carlson CD, Foorman BR (2004) Kindergarten prediction of reading skills: a longitudinal comparative analysis. J Educ Psychol 96:265–282. https://doi.org/10.1037/0022-0663.96.2.265
Scheele AF, Leseman PPM, Mayo AY (2010) The home language environment of monolingual and bilingual children and their language proficiency. Appl Psycholinguist 31:117–140. https://doi.org/10.1017/S0142716409990191
Schmitt SA, Simpson AM, Friend M (2011) A longitudinal assessment of the home literacy environment and early language. Infant Child Dev 20:409–431. https://doi.org/10.1002/icd
Schurr R, Zelman A, Mezer AA (2020) Subdividing the superior longitudinal fasciculus using local quantitative MRI. Neuroimage 208:116439. https://doi.org/10.1016/j.neuroimage.2019.116439
Sierpowska J, Gabarrós A, Fernandez-Coello A, Camins À, Castañer S, Juncadella M, Morís J, Rodríguez-Fornells A (2017) Words are not enough: non-word repetition as an indicator of arcuate fasciculus integrity during brain tumor resection. J Neurosurg 126:435–445. https://doi.org/10.3171/2016.2.JNS151592
Skare S, Bammer R (2010) Jacobian weighting of distortion corrected EPI data. Proceedings of the International Society for Magnetic Resonance in Medicine.
Smith RE, Tournier JD, Calamante F, Connelly A (2012) Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information. Neuroimage 62:1924–1938. https://doi.org/10.1016/j.neuroimage.2012.06.005
Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, Bannister PR, De Luca M, Drobnjak I, Flitney DE, Niazy RK, Saunders J, Vickers J, Zhang Y, De Stefano N, Brady JM, Matthews PM (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23:208–219
Storch SA, Whitehurst GJ (2001) The role of family and home in the literacy development of children from low-income backgrounds. New Dir Child Adolesc Dev 2001:53–72
Storch SA, Whitehurst GJ (2002) Oral language and code-related precursors to reading: evidence from a longitudinal structural model. Dev Psychol 38:934–947
Tau GZ, Peterson BS (2010) Normal development of brain circuits. Neuropsychopharmacology 35:147–168. https://doi.org/10.1038/npp.2009.115
Thiebaut De Schotten M, Cohen L, Amemiya E, Braga LW, Dehaene S (2014) Learning to read improves the structure of the arcuate fasciculus. Cereb Cortex 24:989–995. https://doi.org/10.1093/cercor/bhs383
Tingley D, Yamamoto T, Hirose K, Keele L, Imai K (2014) Mediation: R package for causal mediation analysis. J Stat Softw 59:1–38
Tournier JD, Calamante F, Connelly A (2012) MRtrix: diffusion tractography in crossing fiber regions. Int J Imaging Syst Technol 22:53–66. https://doi.org/10.1002/ima.22005
Tournier JD, Calamante F, Gadian DG, Connelly A (2004) Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage 23:1176–1185. https://doi.org/10.1016/j.neuroimage.2004.07.037
Tournier JD, Smith R, Raffelt D, Tabbara R, Dhollander T, Pietsch M, Christiaens D, Jeurissen B, Yeh CH, Connelly A (2019) MRtrix3: a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 202:116137. https://doi.org/10.1016/j.neuroimage.2019.116137
Turesky T, Shama T, Kakon S, Haque R, Islam N, Someshwar A, Petri W, Nelson C, Gaab N (2021a) Brain morphometry and diminished physical growth in Bangladeshi children growing up in extreme poverty: a longitudinal study. Dev Cogn Neurosci 52:101029
Turesky TK, Vanderauwera J, Gaab N (2021b) Imaging the rapidly develo** brain: current challenges for MRI studies in the first five years of life. Dev Cogn Neurosci 47:100893. https://doi.org/10.1016/j.dcn.2020.100893
Tustison NJ, Avants BB, Cook PA, Zheng Y, Egan A, Yushkevich PA, Gee JC (2010) N4ITK: improved N3 bias correction. IEEE Trans Med Imaging 29:1310–1320. https://doi.org/10.1109/TMI.2010.2046908
van Bergen E, van der Leij A, de Jong PF (2014) The intergenerational multiple deficit model and the case of dyslexia. Front Hum Neurosci 8:1–13. https://doi.org/10.3389/fnhum.2014.00346
van Bergen E, Van Zuijen TL, Bishop D, de Jong PF (2016) Why are home literacy environment and children’s reading skills associated? What parental skills reveal. Read Res Q 52:147–160
Vanderauwera J, van Setten ERH, Maurits NM, Maassen BAM (2019) The interplay of socio-economic status represented by paternal educational level, white matter structure and reading. PLoS ONE 14:1–18. https://doi.org/10.1371/journal.pone.0215560
Veraart J, Fieremans E, Novikov DS (2016a) Diffusion MRI noise map** using random matrix theory. Magn Reson Med 76:1582–1593. https://doi.org/10.1002/mrm.26059
Veraart J, Novikov DS, Christiaens D, Ades-aron B, Sijbers J, Fieremans E (2016b) Denoising of diffusion MRI using random matrix theory. Neuroimage 142:394–406. https://doi.org/10.1016/j.neuroimage.2016.08.016
Wandell BA, Rauschecker AM, Yeatman JD (2012) Learning to see words. Annu Rev Psychol 63:31–53. https://doi.org/10.1146/annurev-psych-120710-100434
Wang Y, Mauer MV, Raney T, Peysakhovich B, Becker BLC, Sliva DD, Gaab N (2017) Development of tract-specific white matter pathways during early reading development in at-risk children and typical controls. Cereb Cortex 27:2469–2485. https://doi.org/10.1093/cercor/bhw095
Washington JA, Branum-Martin L, Sun C, Lee-James R (2018) The impact of dialect density on the growth of language and reading in African American children. Lang Speech Hear Serv Sch 49:232–247. https://doi.org/10.1044/2018_LSHSS-17-0063
Yagmurlu K, Middlebrooks EH, Tanriover N, Rhoton AL (2016) Fiber tracts of the dorsal language stream in the human brain. J Neurosurg 124:1396–1405. https://doi.org/10.3171/2015.5.JNS15455
Yeatman JD, Dougherty RF, Ben-Shachar M, Wandell BA (2012a) Development of white matter and reading skills. Proc Natl Acad Sci USA 109:E3045–E3053. https://doi.org/10.1073/pnas.1206792109
Yeatman JD, Dougherty RF, Myall NJ, Wandell BA, Feldman HM (2012b) Tract profiles of white matter properties: automating fiber-tract quantification. PLoS ONE. https://doi.org/10.1371/journal.pone.0049790
Zöllei L, Iglesias JE, Ou Y, Grant PE, Fischl B (2020) Infant FreeSurfer: an automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0–2 years. Neuroimage. https://doi.org/10.1016/j.neuroimage.2020.116946
Zuckerman B (2009) Promoting early literacy in pediatric practice: twenty years of reach out and read. Pediatrics 124:1660–1665
Zuk J, Dunstan J, Norton E, Yu X, Ozernov-Palchik O, Wang Y, Hogan TP, Gabrieli JDE, Gaab N (2021a) Multifactorial pathways facilitate resilience among kindergarteners at risk for dyslexia: a longitudinal behavioral and neuroimaging study. Dev Sci 24:1–18. https://doi.org/10.1111/desc.12983
Zuk J, Yu X, Sanfilippo J, Figuccio MJ, Dunstan J, Carruthers C, Sideridis G, Turesky TK, Gagoski B, Grant PE, Gaab N (2021b) White matter in infancy is prospectively associated with language outcomes in kindergarten. Dev Cogn Neurosci 50:100973. https://doi.org/10.1016/j.dcn.2021.100973
Acknowledgements
We would like to thank all participating families for their long-term dedication to this study. We are grateful for all additional members of the research team who contributed to data collection and quality control, especially Bryce Becker, Danielle Silva, Michael Figuccio, Doroteja Rubez, and Elizabeth Escalante, and Megan Loh. We also thank Carolyn King for her feedback on the manuscript.
Funding
This work was funded by NIH–NICHD R01 HD065762, the William Hearst Fund (Harvard University), and the Harvard Catalyst/NIH (5UL1RR025758) to N.G.; the Harvard Brain Initiative Transitions Program to T.K.T; the Ruth Taylor Research Fund (Queen’s University) to J.S.; and the Sackler Scholar Program in Psychobiology to J.Z.
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This study was approved by the Institutional Review Board of Boston Children’s Hospital (IRB-P00023182).
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Turesky, T.K., Sanfilippo, J., Zuk, J. et al. Home language and literacy environment and its relationship to socioeconomic status and white matter structure in infancy. Brain Struct Funct 227, 2633–2645 (2022). https://doi.org/10.1007/s00429-022-02560-4
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DOI: https://doi.org/10.1007/s00429-022-02560-4