White matter in infancy is prospectively associated with language outcome in kindergarten

Abstract

Language acquisition is of central importance to a child's development. Although the trajectory of acquisition is shaped by input and experience postnatally, the neural basis for language emerges prenatally. Thus a fundamental question remains unexamined: to what extent may the structural foundations for language established in infancy predict long-term language abilities? In this longitudinal neuroimaging investigation of children from infancy to kindergarten, we find that white matter organization in infancy is prospectively associated with subsequent language abilities, specifically between: (i) the left arcuate fasciculus in infancy and subsequent phonological awareness and vocabulary knowledge, and (ii) the left corticospinal tract in infancy and phonological awareness and phonological memory in kindergarten. Results are independent of age and home literacy environment. These findings directly link white matter organization in infancy with language abilities after school entry, and suggest that structural organization in infancy sets an important foundation for subsequent language development.

Multimodal brain features at preschool age and the relationship with pre-reading measures one year later: an exploratory study

“…Our multiparametric analysis approach demonstrated that children aged 3.5 with a relatively more mature SLF coinciding with cortical features of the angular gyrus, thalamus, fusiform gyrus, middle temporal regions, and the dorsolateral prefrontal cortex are associated with better pre-reading skills at 4.5 years of age. Though this finding would not survive FDR correction, this association between the SLF and pre-reading measures is consistent with recent findings that the microstructure of the arcuate fasciculus (a sub-section of the SLF) during infancy is associated with phonological awareness skills (Woodcock Johnson Oral Language Assessment) and vocabulary knowledge (Peabody Picture Vocabulary Test -IV) in Kindergarten (Zuk et al, 2019). The SLF, including the arcuate fasciculus, supports communication between specific regions and networks in the brain and is related to pre-reading skills.…”

“…Children aged 6-7 years who subsequently received a diagnosis of dyslexia had reduced cortical thickness in left hemisphere reading-related regions compared to children who did not eventually receive a diagnosis (Clark et al, 2014). While neuroimaging studies have identified isolated imaging measures associated with reading ability in school-age children, the neurobiological development underlying the development of reading skills may begin earlier in life (Zuk et al, 2019). Even before formal reading education, the development of language and pre-reading skills are supported by the developing structural and functional architecture of the brain.…”

“…In general, children with higher reading proficiency show faster development of reading-related brain regions than children with poor reading skills (Yeatman et al, 2012b; Wang et al, 2017; Reynolds et al, 2019b). While there are few longitudinal studies focused on reading and language development during the pre-school period, one recent study reports that infant arcuate fasciculus and corticospinal tract microstructure predicts phonological processing and vocabulary at 5 years of age (Zuk et al, 2019). These studies suggest associations between early brain structure or function and the development of reading skills in children, but how multimodal neurobiological features underlie pre-reading measures in preschool aged children, before formal reading education, is still not well-understood.…”

Neurobiological predispositions for musicality: White matter in infancy predicts school‐age music aptitude

“…ac.uk/fsl; Basser et al, 1994;Langer et al, 2017;Smith et al, 2004;Zuk et al, 2021). Diffusion-weighted images were subsequently processed with the VISTALab mrDiffusion toolbox and diffusion MRI software suite (www.vistalab.com), which included tensor-fitting estimations with a linear least-squares (LS) fit for diffusion tensor fitting.…”

“…White matter pathways were quantified utilizing the Automated Fiber Quantification (AFQ) software package (https://github.com/jyeatman/ AFQ; Yeatman et al, 2012). Procedures employed follow those previously described in prior investigations with infants with the present research team (Langer et al, 2017;Zuk et al, 2021). In summary, whole-brain tractography was conducted via a deterministic streamline tracking algorithm (Basser et al, 1994;Mori et al, 1999), with an FA threshold of 0.1 and angle threshold of 40 • (in accordance with previous investigations with this age range (Langer et al, 2017;Zuk et al, 2021)).…”