A large-scale investigation of white matter microstructural associations with reading ability.

Neuroimage

Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, 43 Vassar Street, Bldg. 46, Room 4033 Cambridge, MA, 02139, USA. Electronic address:

Published: April 2022

Reading involves the functioning of a widely distributed brain network, and white matter tracts are responsible for transmitting information between constituent network nodes. Several studies have analyzed fiber bundle microstructural properties to shed insights into the neural basis of reading abilities and disabilities. Findings have been inconsistent, potentially due to small sample sizes and varying methodology. To address this, we analyzed a large data set of 686 children ages 5-18 using state-of-the-art neuroimaging acquisitions and processing techniques. We searched for associations between fractional anisotropy (FA) and single-word and single-nonword reading skills in children with diverse reading abilities across multiple tracts previously thought to contribute to reading. We also looked for group differences in tract FA between typically reading children and children with reading disabilities. FA of the white matter increased with age across all participants. There were no significant correlations between overall reading abilities and tract FAs across all children, and no significant group differences in tract FA between children with and without reading disabilities. There were associations between FA and nonword reading ability in older children (ages 9 and above). Higher FA in the right superior longitudinal fasciculus (SLF) and left inferior cerebellar peduncle (ICP) correlated with better nonword reading skills. These results suggest that letter-sound correspondence skills, as measured by nonword reading, are associated with greater white matter coherence among older children in these two tracts, as indexed by higher FA.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8919267PMC
http://dx.doi.org/10.1016/j.neuroimage.2022.118909DOI Listing

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