ArticleHuman brain mapping2023
White matter brain structure predicts language performance and learning success.
Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Structure-function dynamics in healthy cognitive aging: a graph signal processing approach.Brain structure & function · 2026Article
- Microglia Pyroptosis-Derived IL-18 Drives White Matter Injury in Developing Brain following Hypothermic Hypoxia-Ischemia.Neuroscience bulletin · 2026Article
- Persistent neuroimmune alterations in children who are HIV-exposed but uninfected at age 6-7 years: Associations with language development in a South African birth cohort.bioRxiv : the preprint server for biology · 2026Article
- Age-Dependent Process Governs Executive Function Disability in Autistic Children.Journal of autism and developmental disorders · 2025Article
- TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.Medical image analysis · 2024Article
- White matter plasticity during second language learning within and across hemispheres.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- A longitudinal resource for population neuroscience of school-age children and adolescents in China.Scientific data · 2023Article
- Article
- White matter brain structure predicts language performance and learning success.Human brain mapping · 2023Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Individual differences in the ability to process language have long been discussed. Much of the neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants' native language as well as the improvement thereof by multiday training. We identified specific network motifs by singular value decomposition that indeed related white matter structural connectivity to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance, suggesting an anatomical predisposition for the individual ability to process syntactically complex sentences. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brain's white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.
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