Reading in childhood: Does it shape the adult brain?
Overview
Reading is a cognitive activity that recruits and tunes brain circuitry connecting primary- and language-processing regions. This project investigated whether metrics of the brain’s physical structure correlate with reading and cognitive performance and whether the frequency of childhood reading influences brain-reading associations.
Utilising a longitudinal dataset from Generation Scotland, the study examined measures of cortical surface area (CSA) and cortical thickness (CT) via a surface-based vertex-wise approach, alongside diffusion tensor imaging (DTI) to map critical white matter tracts in left temporo-parietal and caudal inferior frontal/precentral regions.
Building on prior evidence linking adult phonological decoding, word decoding, and print exposure to localised structural variations (e.g., left superior temporal sulcus, right superior temporal gyrus, and left supramarginal gyrus), the study tested whether adult brain structures reflect early childhood reading abilities or require prolonged reading engagement to consolidate.
Core Findings
The results demonstrate that reading performance correlates with four distinct structural measures within the reading network—highlighting the contribution of total left CSA and left superior temporal gyrus CSA in particular—with childhood reading frequency partially mediating these brain-behaviour relationships.
This work offers foundational insights into the subtle, complex interplay between cognitive acquisition, environmental print exposure, and long-term cortical development across diverse socioeconomic backgrounds.
Reflection
Working on this longitudinal dyslexia dataset was a humbling yet transformative experience that reshaped my approach to cognitive neuroscience. This project taught me that compelling research requires an honest balance between conceptual novelty and computational feasibility.
At the time, wrestling with high-dimensional, data-driven pipelines pushed the boundaries of my analytical skills, revealing just how profoundly different methodologies—even when addressing the exact same core topic like dyslexia—can transform the research process. It was this realisation that inspired my commitment to mastering advanced statistical modelling and computational pipelines. It’s where the rubber meets the road!
References
- Johns, C. L., Jahn, A. A., Jones, H. R., Kush, D., Molfese, P. J., Van Dyke, J. A., … & Braze, D. (2018). Individual differences in decoding skill, print exposure, and cortical structure in young adults. Language, Cognition and Neuroscience, 33(10), 1275-1295.
- Taubert, M., Villringer, A., & Ragert, P. (2012). Learning-related gray and white matter changes in humans: an update. The Neuroscientist, 18(4), 320-325.
- Myers, C. A., Vandermosten, M., Farris, E. A., Hancock, R., Gimenez, P., Black, J. M., … & Hoeft, F. (2014). White matter morphometric changes uniquely predict children’s reading acquisition. Psychological science, 25(10), 1870-1883.