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Exploring short-term neurobehavioral trajectories of audiovisual learning in prereaders as early predictors of reading development
Poster Session F, Friday, October 2, 2:45 - 4:45 pm, Wangari Maathai
Chiara Turri1, Fiona Borská1, Bob Kapteijns1, Jurgen Tijms2, Marjolein Tool1, Rogier Kievit3, Milene Bonte1; 1Maastricht University, 2University of Amsterdam, 3Radboud University
Developmental dyslexia is typically diagnosed at 8–9 years of age, following persistent difficulties in learning to read despite extensive instruction, often negatively affecting motivation and emotional well-being. Early prediction of reading difficulties currently relies on risk indicators such as familial risk of dyslexia and static tests of reading precursors, including phonemic awareness, rapid automatized naming, and letter knowledge. However, traditional static indicators often lead to over-identification of at-risk children and have limited predictive accuracy due to their sensitivity to contextual variables, such as motivation, home literacy environment, and socioeconomic background. This calls for novel screening measures that trace rapid changes during learning rather than taking snapshots of children’s pre-existing knowledge. The present longitudinal EEG study explores individual trajectories of short-term audiovisual learning in pre-readers with (FRD+) and without (FRD-) familial risk of dyslexia as dynamic early predictors of reading development. At baseline (currently N=72, data collection ongoing), we used growth curve modeling to characterize children’s behavioral (accuracy) and neural (ERP) trajectories during a ~ 20-minute Letter/symbol - Speech Sound (LSS) learning task. Preliminary results suggest three different clusters of low, mid, and high learners based on accuracy trajectories, and no performance difference between FRD+ and FRD-. With learning, we observe a significant linear decrease in ERP amplitude in areas associated with letter - speech sound couplings (i.e., bilateral frontotemporal and right temporoparietal sites), suggesting that recognizing the letter-sound pairs requires progressively less effort. Additionally, we measured static reading precursors, which show significantly lower scores for FRD+ on phonological tests. In the first follow-up measurement (currently N=45, data collection ongoing), we are assessing reading abilities and tracking reading-related neural changes in the same cohort of children at the end of their first year of formal reading instruction. Preliminary findings show that, after taking into account static reading precursors and familial risk of dyslexia, the intercept and slope parameters extracted from children’s LSS learning accuracy trajectory account for significant additional variance in reading performance. This indicates that higher initial accuracy of LSS matching and a less steep learning rate in the rest of the LSS task at baseline are predictive of more automatized reading one year later. The inclusion of the slope of the ERP trajectory over right temporoparietal sites further increases the variance explained by the model, with a slower decrease in amplitude associated with better reading outcomes. In further analyses, we will test whether these neurobehavioral trajectories are predictive of the level of cortical specialization for (1) visual word recognition and (2) mapping Dutch letter-speech sound pairs, measured with the EEG. Together, our results will provide new insights into the characterization of individual differences in reading acquisition at behavioral and neural levels. In this way, our study aims to contribute to designing more sensitive and reliable screening tools for early detection of reading difficulties and to building longitudinal risk models of (a)typical inter-individual variability in learning across development.
Topic Areas: Disorders: Developmental, Reading