Bayesian and Computational Modeling of Dyslexia in Mono- and Bilingual Children
Bayesian Modeling
Dual-Route
Dyslexia
Bilingualism
Overview
This project develops Bayesian and computational models of dyslexia to refine subtyping, capture cross-linguistic variability, and improve prediction of reading outcomes in mono- and bilingual children.
What we do
We combine Bayesian inference with dual-route computational models to represent individual variability and uncertainty, and to separate language-specific effects from domain-general constraints across orthographies.
Key components
- Bayesian modeling of reading mechanisms and individual differences
- Dual-route frameworks for word reading and spelling
- Cross-linguistic and bilingual modeling of dyslexia profiles
- Predictive models of reading ability and developmental trajectories