Emerging technologies and neuroscience-based approaches in dyslexia: a narrative review toward integrative and personalized solutions.

BACKGROUND

Developmental dyslexia is a common neurodevelopmental disorder that impairs reading ability despite adequate intelligence and education, affecting up to 17% of children worldwide. Advances in neuroscience have revealed complex mechanisms involving phonological, visual, and temporal processing, with cross-linguistic variability. At the same time, technological innovation is driving a shift toward AI-powered diagnostics, immersive learning tools, and neurostimulation-based interventions.

METHODS

This narrative review synthesizes evidence from recent research published between 2015 and 2025, focusing on four thematic areas: (1) neurobiological underpinnings of dyslexia, (2) diagnostic innovations using AI and eye- or handwriting-based deep learning, (3) neurostimulation and immersive VR/AR interventions, and (4) policy, equity, and ethical considerations. Studies were identified through major academic databases and thematically analyzed to highlight trends, strengths, and limitations.

RESULTS

AI-based diagnostic tools using eye-tracking and handwriting features have achieved reported accuracies exceeding 80% in multiple pilot studies. VR/game-based programs and neurostimulation interventions (TMS, tDCS) have shown promising short-term effects on reading fluency and phonological processing, though evidence for long-term literacy transfer remains limited. Across studies, methodological heterogeneity and small sample sizes constrain generalizability. Significant disparities in access persist across socioeconomic, linguistic, and geographic contexts.

CONCLUSIONS

While these technologies offer promising avenues for more personalized and scalable dyslexia care, their integration must be accompanied by stronger evidence, ethical safeguards, and equity-focused policies. Technology should augment, not replace, human interaction in inclusive education. Future research should prioritize larger trials, cross-linguistic validation, and sustainable implementation strategies.