Uncovering neurobiology of transdiagnostic oral language development

Objective

Understanding and producing language are uniquely human abilities that rely on distributed neural networks and develop over many years. Language disorders including developmental dyslexia and Developmental Language Disorder (DLD) disrupt these processes in distinct ways: dyslexia primarily affects phonological processing and decoding, while DLD impairs broader oral language skills, including grammar across comprehension and production. Both disorders are multifactorial and overlapping, sharing deficits in reading/writing and vocabulary, yet their neural bases remain poorly understood. Most neuroimaging studies investigate only one disorder, overlooking comorbidities and the influence of bilingualism. Bilingual children display individual language profiles, currently leading to being over- and under-identified for DLD or dyslexia services. In this project, we will recruit 120 Basque-Spanish bilingual children aged 8 to 10 years, spanning DLD (N=40), dyslexia (N=40), comorbid DLD+dyslexia (N=20), and controls (N=20). Exclusion criteria include other neurodevelopmental disorders and low nonverbal IQ. Multimodal MRI will capture structural and functional neural profiles, which we will analyze to: (1) test hypothesis-driven predictions based on diagnostic categories while controlling for bilingual experience; (2) apply machine learning to identify multivariate brain-behavior relationships; and (3) adopt a transdiagnostic approach to examine variability in neural and behavioral profiles independent of diagnostic labels. The Uncovering Neurobiology of Transdiagnostic Oral Language Development (UNTOLD) project enables direct comparison across disorders, disentangling shared and disorder-specific neural mechanisms while explicitly incorporating bilingualism as a core factor. Findings will inform development of improved screening tools and personalized interventions tailored to individual neural profiles, with particular relevance for bilingual populations.