This report presents an open-source dataset investigating neurodevelopmental profiles in children. The dataset consists of EEG, ERP, and cognitive assessments from 100 Iranian non-clinical participants (age range 6-11 years, Mean = 8.52 ± 1.5 SD). Notably, this is a smaller group drawn from a larger longitudinal ongoing study. The research aligns with the Research Domain Criteria (RDoC) framework, aiming to enhance diagnostic precision and intervention efficacy for specific learning disabilities (SLD) using EEG/ERP measures and machine learning. Cognitive assessments included non-verbal intelligence (Raven Test), attention (IVA-2), and working memory tasks. EEG recordings captured resting-state (eyes closed/open) and brain activity during working memory tasks with numerical and non-numerical stimuli (ERPs). Additionally, demographic information such as age, gender, education, handedness, parental history of learning difficulties, and child symptom inventory-4 (CSI-4) were collected. This dataset provides a valuable resource for exploring the neurophysiological correlates of cognitive functions in typically developing children, which can advance our understanding of the neural foundations of cognitive development in children.
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| http://dx.doi.org/10.1038/s41597-025-04624-6 | DOI Listing |
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