| Article Title En | Iranian 6-11 years age population-based EEG, ERP, and cognition dataset |
|---|---|
| Authors | , Mohammad Ali Nazari, Sevda Abbasi, Maryam Rezaeian, Soomaayeh Heysieattalab, Farhad Farkhondeh Tale Navi |
| Journal | Scientific Data |
| Paper Type | Full Paper |
| Published At | 2025/2/22 |
| Journal Grade | ISI |
| Journal Type | Typographic |
| Journal Country | United Kingdom |
Abstract
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.