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<p>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.</p>

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Iranian 6-11 years age population-based EEG, ERP, and cognition dataset

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月22日

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  • Mohammad Ali Nazari,
  • Sevda Abbasi,
  • Maryam Rezaeian,
  • Soomaayeh Heysieattalab,
  • Hosein Safakheil,
  • Ali Motie Nasrabadi,
  • Zeynab Barzegar,
  • Mohammad Taghi Joghataei,
  • Zohreh Asgharian,
  • Farshid Ghobadzadeh,
  • Mohammadreza Alizadeh,
  • Parvin Amini Yeganeh,
  • Ayda Khayyat Naghadehi,
  • Kiana Azizi,
  • Mahdieh Alizadeh Chakharlou,
  • AmirHossein Nasiri,
  • Mohsen Davoudkhani,
  • Mohsen Rezaeian,
  • Mohsen Safakheil,
  • Amirreza Katebi,
  • Masoumeh Hasanzadeh Tahraband,
  • Sahar Delkhahi,
  • Haniyeh Soltani,
  • Vajihe Shahrabi Farahani,
  • Kimia Ghasemkhani,
  • Erfan Nazari,
  • Farhad Farkhondeh Tale Navi

摘要

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.