Overview

The Healthy Brain Network (HBN) EEG dataset represents one of the largest open-access developmental neuroimaging initiatives, with 3,602 participants aged 5-22 years across 11 dataset releases. This dashboard provides comprehensive insights into participant demographics, mental health patterns, and data availability to help researchers understand and utilize this valuable resource.

This dashboard complements our other HBN content:

  • 📄 HBN-EEG Research Paper - Read about the FAIR implementation and BIDS formatting of the HBN dataset, including methodology and validation
  • 📊 HBN-EEG Dataset Downloads - Access the complete dataset releases, example data, and technical documentation for all 11 releases

Each resource addresses a different aspect of the HBN-EEG dataset: the paper details the scientific methodology, the data portal provides access to downloads and technical specs, and this dashboard enables data exploration.

3,602
Total Participants
11
Dataset Releases
5-22
Age Range (years)
13
EEG Task Paradigms
Age Distribution
Sex Distribution
EEG Task Data Availability
Mental Health Metrics Correlation
Mental Health Patterns by Age Group

Release-Specific Analysis

-
Total Participants
-
Gender Distribution
-
Age Range (years)

Task Status Distribution

Data Status Categories

Available: Data and event markers available, passes quality checks
Caution: Data exists but may have quality issues, look for quality reports.
Unavailable: Task is not available.
No Event: Task is available but no event markers were found.

Key Insights

Demographics & Development

  • Age Distribution: The dataset shows a robust developmental span with peak representation in middle childhood (6-10 years), providing excellent coverage for studying developmental trajectories
  • Sex Balance: 64.1% male, 35.9% female participants, reflecting typical recruitment patterns in neurodevelopmental research
  • Developmental Coverage: Strong representation across critical developmental periods from early childhood through early adulthood

Mental Health Patterns

  • Correlation Structure: Mental health metrics show expected patterns - p-factor correlates positively with both internalizing (r=0.16) and externalizing (r=0.22) behaviors
  • Developmental Trends: Internalizing symptoms increase markedly with age, from -0.23 in early childhood to 0.52 in late adolescence/early adulthood
  • Age-Related Changes: Externalizing behaviors peak in early childhood (0.26) and decrease with age, while attention difficulties remain relatively stable

Data Quality & Availability

  • High-Quality Core Tasks: RestingState (86.3%) and movie-watching tasks (70-82%) show excellent data availability
  • Challenging Paradigms: Sequence learning tasks show lower completion rates (22-40%), likely due to age-appropriateness and task difficulty
  • Task Categorization: Passive viewing tasks generally show higher completion rates than active cognitive tasks

Research Implications

  • Large-Scale Analyses: With 3,547 participants having complete mental health data, the dataset supports robust statistical analyses and machine learning approaches
  • Cross-Task Studies: High availability of core tasks enables comprehensive cross-paradigm analyses
  • Developmental Studies: Excellent age coverage supports both cross-sectional and cohort-based developmental research

Technical Notes

This dashboard visualizes comprehensive analysis of the HBN master participants dataset. Data processing included:

  • Age group categorization for developmental analysis
  • Task availability rate calculations across all paradigms
  • Mental health correlation analysis with 3,547 complete cases
  • Quality control metrics based on data availability flags

For detailed dataset information and download links, visit the HBN-EEG data page .

Data Source: HBN Master Participants List (Releases 1-11)
Analysis Date: January 2024
Sample Size: 3,602 participants
Mental Health Sample: 3,547 participants with complete data