README
The HBN-EEG Dataset
This is Release 9 of HBN-EEG, the EEG and (soon-released) Eye-Tracking Section of the Child Mind Network Healthy Brain Network (HBN) Project, curated into the Brain Imaging Data Structure (BIDS) format. This dataset is part of a larger initiative to advance the understanding of child and adolescent mental health through collecting and analyzing neuroimaging, behavioral, and genetic data (Alexander et al., Sci Data 2017).
Data Description
This dataset comprises electroencephalogram (EEG) data and behavioral responses collected during EEG experiments from participants involved in the HBN project.
Contents
- EEG Data: High-resolution EEG recordings capture a wide range of neural activity during various tasks.
- Behavioral Responses: Participant responses during EEG tasks, including reaction times and accuracy. This data was originally recorded within the behavior directory of the HBN data. The data is now included with the EEG data within the
_events.tsv
files.
Special Features
- Hierarchical Event Descriptors (HED): Events, including the original EEG events and the included behavioral events, have clear explanations, including proper HED annotation suitable for systematic meta and mega analysis of the data.
- P-Factor, Attention, Internalization and Externalization: Derived from the CBCL questionnaire, these factors provide valuable insights into the psychopathology of the participants, adding a rich layer of interpretation to the EEG and behavioral data.
- Data quality and availability: We performed minimal quality control to ensure that the data was not corrupted, each task had its necessary events, and was ready for preprocessing. The results of this quality control are available in the
participants.tsv
file.
- Future Releases: We are committed to enhancing this dataset with additional, valuable features in its next stages, including:
- Personalized EEG Electrode Locations: To offer more detailed insights into individual neural activity patterns.
- Personalized Lead Field Matrix: Enabling better understanding and interpretation of EEG data.
- Eye-Tracking Data: Providing a window into the visual attention and processing mechanisms during EEG experiments.
Copyright and License
This dataset is licensed under the Creative Commons Attribution 4.0 International License (CC BY SA 4.0). Please cite the original HBN publication (https://dx.doi.org/10.1038/sdata.2017.181) as well as the dataset paper (https://doi.org/10.1101/2024.10.03.615261).
Acknowledgments
We would like to express our gratitude to all participants and their families, whose contributions have made this project possible. We also thank our dedicated team of researchers and clinicians for their efforts in collecting, processing, and curating this data.