metadata
pretty_name: Healthy Brain Network (HBN) EEG - Release 9 (BDF Converted)
license: cc-by-sa-4.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- visual
- clinical-intervention
- development
size_categories:
- n<1K
task_categories:
- other
Healthy Brain Network (HBN) EEG - Release 9 (BDF Converted)
Dataset ID: eeg2025r9mini
Shirazi2024_R9_bdf_mini
Canonical aliases: HBN_r9_bdf_mini
At a glance: EEG · Visual clinical/intervention · development · 20 subjects · 237 recordings · CC-BY-SA 4.0
Load this dataset
This repo is a pointer. The raw EEG data lives at its canonical source (OpenNeuro / NEMAR); EEGDash streams it on demand and returns a PyTorch / braindecode dataset.
# pip install eegdash
from eegdash import EEGDashDataset
ds = EEGDashDataset(dataset="eeg2025r9mini", cache_dir="./cache")
print(len(ds), "recordings")
You can also load it by canonical alias — these are registered classes in eegdash.dataset:
from eegdash.dataset import HBN_r9_bdf_mini
ds = HBN_r9_bdf_mini(cache_dir="./cache")
If the dataset has been mirrored to the HF Hub in braindecode's Zarr layout, you can also pull it directly:
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/eeg2025r9mini")
Dataset metadata
| Subjects | 20 |
| Recordings | 237 |
| Tasks (count) | 10 |
| Channels | 129 (×237) |
| Sampling rate (Hz) | 100 (×237) |
| Size on disk | 3.0 GB |
| Recording type | EEG |
| Experimental modality | Visual |
| Paradigm type | Clinical/Intervention |
| Population | Development |
| Source | nemar |
| License | CC-BY-SA 4.0 |
Links
- DOI: 10.18112/openneuro.ds005514.v1.0.1
- NEMAR: eeg2025r9mini
- Browse 700+ datasets: EEGDash catalog
- Docs: https://eegdash.org
- Code: https://github.com/eegdash/EEGDash
Auto-generated from dataset_summary.csv and the EEGDash API. Do not edit this file by hand — update the upstream source and re-run scripts/push_metadata_stubs.py.