Datasets:

eeg2025r9mini / README.md
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Metadata stub for eeg2025r9mini
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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


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.