dataset_id stringclasses 1
value | title stringclasses 1
value | source stringclasses 1
value | source_url stringclasses 1
value | doi stringclasses 1
value | license stringclasses 1
value | loader dict | catalog stringclasses 1
value | generated_by stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|
ds005752 | The NIMH Healthy Research Volunteer Dataset | openneuro | https://openneuro.org/datasets/ds005752 | 10.18112/openneuro.ds005752.v2.1.0 | CC0 | {
"library": "eegdash",
"class": "EEGDashDataset",
"kwargs": {
"dataset": "ds005752"
}
} | https://huggingface.co/spaces/EEGDash/catalog | huggingface-space/scripts/push_metadata_stubs.py |
The NIMH Healthy Research Volunteer Dataset
Dataset ID: ds005752
Nugent2024
At a glance: MEG · Multisensory other · healthy · 123 subjects · 1055 recordings · CC0
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="ds005752", cache_dir="./cache")
print(len(ds), "recordings")
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/ds005752")
Dataset metadata
| Subjects | 123 |
| Recordings | 1055 |
| Tasks (count) | 10 |
| Channels | 305 (×240), 306 (×183), 304 (×123), 302 (×117), 303 (×110), 301 (×71), 382 (×59), 300 (×57), 378 (×20), 377 (×16), 379 (×16), 381 (×15), 380 (×15), 299 (×3), 387 (×1), 388 (×1) |
| Sampling rate (Hz) | 1200 (×926), 4800 (×121) |
| Total duration (h) | 102.6 |
| Size on disk | 662.7 GB |
| Recording type | MEG |
| Experimental modality | Multisensory |
| Paradigm type | Other |
| Population | Healthy |
| Source | openneuro |
| License | CC0 |
Links
- DOI: 10.18112/openneuro.ds005752.v2.1.0
- OpenNeuro: ds005752
- 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.
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