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Mainsah2025-Q
Dataset ID: nm000321
Mainsah2025_Q
At a glance: EEG · Visual clinical/intervention · other · 36 subjects · 360 recordings · CC-BY-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="nm000321", 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/nm000321")
Dataset metadata
| Subjects | 36 |
| Recordings | 360 |
| Tasks (count) | 1 |
| Channels | 32 (×360) |
| Sampling rate (Hz) | 256.0000930697907 (×208), 256.00008203487505 (×52), 256 (×43), 256.00010076264726 (×16), 256.0001098418278 (×12), 256.00012071918457 (×12), 256.0001184842897 (×7), 256.00008886963377 (×4), 256.00009694678226 (×3), 256.00010663894057 (×3) |
| Total duration (h) | 13.1 |
| Size on disk | 1.1 GB |
| Recording type | EEG |
| Experimental modality | Visual |
| Paradigm type | Clinical/Intervention |
| Population | Other |
| Source | nemar |
| License | CC-BY-4.0 |
Links
- DOI: 10.13026/0byy-ry86
- NEMAR: nm000321
- 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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