EEGDash/ds000247

MEG-BIDS OMEGA RestingState_sample

Dataset ID: ds000247

Niso2018

Canonical aliases: OMEGA

At a glance: MEG · Resting State resting-state · healthy · 6 subjects · 10 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="ds000247", 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 OMEGA
ds = OMEGA(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/ds000247")

Dataset metadata

Subjects	6
Recordings	10
Tasks (count)	2
Channels	297 (×5), 330 (×3), 300 (×2)
Sampling rate (Hz)	2400 (×10)
Total duration (h)	1.0
Size on disk	10.3 GB
Recording type	MEG
Experimental modality	Resting State
Paradigm type	Resting-state
Population	Healthy
Source	openneuro
License	CC0
NEMAR citations	3.0

Links

• DOI: 10.18112/openneuro.ds000247.v1.0.2
• OpenNeuro: ds000247
• Browse 700+ datasets: EEGDash catalog
• Docs: https://eegdash.org
• Code: https://github.com/eegdash/EEGDash

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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.