EEGDash/ds005261

Gloups_MEG

Dataset ID: ds005261

Todorovic2024

Canonical aliases: Todorovic2023

At a glance: MEG · Unknown learning · healthy · 17 subjects · 128 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="ds005261", 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 Todorovic2023
ds = Todorovic2023(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/ds005261")

Dataset metadata

Subjects	17
Recordings	128
Tasks (count)	2
Channels	248 (×71), 278 (×31), 245 (×24)
Sampling rate (Hz)	2034.5100996195154 (×31), 2034.5101318359375 (×7)
Total duration (h)	3.0
Size on disk	137.2 GB
Recording type	MEG
Experimental modality	Unknown
Paradigm type	Learning
Population	Healthy
Source	openneuro
License	CC0
NEMAR citations	0.0

Links

• DOI: 10.18112/openneuro.ds005261.v3.0.0
• OpenNeuro: ds005261
• 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.