EEGDash/ds003483

Logical reasoning study

Dataset ID: ds003483

Cognitive2021

Canonical aliases: Maestu2021

At a glance: MEG · Unknown decision-making · healthy · 21 subjects · 41 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="ds003483", 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 Maestu2021
ds = Maestu2021(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/ds003483")

Dataset metadata

Subjects	21
Recordings	41
Tasks (count)	2
Channels	320 (×41)
Sampling rate (Hz)	1000 (×41)
Total duration (h)	11.0
Size on disk	24.5 GB
Recording type	MEG
Experimental modality	Unknown
Paradigm type	Decision-making
Population	Healthy
Source	openneuro
License	CC0
NEMAR citations	3.0

Links

• DOI: 10.18112/openneuro.ds003483.v1.0.2
• OpenNeuro: ds003483
• 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.