metadata
pretty_name: Logical reasoning study
license: cc0-1.0
tags:
- meg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- unknown
- decision-making
size_categories:
- n<1K
task_categories:
- other
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
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.