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ds003633
ForrestGump-MEG
openneuro
https://openneuro.org/datasets/ds003633
10.18112/openneuro.ds003633.v1.0.3
CC0
{ "library": "eegdash", "class": "EEGDashDataset", "kwargs": { "dataset": "ds003633" } }
https://huggingface.co/spaces/EEGDash/catalog
huggingface-space/scripts/push_metadata_stubs.py

ForrestGump-MEG

Dataset ID: ds003633

Liu2021

Canonical aliases: ForrestGump_MEG

At a glance: MEG · Multisensory perception · healthy · 12 subjects · 96 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="ds003633", 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 ForrestGump_MEG
ds = ForrestGump_MEG(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/ds003633")

Dataset metadata

Subjects 12
Recordings 96
Tasks (count) 2
Channels 409 (×89), 378 (×7)
Sampling rate (Hz) 600 (×89), 1200 (×7)
Total duration (h) 22.0
Size on disk 73.5 GB
Recording type MEG
Experimental modality Multisensory
Paradigm type Perception
Population Healthy
Source openneuro
License CC0
NEMAR citations 1.0

Links


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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