Datasets:

Dataset Viewer
Auto-converted to Parquet Duplicate
dataset_id
stringclasses
1 value
title
stringclasses
1 value
source
stringclasses
1 value
source_url
stringclasses
1 value
doi
stringclasses
1 value
license
stringclasses
1 value
loader
dict
catalog
stringclasses
1 value
generated_by
stringclasses
1 value
ds006720
Alpha power indexes working memory load for durations
openneuro
https://openneuro.org/datasets/ds006720
10.18112/openneuro.ds006720.v1.0.0
CC0
{ "library": "eegdash", "class": "EEGDashDataset", "kwargs": { "dataset": "ds006720" } }
https://huggingface.co/spaces/EEGDash/catalog
huggingface-space/scripts/push_metadata_stubs.py

Alpha power indexes working memory load for durations

Dataset ID: ds006720

Herbst2025

At a glance: MEG · Auditory memory · healthy · 24 subjects · 246 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="ds006720", cache_dir="./cache")
print(len(ds), "recordings")

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/ds006720")

Dataset metadata

Subjects 24
Recordings 246
Tasks (count) 3
Channels 328 (×209), 321 (×11), 340 (×2), 390 (×1)
Sampling rate (Hz) 1000 (×222), 2000 (×1)
Total duration (h) 30.7
Size on disk 136.5 GB
Recording type MEG
Experimental modality Auditory
Paradigm type Memory
Population Healthy
Source openneuro
License CC0

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.

Downloads last month
40