EEGDash/ds007358

A subset of large-scale EEG dataset (India + Tanzania)

Dataset ID: ds007358

Vianney2026

Canonical aliases: Vianney2025

At a glance: EEG · Resting State resting-state · healthy · 2000 subjects · 6000 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="ds007358", 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 Vianney2025
ds = Vianney2025(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/ds007358")

Dataset metadata

Subjects	2000
Recordings	6000
Tasks (count)	3
Channels	62 (×2408), 60 (×833), 74 (×811), 72 (×770), 68 (×707), 50 (×216), 66 (×150), 56 (×63), 48 (×29), 44 (×6), 54 (×4), 65 (×3)
Sampling rate (Hz)	128 (×5733), 256 (×267)
Total duration (h)	276.1
Size on disk	16.1 GB
Recording type	EEG
Experimental modality	Resting State
Paradigm type	Resting-state
Population	Healthy
Source	openneuro
License	CC0

Links

• DOI: 10.18112/openneuro.ds007358.v1.0.0
• OpenNeuro: ds007358
• 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.