EEGDash/ds004850

ODE

Dataset ID: ds004850

Johnson2023_ODE

Canonical aliases: Johnson2024

At a glance: EEG · Unknown memory · unknown · 1 subjects · 1 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="ds004850", 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 Johnson2024
ds = Johnson2024(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/ds004850")

Dataset metadata

Subjects	1
Recordings	1
Tasks (count)	1
Channels	64 (×1)
Sampling rate (Hz)	128 (×1)
Total duration (h)	0.5
Size on disk	79.2 MB
Recording type	EEG
Experimental modality	Unknown
Paradigm type	Memory
Population	Unknown
BIDS version	1.8.0
Source	openneuro
License	CC0
NEMAR citations	0

Tasks

• nback

Upstream README

Verbatim from the dataset's authors — the canonical description.

ODE dataset This is a placeholder dataset.

People

Authors

• Tony Johnson
• Stephen Gordon
• Jon Touryan
• Kevin King (senior)

Contact

• Kevin King

Links

• DOI: 10.18112/openneuro.ds004850.v1.0.0
• OpenNeuro: ds004850
• Browse 700+ datasets: EEGDash catalog
• Docs: https://eegdash.org
• Code: https://github.com/eegdash/EEGDash

Provenance

• Backend: s3 — s3://openneuro.org/ds004850
• Exact size: 83,056,630 bytes (79.2 MB)
• Ingested: 2026-04-06
• Stats computed: 2026-04-04

---

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.