Datasets:

EEGDash
/

ds004859

pretty_name: iEEG on children during Stroop task
license: cc0-1.0
tags:
  - ieeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - visual
  - attention
  - stroop
size_categories:
  - n<1K
task_categories:
  - other
authors:
  - Kazuki Sakakura
  - Eishi Asano

iEEG on children during Stroop task

Dataset ID: ds004859

Sakakura2023_children_Stroop

Canonical aliases: Sakakura2024

At a glance: IEEG · Visual attention · unknown · 7 subjects · 9 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="ds004859", 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 Sakakura2024
ds = Sakakura2024(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/ds004859")

Dataset metadata


Subjects	7
Age range	10–17 yrs, mean 15.1
Recordings	9
Tasks (count)	1
Sessions	2
Channels	128 (×8), 108 (×1)
Sampling rate (Hz)	1000 (×9)
Total duration (h)	2.7
Size on disk	2.3 GB
Recording type	IEEG
Experimental modality	Visual
Paradigm type	Attention
Population	Unknown
BIDS version	1.7.0
Source	openneuro
License	CC0
NEMAR citations	0

Tasks

stroop

People

Authors

Kazuki Sakakura
Eishi Asano (senior)

Contact

Kaz Sakakura

Funding

Provenance

Backend: s3 — s3://openneuro.org/ds004859
Exact size: 2,435,511,071 bytes (2.3 GB)
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.