EEGDash/ds007463

Very-High-Density Diffuse Optical Tomography System Validation Dataset

Dataset ID: ds007463

Fogarty2026_Very

Canonical aliases: Fogarty2025

At a glance: FNIRS · Visual perception · healthy · 8 subjects · 88 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="ds007463", 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 Fogarty2025
ds = Fogarty2025(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/ds007463")

Dataset metadata

Subjects	8
Recordings	88
Tasks (count)	14
Channels	19086 (×14), 19426 (×11), 21518 (×11), 19620 (×11), 19528 (×11), 19908 (×10), 20218 (×10), 20874 (×10)
Sampling rate (Hz)	7.8125 (×88)
Total duration (h)	18.9
Size on disk	69.3 GB
Recording type	FNIRS
Experimental modality	Visual
Paradigm type	Perception
Population	Healthy
Source	openneuro
License	CC0

Links

• DOI: 10.18112/openneuro.ds007463.v1.1.1
• OpenNeuro: ds007463
• Browse 700+ datasets: EEGDash catalog
• Docs: https://eegdash.org
• Code: https://github.com/eegdash/EEGDash

---

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.