EEGDash/ds004370

PRIOS

Dataset ID: ds004370

Blooijs2022_PRIOS

Canonical aliases: PRIOS

At a glance: IEEG · Anesthesia clinical/intervention · surgery · 7 subjects · 15 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="ds004370", 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 PRIOS
ds = PRIOS(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/ds004370")

Dataset metadata

Subjects	7
Recordings	15
Tasks (count)	2
Channels	133 (×7), 68 (×6), 64 (×2)
Sampling rate (Hz)	2048 (×15)
Total duration (h)	10.2
Size on disk	27.6 GB
Recording type	IEEG
Experimental modality	Anesthesia
Paradigm type	Clinical/Intervention
Population	Surgery
Source	openneuro
License	CC0
NEMAR citations	1.0

Links

• DOI: 10.18112/openneuro.ds004370.v1.0.2
• OpenNeuro: ds004370
• 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.