EEGDash/ds006817

Visual Attribute-Specific Contextual Trajectory Paradigm 2.0

Dataset ID: ds006817

Lowe2025

Canonical aliases: VisualContextTrajectory_v2 · Lowe2025

At a glance: EEG · Unknown unknown · unknown · 34 subjects · 34 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="ds006817", 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 VisualContextTrajectory_v2
ds = VisualContextTrajectory_v2(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/ds006817")

Dataset metadata

Subjects	34
Recordings	34
Tasks (count)	1
Channels	65 (×34)
Sampling rate (Hz)	1024 (×34)
Total duration (h)	21.7
Size on disk	9.7 GB
Recording type	EEG
Experimental modality	Unknown
Paradigm type	Unknown
Population	Unknown
Source	openneuro
License	CC0

Links

• DOI: 10.18112/openneuro.ds006817.v1.0.0
• OpenNeuro: ds006817
• 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.