Datasets:

EEGDash
/

ds006817

pretty_name: Visual Attribute-Specific Contextual Trajectory Paradigm 2.0
license: cc0-1.0
tags:
  - eeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - unknown
size_categories:
  - n<1K
task_categories:
  - other

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

Visual Attribute-Specific Contextual Trajectory Paradigm 2.0

Load this dataset

Dataset metadata

Links