EEGDash/ds006866

Discrepancy between self-report and neurophysiological markers of socio-affective responses in lonely individuals

Dataset ID: ds006866

Maka2025_Discrepancy

At a glance: EEG · Visual affect · healthy · 148 subjects · 148 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="ds006866", cache_dir="./cache")
print(len(ds), "recordings")

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/ds006866")

Dataset metadata

Subjects	148
Recordings	148
Tasks (count)	1
Channels	69 (×148)
Sampling rate (Hz)	1000 (×148)
Total duration (h)	123.4
Size on disk	116.2 GB
Recording type	EEG
Experimental modality	Visual
Paradigm type	Affect
Population	Healthy
Source	openneuro
License	CC0

Links

• DOI: 10.18112/openneuro.ds006866.v1.0.0
• OpenNeuro: ds006866
• 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.