EEGDash/ds006910

Auditory Naming EC

Dataset ID: ds006910

Kochi2025_Auditory_Naming_EC

At a glance: IEEG · Auditory other · unknown · 121 subjects · 384 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="ds006910", 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/ds006910")

Dataset metadata

Subjects	121
Recordings	384
Tasks (count)	1
Channels	128 (×269), 138 (×14), 136 (×11), 112 (×9), 140 (×8), 164 (×8), 134 (×7), 110 (×6), 142 (×5), 156 (×5), 150 (×5), 132 (×4), 148 (×4), 144 (×4), 130 (×4), 160 (×3), 154 (×3), 84 (×3), 118 (×3), 96 (×3), 152 (×3), 64 (×2), 58 (×1)
Sampling rate (Hz)	1000 (×384)
Total duration (h)	130.1
Size on disk	44.6 GB
Recording type	IEEG
Experimental modality	Auditory
Paradigm type	Other
Population	Unknown
Source	openneuro
License	CC0

Links

• DOI: 10.18112/openneuro.ds006910.v1.0.1
• OpenNeuro: ds006910
• 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.