dataset_id stringclasses 1
value | title stringclasses 1
value | source stringclasses 1
value | source_url stringclasses 1
value | doi stringclasses 1
value | license stringclasses 1
value | loader dict | catalog stringclasses 1
value | generated_by stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|
ds006107 | iEEG_Neural_spatial_volatility | openneuro | https://openneuro.org/datasets/ds006107 | 10.18112/openneuro.ds006107.v1.0.0 | CC0 | {
"library": "eegdash",
"class": "EEGDashDataset",
"kwargs": {
"dataset": "ds006107"
}
} | https://huggingface.co/spaces/EEGDash/catalog | huggingface-space/scripts/push_metadata_stubs.py |
iEEG_Neural_spatial_volatility
Dataset ID: ds006107
Kuroda2025
Canonical aliases: Kuroda2024
At a glance: IEEG · Sleep sleep · unknown · 166 subjects · 167 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="ds006107", 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 Kuroda2024
ds = Kuroda2024(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/ds006107")
Dataset metadata
| Subjects | 166 |
| Recordings | 167 |
| Tasks (count) | 1 |
| Channels | 128 (×30), 112 (×19), 104 (×7), 108 (×6), 118 (×6), 124 (×5), 102 (×5), 132 (×5), 100 (×5), 120 (×5), 106 (×5), 138 (×4), 130 (×4), 58 (×4), 140 (×3), 110 (×3), 116 (×3), 34 (×2), 86 (×2), 136 (×2), 150 (×2), 84 (×2), 114 (×2), 64 (×2), 126 (×2), 144 (×2), 72 (×2), 98 (×2), 48 (×1), 78 (×1), 68 (×1), 94 (×1), 80 (×1), 44 (×1), 134 (×1), 73 (×1), 70 (×1), 52 (×1), 109 (×1), 156 (×1), 88 (×1), 28 (×1), 74 (×1), 69 (×1), 38 (×1), 164 (×1), 82 (×1), 56 (×1), 96 (×1), 54 (×1), 133 (×1), 90 (×1), 46 (×1), 122 (×1) |
| Sampling rate (Hz) | 1000 (×167) |
| Total duration (h) | 16.5 |
| Size on disk | 11.9 GB |
| Recording type | IEEG |
| Experimental modality | Sleep |
| Paradigm type | Sleep |
| Population | Unknown |
| Source | openneuro |
| License | CC0 |
Links
- DOI: 10.18112/openneuro.ds006107.v1.0.0
- OpenNeuro: ds006107
- 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.
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