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OcularLDT
Dataset ID: ds002312
Brooks2019
Canonical aliases: OcularLDT · ocular_ldt
At a glance: MEG · Visual perception · healthy · 19 subjects · 23 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="ds002312", 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 OcularLDT
ds = OcularLDT(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/ds002312")
Dataset metadata
| Subjects | 19 |
| Recordings | 23 |
| Tasks (count) | 1 |
| Channels | 257 (×23) |
| Sampling rate (Hz) | 1000 (×15) |
| Total duration (h) | 7.1 |
| Size on disk | 34.1 GB |
| Recording type | MEG |
| Experimental modality | Visual |
| Paradigm type | Perception |
| Population | Healthy |
| Source | openneuro |
| License | CC0 |
Links
- DOI: 10.18112/openneuro.ds002312.v1.0.0
- OpenNeuro: ds002312
- 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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