metadata
pretty_name: 'M3CV: Multi-subject, Multi-session, Multi-task EEG Database'
license: cc-by-4.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
size_categories:
- 1K<n<10K
task_categories:
- other
M3CV: Multi-subject, Multi-session, Multi-task EEG Database
Dataset ID: nm000166
Huang2018
At a glance: EEG · 95 subjects · 2469 recordings · CC BY 4.0
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="nm000166", 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/nm000166")
Dataset metadata
| Subjects | 95 |
| Recordings | 2469 |
| Tasks (count) | 13 |
| Channels | 64 (×2469) |
| Sampling rate (Hz) | 250 (×2469) |
| Total duration (h) | 100.5 |
| Size on disk | 21.6 GB |
| Recording type | EEG |
| Source | nemar |
| License | CC BY 4.0 |
Links
- DOI: 10.1016/j.neuroimage.2022.119666
- NEMAR: nm000166
- 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.