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ds005752 / README.md
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Metadata stub for ds005752
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metadata
pretty_name: The NIMH Healthy Research Volunteer Dataset
license: cc0-1.0
tags:
  - meg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - multisensory
  - other
size_categories:
  - 1K<n<10K
task_categories:
  - other

The NIMH Healthy Research Volunteer Dataset

Dataset ID: ds005752

Nugent2024

At a glance: MEG · Multisensory other · healthy · 123 subjects · 1055 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="ds005752", 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/ds005752")

Dataset metadata

Subjects 123
Recordings 1055
Tasks (count) 10
Channels 305 (×240), 306 (×183), 304 (×123), 302 (×117), 303 (×110), 301 (×71), 382 (×59), 300 (×57), 378 (×20), 377 (×16), 379 (×16), 381 (×15), 380 (×15), 299 (×3), 387 (×1), 388 (×1)
Sampling rate (Hz) 1200 (×926), 4800 (×121)
Total duration (h) 102.6
Size on disk 662.7 GB
Recording type MEG
Experimental modality Multisensory
Paradigm type Other
Population Healthy
Source openneuro
License CC0

Links


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.