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nm000343
Hinss2021
nemar
https://openneuro.org/datasets/nm000343
10.1038/s41597-022-01898-y
CC-BY-SA-4.0
{ "library": "eegdash", "class": "EEGDashDataset", "kwargs": { "dataset": "nm000343" } }
https://huggingface.co/spaces/EEGDash/catalog
huggingface-space/scripts/push_metadata_stubs.py

Hinss2021

Dataset ID: nm000343

Hinss2021

Canonical aliases: Hinss2021_v2

At a glance: EEG · Visual attention · healthy · 15 subjects · 30 recordings · CC-BY-SA-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="nm000343", 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 Hinss2021_v2
ds = Hinss2021_v2(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/nm000343")

Dataset metadata

Subjects 15
Recordings 30
Tasks (count) 1
Channels 61 (×30)
Sampling rate (Hz) 500 (×30)
Total duration (h) 4.0
Size on disk 1.2 GB
Recording type EEG
Experimental modality Visual
Paradigm type Attention
Population Healthy
Source nemar
License CC-BY-SA-4.0

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.

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