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ds005241
NeuroMorph: A High-Temporal Resolution MEG Dataset for Morpheme-Based Linguistic Analysis
openneuro
https://openneuro.org/datasets/ds005241
10.18112/openneuro.ds005241.v1.1.0
CC0
{ "library": "eegdash", "class": "EEGDashDataset", "kwargs": { "dataset": "ds005241" } }
https://huggingface.co/spaces/EEGDash/catalog
huggingface-space/scripts/push_metadata_stubs.py

NeuroMorph: A High-Temporal Resolution MEG Dataset for Morpheme-Based Linguistic Analysis

Dataset ID: ds005241

Rodriguez2024

Canonical aliases: NeuroMorph · neuromorph

At a glance: MEG · Unknown other · healthy · 24 subjects · 117 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="ds005241", 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 NeuroMorph
ds = NeuroMorph(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/ds005241")

Dataset metadata

Subjects 24
Recordings 117
Tasks (count) 2
Channels 256 (×117)
Sampling rate (Hz) 1000 (×27)
Total duration (h) 3.7
Size on disk 140.5 GB
Recording type MEG
Experimental modality Unknown
Paradigm type Other
Population Healthy
Source openneuro
License CC0
NEMAR citations 0.0

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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