EEGdash›NeMAR›ON007181

Iss. 7181 · 59 subjects · 59 recordings · CC0

Dataset Brief · Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zo…

ON007181: eeg dataset, 59 subjects#

Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia

Citation: Li Li, Qi Han, Haolei Bai, Xiaolong Zhang, Yong Liu, Chao He (—). Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia. 10.82901/nemar.on007181

59-participant EEG dataset — Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia.

Data & curation Li Li · Qi Han · Haolei Bai · Xiaolong Zhang · Yong Liu · Chao He

EEG · 24 ch1024 HzBIDS 1.8.0Task · sleep

Layer 01Study

What was asked

Hypothesis, independent & dependent variables, paradigm, cohort, and the editorial caveats around what the recordings can and cannot answer.

Layer 02Signal · BIDS

What was recorded

Sidecars, channels & electrodes, coordinate system, event semantics, and quality stats from the NEMAR pipeline when available.

Layer 03Training · ML

What you can train on

Recommended access modes — MNE Raw, braindecode windows, PyTorch DataLoader — plus the targets the metadata makes addressable.

§ 01Access · Get started

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import ON007181

dataset = ON007181(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Query & Filter

Filter by subject

dataset = ON007181(cache_dir="./data", subject="01")

Advanced query

dataset = ON007181(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Iterate recordings

for rec in dataset:
    print(rec.subject, rec.raw.info['sfreq'])

Cite This Dataset

If you use this dataset in your research, please cite the original authors.

BibTeX

@dataset{on007181,
  title = {Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia},
  author = {Li Li and Qi Han and Haolei Bai and Xiaolong Zhang and Yong Liu and Chao He},
  doi = {10.82901/nemar.on007181},
  url = {https://doi.org/10.82901/nemar.on007181},
}

§ 02Study · The README

About This Dataset#

This dataset includes anatomical T1-weighted MRI and raw multi-echo resting-state fMRI, as well as PSG data from a study investigating the difference between healthy controls (HC) and zoster-associated neuralgia (ZAN) patients.

MRI and PSG data were partially overlapping across participants. Participants with available data in at least one modality were included in the dataset, following the BIDS specification. - For project code and full analysis pipelines (including between-subject comparisons, functional connectivity analyses, and correlation-based statistical modeling), see:

project-zan-neuro

zan/

sub-01/
anat/sub-01_T1w.nii.gz func/sub-01_task-rest_bold.nii.gz

DOI

Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia

Summary

sub-02/
anat/sub-02_T1w.nii.gz func/sub-02_task-rest_bold.nii.gz eeg/ sub-02_task-sleep_acq-PSG_eeg.edf

sub-03/ …

How to cite These data are associated with a manuscript currently under revision. Please cite the dataset DOI when using these data. Contacts - Haolei Bai — ellebai83@gmail.com

(You may also contact the corresponding author from the manuscript.) License This dataset is shared under **CC0**.

§ 03Cohort · Participants

Cohort#

Dataset Statistics#

Age distribution by gender (n=59, range 44–70 yr, mean 61.2 yr)

405055606570

Female · 31Male · 28

Sex composition

Female
35
Male
31
F : M ratio
1.13 : 1

53% female · n = 66 subjects with reported sex.

Channel counts: 24 ch (n=59 recordings)

Sampling frequencies: 1024.0 Hz (n=59 recordings)

§ 04Signal · Electrodes & trace

Signal · Electrodes & live trace#

Fig. 01 Signal & montage 24 ch · EEG · 1024 Hz · 59 subjects, 59 recordings

Live trace viewer — sub-02 · task-sleep

Showing one representative recording out of 59 subjects and 59 recordings in this dataset. Browse the full set on OpenNeuro; drop any other _eeg.{set,edf,bdf,vhdr} file onto the viewer (or pass ?eeg=<url>) to inspect it.

No scalp electrode layout is currently indexed for this dataset. Once the eegdash montage registry ingests it, the interactive viewer will appear here automatically.

NEMAR Processing Statistics#

The plots below are generated by NEMAR’s automated EEG pipeline. The histogram shows pipeline success for data cleaning and ICA decomposition, the percentage of data frames and EEG channels retained after artefact removal, line noise per channel (RMS, dB), and the age/gender distribution of participants.

HED event descriptors word cloud

§ 05Manifest · BIDS tree

Manifest#

File Explorer#

Browse the BIDS file structure of this dataset. Records are fetched on demand from the EEGDash catalog the first time you open the explorer.

Recordings—

Files—

Subjects—

Modalities—

Click to load file structure…

§ 06API · Programmatic access

API Reference#

Signature

eegdash.dataset

class

eegdash.dataset.ON007181(cache_dir, query=None, s3_bucket=None, **kwargs)

Bases: EEGDashDataset

Author (year)—

Canonical—

Importable asON007181

Sourceeegdash/dataset/registry.py · [source ↗]

class eegdash.dataset.ON007181(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia

Study:: on007181 (NeMAR)
Author (year):: nan
Canonical:: —

Also importable as: ON007181, nan.

Modality: eeg. Subjects: 59; recordings: 59; tasks: 1.

Parameters:

cache_dir (str | Path) – Directory where data are cached locally.
query (dict | None) – Additional MongoDB-style filters to AND with the dataset selection. Must not contain the key dataset.
s3_bucket (str | None) – Base S3 bucket used to locate the data.
**kwargs (dict) – Additional keyword arguments forwarded to EEGDashDataset.

data_dir#

Local dataset cache directory (cache_dir / dataset_id).

Type:: Path

query#

Merged query with the dataset filter applied.

Type:: dict

records#

Metadata records used to build the dataset, if pre-fetched.

Type:: list[dict] | None

Notes

Each item is a recording; recording-level metadata are available via dataset.description. query supports MongoDB-style filters on fields in ALLOWED_QUERY_FIELDS and is combined with the dataset filter. Dataset-specific caveats are not provided in the summary metadata.

References

OpenNeuro dataset: https://openneuro.org/datasets/on007181 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=on007181 DOI: https://doi.org/10.82901/nemar.on007181

Examples

>>> from eegdash.dataset import ON007181
>>> dataset = ON007181(cache_dir="./data")
>>> recording = dataset[0]
>>> raw = recording.load()

__init__(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

save(path: str, overwrite: bool = False, offset: int = 0)[source]#

Save datasets to files by creating one subdirectory for each dataset:

path/
    0/
        0-raw.fif | 0-epo.fif
        description.json
        raw_preproc_kwargs.json (if raws were preprocessed)
        window_kwargs.json (if this is a windowed dataset)
        window_preproc_kwargs.json  (if windows were preprocessed)
        target_name.json (if target_name is not None and dataset is raw)
    1/
        1-raw.fif | 1-epo.fif
        description.json
        raw_preproc_kwargs.json (if raws were preprocessed)
        window_kwargs.json (if this is a windowed dataset)
        window_preproc_kwargs.json  (if windows were preprocessed)
        target_name.json (if target_name is not None and dataset is raw)

Parameters:

path (str) –

Directory in which subdirectories are created to store
-raw.fif | -epo.fif and .json files to.
overwrite (bool) – Whether to delete old subdirectories that will be saved to in this call.
offset (int) – If provided, the integer is added to the id of the dataset in the concat. This is useful in the setting of very large datasets, where one dataset has to be processed and saved at a time to account for its original position.

Access modesMNE → braindecode → PyTorch → ML

.rawMNE Raw object — standard tools (filter, epoch, ICA, plot_psd).mne

BaseConcatDatasetEach record is a lazy BaseDataset from braindecode — windowed via create_windows_from_events.braindecode

DataLoaderWraps the windowed dataset into a PyTorch DataLoader; supports parallel workers and on-the-fly augmentations.pytorch

Zarr cacheOptional braindecode Zarr mirror for fast resume; persisted to cache_dir.zarr

Hugging FaceNo per-dataset mirror published yet — browse the EEGDash org listing for sibling datasets. See the datasets loader API.huggingface

Croissant 1.0Machine-readable JSON-LD descriptor — ON007181.croissant.json (MLCommons schema, ingestible by PyTorch / TensorFlow / JAX).mlcommons

Examples using EEGDashcurated · start here

Find datasets with the EEGDash APIQuery the catalogue, filter by task or modality, list candidates.

Load one EEG recordingResolve a single record to an MNE Raw with channels and events.

EEG recording to PyTorch DataLoaderWrap braindecode windows in a DataLoader for model training.

Preprocess EEG and create windowsFilter, resample, epoch — and persist the windowed dataset.

Save and reload prepared dataCache a windowed dataset to disk and reattach it without recompute.

Download a dataset locallyPrefetch BIDS files to a local cache and validate the layout.

Swap any load_dataset(...) call for on007181 to reproduce the tutorial on this dataset.

Citation

Li Li, Qi Han, Haolei Bai, Xiaolong Zhang, Yong Liu, … (n.d.). Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia. 10.82901/nemar.on007181

Provenance

¹Contributed to nemar in BIDS format.

²Curated & ingested by the EEGDash catalog; see CITATION.cff for canonical reference.

³Persistent identifier: 10.82901/nemar.on007181.

Related & sibling datasets

ON003825EEG · 50 subj NM000132EEG · 40 subj ON007176EEG · 45 subj NM000180EEG · 45 subj ON004018EEG · 16 subj

+ 1 more — see See Also below →

BIDS

BIDS 1.8.0

Sidecars

events · events.json · channels · eeg.json

Provenance

CC0 · 10.82901/nemar.on007181

Machine-readable

schema.org/Dataset · Croissant

Mirrors

OpenNeuro · NEMAR · HF org

Dataset ID	`ON007181`
Title	Structural MRI, Resting-state fMRI, and PSG/EEG Dataset of Zoster-associated Neuralgia
Author (year)	—
Canonical	—
Importable as	`ON007181`
Year	—
Authors	Li Li, Qi Han, Haolei Bai, Xiaolong Zhang, Yong Liu, Chao He
License	CC0
Citation / DOI	10.82901/nemar.on007181
Source links	OpenNeuro \| NeMAR \| Source URL

ON007181: eeg dataset, 59 subjects#

Quickstart#

About This Dataset#

Cohort#

Dataset Statistics#

Signal · Electrodes & live trace#

NEMAR Processing Statistics#

Manifest#

File Explorer#

API Reference#

Citation

Provenance

Related & sibling datasets

See Also#