DS004902#

A Resting-state EEG Dataset for Sleep Deprivation

Access recordings and metadata through EEGDash.

Citation: Chuqin Xiang, Xinrui Fan, Duo Bai, Ke Lv, Xu Lei (2023). A Resting-state EEG Dataset for Sleep Deprivation. 10.18112/openneuro.ds004902.v1.0.8

Modality: eeg Subjects: 71 Recordings: 1228 License: CC0 Source: openneuro Citations: 3.0

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004902

dataset = DS004902(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS004902(cache_dir="./data", subject="01")

Advanced query

dataset = DS004902(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Iterate recordings

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

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

BibTeX

@dataset{ds004902,
  title = {A Resting-state EEG Dataset for Sleep Deprivation},
  author = {Chuqin Xiang and Xinrui Fan and Duo Bai and Ke Lv and Xu Lei},
  doi = {10.18112/openneuro.ds004902.v1.0.8},
  url = {https://doi.org/10.18112/openneuro.ds004902.v1.0.8},
}

About This Dataset#

General information

The dataset provides resting-state EEG data (eyes open,partially eyes closed) from 71 participants who underwent two experiments involving normal sleep (NS—session1) and sleep deprivation(SD—session2) .The dataset also provides information on participants’ sleepiness and mood states. （Please note here Session 1 (NS) and Session 2 (SD) is not the time order, the time order is counterbalanced across participants and is listed in metadata.）

Dataset

View full README

General information

The dataset provides resting-state EEG data (eyes open,partially eyes closed) from 71 participants who underwent two experiments involving normal sleep (NS—session1) and sleep deprivation(SD—session2) .The dataset also provides information on participants’ sleepiness and mood states. （Please note here Session 1 (NS) and Session 2 (SD) is not the time order, the time order is counterbalanced across participants and is listed in metadata.）

Dataset

Presentation

The data collection was initiated in March 2019 and was terminated in December 2020. The detailed description of the dataset is currently under working by Chuqin Xiang,Xinrui Fan,Duo Bai,Ke Lv and Xu Lei, and will submit to Scientific Data for publication.

EEG acquisition

  • EEG system (Brain Products GmbH, Steing- rabenstr, Germany, 61 electrodes)

  • Sampling frequency: 500Hz

  • Impedances were kept below 5k

Contact

  • If you have any questions or comments, please contact:

  • Xu Lei: xlei@swu.edu.cn

Article

Xiang, C., Fan, X., Bai, D. et al. A resting-state EEG dataset for sleep deprivation. Sci Data 11, 427 (2024). https://doi.org/10.1038/s41597-024-03268-2

Dataset Information#

Dataset ID

DS004902

Title

A Resting-state EEG Dataset for Sleep Deprivation

Year

2023

Authors

Chuqin Xiang, Xinrui Fan, Duo Bai, Ke Lv, Xu Lei

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds004902.v1.0.8

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds004902,
  title = {A Resting-state EEG Dataset for Sleep Deprivation},
  author = {Chuqin Xiang and Xinrui Fan and Duo Bai and Ke Lv and Xu Lei},
  doi = {10.18112/openneuro.ds004902.v1.0.8},
  url = {https://doi.org/10.18112/openneuro.ds004902.v1.0.8},
}

Found an issue with this dataset?

If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!

Report an Issue on GitHub

Technical Details#

Subjects & recordings

  • Subjects: 71

  • Recordings: 1228

  • Tasks: 2

Channels & sampling rate

  • Channels: 61

  • Sampling rate (Hz): 500.0 (430), 5000.0 (6)

  • Duration (hours): 0.0

Tags

  • Pathology: Not specified

  • Modality: —

  • Type: —

Files & format

  • Size on disk: 8.3 GB

  • File count: 1228

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds004902.v1.0.8

Provenance

API Reference#

Use the DS004902 class to access this dataset programmatically.

class eegdash.dataset.DS004902(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004902. Modality: eeg; Experiment type: Resting state; Subject type: Healthy. Subjects: 71; recordings: 218; tasks: 2.

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/ds004902 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004902

Examples

>>> from eegdash.dataset import DS004902
>>> dataset = DS004902(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, overwrite=False)[source]#

Save the dataset to disk.

Parameters:

  • path (str or Path) – Destination file path.

  • overwrite (bool, default False) – If True, overwrite existing file.

Return type:

None

See Also#