DS006366#

Mouse Sleep Staging Validation dataset (MSSV)

Access recordings and metadata through EEGDash.

Citation: Laura Rose, Alexander Neergaard Zahid, Javier García Ciudad, Christine Egebjerg, Louise Piilgaard, Frederikke Lynge Sørensen, Mie Andersen, Tessa Radovanovic, Anastasia Tsopanidou, Maiken Nedergaard, Sébastien Arthaud, Renato Maciel, Christelle Peyron, Chiara Berteotti, Viviana Lo Martire, Alessandro Silvani, Giovanna Zoccoli, Micaela Borsa, Antoine Adamantidis, Morten Mørup, Birgitte Rahbek Kornum (2025). Mouse Sleep Staging Validation dataset (MSSV). 10.18112/openneuro.ds006366.v1.0.1

Modality: eeg Subjects: 92 Recordings: 395 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006366

dataset = DS006366(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 = DS006366(cache_dir="./data", subject="01")

Advanced query

dataset = DS006366(
    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{ds006366,
  title = {Mouse Sleep Staging Validation dataset (MSSV)},
  author = {Laura Rose and Alexander Neergaard Zahid and Javier García Ciudad and Christine Egebjerg and Louise Piilgaard and Frederikke Lynge Sørensen and Mie Andersen and Tessa Radovanovic and Anastasia Tsopanidou and Maiken Nedergaard and Sébastien Arthaud and Renato Maciel and Christelle Peyron and Chiara Berteotti and Viviana Lo Martire and Alessandro Silvani and Giovanna Zoccoli and Micaela Borsa and Antoine Adamantidis and Morten Mørup and Birgitte Rahbek Kornum},
  doi = {10.18112/openneuro.ds006366.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006366.v1.0.1},
}

About This Dataset#

Mouse Sleep Staging Validation dataset (MSSV)

This dataset contains EEG recordings with sleep scores from 92 healthy mice. The recordings and sleep scores were collected from five different labs:

Department of Biomedical and Neuromotor Sciences, Università di Bologna, Italy.
Center for Translational Neuroscience, University of Copenhagen, Denmark.
Department of Neuroscience, University of Copenhagen, Denmark.
Zentrum für Experimentelle Neurologie, Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland.

Dataset Information#

Dataset ID	`DS006366`
Title	Mouse Sleep Staging Validation dataset (MSSV)
Year	2025
Authors	Laura Rose, Alexander Neergaard Zahid, Javier García Ciudad, Christine Egebjerg, Louise Piilgaard, Frederikke Lynge Sørensen, Mie Andersen, Tessa Radovanovic, Anastasia Tsopanidou, Maiken Nedergaard, Sébastien Arthaud, Renato Maciel, Christelle Peyron, Chiara Berteotti, Viviana Lo Martire, Alessandro Silvani, Giovanna Zoccoli, Micaela Borsa, Antoine Adamantidis, Morten Mørup, Birgitte Rahbek Kornum
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006366.v1.0.1
Source links	OpenNeuro \| NeMAR \| Source URL

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: 92
Recordings: 395
Tasks: 1

Channels & sampling rate

Channels: 3 (142), 2 (86), 5 (68)
Sampling rate (Hz): 128.0
Duration (hours): 0.0

API Reference#

Use the DS006366 class to access this dataset programmatically.

class eegdash.dataset.DS006366(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006366. Modality: eeg; Experiment type: Sleep; Subject type: Healthy. Subjects: 92; recordings: 148; 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/ds006366 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006366

Examples

>>> from eegdash.dataset import DS006366
>>> dataset = DS006366(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