DS007176#

Longitudinal EEG Test-Retest Reliability in Healthy Individuals

Access recordings and metadata through EEGDash.

Citation: Verónica Henao Isaza, Valeria Cadavid Castro, Luisa María Zapata Saldarriaga, Yorguin-Jose Mantilla-Ramos, Jazmín Ximena Suarez Revelo, Carlos Andrés Tobón Quintero, John Fredy Ochoa Gómez (2026). Longitudinal EEG Test-Retest Reliability in Healthy Individuals. 10.18112/openneuro.ds007176.v1.0.1

Modality: eeg Subjects: 45 Recordings: 1656 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS007176

dataset = DS007176(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 = DS007176(cache_dir="./data", subject="01")

Advanced query

dataset = DS007176(
    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{ds007176,
  title = {Longitudinal EEG Test-Retest Reliability in Healthy Individuals},
  author = {Verónica Henao Isaza and Valeria Cadavid Castro and Luisa María Zapata Saldarriaga and Yorguin-Jose Mantilla-Ramos and Jazmín Ximena Suarez Revelo and Carlos Andrés Tobón Quintero and John Fredy Ochoa Gómez},
  doi = {10.18112/openneuro.ds007176.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds007176.v1.0.1},
}

About This Dataset#

Longitudinal EEG Test-Retest Reliability in Healthy Individuals

Dataset Description

This dataset contains longitudinal resting-state EEG recordings from 43 healthy adults, collected over four sessions spanning approximately two years, with an average interval of 7.2 months between sessions. The dataset includes raw EEG data and relevant metadata

Dataset Information#

Dataset ID	`DS007176`
Title	Longitudinal EEG Test-Retest Reliability in Healthy Individuals
Year	2026
Authors	Verónica Henao Isaza, Valeria Cadavid Castro, Luisa María Zapata Saldarriaga, Yorguin-Jose Mantilla-Ramos, Jazmín Ximena Suarez Revelo, Carlos Andrés Tobón Quintero, John Fredy Ochoa Gómez
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds007176.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: 45
Recordings: 1656
Tasks: 2

Channels & sampling rate

Channels: 60
Sampling rate (Hz): 1000.0
Duration (hours): 0.0

API Reference#

Use the DS007176 class to access this dataset programmatically.

class eegdash.dataset.DS007176(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds007176. Modality: eeg; Experiment type: Resting-state; Subject type: Healthy. Subjects: 45; recordings: 300; 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/ds007176 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds007176

Examples

>>> from eegdash.dataset import DS007176
>>> dataset = DS007176(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