DS006107: ieeg dataset, 166 subjects#

iEEG_Neural_spatial_volatility

Access recordings and metadata through EEGDash.

Citation: Naoto Kuroda, Eishi Asano, Nobukazu Nakasato (2025). iEEG_Neural_spatial_volatility. 10.18112/openneuro.ds006107.v1.0.0

Modality: ieeg Subjects: 166 Recordings: 167 License: CC0 Source: openneuro

Metadata: Complete (90%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006107

dataset = DS006107(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS006107(cache_dir="./data", subject="01")

Advanced query

dataset = DS006107(
    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{ds006107,
  title = {iEEG_Neural_spatial_volatility},
  author = {Naoto Kuroda and Eishi Asano and Nobukazu Nakasato},
  doi = {10.18112/openneuro.ds006107.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds006107.v1.0.0},
}

About This Dataset#

No README content is available for this dataset.

Dataset Information#

Dataset ID

DS006107

Title

iEEG_Neural_spatial_volatility

Author (year)

Kuroda2025

Canonical

Kuroda2024

Importable as

DS006107, Kuroda2025, Kuroda2024

Year

2025

Authors

Naoto Kuroda, Eishi Asano, Nobukazu Nakasato

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds006107.v1.0.0

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds006107,
  title = {iEEG_Neural_spatial_volatility},
  author = {Naoto Kuroda and Eishi Asano and Nobukazu Nakasato},
  doi = {10.18112/openneuro.ds006107.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds006107.v1.0.0},
}

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: 166

  • Recordings: 167

  • Tasks: 1

Channels & sampling rate

  • Channels: 128 (30), 112 (19), 104 (7), 108 (6), 118 (6), 124 (5), 102 (5), 132 (5), 100 (5), 120 (5), 106 (5), 138 (4), 130 (4), 58 (4), 140 (3), 110 (3), 116 (3), 34 (2), 86 (2), 136 (2), 150 (2), 84 (2), 114 (2), 64 (2), 126 (2), 144 (2), 72 (2), 98 (2), 48, 78, 68, 94, 80, 44, 134, 73, 70, 52, 109, 156, 88, 28, 74, 69, 38, 164, 82, 56, 96, 54, 133, 90, 46, 122

  • Sampling rate (Hz): 1000.0

  • Duration (hours): 16.50111111111111

Tags

  • Pathology: Not specified

  • Modality: Sleep

  • Type: Sleep

Files & format

  • Size on disk: 11.9 GB

  • File count: 167

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds006107.v1.0.0

Provenance

API Reference#

Use the DS006107 class to access this dataset programmatically.

class eegdash.dataset.DS006107(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

iEEG_Neural_spatial_volatility

Study:

ds006107 (OpenNeuro)

Author (year):

Kuroda2025

Canonical:

Kuroda2024

Also importable as: DS006107, Kuroda2025, Kuroda2024.

Modality: ieeg; Experiment type: Sleep; Subject type: Unknown. Subjects: 166; recordings: 167; 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/ds006107 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006107 DOI: https://doi.org/10.18112/openneuro.ds006107.v1.0.0

Examples

>>> from eegdash.dataset import DS006107
>>> dataset = DS006107(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#