DS007120#

iEEG_comprehensive_HFA_model_part2

Access recordings and metadata through EEGDash.

Citation: Keisuke Hatano, Naoto Kuroda, Hiroshi Uda, Kazuki Sakakura, Michael J. Cools, Aimee F. Luat, Shin-Ichiro Osawa, Hitoshi Nemoto, Kazushi Ukishiro, Hidenori Endo, Nobukazu Nakasato, Yutaro Takayama, Keiya Iijima, Masaki Iwasaki, Eishi Asano (2025). iEEG_comprehensive_HFA_model_part2. 10.18112/openneuro.ds007120.v1.0.0

Modality: ieeg Subjects: 65 Recordings: 420 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS007120

dataset = DS007120(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 = DS007120(cache_dir="./data", subject="01")

Advanced query

dataset = DS007120(
    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{ds007120,
  title = {iEEG_comprehensive_HFA_model_part2},
  author = {Keisuke Hatano and Naoto Kuroda and Hiroshi Uda and Kazuki Sakakura and Michael J. Cools and Aimee F. Luat and Shin-Ichiro Osawa and Hitoshi Nemoto and Kazushi Ukishiro and Hidenori Endo and Nobukazu Nakasato and Yutaro Takayama and Keiya Iijima and Masaki Iwasaki and Eishi Asano},
  doi = {10.18112/openneuro.ds007120.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds007120.v1.0.0},
}

About This Dataset#

This dataset contains intracranial EEG data recorded during non-REM sleep and used in Hatano et al. (in press).

Authors: Keisuke Hatano, Naoto Kuroda, Hiroshi Uda, Kazuki Sakakura, Michael J. Cools, Aimee F. Luat, Shin-Ichiro Osawa, Hitoshi Nemoto, Kazushi Ukishiro, Hidenori Endo, Nobukazu Nakasato, Yutaro Takayama, Keiya Iijima, Masaki Iwasaki, Eishi Asano

Funding: National Institutes of Health (NIH; NS064033 to E.A.); Uehara Memorial Foundation Postdoctoral Fellowship (202441017 to K.H.; 20210301 to H.U.); Japan Society for the Promotion of Science (JP22J23281, JP22KJ0323, and 202560576 to N.K.; 202560628 to H.U.; JP19K09494 and 22K09296 to M.I.)

Dataset Information#

Dataset ID	`DS007120`
Title	iEEG_comprehensive_HFA_model_part2
Year	2025
Authors	Keisuke Hatano, Naoto Kuroda, Hiroshi Uda, Kazuki Sakakura, Michael J. Cools, Aimee F. Luat, Shin-Ichiro Osawa, Hitoshi Nemoto, Kazushi Ukishiro, Hidenori Endo, Nobukazu Nakasato, Yutaro Takayama, Keiya Iijima, Masaki Iwasaki, Eishi Asano
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds007120.v1.0.0
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: 65
Recordings: 420
Tasks: 1

Channels & sampling rate

Channels: 128 (13), 112 (10), 104 (5), 132 (4), 110 (4), 118 (3), 140 (2), 130 (2), 108 (2), 120 (2), 126 (2), 56 (2), 150 (2), 138 (2), 100 (2), 106 (2), 122, 136, 116, 156, 144, 34, 164, 98, 124, 134, 84
Sampling rate (Hz): 1000.0
Duration (hours): 0.0

API Reference#

Use the DS007120 class to access this dataset programmatically.

class eegdash.dataset.DS007120(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds007120. Modality: ieeg. Subjects: 65; recordings: 70; 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/ds007120 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds007120

Examples

>>> from eegdash.dataset import DS007120
>>> dataset = DS007120(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