DS007420: fnirs dataset, 12 subjects#

A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task

Access recordings and metadata through EEGDash.

Citation: Gao, Yuanyuan, Rogers, De’Ja, von Lühmann, Alexander, Ortega-Martinez, Antonio, Boas, David, Yücel, Meryem (2026). A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task. 10.18112/openneuro.ds007420.v1.0.2

Modality: fnirs Subjects: 12 Recordings: 60 License: CC0 Source: openneuro

Metadata: Complete (90%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS007420

dataset = DS007420(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS007420(cache_dir="./data", subject="01")

Advanced query

dataset = DS007420(
    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{ds007420,
  title = {A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task},
  author = {Gao, Yuanyuan and Rogers, De’Ja and von Lühmann, Alexander and Ortega-Martinez, Antonio and Boas, David and Yücel, Meryem},
  doi = {10.18112/openneuro.ds007420.v1.0.2},
  url = {https://doi.org/10.18112/openneuro.ds007420.v1.0.2},
}

About This Dataset#

No README content is available for this dataset.

Dataset Information#

Dataset ID

DS007420

Title

A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task

Author (year)

Gao2026_Light_Weight_Multi

Canonical

Gao2024

Importable as

DS007420, Gao2026_Light_Weight_Multi, Gao2024

Year

2026

Authors

Gao, Yuanyuan, Rogers, De’Ja, von Lühmann, Alexander, Ortega-Martinez, Antonio, Boas, David, Yücel, Meryem

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds007420.v1.0.2

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds007420,
  title = {A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task},
  author = {Gao, Yuanyuan and Rogers, De’Ja and von Lühmann, Alexander and Ortega-Martinez, Antonio and Boas, David and Yücel, Meryem},
  doi = {10.18112/openneuro.ds007420.v1.0.2},
  url = {https://doi.org/10.18112/openneuro.ds007420.v1.0.2},
}

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: 12

  • Recordings: 60

  • Tasks: 4

Channels & sampling rate

  • Channels: 200

  • Sampling rate (Hz): 8.719308035714286 (52), 11.625744047619047 (4), 8.719308035714288 (3), 11.625744047619051

  • Duration (hours): Not calculated

Tags

  • Pathology: Healthy

  • Modality: Motor

  • Type: Motor

Files & format

  • Size on disk: 560.7 MB

  • File count: 60

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds007420.v1.0.2

Provenance

API Reference#

Use the DS007420 class to access this dataset programmatically.

class eegdash.dataset.DS007420(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

A Light Weight Multi-Distance fNIRS Dataset for Ball-Squeezing Task and Purposeful Motion Artifact Creation Task

Study:

ds007420 (OpenNeuro)

Author (year):

Gao2026_Light_Weight_Multi

Canonical:

Gao2024

Also importable as: DS007420, Gao2026_Light_Weight_Multi, Gao2024.

Modality: fnirs; Experiment type: Motor; Subject type: Healthy. Subjects: 12; recordings: 60; tasks: 4.

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/ds007420 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds007420 DOI: https://doi.org/10.18112/openneuro.ds007420.v1.0.2

Examples

>>> from eegdash.dataset import DS007420
>>> dataset = DS007420(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#