DS007473: fnirs dataset, 5 subjects#

High-Density Diffuse Optical Tomography Audiovisual Movie Viewing Dataset

Access recordings and metadata through EEGDash.

Citation: Morgan Fogarty, Kalyan Tripathy, Alexandra M Svoboda, Mariel L Schroeder, Sean M Rafferty, Edward J Richter, Christopher Tracy, Patricia K Mansfield, Madison Booth, Andrew K Fishell, Arefeh Sherafati, Zachary E Markow, Muriah D Wheelock, Ana Maria Arbelaez, Bradley L Schlaggar, Christopher D Smyser, Adam T Eggebrecht, Joseph P Culver (2026). High-Density Diffuse Optical Tomography Audiovisual Movie Viewing Dataset. 10.18112/openneuro.ds007473.v1.0.0

Modality: fnirs Subjects: 5 Recordings: 189 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS007473

dataset = DS007473(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS007473(cache_dir="./data", subject="01")

Advanced query

dataset = DS007473(
    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{ds007473,
  title = {High-Density Diffuse Optical Tomography Audiovisual Movie Viewing Dataset},
  author = {Morgan Fogarty and Kalyan Tripathy and Alexandra M Svoboda and Mariel L Schroeder and Sean M Rafferty and Edward J Richter and Christopher Tracy and Patricia K Mansfield and Madison Booth and Andrew K Fishell and Arefeh Sherafati and Zachary E Markow and Muriah D Wheelock and Ana Maria Arbelaez and Bradley L Schlaggar and Christopher D Smyser and Adam T Eggebrecht and Joseph P Culver},
  doi = {10.18112/openneuro.ds007473.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds007473.v1.0.0},
}

About This Dataset#

This dataset consists of 5 participants completing functional localizer and movie viewing tasks. These data are stored in SNIRF format with optode and landmark locations associated with subject specific head models. See the corresponding publication for more information about this dataset: Tripathy K, Fogarty M, et al., “Mapping brain function in adults and young children during naturalistic viewing with high-density diffuse optical tomography.” Human Brain Mapping. 2024 May;45(7):e26684. doi: 10.1002/hbm.26684. PMID: 38703090; PMCID: PMC11069306. Kalyan Tripathy, Zachary E. Markow, Morgan Fogarty, Mariel L. Schroeder, Alexa M. Svoboda, Adam T. Eggebrecht, Bradley L. Schlaggar, Jason W. Trobaugh, Joseph P. Culver, “Multisensory naturalistic decoding with high-density diffuse optical tomography,” Neurophoton. 12(1) 015002 (23 January 2025) https://doi.org/10.1117/1.NPh.12.1.015002

Dataset Information#

Dataset ID

DS007473

Title

High-Density Diffuse Optical Tomography Audiovisual Movie Viewing Dataset

Author (year)

Fogarty2026_High

Canonical

Tripathy2024

Importable as

DS007473, Fogarty2026_High, Tripathy2024

Year

2026

Authors

Morgan Fogarty, Kalyan Tripathy, Alexandra M Svoboda, Mariel L Schroeder, Sean M Rafferty, Edward J Richter, Christopher Tracy, Patricia K Mansfield, Madison Booth, Andrew K Fishell, Arefeh Sherafati, Zachary E Markow, Muriah D Wheelock, Ana Maria Arbelaez, Bradley L Schlaggar, Christopher D Smyser, Adam T Eggebrecht, Joseph P Culver

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds007473.v1.0.0

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds007473,
  title = {High-Density Diffuse Optical Tomography Audiovisual Movie Viewing Dataset},
  author = {Morgan Fogarty and Kalyan Tripathy and Alexandra M Svoboda and Mariel L Schroeder and Sean M Rafferty and Edward J Richter and Christopher Tracy and Patricia K Mansfield and Madison Booth and Andrew K Fishell and Arefeh Sherafati and Zachary E Markow and Muriah D Wheelock and Ana Maria Arbelaez and Bradley L Schlaggar and Christopher D Smyser and Adam T Eggebrecht and Joseph P Culver},
  doi = {10.18112/openneuro.ds007473.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds007473.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: 5

  • Recordings: 189

  • Tasks: 19

Channels & sampling rate

  • Channels: 6782 (71), 6928 (43), 6880 (38), 6750 (31), 7030 (6)

  • Sampling rate (Hz): 10.41666666666667

  • Duration (hours): 51.12245333333332

Tags

  • Pathology: Healthy

  • Modality: Multisensory

  • Type: Perception

Files & format

  • Size on disk: 36.3 GB

  • File count: 189

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds007473.v1.0.0

Provenance

API Reference#

Use the DS007473 class to access this dataset programmatically.

class eegdash.dataset.DS007473(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

High-Density Diffuse Optical Tomography Audiovisual Movie Viewing Dataset

Study:

ds007473 (OpenNeuro)

Author (year):

Fogarty2026_High

Canonical:

Tripathy2024

Also importable as: DS007473, Fogarty2026_High, Tripathy2024.

Modality: fnirs; Experiment type: Perception; Subject type: Healthy. Subjects: 5; recordings: 189; tasks: 19.

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/ds007473 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds007473 DOI: https://doi.org/10.18112/openneuro.ds007473.v1.0.0

Examples

>>> from eegdash.dataset import DS007473
>>> dataset = DS007473(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#