DS004696#

HAPwave_bids

Access recordings and metadata through EEGDash.

Citation: Ojeda Valencia, G., Gregg, N., Huang, H., Lundstrom, B., Brinkmann, B., Pal Attia1, T., Van Gompel, J., Bernstein,M., In, M., Huston, J., Worrell1, G., Miller, K., Hermes, D. (2023). HAPwave_bids. 10.18112/openneuro.ds004696.v1.0.1

Modality: ieeg Subjects: 8 Recordings: 8 License: CC0 Source: openneuro Citations: 1.0

Metadata: Good (80%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004696

dataset = DS004696(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 = DS004696(cache_dir="./data", subject="01")

Advanced query

dataset = DS004696(
    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{ds004696,
  title = {HAPwave_bids},
  author = {Ojeda Valencia, G. and Gregg, N. and Huang, H. and Lundstrom, B. and Brinkmann, B. and Pal Attia1, T. and Van Gompel, J. and Bernstein,M. and In, M. and Huston, J. and Worrell1, G. and Miller, K. and Hermes, D.},
  doi = {10.18112/openneuro.ds004696.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds004696.v1.0.1},
}

About This Dataset#

Information

This dataset contains intracranial EEG (iEEG) recordings from 8 patients during single pulse electrical stimulation used in the publication of: Ojeda Valencia G, Gregg N, Huang H, Lundstrom B, Brinkmann B, Pal Attia T, Van Gompel J, Bernstein M, In MH, Huston J, Worrell G, Miller KJ, and Hermes D. 2023. Signatures of electrical stimulation driven network interactions in the human limbic system. Journal of Neuroscience (in press).

License

This dataset is made available under the Public Domain Dedication and License CC v1.0, whose full text can be found at https://creativecommons.org/publicdomain/zero/1.0/.

View full README

Information

This dataset contains intracranial EEG (iEEG) recordings from 8 patients during single pulse electrical stimulation used in the publication of: Ojeda Valencia G, Gregg N, Huang H, Lundstrom B, Brinkmann B, Pal Attia T, Van Gompel J, Bernstein M, In MH, Huston J, Worrell G, Miller KJ, and Hermes D. 2023. Signatures of electrical stimulation driven network interactions in the human limbic system. Journal of Neuroscience (in press).

License

This dataset is made available under the Public Domain Dedication and License CC v1.0, whose full text can be found at https://creativecommons.org/publicdomain/zero/1.0/. We hope that all users will follow the ODC Attribution/Share-Alike Community Norms (http://www.opendatacommons.org/norms/odc-by-sa/); in particular, while not legally required, we hope that all users of the data will acknowledge by citing the following in any publication: Ojeda Valencia G, Gregg N, Huang H, Lundstrom B, Brinkmann B, Pal Attia T, Van Gompel J, Bernstein M, In MH, Huston J, Worrell G, Miller KJ, and Hermes D. 2023. Signatures of electrical stimulation driven network interactions in the human limbic system. Journal of Neuroscience. DOI: https://doi.org/10.1523/JNEUROSCI.2201-22.2023

Task Description

Patients were resting in the hospital bed, while single pulse stimulation was performed. The stimulation had a duration of 200 microseconds, was biphasic and had an amplitude of 6mA. For subject 7 stimulation amplitude was sometimes reduced to 4mA to minimize interictal responses.

Code

Code to analyses these data is available at: MultimodalNeuroimagingLab/HAPwave

Dataset

This data is organized according to the Brain Imaging Data Structure specification (BIDS version 1.12.0). A community- driven specification for organizing neurophysiology data along with its metadata. For more information on this data specification, see https://bids-specification.readthedocs.io/en/stable/ Each subject has their own folder (e.g., ‘sub-01’) containing intracranial EEG (iEEG) recordings from 8 patients during single pulse electrical stimulation, as well as the metadata needed to understand the raw data and event timing.

Acknowledgements

This project was funded by the National Institute Of Mental Health of the National Institutes of Health Brain Initiative under Award Number R01 MH122258, “CRCNS: Processing speed in the human connectome across the lifespan”. The overall goal of this project is to develop a large database of single pulse stimulation data and develop tools to advance our understanding of the human connectome across the lifespan. The data was collected by Dora Hermes, Nick Gregg, Brian Lundstrom, Cindy Nelson, Gabriela Ojeda Valencia, Gregg Worrell and Kai J. Miller. The BIDS formatting was performed by Dora Hermes and Gabriela Ojeda Valencia.

Contact

Please contact Dora Hermes (hermes.dora@mayo.edu) or Gabriela Ojeda Valencia (OjedaValencia.Alma@mayo.edu) for questions.

Dataset Information#

Dataset ID	`DS004696`
Title	HAPwave_bids
Year	2023
Authors	Ojeda Valencia, G., Gregg, N., Huang, H., Lundstrom, B., Brinkmann, B., Pal Attia1, T., Van Gompel, J., Bernstein,M., In, M., Huston, J., Worrell1, G., Miller, K., Hermes, D.
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds004696.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: 8
Recordings: 8
Tasks: 1

Channels & sampling rate

Channels: Varies
Sampling rate (Hz): Varies
Duration (hours): 0.0

API Reference#

Use the DS004696 class to access this dataset programmatically.

class eegdash.dataset.DS004696(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004696. Modality: ieeg; Experiment type: Clinical/Intervention; Subject type: Epilepsy. Subjects: 10; recordings: 5243; 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/ds004696 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004696

Examples

>>> from eegdash.dataset import DS004696
>>> dataset = DS004696(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