DS004127#

Somatosensory Cortex Rat DISC Data

Access recordings and metadata through EEGDash.

Citation: Amada Abrego, Wasif Khan, John P Seymour (2022). Somatosensory Cortex Rat DISC Data. 10.18112/openneuro.ds004127.v3.0.0

Modality: ieeg Subjects: 8 Recordings: 222 License: CC0 Source: openneuro Citations: 1.0

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004127

dataset = DS004127(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS004127(cache_dir="./data", subject="01")

Advanced query

dataset = DS004127(
    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{ds004127,
  title = {Somatosensory Cortex Rat DISC Data},
  author = {Amada Abrego and Wasif Khan and John P Seymour},
  doi = {10.18112/openneuro.ds004127.v3.0.0},
  url = {https://doi.org/10.18112/openneuro.ds004127.v3.0.0},
}

About This Dataset#

Project Title: DISC Validation in Rat Somatosensory Cortex Project ID: 000

Expected experimentation period: Start date: N/A End date: N/A

Project Description: DISC were implanted in rat somatosensory cortex. While anesthetized, whiskers were being stimulated using an air puffer. Task name corresponds to the id of the whisker being stimulated. For more information of the task go to our biorxiv’s paper: https://www.biorxiv.org/content/10.1101/2021.09.20.460996v3

Participant categories: N/A

Trigger channels: N/A

Events: N/A

Dataset Information#

Dataset ID

DS004127

Title

Somatosensory Cortex Rat DISC Data

Year

2022

Authors

Amada Abrego, Wasif Khan, John P Seymour

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds004127.v3.0.0

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds004127,
  title = {Somatosensory Cortex Rat DISC Data},
  author = {Amada Abrego and Wasif Khan and John P Seymour},
  doi = {10.18112/openneuro.ds004127.v3.0.0},
  url = {https://doi.org/10.18112/openneuro.ds004127.v3.0.0},
}

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: 8

  • Recordings: 222

  • Tasks: —

Channels & sampling rate

  • Channels: 128 (28), 112 (9), 104 (9), 102 (9), 110 (9), 105 (6), 106 (2), 111

  • Sampling rate (Hz): 20000.0

  • Duration (hours): 0.0

Tags

  • Pathology: Other

  • Modality: Tactile

  • Type: Other

Files & format

  • Size on disk: 187.5 GB

  • File count: 222

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds004127.v3.0.0

Provenance

API Reference#

Use the DS004127 class to access this dataset programmatically.

class eegdash.dataset.DS004127(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004127. Modality: ieeg; Experiment type: Other; Subject type: Other. Subjects: 8; recordings: 73; tasks: 11.

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/ds004127 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004127

Examples

>>> from eegdash.dataset import DS004127
>>> dataset = DS004127(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#