DS006519#

Dataset of intracranial EEG during cortical stimulations evoking negative motor responses

Access recordings and metadata through EEGDash.

Citation: Andrei Barborica, Cristina Ghita, Laurentiu Tofan, Irina Oane, Ioana Mindruta (2025). Dataset of intracranial EEG during cortical stimulations evoking negative motor responses. 10.18112/openneuro.ds006519.v1.0.0

Modality: ieeg Subjects: 21 Recordings: 397 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006519

dataset = DS006519(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 = DS006519(cache_dir="./data", subject="01")

Advanced query

dataset = DS006519(
    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{ds006519,
  title = {Dataset of intracranial EEG during cortical stimulations evoking negative motor responses},
  author = {Andrei Barborica and Cristina Ghita and Laurentiu Tofan and Irina Oane and Ioana Mindruta},
  doi = {10.18112/openneuro.ds006519.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds006519.v1.0.0},
}

About This Dataset#

In this dataset we included iEEG recordings of responses to 41 intracranial high frequency stimulations evoking negative motor responses, in 23 patients undergoing stereo-EEG presurgical evaluation for drug-resistant epilepsy.

The dataset contains 24 seconds of iEEG data around each stimulation, 9-10 seconds before the start of the stimulation, up to 5 seconds of intracranial stimulation and 9-10 seconds after the end of the stimulation. Each recording contains two 5 second epochs, pre-stimulation (used as baseline in the connectivity analysis) and post-stimulation.

We have used high-frequency bipolar stimulations of different areas of the brain, using biphasic pulses having a duration of 1 ms, at a frequency of 43.2 Hz (alternating polarity) or 50 Hz (non-alternating), current intensity between 0.25 to 3 mA, for up to 5 s.

The contact pair on which stimulation is applied, the current intensity level and evoked effect are specified in the events tsv.

Not all patients in which stimulations evoked negative motor responses met the inclusion criteria for network analysis that requires running the freesurfer pipeline, for instance patients having prior resections, therefore there are subjects that do not contain anatomy data and are not included in the dataset. However, they are included in the numbering of patients to match the table in the companion manuscript.

Contact: andrei.barborica@fizica.unibuc.ro

Dataset Information#

Dataset ID	`DS006519`
Title	Dataset of intracranial EEG during cortical stimulations evoking negative motor responses
Year	2025
Authors	Andrei Barborica, Cristina Ghita, Laurentiu Tofan, Irina Oane, Ioana Mindruta
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006519.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: 21
Recordings: 397
Tasks: 1

Channels & sampling rate

Channels: 33 (10), 35 (10), 37 (8), 32 (4), 31 (4), 52 (4), 41 (4), 150 (2), 25 (2), 63 (2), 56 (2), 176 (2), 61 (2), 47 (2), 69 (2), 101 (2), 89 (2), 43 (2), 34 (2), 40 (2)
Sampling rate (Hz): 4096.0 (62), 512.0 (8)
Duration (hours): 0.0

API Reference#

Use the DS006519 class to access this dataset programmatically.

class eegdash.dataset.DS006519(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006519. Modality: ieeg; Experiment type: Clinical/Intervention; Subject type: Epilepsy. Subjects: 21; recordings: 35; 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/ds006519 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006519

Examples

>>> from eegdash.dataset import DS006519
>>> dataset = DS006519(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