DS006033#

Synchronous EEG and fMRI dataset on inner speech

Access recordings and metadata through EEGDash.

Citation: Foteini Simistira Liwicki (2025). Synchronous EEG and fMRI dataset on inner speech. 10.18112/openneuro.ds006033.v1.0.1

Modality: eeg Subjects: 3 Recordings: 63 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006033

dataset = DS006033(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS006033(cache_dir="./data", subject="01")

Advanced query

dataset = DS006033(
    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{ds006033,
  title = {Synchronous EEG and fMRI dataset on inner speech},
  author = {Foteini Simistira Liwicki},
  doi = {10.18112/openneuro.ds006033.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006033.v1.0.1},
}

About This Dataset#

Inner Speech EEG-fMRI Dataset

Description

This dataset contains simultaneous EEG-fMRI recordings for inner speech experiments. Data were collected using a 3T MRI scanner and 64-channel BrainProducts EEG system. The EEG data have undergone preprocessing, including pulse artifact removal, using the BrainVision Analyzer software. No further data transformations have been applied to ensure the dataset remains BIDS-compliant as “raw”.

View full README

Inner Speech EEG-fMRI Dataset

Description

This dataset contains simultaneous EEG-fMRI recordings for inner speech experiments. Data were collected using a 3T MRI scanner and 64-channel BrainProducts EEG system. The EEG data have undergone preprocessing, including pulse artifact removal, using the BrainVision Analyzer software. No further data transformations have been applied to ensure the dataset remains BIDS-compliant as “raw”.

Subjects

  • Number of subjects: 3

  • Sessions per subject: 2

  • Tasks: Inner speech

Experimental Protocol

  • Each trial includes a fixation period (2s), stimulus display (2s), and rest (12s).

  • 8 words were presented in random order, each repeated 40 times.

  • EEG sampled at 5000 Hz, fMRI acquired with TR=2s.

Data Organization

  • Functional MRI data: sub-xx/ses-xx/func/

  • EEG data: sub-xx/ses-xx/eeg/

  • Event markers: events.tsv

  • BIDS-compatible metadata included in JSON sidecars.

Contact

For inquiries, contact: Foteini Simistira Liwicki (Foteini.liwicki@ltu.se)

Dataset Information#

Dataset ID

DS006033

Title

Synchronous EEG and fMRI dataset on inner speech

Year

2025

Authors

Foteini Simistira Liwicki

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds006033.v1.0.1

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds006033,
  title = {Synchronous EEG and fMRI dataset on inner speech},
  author = {Foteini Simistira Liwicki},
  doi = {10.18112/openneuro.ds006033.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006033.v1.0.1},
}

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: 3

  • Recordings: 63

  • Tasks: 1

Channels & sampling rate

  • Channels: 64

  • Sampling rate (Hz): 5000.0

  • Duration (hours): 0.0

Tags

  • Pathology: Healthy

  • Modality: Visual

  • Type: Other

Files & format

  • Size on disk: 15.3 GB

  • File count: 63

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds006033.v1.0.1

Provenance

API Reference#

Use the DS006033 class to access this dataset programmatically.

class eegdash.dataset.DS006033(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006033. Modality: eeg; Experiment type: Other; Subject type: Healthy. Subjects: 3; recordings: 5; 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/ds006033 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006033

Examples

>>> from eegdash.dataset import DS006033
>>> dataset = DS006033(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#