DS006126#

TDCS Modulation of Visual Cortex in Motor Imagery

Access recordings and metadata through EEGDash.

Citation: Anthony Mensah, Gleb Perevoznyuk, Artyom Batov, Aleksandra S. Pleskovskaya (2025). TDCS Modulation of Visual Cortex in Motor Imagery. 10.18112/openneuro.ds006126.v1.0.0

Modality: eeg Subjects: 5 Recordings: 652 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006126

dataset = DS006126(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 = DS006126(cache_dir="./data", subject="01")

Advanced query

dataset = DS006126(
    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{ds006126,
  title = {TDCS Modulation of Visual Cortex in Motor Imagery},
  author = {Anthony Mensah and Gleb Perevoznyuk and Artyom Batov and Aleksandra S. Pleskovskaya},
  doi = {10.18112/openneuro.ds006126.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds006126.v1.0.0},
}

About This Dataset#

TDCS Neuromodulated Motor Imagery TMS Dataset

Research/Experiment Description

[Your research description goes here]

Dataset Information#

Dataset ID	`DS006126`
Title	TDCS Modulation of Visual Cortex in Motor Imagery
Year	2025
Authors	Anthony Mensah, Gleb Perevoznyuk, Artyom Batov, Aleksandra S. Pleskovskaya
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006126.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: 5
Recordings: 652
Tasks: 6

Channels & sampling rate

Channels: 3
Sampling rate (Hz): 5000.0
Duration (hours): 0.0

API Reference#

Use the DS006126 class to access this dataset programmatically.

class eegdash.dataset.DS006126(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006126. Modality: eeg; Experiment type: Motor; Subject type: Healthy. Subjects: 5; recordings: 90; tasks: 6.

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/ds006126 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006126

Examples

>>> from eegdash.dataset import DS006126
>>> dataset = DS006126(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