DS006897: eeg dataset, 41 subjects#

No effect of rhythmic visual stimulation on experimental pain perception

Access recordings and metadata through EEGDash.

Citation: Roy, N., Coll, MP, Coll LAB (2025). No effect of rhythmic visual stimulation on experimental pain perception. 10.18112/openneuro.ds006897.v1.0.0

Modality: eeg Subjects: 41 Recordings: 41 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006897

dataset = DS006897(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 = DS006897(cache_dir="./data", subject="01")

Advanced query

dataset = DS006897(
    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{ds006897,
  title = {No effect of rhythmic visual stimulation on experimental pain perception},
  author = {Roy, N. and Coll, MP and Coll LAB},
  doi = {10.18112/openneuro.ds006897.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds006897.v1.0.0},
}

About This Dataset#

No effect of rhythmic visual stimulation on experimental pain perception

This dataset contains EEG recordings from 41 participants, collected as part of a study investigating the effect of rhythmic visual stimulation on experimental pain perception. Data were collected at Université Laval, Québec, Canada. This work was funded by the Fonds de recherche du Québec – Santé (FRQS) and the Quebec Pain Research Network (QPRN). For full details on the dataset and study design, please refer to the related publication. The analytical code used to process and analyze the data is publicly available at mpcoll/2025_painrvs.

Related publication

Roy, N., Deslauriers, C., Côté-Cazes, T., Etcheverry, A., & Coll, M.-P. ([Year]). No effect of rhythmic visual stimulation on experimental pain perception. [Journal Name],*[Volume]*([Issue]), [Page range]. [DOI or URL]

Notes

Participant numbering in this dataset starts at 12. Participants 1 to 11 were pilot participants who completed earlier iterations of the experimental protocol or experienced significant technical issues, and are therefore not included.

Dataset Information#

Dataset ID	`DS006897`
Title	No effect of rhythmic visual stimulation on experimental pain perception
Author (year)	—
Canonical	—
Importable as	`DS006897`
Year	2025
Authors	Roy, N., Coll, MP, Coll LAB
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006897.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: 41
Recordings: 41
Tasks: 1

Channels & sampling rate

Channels: 63
Sampling rate (Hz): 500.0
Duration (hours): Not calculated

Electrode Layout#

Electrode layout — EEG · 63 sensors — 63 channels

Dataset Statistics#

Age distribution (n=41, range 18–40 yr)

152025303540

Sex distribution

21

20

Female Male Total: 41

Channel counts: 63 ch (n=41 recordings)

Sampling frequencies: 500.0 Hz (n=41 recordings)

NEMAR Processing Statistics#

The plots below are generated by NEMAR’s automated EEG pipeline. The histogram shows pipeline success for data cleaning and ICA decomposition, the percentage of data frames and EEG channels retained after artefact removal, line noise per channel (RMS, dB), and the age/gender distribution of participants.

HED event descriptors word cloud

File Explorer#

Browse the BIDS file structure of this dataset. Records are fetched on demand from the EEGDash catalog the first time you open the explorer.

Files: —

Size: —

Subjects: —

Click to load file structure…

API Reference#

Use the DS006897 class to access this dataset programmatically.

class eegdash.dataset.DS006897(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

No effect of rhythmic visual stimulation on experimental pain perception

Study:: ds006897 (OpenNeuro)
Author (year):: nan
Canonical:: —

Also importable as: DS006897, nan.

Modality: eeg. Subjects: 41; recordings: 41; 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/ds006897 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006897 DOI: https://doi.org/10.18112/openneuro.ds006897.v1.0.0

Examples

>>> from eegdash.dataset import DS006897
>>> dataset = DS006897(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: str, overwrite: bool = False, offset: int = 0)[source]#

Save datasets to files by creating one subdirectory for each dataset:

path/
    0/
        0-raw.fif | 0-epo.fif
        description.json
        raw_preproc_kwargs.json (if raws were preprocessed)
        window_kwargs.json (if this is a windowed dataset)
        window_preproc_kwargs.json  (if windows were preprocessed)
        target_name.json (if target_name is not None and dataset is raw)
    1/
        1-raw.fif | 1-epo.fif
        description.json
        raw_preproc_kwargs.json (if raws were preprocessed)
        window_kwargs.json (if this is a windowed dataset)
        window_preproc_kwargs.json  (if windows were preprocessed)
        target_name.json (if target_name is not None and dataset is raw)