DS005293#

95 By BP

Access recordings and metadata through EEGDash.

Citation: Zhao Xiangyue, Zhou Jingyao, Zhang Libo, Duan Haoqing, Wei Shiyu, Bi Yanzhi, Hu Li (2024). 95 By BP. 10.18112/openneuro.ds005293.v1.0.0

Modality: eeg Subjects: 95 Recordings: 3996 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS005293

dataset = DS005293(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 = DS005293(cache_dir="./data", subject="01")

Advanced query

dataset = DS005293(
    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{ds005293,
  title = {95 By BP},
  author = {Zhao Xiangyue and Zhou Jingyao and Zhang Libo and Duan Haoqing and Wei Shiyu and Bi Yanzhi and Hu Li},
  doi = {10.18112/openneuro.ds005293.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds005293.v1.0.0},
}

About This Dataset#

1.Study introduction: In this experiment, the intensity of laser stimulation varied individually based on participants’pain thresholds. Prior to the formal commencement of the experiment, participants underwent a series of stimuli of increasing intensity, incrementally rising from low to high in 0.25J steps until reaching the maximum tolerable intensity for each individual. Participants were instructed to verbally report the perceived pain intensity of each laser stimulation using a numerical rating scale (NRS) ranging from 0 (no sensation) to 10 (the maximum tolerable level of pain), with 4 indicating the pain perception threshold akin to a pricking sensation. In this study, each participant received four levels of stimulation intensity, corresponding to ratings of 2, 4, 6, and 8 on the NRS (E1: 2.0 ± 0.2 J; E2: 2.7 ± 0.3 J; E3: 3.4 ± 0.3 J; E4: 4.1 ± 0.4 J). 2.Participant task information(description of the experiment): Participants received laser stimulation and subsequently provided pain intensity ratings one by one. 3.Participant instructions(as exact as possible): The participants were instructed to relax and sit comfortably on a chair, focusing their attention on the sensation of laser stimulation. The experimental environment was quiet, with a constant room temperature, and no unrelated individuals were present. Both the participants and the experimenter wore protective goggles. The experimental design employed a two-factor repeated measures within-subject design, with 4 levels of stimulation intensity crossed with 2 levels of stimulation location (left hand dorsum and right hand dorsum), resulting in a total of 8 conditions (stimulation locations: left hand dorsum and right hand dorsum). There were 10 trials for each condition, totaling 80 trials. Participants received pain stimulation and provided ratings for each trial individually.

Dataset Information#

Dataset ID	`DS005293`
Title	95 By BP
Year	2024
Authors	Zhao Xiangyue, Zhou Jingyao, Zhang Libo, Duan Haoqing, Wei Shiyu, Bi Yanzhi, Hu Li
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds005293.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: 95
Recordings: 3996
Tasks: 1

Channels & sampling rate

Channels: 60 (570), 63 (570)
Sampling rate (Hz): 1000.0
Duration (hours): 0.0

API Reference#

Use the DS005293 class to access this dataset programmatically.

class eegdash.dataset.DS005293(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds005293. Modality: eeg; Experiment type: Perception; Subject type: Healthy. Subjects: 95; recordings: 570; 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/ds005293 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds005293

Examples

>>> from eegdash.dataset import DS005293
>>> dataset = DS005293(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