DS004033#

Electrode walking study

Access recordings and metadata through EEGDash.

Citation: Joanna Scanlon, Nadine Jacobsen, Marike Maack, Stefan Debener (2022). Electrode walking study. 10.18112/openneuro.ds004033.v1.0.0

Modality: eeg Subjects: 18 Recordings: 293 License: CC0 Source: openneuro Citations: 2.0

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004033

dataset = DS004033(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 = DS004033(cache_dir="./data", subject="01")

Advanced query

dataset = DS004033(
    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{ds004033,
  title = {Electrode walking study},
  author = {Joanna Scanlon and Nadine Jacobsen and Marike Maack and Stefan Debener},
  doi = {10.18112/openneuro.ds004033.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds004033.v1.0.0},
}

About This Dataset#

The electrode and synchronized walking study: Participants performed 3 tasks outside: eyes open/eyes close, standing, walking alone & walking with experimenter oddball task, and 3 walking with experimenter tasks Only part of the second task (standing and walking oddball) was used for the first paper. Each of 18 participants performed the task using both active (session 1) and passive (session 2) electrodes, in counterbalanced order Task 1: Eyes open / Eyes closed; 1. Participant stands facing a wall with eyes open (or closed) for 1 min. Then 1 min of eyes closed (or open). This is counterbalanced and repeated. 2X each type. Task 2: Oddball task: Standing / Walking alone / Walking together. Participants performed an oddball task in which they listened to the tones through headphones and silently counted the deviant tones. The tones were 800 and 1000 Hz, with the standard/target status counterbalanced across participants. During the walking conditions, participants walked clockwise around an outdoor (roofed) basketball arena, following pylons. Each block was about 5-6 minutes. Blocks were counterbalanced and repeated 2X each. Task 3: Walking together: Natural / Control / Synchronize 3. Participants walked with the experimenter for 6 minutes in 3 conditions. The experimenter listened to a metronome while walking, and synchronized their steps with it (also true during walking together oddball task). During Natural walking, participant is just asked to walk with the experimenter, with no other instruction. In Control, participant is blinded using side-blinders which block their view of the experimenter. In Synchronize, participants try to synchronize their steps with the experimenter. All walking & oddball conditions started with a countdown (this has a specific trigger for oddball conds, not for task 3 conds. It plays during the first ~ 12 seconds of the 6 min trial

Joanna Scanlon (Feb 2022)

Dataset Information#

Dataset ID	`DS004033`
Title	Electrode walking study
Year	2022
Authors	Joanna Scanlon, Nadine Jacobsen, Marike Maack, Stefan Debener
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds004033.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: 18
Recordings: 293
Tasks: 1

Channels & sampling rate

Channels: 64 (36), 67 (36)
Sampling rate (Hz): 500.0
Duration (hours): 0.0

API Reference#

Use the DS004033 class to access this dataset programmatically.

class eegdash.dataset.DS004033(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004033. Modality: eeg; Experiment type: Motor. Subjects: 18; recordings: 36; tasks: 2.

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/ds004033 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004033

Examples

>>> from eegdash.dataset import DS004033
>>> dataset = DS004033(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