DS006945: eeg dataset, 5 subjects#

Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles)

Access recordings and metadata through EEGDash.

Citation: Shantanu Sarkar, Kevin Nathan, Jose L. Contreras-Vidal (2025). Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles). 10.18112/openneuro.ds006945.v1.2.1

Modality: eeg Subjects: 5 Recordings: 14 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006945

dataset = DS006945(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS006945(cache_dir="./data", subject="01")

Advanced query

dataset = DS006945(
    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{ds006945,
  title = {Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles)},
  author = {Shantanu Sarkar and Kevin Nathan and Jose L. Contreras-Vidal},
  doi = {10.18112/openneuro.ds006945.v1.2.1},
  url = {https://doi.org/10.18112/openneuro.ds006945.v1.2.1},
}

About This Dataset#

Neuroimaging Data Collected During Kinesthetic Motor Imagery of Walking vs. Rest This dataset includes multimodal neuroimaging recordings from five participants performing kinesthetic motor imagery (KI) while viewing themselves walking in an exoskeleton. The dataset includes synchronized MRI (structural and functional) and EEG recordings organized according to the BIDS specification. Functional MRI data were acquired in two runs while participants viewed a 10-minute video, along with a separate baseline scan during which participants simulated a resting state for approximately 5 minutes. MRI sessions were conducted after participants completed nine sessions of EEG‑controlled exoskeleton walking and standing experiments. Dataset link: <a href=”https://openneuro.org/datasets/ds006940” target=”_blank”> https://openneuro.org/datasets/ds006940 </a> MRI Acquisition: - Scanner: Philips Ingenia 3.0T (Koninklijke Philips N.V., The Netherlands) - Structural scans: T1‑weighted anatomical images - Functional scans (fMRI): Participants viewed a 10‑minute video of themselves walking in the exoskeleton, filmed from a first‑person perspective. The video contained 11 Stop‑Walk‑Stop (SWS) cycles. During viewing, participants were instructed to evoke KI in synchrony with the exoskeleton movements. - Baseline condition: Participants mentally simulated resting state for approximately 5 minutes while fMRI data was recorded.

View full README

Neuroimaging Data Collected During Kinesthetic Motor Imagery of Walking vs. Rest This dataset includes multimodal neuroimaging recordings from five participants performing kinesthetic motor imagery (KI) while viewing themselves walking in an exoskeleton. The dataset includes synchronized MRI (structural and functional) and EEG recordings organized according to the BIDS specification. Functional MRI data were acquired in two runs while participants viewed a 10-minute video, along with a separate baseline scan during which participants simulated a resting state for approximately 5 minutes. MRI sessions were conducted after participants completed nine sessions of EEG‑controlled exoskeleton walking and standing experiments. Dataset link: <a href=”https://openneuro.org/datasets/ds006940” target=”_blank”> https://openneuro.org/datasets/ds006940 </a> MRI Acquisition: - Scanner: Philips Ingenia 3.0T (Koninklijke Philips N.V., The Netherlands) - Structural scans: T1‑weighted anatomical images - Functional scans (fMRI): Participants viewed a 10‑minute video of themselves walking in the exoskeleton, filmed from a first‑person perspective. The video contained 11 Stop‑Walk‑Stop (SWS) cycles. During viewing, participants were instructed to evoke KI in synchrony with the exoskeleton movements. - Baseline condition: Participants mentally simulated resting state for approximately 5 minutes while fMRI data was recorded.

EEG Acquisition: - MR‑compatible EEG cap (Brain Products GmbH, Gilching, Germany) - Electrode locations are provided in EEGLAB format. - 59 scalp channels + 4 EOG channels + 1 ECG channel

Stimuli: - A video stimulus (stimuli/walking_exoskeleton_S1.mp4) was presented during walking tasks.

Participants: Five healthy adults out of seven participated in the EEG‑controlled exoskeleton experiments. Participants S6 and S7 did not undergo MRI scanning due to a pause in data collection during the COVID‑19 pandemic. <h3>Folder Structure (Example: Participant S1)</h3> <hr> <pre>

├── dataset_description.json
├── README
├── derivatives
│   └── sub-01
│       └── ses-01
│           ├── anat
│           │   └── sub-01_ses-01_T1w.nii
│           ├── dwi
│           │   ├── sub-01_ses-01_run-001_dwi.json
│           │   ├── sub-01_ses-01_run-001_dwi.bval
│           │   ├── sub-01_ses-01_run-001_dwi.bvec
│           │   └── sub-01_ses-01_run-001_dwi.nii.gz
│           │
│           └── spm
│               ├── sub-01_ses-01_beta_0001.nii
│               ├── ...
│               ├── sub-01_ses-01_beta_0008.nii
│               ├── sub-01_ses-01_con_0001.nii
│               ├── ...
│               ├── sub-01_ses-01_con_0004.nii
│               ├── sub-01_ses-01_smpt_0001.nii
│               ├── ...
│               ├── sub-01_ses-01_smpt_0004.nii
│               ├── sub-01_ses-01_mask.mat
│               ├── sub-01_ses-01_resms.mat
│               ├── sub-01_ses-01_rpv.mat
│               └── sub-01_ses-01_spm.mat
│
├── stimuli
│   └── walking_exoskeleton_S1.mp4
│
├── sub-01
│   └── ses-01
│       ├── anat
│       │   ├── sub-01_ses-01_T1w.json
│       │   └── sub-01_ses-01_T1w.nii
│       ├── eeg
│       │   ├── sub-01_ses-01_coordsystem.json
│       │   ├── sub-01_ses-01_electrodes.json
│       │   ├── sub-01_ses-01_electrodes.tsv
│       │   ├── sub-01_ses-01_task-baseline_eeg.eeg
│       │   ├── sub-01_ses-01_task-baseline_eeg.json
│       │   ├── sub-01_ses-01_task-baseline_eeg.vhdr
│       │   ├── sub-01_ses-01_task-baseline_eeg.vmrk
│       │   ├── sub-01_ses-01_task-walking1_eeg.eeg
│       │   ├── ...
│       │   └── sub-01_ses-01_task-walking2_eeg.vmrk
│       │
│       └── func
│           ├── sub-01_ses-01_task-baseline_run-001_bold.json
│           ├── sub-01_ses-01_task-baseline_run-001_bold.nii.gz
│           ├── sub-01_ses-01_task-walking1_run-001_bold.json
│           ├── sub-01_ses-01_task-walking1_run-001_bold.nii.gz
│           ├── sub-01_ses-01_task-walking2_run-001_bold.json
│           └── sub-01_ses-01_task-walking2_run-001_bold.nii.gz

</pre>

Validation Data

A validation file (derivatives/MRI_DataValidation.xls) is provided to summarize dataset completeness and quality checks. - Sheet: Files

Lists presence/absence of EEG, MRI, and SPM outputs across subjects (S1–S5). Includes counts for beta, con, spmT maps, and DTI volumes.

  • Sheet: VMRK-R128 Reports event marker counts (R128 triggers) for baseline, walking1, and walking2 tasks.

  • Sheet: EEG-Duration Provides task durations (minutes) for ‘baseline’, ‘walking1’, and ‘walking2’ EEG recordings.

Notes on Organization

* Raw data (anat, func, eeg) are stored under each subject directory (sub-XX/ses-YY). * Derivatives: Preprocessed outputs are stored separately under derivatives/sub-XX/ses-YY, including:

&emsp;- Statistical Parametric Mapping (SPM) outputs

&emsp;- SPM-normalized (warped) anatomical scans

&emsp;- Diffusion Tensor Imaging (DTI) derivatives

&emsp;- Validation Excel file

* The video stimulus is stored in the top-level stimuli/ folder. * Naming conventions follow BIDS entities:

&emsp;- sub-&lt;label&gt; : subject identifier

&emsp;- ses-&lt;label&gt; : session identifier

&emsp;- task-&lt;label&gt; : task name (baseline, walking1, walking2)

&emsp;- run-&lt;index&gt; : run number

Citation

If you use this dataset, please cite the associated study and acknowledge the contributors.

Dataset Information#

Dataset ID

DS006945

Title

Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles)

Author (year)

Sarkar2025_T1_Weighted_Structural

Canonical

—

Importable as

DS006945, Sarkar2025_T1_Weighted_Structural

Year

2025

Authors

Shantanu Sarkar, Kevin Nathan, Jose L. Contreras-Vidal

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds006945.v1.2.1

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds006945,
  title = {Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles)},
  author = {Shantanu Sarkar and Kevin Nathan and Jose L. Contreras-Vidal},
  doi = {10.18112/openneuro.ds006945.v1.2.1},
  url = {https://doi.org/10.18112/openneuro.ds006945.v1.2.1},
}

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: 5

  • Recordings: 14

  • Tasks: 3

Channels & sampling rate

  • Channels: 64

  • Sampling rate (Hz): 5000.0

  • Duration (hours): 2.110611111111111

Tags

  • Pathology: Healthy

  • Modality: Visual

  • Type: Motor

Files & format

  • Size on disk: 5.4 GB

  • File count: 14

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds006945.v1.2.1

Provenance

API Reference#

Use the DS006945 class to access this dataset programmatically.

class eegdash.dataset.DS006945(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles)

Study:

ds006945 (OpenNeuro)

Author (year):

Sarkar2025_T1_Weighted_Structural

Canonical:

—

Also importable as: DS006945, Sarkar2025_T1_Weighted_Structural.

Modality: eeg; Experiment type: Motor; Subject type: Healthy. Subjects: 5; recordings: 14; tasks: 3.

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/ds006945 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006945 DOI: https://doi.org/10.18112/openneuro.ds006945.v1.2.1

Examples

>>> from eegdash.dataset import DS006945
>>> dataset = DS006945(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#