.. This documentation page is generated during the Sphinx build. The underlying code is manually maintained and not autogenerated. eegdash.dataset.DS006648 ======================== participants.tsv (OpenNeuro ``ds006648``). Access recordings and metadata through EEGDash. .. rst-class:: sd-badges :bdg-light:`Modality: ['eeg']` :bdg-light:`Tasks: 0` :bdg-light:`License: CC0` :bdg-light:`Subjects: 0` :bdg-light:`Recordings: 0` :bdg-light:`Source: openneuro` Dataset Information ------------------- .. list-table:: :widths: 25 75 :header-rows: 0 * - Dataset ID - ``DS006648`` * - Title - participants.tsv * - Year - 2025 * - Authors - Soma Chaudhuri, Joydeep Bhattacharya * - License - CC0 * - Citation / DOI - `doi:10.18112/openneuro.ds006648.v1.0.0 `__ * - Source links - `OpenNeuro `__ | `NeMAR `__ | `Source URL `__ .. dropdown:: Copy-paste BibTeX :class-container: sd-shadow-sm :class-title: sd-bg-light .. code-block:: bibtex @dataset{ds006648, title = {participants.tsv}, author = {Soma Chaudhuri and Joydeep Bhattacharya}, doi = {10.18112/openneuro.ds006648.v1.0.0}, url = {https://doi.org/10.18112/openneuro.ds006648.v1.0.0}, } Highlights ---------- .. grid:: 1 2 3 3 :gutter: 2 .. grid-item-card:: Subjects & recordings :class-card: sd-border-1 - Subjects: 0 - Recordings: 0 - Tasks: 0 .. grid-item-card:: Channels & sampling rate :class-card: sd-border-1 - Channels: 70 - Sampling rate (Hz): 512.0 - Duration (hours): 0 .. grid-item-card:: Tasks & conditions :class-card: sd-border-1 - Tasks: 0 - Experiment type: Unknown - Subject type: Unknown .. grid-item-card:: Files & format :class-card: sd-border-1 - Size on disk: Unknown - File count: Unknown - Format: Unknown .. grid-item-card:: License & citation :class-card: sd-border-1 - License: CC0 - DOI: doi:10.18112/openneuro.ds006648.v1.0.0 .. grid-item-card:: Provenance :class-card: sd-border-1 - Source: openneuro - OpenNeuro: `ds006648 `__ - NeMAR: `ds006648 `__ Quickstart ---------- **Install** .. code-block:: bash pip install eegdash **Load a recording** .. code-block:: python from eegdash.dataset import DS006648 dataset = DS006648(cache_dir="./data") recording = dataset[0] raw = recording.load() **Filter/query** .. tab-set:: .. tab-item:: Basic .. code-block:: python dataset = DS006648(cache_dir="./data", subject="01") .. tab-item:: Advanced .. code-block:: python dataset = DS006648( cache_dir="./data", query={"subject": {"$in": ["01", "02"]}}, ) Quality & caveats ----------------- - No dataset-specific caveats are listed in the available metadata. API --- .. currentmodule:: eegdash.dataset .. autoclass:: eegdash.dataset.DS006648 :members: __init__, save :show-inheritance: :member-order: bysource See Also -------- * :class:`eegdash.dataset.EEGDashDataset` * :mod:`eegdash.dataset` * `OpenNeuro dataset page `__ * `NeMAR dataset page `__