| --- |
| pretty_name: "Categorized Free Recall with Open-Loop Stimulation at Encoding" |
| license: cc0-1.0 |
| tags: |
| - ieeg |
| - neuroscience |
| - eegdash |
| - brain-computer-interface |
| - pytorch |
| - visual |
| - clinical-intervention |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| --- |
| |
| # Categorized Free Recall with Open-Loop Stimulation at Encoding |
|
|
| **Dataset ID:** `ds005491` |
|
|
| _Herrema2024_Categorized_ |
|
|
| **Canonical aliases:** `catFR_open_loop` · `RAM_catFR` · `catFR_stim` |
|
|
| > **At a glance:** IEEG · Visual clinical/intervention · unknown · 19 subjects · 51 recordings · CC0 |
|
|
| ## Load this dataset |
|
|
| This repo is a **pointer**. The raw EEG data lives at its canonical source |
| (OpenNeuro / NEMAR); [EEGDash](https://github.com/eegdash/EEGDash) streams it |
| on demand and returns a PyTorch / braindecode dataset. |
|
|
| ```python |
| # pip install eegdash |
| from eegdash import EEGDashDataset |
| |
| ds = EEGDashDataset(dataset="ds005491", cache_dir="./cache") |
| print(len(ds), "recordings") |
| ``` |
|
|
| You can also load it by canonical alias — these are registered classes in `eegdash.dataset`: |
|
|
| ```python |
| from eegdash.dataset import catFR_open_loop |
| ds = catFR_open_loop(cache_dir="./cache") |
| ``` |
|
|
| If the dataset has been mirrored to the HF Hub in braindecode's Zarr layout, |
| you can also pull it directly: |
|
|
| ```python |
| from braindecode.datasets import BaseConcatDataset |
| ds = BaseConcatDataset.pull_from_hub("EEGDash/ds005491") |
| ``` |
|
|
|
|
| ## Dataset metadata |
|
|
| | | | |
| |---|---| |
| | **Subjects** | 19 | |
| | **Recordings** | 51 | |
| | **Tasks (count)** | 1 | |
| | **Channels** | 64 (×5), 126 (×5), 88 (×4), 85 (×3), 93 (×3), 113 (×2), 163 (×2), 104 (×2), 155 (×2), 133 (×2), 116 (×2), 119 (×1), 72 (×1), 68 (×1), 92 (×1), 96 (×1), 127 (×1), 177 (×1), 146 (×1), 78 (×1), 128 (×1), 124 (×1), 110 (×1), 70 (×1), 80 (×1), 14 (×1), 115 (×1), 130 (×1), 112 (×1), 16 (×1) | |
| | **Sampling rate (Hz)** | 500 (×39), 1600 (×6), 999 (×4), 1000 (×2) | |
| | **Total duration (h)** | 46.7 | |
| | **Size on disk** | 22.5 GB | |
| | **Recording type** | IEEG | |
| | **Experimental modality** | Visual | |
| | **Paradigm type** | Clinical/Intervention | |
| | **Population** | Unknown | |
| | **Source** | openneuro | |
| | **License** | CC0 | |
| | **NEMAR citations** | 0.0 | |
|
|
| ## Links |
|
|
| - **DOI:** [10.18112/openneuro.ds005491.v1.0.0](https://doi.org/10.18112/openneuro.ds005491.v1.0.0) |
| - **OpenNeuro:** [ds005491](https://openneuro.org/datasets/ds005491) |
| - **Browse 700+ datasets:** [EEGDash catalog](https://huggingface.co/spaces/EEGDash/catalog) |
| - **Docs:** <https://eegdash.org> |
| - **Code:** <https://github.com/eegdash/EEGDash> |
|
|
| --- |
|
|
| _Auto-generated from [dataset_summary.csv](https://github.com/eegdash/EEGDash/blob/main/eegdash/dataset/dataset_summary.csv) and the [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds005491). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._ |
|
|
