| --- |
| pretty_name: "Paired Associates Learning: Memory for Word Pairs in Cued Recall" |
| license: cc0-1.0 |
| tags: |
| - ieeg |
| - neuroscience |
| - eegdash |
| - brain-computer-interface |
| - pytorch |
| - visual |
| - memory |
| - epilepsy |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| --- |
| |
| # Paired Associates Learning: Memory for Word Pairs in Cued Recall |
|
|
| **Dataset ID:** `ds005059` |
|
|
| _Herrema2024_Paired_ |
|
|
| **Canonical aliases:** `PAL` |
|
|
| > **At a glance:** IEEG · Visual memory · epilepsy · 69 subjects · 282 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="ds005059", 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 PAL |
| ds = PAL(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/ds005059") |
| ``` |
|
|
|
|
| ## Dataset metadata |
|
|
| | | | |
| |---|---| |
| | **Subjects** | 69 | |
| | **Recordings** | 282 | |
| | **Tasks (count)** | 1 | |
| | **Channels** | 112 (×22), 126 (×15), 85 (×11), 110 (×10), 128 (×10), 104 (×9), 88 (×9), 100 (×9), 72 (×8), 64 (×8), 186 (×8), 102 (×7), 116 (×7), 121 (×7), 92 (×6), 142 (×6), 119 (×5), 97 (×5), 95 (×5), 94 (×5), 106 (×4), 140 (×4), 124 (×4), 96 (×4), 123 (×4), 139 (×4), 86 (×4), 130 (×4), 68 (×4), 87 (×3), 107 (×3), 188 (×3), 84 (×3), 120 (×3), 58 (×3), 74 (×3), 114 (×3), 83 (×3), 108 (×3), 55 (×3), 80 (×3), 117 (×3), 173 (×3), 118 (×2), 141 (×2), 73 (×2), 138 (×2), 115 (×2), 122 (×2), 111 (×2), 149 (×2), 60 (×1), 146 (×1), 77 (×1), 67 (×1), 93 (×1), 76 (×1), 46 (×1), 53 (×1), 14 (×1), 99 (×1), 177 (×1), 90 (×1), 98 (×1), 52 (×1), 133 (×1), 16 (×1) | |
| | **Sampling rate (Hz)** | 1000 (×193), 500 (×71), 1024 (×8), 499.7071 (×6), 1600 (×4) | |
| | **Total duration (h)** | 261.3 | |
| | **Size on disk** | 167.3 GB | |
| | **Recording type** | IEEG | |
| | **Experimental modality** | Visual | |
| | **Paradigm type** | Memory | |
| | **Population** | Epilepsy | |
| | **Source** | openneuro | |
| | **License** | CC0 | |
| | **NEMAR citations** | 0.0 | |
|
|
| ## Links |
|
|
| - **DOI:** [10.18112/openneuro.ds005059.v1.0.6](https://doi.org/10.18112/openneuro.ds005059.v1.0.6) |
| - **OpenNeuro:** [ds005059](https://openneuro.org/datasets/ds005059) |
| - **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/ds005059). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._ |
|
|
