---
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`._