Metadata stub for ds005059

README.md

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+---
+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`._

eegdash.json

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+{
+  "dataset_id": "ds005059",
+  "title": "Paired Associates Learning: Memory for Word Pairs in Cued Recall",
+  "source": "openneuro",
+  "source_url": "https://openneuro.org/datasets/ds005059",
+  "doi": "10.18112/openneuro.ds005059.v1.0.6",
+  "license": "CC0",
+  "loader": {
+    "library": "eegdash",
+    "class": "EEGDashDataset",
+    "kwargs": {
+      "dataset": "ds005059"
+    }
+  },
+  "catalog": "https://huggingface.co/spaces/EEGDash/catalog",
+  "generated_by": "huggingface-space/scripts/push_metadata_stubs.py"
+}