| --- |
| pretty_name: "Spatial Navigation Memory of Object Locations" |
| license: cc0-1.0 |
| tags: |
| - ieeg |
| - neuroscience |
| - eegdash |
| - brain-computer-interface |
| - pytorch |
| - visual |
| - memory |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| --- |
| |
| # Spatial Navigation Memory of Object Locations |
|
|
| **Dataset ID:** `ds005522` |
|
|
| _Herrema2024_Spatial_ |
|
|
| > **At a glance:** IEEG · Visual memory · unknown · 55 subjects · 176 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="ds005522", cache_dir="./cache") |
| print(len(ds), "recordings") |
| ``` |
|
|
| 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/ds005522") |
| ``` |
|
|
|
|
| ## Dataset metadata |
|
|
| | | | |
| |---|---| |
| | **Subjects** | 55 | |
| | **Recordings** | 176 | |
| | **Tasks (count)** | 1 | |
| | **Channels** | 133 (×8), 110 (×8), 88 (×7), 120 (×7), 72 (×6), 188 (×6), 173 (×6), 126 (×6), 108 (×5), 56 (×5), 46 (×4), 128 (×4), 127 (×4), 68 (×4), 112 (×4), 64 (×4), 144 (×3), 146 (×3), 92 (×3), 123 (×3), 186 (×3), 124 (×3), 50 (×3), 104 (×3), 182 (×3), 86 (×3), 160 (×2), 59 (×2), 180 (×2), 138 (×2), 163 (×2), 85 (×2), 75 (×2), 140 (×2), 111 (×2), 70 (×2), 130 (×2), 63 (×2), 170 (×2), 96 (×2), 166 (×2), 158 (×2), 118 (×2), 100 (×2), 90 (×1), 54 (×1), 151 (×1), 105 (×1), 109 (×1), 94 (×1), 149 (×1), 172 (×1), 122 (×1), 174 (×1), 76 (×1), 78 (×1), 178 (×1), 84 (×1), 165 (×1), 125 (×1), 177 (×1), 169 (×1), 136 (×1), 80 (×1), 60 (×1), 116 (×1) | |
| | **Sampling rate (Hz)** | 1000 (×70), 500 (×61), 1600 (×26), 999 (×13), 2000 (×4), 1999 (×2) | |
| | **Total duration (h)** | 145.2 | |
| | **Size on disk** | 107.5 GB | |
| | **Recording type** | IEEG | |
| | **Experimental modality** | Visual | |
| | **Paradigm type** | Memory | |
| | **Population** | Unknown | |
| | **Source** | openneuro | |
| | **License** | CC0 | |
| | **NEMAR citations** | 0.0 | |
|
|
| ## Links |
|
|
| - **DOI:** [10.18112/openneuro.ds005522.v1.0.0](https://doi.org/10.18112/openneuro.ds005522.v1.0.0) |
| - **OpenNeuro:** [ds005522](https://openneuro.org/datasets/ds005522) |
| - **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/ds005522). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._ |
|
|
