Metadata stub for ds003505

README.md

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+---
+pretty_name: "VEPCON: Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes"
+license: cc0-1.0
+tags:
+  - eeg
+  - neuroscience
+  - eegdash
+  - brain-computer-interface
+  - pytorch
+size_categories:
+  - n<1K
+task_categories:
+  - other
+---
+
+# VEPCON: Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes
+
+**Dataset ID:** `ds003505`
+
+_Pascucci2021_
+
+**Canonical aliases:** `VEPCON`
+
+> **At a glance:** EEG · 19 subjects · 37 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="ds003505", 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 VEPCON
+ds = VEPCON(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/ds003505")
+```
+
+
+## Dataset metadata
+
+| | |
+|---|---|
+| **Subjects** | 19 |
+| **Recordings** | 37 |
+| **Tasks (count)** | 2 |
+| **Channels** | 128 (×37) |
+| **Sampling rate (Hz)** | 2048 (×37) |
+| **Size on disk** | 29.0 GB |
+| **Recording type** | EEG |
+| **Source** | openneuro |
+| **License** | CC0 |
+| **NEMAR citations** | 5.0 |
+
+## Links
+
+- **DOI:** [10.18112/openneuro.ds003505.v1.1.1](https://doi.org/10.18112/openneuro.ds003505.v1.1.1)
+- **OpenNeuro:** [ds003505](https://openneuro.org/datasets/ds003505)
+- **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/ds003505). 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": "ds003505",
+  "title": "VEPCON: Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes",
+  "source": "openneuro",
+  "source_url": "https://openneuro.org/datasets/ds003505",
+  "doi": "10.18112/openneuro.ds003505.v1.1.1",
+  "license": "CC0",
+  "loader": {
+    "library": "eegdash",
+    "class": "EEGDashDataset",
+    "kwargs": {
+      "dataset": "ds003505"
+    }
+  },
+  "catalog": "https://huggingface.co/spaces/EEGDash/catalog",
+  "generated_by": "huggingface-space/scripts/push_metadata_stubs.py"
+}