EEGDash/ds007006

---
pretty_name: "VR-Compassion Cultivation Training"
license: cc0-1.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- multisensory
- affect
size_categories:
- n<1K
task_categories:
- other
---

# VR-Compassion Cultivation Training

**Dataset ID:** `ds007006`

_Wu2025_

> **At a glance:** EEG · Multisensory affect · healthy · 10 subjects · 50 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="ds007006", 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/ds007006")
```

## Dataset metadata

| | |
|---|---|
| **Subjects** | 10 |
| **Recordings** | 50 |
| **Tasks (count)** | 5 |
| **Channels** | 64 (×50) |
| **Sampling rate (Hz)** | 256 (×50) |
| **Total duration (h)** | 3.6 |
| **Size on disk** | 918.7 MB |
| **Recording type** | EEG |
| **Experimental modality** | Multisensory |
| **Paradigm type** | Affect |
| **Population** | Healthy |
| **Source** | openneuro |
| **License** | CC0 |

## Links

- **DOI:** [10.18112/openneuro.ds007006.v1.0.0](https://doi.org/10.18112/openneuro.ds007006.v1.0.0)
- **OpenNeuro:** [ds007006](https://openneuro.org/datasets/ds007006)
- **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/ds007006). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._

数据集名称：VR慈悲冥想训练（VR-Compassion Cultivation Training）
许可证：CC0 1.0协议
标签：
- 脑电图（EEG）
- 神经科学
- EEGDash
- 脑机接口（brain-computer-interface）
- PyTorch
- 多感官
- 情感（affect）
规模类别：
- 样本数少于1000（n<1K）
任务类别：
- 其他（other）

# VR慈悲冥想训练（VR-Compassion Cultivation Training）

**数据集编号**：`ds007006`

_Wu等人，2025年_

> **概览**：脑电图（EEG）、多感官情感、健康受试人群、10名受试者、50条记录、CC0许可证

## 加载该数据集

本仓库仅为**索引指针**。原始脑电图数据存储于其标准源地址（OpenNeuro / NEMAR）；[EEGDash](https://github.com/eegdash/EEGDash) 可按需流式加载该数据，并返回PyTorch / Braindecode格式的数据集。

python
# pip install eegdash
from eegdash import EEGDashDataset

ds = EEGDashDataset(dataset="ds007006", cache_dir="./cache")
print(len(ds), "recordings")

若该数据集已按照Braindecode的Zarr格式镜像至Hugging Face Hub（HF Hub），你也可以直接拉取：

python
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/ds007006")

## 数据集元数据

| 指标 | 数值 |
|---|---|
| **受试者人数** | 10 |
| **记录条数** | 50 |
| **任务（数量）** | 5 |
| **通道数** | 64（×50） |
| **采样率（Hz）** | 256（×50） |
| **总时长（小时）** | 3.6 |
| **磁盘占用大小** | 918.7 MB |
| **记录类型** | 脑电图（EEG） |
| **实验模态** | 多感官 |
| **范式类型** | 情感相关 |
| **受试人群** | 健康人群 |
| **数据来源** | OpenNeuro |
| **许可证** | CC0 1.0协议 |

## 相关链接

- **数字对象标识符（DOI）**：[10.18112/openneuro.ds007006.v1.0.0](https://doi.org/10.18112/openneuro.ds007006.v1.0.0)
- **OpenNeuro平台地址**：[ds007006](https://openneuro.org/datasets/ds007006)
- **浏览700+数据集**：[EEGDash数据集目录](https://huggingface.co/spaces/EEGDash/catalog)
- **官方文档**：<https://eegdash.org>
- **代码仓库**：<https://github.com/eegdash/EEGDash>

---

本内容自动生成自 [dataset_summary.csv](https://github.com/eegdash/EEGDash/blob/main/eegdash/dataset/dataset_summary.csv) 与 [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds007006)。请勿手动编辑本文件，请更新上游源数据并重新运行 `scripts/push_metadata_stubs.py` 脚本以更新内容。