EEGDash/ds005960

---
pretty_name: "General Info: inst-comp-eeg"
license: cc0-1.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- visual
- attention
size_categories:
- n<1K
task_categories:
- other
---

# General Info: inst-comp-eeg

**Dataset ID:** `ds005960`

_Pena2025_

> **At a glance:** EEG · Visual attention · healthy · 41 subjects · 41 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="ds005960", 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/ds005960")
```

## Dataset metadata

| | |
|---|---|
| **Subjects** | 41 |
| **Recordings** | 41 |
| **Tasks (count)** | 1 |
| **Channels** | 63 (×41) |
| **Sampling rate (Hz)** | 1000 (×41) |
| **Total duration (h)** | 66.9 |
| **Size on disk** | 57.7 GB |
| **Recording type** | EEG |
| **Experimental modality** | Visual |
| **Paradigm type** | Attention |
| **Population** | Healthy |
| **Source** | openneuro |
| **License** | CC0 |

## Links

- **DOI:** [10.18112/openneuro.ds005960.v1.0.0](https://doi.org/10.18112/openneuro.ds005960.v1.0.0)
- **OpenNeuro:** [ds005960](https://openneuro.org/datasets/ds005960)
- **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/ds005960). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._

pretty_name: "通用信息：inst-comp-eeg"
license: CC0 1.0协议
tags:
- 脑电图（EEG）
- 神经科学
- EEGDash
- 脑机接口（brain-computer-interface）
- PyTorch
- 视觉相关
- 注意力
size_categories:
- 样本数少于1000
task_categories:
- 其他

# 通用信息：inst-comp-eeg

**数据集ID：** `ds005960`

_Pena等，2025年_

> **概览：** 脑电图（EEG）·视觉注意力·健康受试人群·41名被试·41次记录·CC0协议

## 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官方来源（OpenNeuro / NEMAR）；[EEGDash](https://github.com/eegdash/EEGDash) 可按需流式读取该数据，并返回PyTorch / braindecode格式的数据集。

python
# 通过pip安装eegdash库
from eegdash import EEGDashDataset

ds = EEGDashDataset(dataset="ds005960", cache_dir="./cache")
print(len(ds), "次记录")

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

python
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/ds005960")

## 数据集元数据

| | |
|---|---|
| **被试数量** | 41 |
| **记录次数** | 41 |
| **任务数** | 1 |
| **通道数** | 63（共41组） |
| **采样率（Hz）** | 1000（共41组） |
| **总时长（小时）** | 66.9 |
| **磁盘占用** | 57.7 GB |
| **记录类型** | 脑电图（EEG） |
| **实验模态** | 视觉 |
| **范式类型** | 注意力 |
| **受试人群** | 健康人群 |
| **数据来源** | OpenNeuro |
| **授权协议** | CC0 |

## 相关链接

- **DOI：** [10.18112/openneuro.ds005960.v1.0.0](https://doi.org/10.18112/openneuro.ds005960.v1.0.0)
- **OpenNeuro平台：** [ds005960](https://openneuro.org/datasets/ds005960)
- **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>

---

_本内容由 [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/ds005960) 自动生成。请勿手动编辑此文件 —— 请更新上游数据源并重新运行 `scripts/push_metadata_stubs.py` 脚本以更新内容。_