EEGDash/ds007139

---
pretty_name: "PURSUE LRP/ERN Flanker"
license: cc0-1.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- visual
- attention
size_categories:
- n<1K
task_categories:
- other
---

# PURSUE LRP/ERN Flanker

**Dataset ID:** `ds007139`

_Couperus2025_LRP_

**Canonical aliases:** `Couperus2021_LRP`

> **At a glance:** EEG · Visual attention · healthy · 292 subjects · 292 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="ds007139", 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 Couperus2021_LRP
ds = Couperus2021_LRP(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/ds007139")
```

## Dataset metadata

| | |
|---|---|
| **Subjects** | 292 |
| **Recordings** | 292 |
| **Tasks (count)** | 1 |
| **Channels** | 32 (×292) |
| **Sampling rate (Hz)** | 500 (×292) |
| **Total duration (h)** | 64.6 |
| **Size on disk** | 14.5 GB |
| **Recording type** | EEG |
| **Experimental modality** | Visual |
| **Paradigm type** | Attention |
| **Population** | Healthy |
| **Source** | openneuro |
| **License** | CC0 |

## Links

- **DOI:** [10.18112/openneuro.ds007139.v1.0.0](https://doi.org/10.18112/openneuro.ds007139.v1.0.0)
- **OpenNeuro:** [ds007139](https://openneuro.org/datasets/ds007139)
- **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/ds007139). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._

数据集显示名: "PURSUE LRP/ERN Flanker"
许可证: cc0-1.0
标签:
- 脑电图（EEG）
- 神经科学
- eegdash
- 脑机接口（brain-computer-interface）
- PyTorch
- 视觉
- 注意力
规模分类:
- n<1K
任务分类:
- 其他

# PURSUE LRP/ERN Flanker 数据集

**数据集标识符:** `ds007139`

_Couperus2025_LRP_

**标准别名:** `Couperus2021_LRP`

> **快速概览:** 脑电图（EEG） · 视觉注意力 · 健康人群 · 292名被试 · 292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（EEG）数据存储于其官方源（OpenNeuro / NEMAR）；[EEGDash](https://github.com/eegdash/EEGDash) 可按需流式加载该数据集，并返回适配 PyTorch / braindecode 的数据集对象。

python
# 安装 eegdash 库
from eegdash import EEGDashDataset

ds = EEGDashDataset(dataset="ds007139", cache_dir="./cache")
print(len(ds), "条记录")

你也可以通过标准别名加载该数据集——这些类已在 `eegdash.dataset` 中完成注册：

python
from eegdash.dataset import Couperus2021_LRP
ds = Couperus2021_LRP(cache_dir="./cache")

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/ds007139")

## 数据集元数据

| 元数据项 | 详情 |
|---|---|
| **被试人数** | 292 |
| **记录条数** | 292 |
| **任务数** | 1 |
| **通道数** | 32（共292组） |
| **采样率（Hz）** | 500（共292组） |
| **总时长（小时）** | 64.6 |
| **磁盘占用** | 14.5 GB |
| **记录类型** | 脑电图（EEG） |
| **实验模态** | 视觉 |
| **实验范式类型** | 注意力 |
| **受试人群** | 健康人群 |
| **数据来源** | OpenNeuro |
| **许可证** | CC0 |

## 相关链接

- **DOI 链接:** [10.18112/openneuro.ds007139.v1.0.0](https://doi.org/10.18112/openneuro.ds007139.v1.0.0)
- **OpenNeuro 页面:** [ds007139](https://openneuro.org/datasets/ds007139)
- **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>

---

本文件由 [dataset_summary.csv](https://github.com/eegdash/EEGDash/blob/main/eegdash/dataset/dataset_summary.csv) 及 [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds007139) 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` 脚本以更新元数据。