EEGDash/ds007096

---
pretty_name: "PURSUE N170 Face Perception"
license: cc0-1.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- visual
- perception
size_categories:
- n<1K
task_categories:
- other
---

# PURSUE N170 Face Perception

**Dataset ID:** `ds007096`

_Couperus2025_PURSUE_N170_Face_

**Canonical aliases:** `Couperus2017`

> **At a glance:** EEG · Visual perception · 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="ds007096", 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 Couperus2017
ds = Couperus2017(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/ds007096")
```

## Dataset metadata

| | |
|---|---|
| **Subjects** | 292 |
| **Recordings** | 292 |
| **Tasks (count)** | 1 |
| **Channels** | 32 (×292) |
| **Sampling rate (Hz)** | 500 (×292) |
| **Total duration (h)** | 51.8 |
| **Size on disk** | 11.6 GB |
| **Recording type** | EEG |
| **Experimental modality** | Visual |
| **Paradigm type** | Perception |
| **Population** | Healthy |
| **Source** | openneuro |
| **License** | CC0 |

## Links

- **DOI:** [10.18112/openneuro.ds007096.v1.0.0](https://doi.org/10.18112/openneuro.ds007096.v1.0.0)
- **OpenNeuro:** [ds007096](https://openneuro.org/datasets/ds007096)
- **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/ds007096). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._

---
数据集展示名："PURSUE N170面部感知数据集（PURSUE N170 Face Perception）"
授权协议：cc0-1.0
标签：
- 脑电图（EEG）
- 神经科学（neuroscience）
- EEGDash
- 脑机接口（brain-computer-interface）
- PyTorch
- 视觉
- 感知
数据集规模类别：
- 样本量少于1000
任务类别：
- 其他
---

# PURSUE N170面部感知数据集（PURSUE N170 Face Perception）

**数据集ID：** `ds007096`

_Couperus2025_PURSUE_N170_Face_

**标准别名：** `Couperus2017`

> **概览：** 脑电图（EEG）· 视觉感知 · 健康人群 · 292名被试 · 292条记录 · CC0

## 加载该数据集

本仓库为**索引指针**。原始脑电图（EEG）数据存储于其官方源地址（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
# 安装eegdash库
from eegdash import EEGDashDataset

ds = EEGDashDataset(dataset="ds007096", 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 Couperus2017
ds = Couperus2017(cache_dir="./cache")

若该数据集已按照braindecode的Zarr格式镜像至Hugging Face Hub，你也可以直接拉取：
python
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/ds007096")

## 数据集元数据

| | |
|---|---|
| **被试数量** | 292 |
| **记录条数** | 292 |
| **任务数量** | 1 |
| **通道数** | 32（共292组） |
| **采样率（Hz）** | 500（共292组） |
| **总时长（小时）** | 51.8 |
| **磁盘占用大小** | 11.6 GB |
| **记录类型** | 脑电图（EEG） |
| **实验模态** | 视觉 |
| **范式类型** | 感知 |
| **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.ds007096.v1.0.0](https://doi.org/10.18112/openneuro.ds007096.v1.0.0)
- **OpenNeuro：** [ds007096](https://openneuro.org/datasets/ds007096)
- **浏览700+数据集：** [EEGDash数据集目录](https://huggingface.co/spaces/EEGDash/catalog)
- **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) 与 [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds007096) 自动生成。请勿手动编辑此文件——请更新上游源数据并重新运行 `scripts/push_metadata_stubs.py` 脚本。*