EEGDash/ds005697

---
pretty_name: "PerceiveImagine"
license: cc0-1.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- visual
- memory
size_categories:
- n<1K
task_categories:
- other
---

# PerceiveImagine

**Dataset ID:** `ds005697`

_Li2024_PerceiveImagine_

**Canonical aliases:** `PerceiveImagine`

> **At a glance:** EEG · Visual memory · healthy · 51 subjects · 51 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="ds005697", 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 PerceiveImagine
ds = PerceiveImagine(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/ds005697")
```

## Dataset metadata

| | |
|---|---|
| **Subjects** | 51 |
| **Recordings** | 51 |
| **Tasks (count)** | 1 |
| **Channels** | 65 (×45), 69 (×6) |
| **Sampling rate (Hz)** | 1000 (×50) |
| **Total duration (h)** | 77.7 |
| **Size on disk** | 66.6 GB |
| **Recording type** | EEG |
| **Experimental modality** | Visual |
| **Paradigm type** | Memory |
| **Population** | Healthy |
| **Source** | openneuro |
| **License** | CC0 |
| **NEMAR citations** | 3.0 |

## Links

- **DOI:** [10.18112/openneuro.ds005697.v1.0.2](https://doi.org/10.18112/openneuro.ds005697.v1.0.2)
- **OpenNeuro:** [ds005697](https://openneuro.org/datasets/ds005697)
- **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/ds005697). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._

pretty_name: "PerceiveImagine（感知想象）"
license: cc0-1.0
tags:
- 脑电图（EEG）
- 神经科学
- EEGDash
- 脑机接口（brain-computer-interface）
- PyTorch
- 视觉
- 记忆
size_categories:
- n<1K
task_categories:
- 其他

# PerceiveImagine（感知想象）

**Dataset ID:** `ds005697`

_Li等，2024：PerceiveImagine_

**Canonical aliases:** `PerceiveImagine`

> **At a glance:** 脑电图（EEG） · 视觉记忆 · 健康人群 · 51名受试者 · 51条记录 · CC0许可

## 加载该数据集

本仓库为**索引指针**。原始脑电图（EEG）数据存储于其官方数据源（OpenNeuro / NEMAR）；[EEGDash](https://github.com/eegdash/EEGDash) 支持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="ds005697", 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 PerceiveImagine
ds = PerceiveImagine(cache_dir="./cache")

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

python
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/ds005697")

## 数据集元数据

| 元数据项 | 数值 |
|---|---|
| **受试者数量** | 51 |
| **记录条数** | 51 |
| **任务数** | 1 |
| **通道数** | 65（×45）、69（×6） |
| **采样率（Hz）** | 1000（×50） |
| **总时长（小时）** | 77.7 |
| **磁盘占用大小** | 66.6 GB |
| **记录类型** | 脑电图（EEG） |
| **实验模态** | 视觉 |
| **范式类型** | 记忆 |
| **研究人群** | 健康人群 |
| **数据来源** | OpenNeuro |
| **许可协议** | CC0 |
| **NEMAR引用量** | 3.0 |

## 相关链接

- **DOI：** [10.18112/openneuro.ds005697.v1.0.2](https://doi.org/10.18112/openneuro.ds005697.v1.0.2)
- **OpenNeuro：** [ds005697](https://openneuro.org/datasets/ds005697)
- **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/ds005697)自动生成。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。_