five

EEGDash/ds007137

收藏
Hugging Face2026-04-20 更新2026-04-26 收录
下载链接:
https://hf-mirror.com/datasets/EEGDash/ds007137
下载链接
链接失效反馈
官方服务:
资源简介:
--- pretty_name: "PURSUE N2pc Visual Search" license: cc0-1.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - attention size_categories: - n<1K task_categories: - other --- # PURSUE N2pc Visual Search **Dataset ID:** `ds007137` _Couperus2025_N2PC_ **Canonical aliases:** `Couperus2021_N2pc` > **At a glance:** EEG · Visual attention · healthy · 294 subjects · 294 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="ds007137", 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_N2pc ds = Couperus2021_N2pc(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/ds007137") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 294 | | **Recordings** | 294 | | **Tasks (count)** | 1 | | **Channels** | 32 (×294) | | **Sampling rate (Hz)** | 500 (×294) | | **Total duration (h)** | 54.4 | | **Size on disk** | 12.2 GB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Attention | | **Population** | Healthy | | **Source** | openneuro | | **License** | CC0 | ## Links - **DOI:** [10.18112/openneuro.ds007137.v1.0.0](https://doi.org/10.18112/openneuro.ds007137.v1.0.0) - **OpenNeuro:** [ds007137](https://openneuro.org/datasets/ds007137) - **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/ds007137). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._

--- pretty_name: "PURSUE N2pc 视觉搜索" license: "CC0 1.0 通用公共领域许可" tags: - 脑电图(Electroencephalogram, EEG) - 神经科学 - EEGDash - 脑机接口(Brain-Computer Interface, BCI) - PyTorch - 视觉 - 注意力 size_categories: - 样本量<1000 task_categories: - 其他 --- # PURSUE N2pc 视觉搜索 **数据集编号:** `ds007137` _Couperus2025_N2PC_ **标准别名:** `Couperus2021_N2pc` > **概览:** 脑电图(EEG) · 视觉注意力 · 健康人群 · 294名受试者 · 294条记录 · CC0许可 ## 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地址(OpenNeuro / NEMAR);[EEGDash](https://github.com/eegdash/EEGDash) 可按需流式加载该数据集,并返回 PyTorch / braindecode 格式的数据集对象。 python # 安装eegdash库 from eegdash import EEGDashDataset ds = EEGDashDataset(dataset="ds007137", 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_N2pc ds = Couperus2021_N2pc(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/ds007137") ## 数据集元数据 | 元数据项 | 详情 | |---|---| | **受试者数量** | 294 | | **记录条数** | 294 | | **任务(数量)** | 1 | | **通道数** | 32(共294组) | | **采样率(Hz)** | 500(共294组) | | **总时长(小时)** | 54.4 | | **磁盘占用** | 12.2 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 | | **许可证** | CC0 | ## 相关链接 - **DOI:** [10.18112/openneuro.ds007137.v1.0.0](https://doi.org/10.18112/openneuro.ds007137.v1.0.0) - **OpenNeuro:** [ds007137](https://openneuro.org/datasets/ds007137) - **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/ds007137) 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` 脚本以完成更新。_
提供机构:
EEGDash
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作