EEGDash/ds005872

--- pretty_name: "EEGEyeNet Dataset" license: cc0-1.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - attention size_categories: - n<1K task_categories: - other --- # EEGEyeNet Dataset **Dataset ID:** `ds005872` _Plomecka2025_ **Canonical aliases:** `EEGEyeNet` > **At a glance:** EEG · Visual attention · healthy · 1 subjects · 1 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="ds005872", 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 EEGEyeNet ds = EEGEyeNet(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/ds005872") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 1 | | **Recordings** | 1 | | **Tasks (count)** | 1 | | **Channels** | 129 (×1) | | **Sampling rate (Hz)** | 500 (×1) | | **Total duration (h)** | 0.1 | | **Size on disk** | 39.9 MB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Attention | | **Population** | Healthy | | **Source** | openneuro | | **License** | CC0 | ## Links - **DOI:** [10.18112/openneuro.ds005872.v1.0.0](https://doi.org/10.18112/openneuro.ds005872.v1.0.0) - **OpenNeuro:** [ds005872](https://openneuro.org/datasets/ds005872) - **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/ds005872). 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: "EEGEyeNet 数据集" 授权协议: cc0-1.0 标签: - 脑电图（EEG） - 神经科学 - EEGDash - 脑机接口 - PyTorch - 视觉 - 注意力 数据集规模分类: - n<1K 任务分类: - 其他 --- # EEGEyeNet 数据集 **数据集编号**: `ds005872` _Plomecka2025_ **规范别名**: `EEGEyeNet` > **概览:** 脑电图（EEG） · 视觉注意力 · 健康人群 · 1名受试者 · 1次记录 · CC0协议 ## 加载该数据集 本仓库为**指针文件**。原始脑电图（EEG）数据存储于其规范来源（OpenNeuro / NEMAR）；[EEGDash](https://github.com/eegdash/EEGDash) 支持按需流式加载，并返回PyTorch / braindecode格式的数据集。 python # pip install eegdash from eegdash import EEGDashDataset ds = EEGDashDataset(dataset="ds005872", cache_dir="./cache") print(len(ds), "条记录") 你也可以通过规范别名加载该数据集——这些别名已在`eegdash.dataset`中注册为类： python from eegdash.dataset import EEGEyeNet ds = EEGEyeNet(cache_dir="./cache") 若该数据集已按照braindecode的Zarr布局镜像至Hugging Face Hub，你也可以直接拉取： python from braindecode.datasets import BaseConcatDataset ds = BaseConcatDataset.pull_from_hub("EEGDash/ds005872") ## 数据集元数据 | | | |---|---| | **受试者数量** | 1 | | **记录次数** | 1 | | **任务（数量）** | 1 | | **通道数** | 129 (×1) | | **采样率（Hz）** | 500 (×1) | | **总时长（h）** | 0.1 | | **磁盘占用大小** | 39.9 MB | | **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.ds005872.v1.0.0](https://doi.org/10.18112/openneuro.ds005872.v1.0.0) - **OpenNeuro平台:** [ds005872](https://openneuro.org/datasets/ds005872) - **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)与[EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds005872)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。