EEGDash/ds006768

--- pretty_name: "Multiple Object Monitoring (EEG)" license: cc0-1.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - attention size_categories: - n<1K task_categories: - other --- # Multiple Object Monitoring (EEG) **Dataset ID:** `ds006768` _Lowe2025_ > **At a glance:** EEG · Visual attention · healthy · 30 subjects · 210 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="ds006768", cache_dir="./cache") print(len(ds), "recordings") ``` 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/ds006768") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 30 | | **Recordings** | 210 | | **Tasks (count)** | 1 | | **Channels** | 64 (×210) | | **Sampling rate (Hz)** | 1000 (×210) | | **Total duration (h)** | 14.5 | | **Size on disk** | 6.5 GB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Attention | | **Population** | Healthy | | **Source** | openneuro | | **License** | CC0 | ## Links - **DOI:** [10.18112/openneuro.ds006768.v1.1.0](https://doi.org/10.18112/openneuro.ds006768.v1.1.0) - **OpenNeuro:** [ds006768](https://openneuro.org/datasets/ds006768) - **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/ds006768). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._--- 数据集名称：多物体监测（EEG） 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 样本量分类： - n<1K 任务分类： - 其他 --- # 多物体监测（EEG） **数据集ID：** `ds006768` _Lowe等，2025年_ > **概览：** 脑电图（EEG）、视觉注意、健康受试人群、30名被试、210份记录、CC0许可证 ## 数据集加载 本仓库仅为**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) 可按需流式读取该数据集，并返回PyTorch / braindecode格式的数据集对象。 python # pip install eegdash from eegdash import EEGDashDataset ds = EEGDashDataset(dataset="ds006768", cache_dir="./cache") print(len(ds), "recordings") 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/ds006768") ## 数据集元数据 | 元数据项 | 详情 | |---|---| | **被试人数** | 30 | | **记录份数** | 210 | | **任务数量** | 1 | | **通道数** | 64 (×210) | | **采样率（Hz）** | 1000 (×210) | | **总时长（h）** | 14.5 | | **磁盘占用大小** | 6.5 GB | | **记录类型** | 脑电图（EEG） | | **实验模态** | 视觉 | | **范式类型** | 注意范式 | | **受试人群** | 健康人群 | | **数据来源** | OpenNeuro | | **许可证** | CC0 1.0 | ## 相关链接 - **DOI：** [10.18112/openneuro.ds006768.v1.1.0](https://doi.org/10.18112/openneuro.ds006768.v1.1.0) - **OpenNeuro平台：** [ds006768](https://openneuro.org/datasets/ds006768) - **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> --- 本内容由[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/ds006768)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`脚本以更新内容。