EEGDash/ds006171

--- pretty_name: "EEG data during three near-threshold visual detection tasks: a no-cue task, a noninformative cue task (50% validity), and an informative cue task (100% validity)" license: cc0-1.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - attention size_categories: - n<1K task_categories: - other --- # EEG data during three near-threshold visual detection tasks: a no-cue task, a noninformative cue task (50% validity), and an informative cue task (100% validity) **Dataset ID:** `ds006171` _Melcon2025_ **Canonical aliases:** `Melcon2024` > **At a glance:** EEG · Visual attention · healthy · 36 subjects · 104 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="ds006171", 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 Melcon2024 ds = Melcon2024(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/ds006171") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 36 | | **Recordings** | 104 | | **Tasks (count)** | 3 | | **Channels** | 144 (×104) | | **Sampling rate (Hz)** | 1024 (×104) | | **Total duration (h)** | 40.9 | | **Size on disk** | 67.8 GB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Attention | | **Population** | Healthy | | **Source** | openneuro | | **License** | CC0 | ## Links - **DOI:** [10.18112/openneuro.ds006171.v1.0.0](https://doi.org/10.18112/openneuro.ds006171.v1.0.0) - **OpenNeuro:** [ds006171](https://openneuro.org/datasets/ds006171) - **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/ds006171). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._pretty_name: "三种近阈值视觉检测任务期间的脑电图（Electroencephalogram, EEG）数据：无线索任务、非信息性线索任务（有效率50%）以及信息性线索任务（有效率100%）" license: cc0-1.0 tags: - 脑电图（EEG） - 神经科学 - EEGDash - 脑机接口 - PyTorch - 视觉 - 注意 size_categories: - n<1000 task_categories: - 其他 # 三种近阈值视觉检测任务期间的脑电图数据：无线索任务、非信息性线索任务（有效率50%）以及信息性线索任务（有效率100%） **数据集编号：** `ds006171` _Melcon2025_ **标准别名：** `Melcon2024` > **概览：** 脑电图（EEG） · 视觉注意 · 健康人群 · 36名被试 · 104条记录 · CC0 ## 加载此数据集 本仓库为**索引指针**。原始脑电数据存储于其标准来源（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="ds006171", 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 Melcon2024 ds = Melcon2024(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/ds006171") ## 数据集元数据 | 指标 | 详情 | |---|---| | **被试人数** | 36 | | **记录条数** | 104 | | **任务类型（数量）** | 3 | | **脑电通道数** | 144条（共104份记录） | | **采样率（Hz）** | 1024（共104份记录） | | **总时长（小时）** | 40.9 | | **磁盘占用大小** | 67.8 GB | | **记录类型** | 脑电图（EEG） | | **实验模态** | 视觉 | | **实验范式类型** | 注意范式 | | **被试群体** | 健康人群 | | **数据来源** | OpenNeuro | | **授权协议** | CC0 | ## 相关链接 - **DOI：** [10.18112/openneuro.ds006171.v1.0.0](https://doi.org/10.18112/openneuro.ds006171.v1.0.0) - **OpenNeuro：** [ds006171](https://openneuro.org/datasets/ds006171) - **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/ds006171)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。