EEGDash/ds006547

--- pretty_name: "Visual EEG Study (BrainVision → BIDS)" license: cc0-1.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - perception size_categories: - n<1K task_categories: - other --- # Visual EEG Study (BrainVision → BIDS) **Dataset ID:** `ds006547` _Ghaffari2025_ **Canonical aliases:** `Ghaffari2024` > **At a glance:** EEG · Visual perception · healthy · 31 subjects · 31 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="ds006547", 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 Ghaffari2024 ds = Ghaffari2024(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/ds006547") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 31 | | **Recordings** | 31 | | **Tasks (count)** | 1 | | **Channels** | 64 (×31) | | **Sampling rate (Hz)** | 500 (×31) | | **Total duration (h)** | 39.2 | | **Size on disk** | 17.6 GB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Perception | | **Population** | Healthy | | **Source** | openneuro | | **License** | CC0 | ## Links - **DOI:** [10.18112/openneuro.ds006547.v1.0.0](https://doi.org/10.18112/openneuro.ds006547.v1.0.0) - **OpenNeuro:** [ds006547](https://openneuro.org/datasets/ds006547) - **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/ds006547). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._pretty_name: "视觉脑电研究（BrainVision → BIDS）" license: "CC0 1.0" tags: - "脑电（EEG）" - "神经科学" - "EEGDash" - "脑机接口" - "PyTorch" - "视觉" - "知觉" size_categories: "样本量小于1000" task_categories: "其他任务类别" --- # 视觉脑电研究（BrainVision → BIDS） **数据集标识符：** `ds006547` _Ghaffari2025_ **标准别名：** `Ghaffari2024` > **概览：** 脑电（EEG）·视觉知觉·健康受试人群·31名受试者·31条记录·CC0许可 ## 加载该数据集 本仓库为**指针型仓库**。原始脑电（EEG）数据存储于其标准数据源（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="ds006547", cache_dir="./cache") print(len(ds), "recordings") 你也可以通过标准别名加载该数据集——这些别名对应 `eegdash.dataset` 中已注册的类： python from eegdash.dataset import Ghaffari2024 ds = Ghaffari2024(cache_dir="./cache") 若该数据集已按照 braindecode 的 Zarr 布局镜像至 Hugging Face Hub，你也可以直接拉取该数据集： python from braindecode.datasets import BaseConcatDataset ds = BaseConcatDataset.pull_from_hub("EEGDash/ds006547") ## 数据集元数据 | 条目 | 详情 | |---|---| | **受试者数量** | 31 | | **记录条数** | 31 | | **任务数** | 1 | | **电极通道数** | 64（共31组） | | **采样率（Hz）** | 500（共31组） | | **总时长（小时）** | 39.2 | | **磁盘占用大小** | 17.6 GB | | **记录类型** | 脑电（EEG） | | **实验模态** | 视觉 | | **范式类型** | 知觉 | | **受试人群** | 健康人群 | | **数据来源** | OpenNeuro | | **许可协议** | CC0 | ## 相关链接 - **DOI：** [10.18112/openneuro.ds006547.v1.0.0](https://doi.org/10.18112/openneuro.ds006547.v1.0.0) - **OpenNeuro 数据集页面：** [ds006547](https://openneuro.org/datasets/ds006547) - **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) 及 [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds006547) 自动生成。请勿手动编辑本文件，请更新上游数据源后重新运行 `scripts/push_metadata_stubs.py` 进行更新。_