EEGDash/ds005946

--- pretty_name: "ERC_CoG PROMENADE - WP2 - MetaImagery (Metaphor and Mental Imagery)" license: cc0-1.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - perception size_categories: - n<1K task_categories: - other --- # ERC_CoG PROMENADE - WP2 - MetaImagery (Metaphor and Mental Imagery) **Dataset ID:** `ds005946` _Frau2025_ **Canonical aliases:** `PROMENADE` > **At a glance:** EEG · Visual perception · healthy · 39 subjects · 39 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="ds005946", 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 PROMENADE ds = PROMENADE(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/ds005946") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 39 | | **Recordings** | 39 | | **Tasks (count)** | 1 | | **Channels** | 60 (×39) | | **Sampling rate (Hz)** | 1000 (×39) | | **Total duration (h)** | 18.3 | | **Size on disk** | 14.8 GB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Perception | | **Population** | Healthy | | **Source** | openneuro | | **License** | CC0 | ## Links - **DOI:** [10.18112/openneuro.ds005946.v1.0.1](https://doi.org/10.18112/openneuro.ds005946.v1.0.1) - **OpenNeuro:** [ds005946](https://openneuro.org/datasets/ds005946) - **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/ds005946). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._--- pretty_name: "ERC_CoG PROMENADE - WP2 - 元意象（隐喻与心理意象）" license: "CC0 1.0" tags: - 脑电图(EEG) - 神经科学 - EEGDash - 脑机接口(brain-computer-interface) - PyTorch - 视觉 - 感知 size_categories: - 样本量小于1000 task_categories: - 其他 --- # ERC_CoG PROMENADE - WP2 - 元意象（隐喻与心理意象） **数据集编号：** `ds005946` _Frau，2025_ **标准别名：** `PROMENADE` > **概览：** 脑电图(EEG) · 视觉感知 · 健康人群 · 39名受试者 · 39条记录 · CC0协议 ## 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，并返回PyTorch / braindecode格式的数据集。 python # 安装EEGDash库 pip install eegdash from eegdash import EEGDashDataset ds = EEGDashDataset(dataset="ds005946", 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 PROMENADE ds = PROMENADE(cache_dir="./cache") 若该数据集已按照braindecode的Zarr格式镜像至Hugging Face Hub（HF Hub），你也可以直接拉取： python from braindecode.datasets import BaseConcatDataset ds = BaseConcatDataset.pull_from_hub("EEGDash/ds005946") ## 数据集元数据 | 项目 | 详情 | |---|---| | **受试者数量** | 39 | | **记录条数** | 39 | | **任务数量** | 1 | | **通道数** | 60（×39） | | **采样率（Hz）** | 1000（×39） | | **总时长（小时）** | 18.3 | | **磁盘占用大小** | 14.8 GB | | **记录类型** | 脑电图(EEG) | | **实验模态** | 视觉 | | **范式类型** | 感知 | | **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.ds005946.v1.0.1](https://doi.org/10.18112/openneuro.ds005946.v1.0.1) - **OpenNeuro平台：** [ds005946](https://openneuro.org/datasets/ds005946) - **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/ds005946)自动生成。请勿手动编辑此文件——请更新上游源数据后重新运行`scripts/push_metadata_stubs.py`脚本。_