EEGDash/ds006945

--- pretty_name: "Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles)" license: cc0-1.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - motor size_categories: - n<1K task_categories: - other --- # Dataset: T1-Weighted Structural MRI and fMRI of Participants Viewing Self-Avatar Exoskeleton Walking (11 SWS Cycles) **Dataset ID:** `ds006945` _Sarkar2025_T1_Weighted_Structural_ > **At a glance:** EEG · Visual motor · healthy · 5 subjects · 14 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="ds006945", 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/ds006945") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 5 | | **Recordings** | 14 | | **Tasks (count)** | 3 | | **Channels** | 64 (×14) | | **Sampling rate (Hz)** | 5000 (×14) | | **Total duration (h)** | 2.1 | | **Size on disk** | 5.4 GB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Motor | | **Population** | Healthy | | **Source** | openneuro | | **License** | CC0 | ## Links - **DOI:** [10.18112/openneuro.ds006945.v1.2.1](https://doi.org/10.18112/openneuro.ds006945.v1.2.1) - **OpenNeuro:** [ds006945](https://openneuro.org/datasets/ds006945) - **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/ds006945). 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："数据集：受试者观看自我化身外骨骼行走时的T1加权结构磁共振成像（Magnetic Resonance Imaging, MRI）与功能磁共振成像（functional Magnetic Resonance Imaging, fMRI）数据（11个慢波睡眠周期）" 授权协议：CC0 1.0 标签：脑电图（Electroencephalogram, EEG）、神经科学、EEGDash、脑机接口（Brain-Computer Interface, BCI）、PyTorch、视觉相关、运动相关 样本量类别：样本量小于1000 任务类别：其他 # 数据集：受试者观看自我化身外骨骼行走时的T1加权结构MRI与fMRI数据（11个慢波睡眠周期） **数据集编号：** `ds006945` _Sarkar等人2025年_T1加权结构成像数据集_ > **概览：** EEG · 视觉运动任务 · 健康受试人群 · 5名受试者 · 14次记录 · CC0协议 ## 加载该数据集 本仓库为**指针仓库**，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="ds006945", cache_dir="./cache") print(len(ds), "次记录") 若该数据集已按照braindecode的Zarr格式镜像至Hugging Face Hub，也可直接拉取： python from braindecode.datasets import BaseConcatDataset ds = BaseConcatDataset.pull_from_hub("EEGDash/ds006945") ## 数据集元数据 | 指标 | 详情 | |---|---| | **受试者数量** | 5 | | **记录次数** | 14 | | **任务数量** | 3 | | **电极通道数** | 64（×14） | | **采样率（Hz）** | 5000（×14） | | **总时长（小时）** | 2.1 | | **磁盘占用大小** | 5.4 GB | | **记录类型** | 脑电图（EEG） | | **实验模态** | 视觉模态 | | **范式类型** | 运动范式 | | **受试人群** | 健康人群 | | **数据来源** | OpenNeuro | | **授权协议** | CC0 1.0 | ## 相关链接 - **DOI：** [10.18112/openneuro.ds006945.v1.2.1](https://doi.org/10.18112/openneuro.ds006945.v1.2.1) - **OpenNeuro平台：** [ds006945](https://openneuro.org/datasets/ds006945) - **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/ds006945)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`。_