--- pretty_name: "BigP3BCI Study S1 — 9x8 face/house paradigm (10 healthy subjects)" license: cc-by-4.0 tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - attention size_categories: - n<1K task_categories: - other --- # BigP3BCI Study S1 — 9x8 face/house paradigm (10 healthy subjects) **Dataset ID:** `nm000247` _Mainsah2025_BigP3BCI_S1_ **Canonical aliases:** `BigP3BCI_StudyS1` · `BigP3BCI_S1` > **At a glance:** EEG · Visual attention · healthy · 10 subjects · 120 recordings · CC-BY-4.0 ## 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="nm000247", 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 BigP3BCI_StudyS1 ds = BigP3BCI_StudyS1(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/nm000247") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 10 | | **Recordings** | 120 | | **Tasks (count)** | 1 | | **Channels** | 32 (×120) | | **Sampling rate (Hz)** | 256.0000766323896 (×120) | | **Total duration (h)** | 5.6 | | **Size on disk** | 477.9 MB | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Attention | | **Population** | Healthy | | **Source** | nemar | | **License** | CC-BY-4.0 | ## Links - **NEMAR:** [nm000247](https://nemar.org/dataexplorer/detail?dataset_id=nm000247) - **Browse 700+ datasets:** [EEGDash catalog](https://huggingface.co/spaces/EEGDash/catalog) - **Docs:** - **Code:** --- _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/nm000247). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._