--- pretty_name: "romani-bf2025-erp - NEMAR Dataset" license: other tags: - eeg - neuroscience - eegdash - brain-computer-interface - pytorch - visual - attention size_categories: - 1K **At a glance:** EEG · Visual attention · unknown · 22 subjects · 1022 recordings · Unknown ## 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="nm000272", 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 Romani2025_erp ds = Romani2025_erp(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/nm000272") ``` ## Dataset metadata | | | |---|---| | **Subjects** | 22 | | **Recordings** | 1022 | | **Tasks (count)** | 3 | | **Channels** | 8 (×120) | | **Sampling rate (Hz)** | 250 (×120) | | **Total duration (h)** | 6.3 | | **Size on disk** | Unknown | | **Recording type** | EEG | | **Experimental modality** | Visual | | **Paradigm type** | Attention | | **Population** | Unknown | | **Source** | nemar | | **License** | Unknown | ## Links - **NEMAR:** [nm000272](https://nemar.org/dataexplorer/detail?dataset_id=nm000272) - **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/nm000272). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._