---
pretty_name: "BNCI 2015-003 P300 dataset"
license: other
tags:
  - eeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - auditory
  - attention
size_categories:
  - n<1K
task_categories:
  - other
---

# BNCI 2015-003 P300 dataset

**Dataset ID:** `nm000189`

_Schreuder2015_P300_

**Canonical aliases:** `BNCI2015_P300` · `BNCI2015_003_P300` · `BNCI2015_003_AMUSE`

> **At a glance:** EEG · Auditory attention · healthy · 10 subjects · 20 recordings · CC-BY-NC-ND-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="nm000189", 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 BNCI2015_P300
ds = BNCI2015_P300(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/nm000189")
```


## Dataset metadata

| | |
|---|---|
| **Subjects** | 10 |
| **Recordings** | 20 |
| **Tasks (count)** | 1 |
| **Channels** | 8 (×20) |
| **Sampling rate (Hz)** | 256 (×20) |
| **Total duration (h)** | 0.9 |
| **Size on disk** | 21.8 MB |
| **Recording type** | EEG |
| **Experimental modality** | Auditory |
| **Paradigm type** | Attention |
| **Population** | Healthy |
| **Source** | nemar |
| **License** | CC-BY-NC-ND-4.0 |

## Links

- **NEMAR:** [nm000189](https://nemar.org/dataexplorer/detail?dataset_id=nm000189)
- **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/nm000189). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._