---
pretty_name: "Gwilliams et al. 2023 — Introducing MEG-MASC: a high-quality magneto-encephalography dataset for evaluating natural speech processing"
license: cc0-1.0
tags:
  - eeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
size_categories:
  - 1K<n<10K
task_categories:
  - other
---

# Gwilliams et al. 2023 — Introducing MEG-MASC: a high-quality magneto-encephalography dataset for evaluating natural speech processing

**Dataset ID:** `nm000229`

_Gwilliams2023_

**Canonical aliases:** `MASC_MEG` · `MEG_MASC`

> **At a glance:** EEG · 29 subjects · 1360 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="nm000229", 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 MASC_MEG
ds = MASC_MEG(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/nm000229")
```


## Dataset metadata

| | |
|---|---|
| **Subjects** | 29 |
| **Recordings** | 1360 |
| **Tasks (count)** | 79 |
| **Channels** | 208 (×196) |
| **Sampling rate (Hz)** | 1000 (×196) |
| **Size on disk** | Unknown |
| **Recording type** | EEG |
| **Source** | nemar |
| **License** | CC0 |

## Links

- **DOI:** [10.1038/s41597-023-02752-5](https://doi.org/10.1038/s41597-023-02752-5)
- **NEMAR:** [nm000229](https://nemar.org/dataexplorer/detail?dataset_id=nm000229)
- **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/nm000229). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._