Datasets:

File size: 2,522 Bytes
dc7908a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
---
pretty_name: "NeuroMorph: A High-Temporal Resolution MEG Dataset for Morpheme-Based Linguistic Analysis"
license: cc0-1.0
tags:
  - meg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - unknown
  - other
size_categories:
  - n<1K
task_categories:
  - other
---

# NeuroMorph: A High-Temporal Resolution MEG Dataset for Morpheme-Based Linguistic Analysis

**Dataset ID:** `ds005241`

_Rodriguez2024_

**Canonical aliases:** `NeuroMorph` · `neuromorph`

> **At a glance:** MEG · Unknown other · healthy · 24 subjects · 117 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="ds005241", 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 NeuroMorph
ds = NeuroMorph(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/ds005241")
```


## Dataset metadata

| | |
|---|---|
| **Subjects** | 24 |
| **Recordings** | 117 |
| **Tasks (count)** | 2 |
| **Channels** | 256 (×117) |
| **Sampling rate (Hz)** | 1000 (×27) |
| **Total duration (h)** | 3.7 |
| **Size on disk** | 140.5 GB |
| **Recording type** | MEG |
| **Experimental modality** | Unknown |
| **Paradigm type** | Other |
| **Population** | Healthy |
| **Source** | openneuro |
| **License** | CC0 |
| **NEMAR citations** | 0.0 |

## Links

- **DOI:** [10.18112/openneuro.ds005241.v1.1.0](https://doi.org/10.18112/openneuro.ds005241.v1.1.0)
- **OpenNeuro:** [ds005241](https://openneuro.org/datasets/ds005241)
- **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/ds005241). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._