metadata
pretty_name: BNCI 2025-002 Continuous 2D Trajectory Decoding dataset
license: cc-by-4.0
tags:
- eeg
- neuroscience
- eegdash
- brain-computer-interface
- pytorch
- visual
- motor
- other
size_categories:
- n<1K
task_categories:
- other
BNCI 2025-002 Continuous 2D Trajectory Decoding dataset
Dataset ID: nm000170
Pulferer2025
Canonical aliases: BNCI2025
At a glance: EEG · Visual motor · other · 10 subjects · 90 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 streams it on demand and returns a PyTorch / braindecode dataset.
# pip install eegdash
from eegdash import EEGDashDataset
ds = EEGDashDataset(dataset="nm000170", cache_dir="./cache")
print(len(ds), "recordings")
You can also load it by canonical alias — these are registered classes in eegdash.dataset:
from eegdash.dataset import BNCI2025
ds = BNCI2025(cache_dir="./cache")
If the dataset has been mirrored to the HF Hub in braindecode's Zarr layout, you can also pull it directly:
from braindecode.datasets import BaseConcatDataset
ds = BaseConcatDataset.pull_from_hub("EEGDash/nm000170")
Dataset metadata
| Subjects | 10 |
| Recordings | 90 |
| Tasks (count) | 1 |
| Channels | 60 (×90) |
| Sampling rate (Hz) | 200 (×90) |
| Total duration (h) | 28.2 |
| Size on disk | 3.4 GB |
| Recording type | EEG |
| Experimental modality | Visual |
| Paradigm type | Motor |
| Population | Other |
| Source | nemar |
| License | CC-BY-4.0 |
Links
- NEMAR: nm000170
- Browse 700+ datasets: EEGDash catalog
- Docs: https://eegdash.org
- Code: https://github.com/eegdash/EEGDash
Auto-generated from dataset_summary.csv and the EEGDash API. Do not edit this file by hand — update the upstream source and re-run scripts/push_metadata_stubs.py.