Datasets:

EEGDash
/

ds002001

pretty_name: Rivalry_Tagging
license: other
tags:
  - meg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - visual
  - perception
size_categories:
  - n<1K
task_categories:
  - other

Rivalry_Tagging

Dataset ID: ds002001

Mendola2019

Canonical aliases: Mendola2020

At a glance: MEG · Visual perception · healthy · 11 subjects · 69 recordings · PD

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="ds002001", 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 Mendola2020
ds = Mendola2020(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/ds002001")

Dataset metadata


Subjects	11
Recordings	69
Tasks (count)	2
Sampling rate (Hz)	2400 (×69)
Size on disk	81.7 GB
Recording type	MEG
Experimental modality	Visual
Paradigm type	Perception
Population	Healthy
Source	openneuro
License	PD
NEMAR citations	3.0

Rivalry_Tagging

Load this dataset

Dataset metadata

Links