Datasets:

ds005857 / README.md
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Metadata stub for ds005857
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metadata
pretty_name: ltpDelayRepFRReadOnly
license: cc0-1.0
tags:
  - eeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - visual
  - memory
size_categories:
  - n<1K
task_categories:
  - other

ltpDelayRepFRReadOnly

Dataset ID: ds005857

Broitman2025

Canonical aliases: Broitman2019

At a glance: EEG · Visual memory · unknown · 29 subjects · 110 recordings · CC0

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="ds005857", 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 Broitman2019
ds = Broitman2019(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/ds005857")

Dataset metadata

Subjects 29
Recordings 110
Tasks (count) 1
Channels 137 (×110)
Sampling rate (Hz) 2048 (×110)
Total duration (h) 101.0
Size on disk 284.4 GB
Recording type EEG
Experimental modality Visual
Paradigm type Memory
Population Unknown
Source openneuro
License CC0

Links


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.