Datasets:

ds007591 / README.md
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Metadata stub for ds007591
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metadata
pretty_name: Delineating neural contributions to EEG-based speech decoding
license: cc0-1.0
tags:
  - eeg
  - neuroscience
  - eegdash
  - brain-computer-interface
  - pytorch
  - unknown
  - motor
size_categories:
  - n<1K
task_categories:
  - other

Delineating neural contributions to EEG-based speech decoding

Dataset ID: ds007591

Sato2026_Delineating

Canonical aliases: Sato2025

At a glance: EEG · Unknown motor · healthy · 3 subjects · 21 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="ds007591", 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 Sato2025
ds = Sato2025(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/ds007591")

Dataset metadata

Subjects 3
Recordings 21
Tasks (count) 3
Channels 139 (×21)
Sampling rate (Hz) 256 (×21)
Total duration (h) 6.8
Size on disk 1.6 GB
Recording type EEG
Experimental modality Unknown
Paradigm type Motor
Population Healthy
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.