Datasets:

Dataset Viewer
Auto-converted to Parquet Duplicate
dataset_id
stringclasses
1 value
title
stringclasses
1 value
source
stringclasses
1 value
source_url
stringclasses
1 value
doi
stringclasses
1 value
license
stringclasses
1 value
loader
dict
catalog
stringclasses
1 value
generated_by
stringclasses
1 value
ds004942
SpatialMemory
openneuro
https://openneuro.org/datasets/ds004942
10.18112/openneuro.ds004942.v1.0.0
CC0
{ "library": "eegdash", "class": "EEGDashDataset", "kwargs": { "dataset": "ds004942" } }
https://huggingface.co/spaces/EEGDash/catalog
huggingface-space/scripts/push_metadata_stubs.py

SpatialMemory

Dataset ID: ds004942

Kieffaber2024

At a glance: EEG · Visual memory · healthy · 62 subjects · 62 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="ds004942", cache_dir="./cache")
print(len(ds), "recordings")

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/ds004942")

Dataset metadata

Subjects 62
Recordings 62
Tasks (count) 1
Channels 65 (×62)
Sampling rate (Hz) 1000 (×62)
Total duration (h) 28.3
Size on disk 25.1 GB
Recording type EEG
Experimental modality Visual
Paradigm type Memory
Population Healthy
BIDS version 1.8.0
Source openneuro
License CC0
NEMAR citations 1

Tasks

  • SpatialMemory

Upstream README

Verbatim from the dataset's authors — the canonical description.

Visuo-spatial working memory (VSWM) for sequences is thought to be crucial for daily behaviors. Decades of research indicate that oscillations in the gamma and theta bands play important functional roles in the support of visuo-spatial working memory, but the vast majority of that research emphasizes measures of neural activity during memory retention. The primary aims of the present study were (1) to determine whether oscillatory dynamics in the Theta and Gamma ranges would reflect item-level sequence encoding during a computerized spatial span task, (2) to determine whether item-level sequence recall is also related to these neural oscillations, and (3) to determine the nature of potential changes to these processes in healthy cognitive aging. Results indicate that VSWM sequence encoding is related to later (~700 ms) gamma band oscillatory dynamics and may be preserved in healthy older adults; high gamma power over midline frontal and posterior sites increased monotonically as items were added to the spatial sequence in both age groups. Item-level oscillatory dynamics during the recall of VSWM sequences were related only to theta-gamma phase amplitude coupling (PAC), which increased monotonically with serial position in both age groups. Results suggest that, despite a general decrease in frontal theta power during VSWM sequence recall in older adults, gamma band dynamics during encoding and theta-gamma PAC during retrieval play unique roles in VSWM and that the processes they reflect may be spared in healthy aging.

People

Authors

  • Paul Kieffaber
  • Makenna McGill (senior)

Contact

  • Paul Kieffaber

Links

Provenance

  • Backend: s3s3://openneuro.org/ds004942
  • Exact size: 26,899,933,059 bytes (25.1 GB)
  • Ingested: 2026-04-06
  • Stats computed: 2026-04-04

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.

Downloads last month
34