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ds005557
Free Recall with Closed-Loop Stimulation at Encoding (Encoding Classifier)
openneuro
https://openneuro.org/datasets/ds005557
10.18112/openneuro.ds005557.v1.0.0
CC0
{ "library": "eegdash", "class": "EEGDashDataset", "kwargs": { "dataset": "ds005557" } }
https://huggingface.co/spaces/EEGDash/catalog
huggingface-space/scripts/push_metadata_stubs.py

Free Recall with Closed-Loop Stimulation at Encoding (Encoding Classifier)

Dataset ID: ds005557

Herrema2024_Classifier

At a glance: IEEG · Visual memory · other · 16 subjects · 58 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="ds005557", 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/ds005557")

Dataset metadata

Subjects 16
Recordings 58
Tasks (count) 1
Channels 110 (×7), 112 (×6), 76 (×5), 109 (×4), 126 (×4), 108 (×4), 127 (×3), 67 (×2), 70 (×2), 62 (×2), 64 (×2), 60 (×2), 97 (×2), 120 (×2), 83 (×2), 128 (×2), 125 (×1), 99 (×1), 95 (×1), 118 (×1), 121 (×1), 124 (×1), 136 (×1)
Sampling rate (Hz) 1000 (×58)
Total duration (h) 51.1
Size on disk 34.7 GB
Recording type IEEG
Experimental modality Visual
Paradigm type Memory
Population Other
Source openneuro
License CC0
NEMAR citations 0.0

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.

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