| --- |
| pretty_name: "pyFR: Delayed Free Recall of Word Lists, Preliminary Cognitive Electrophysiology Study" |
| license: cc0-1.0 |
| tags: |
| - ieeg |
| - neuroscience |
| - eegdash |
| - brain-computer-interface |
| - pytorch |
| - visual |
| - memory |
| - surgery |
| - pyfr |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| authors: |
| - "Haydn G. Herrema" |
| - "Michael J. Kahana" |
| --- |
| |
| # pyFR: Delayed Free Recall of Word Lists, Preliminary Cognitive Electrophysiology Study |
|
|
| **Dataset ID:** `ds004865` |
|
|
| _Herrema2023_pyFR_Delayed_Free_ |
|
|
| **Canonical aliases:** `pyFR` |
|
|
| > **At a glance:** IEEG · Visual memory · surgery · 42 subjects · 172 recordings · CC0 |
|
|
| ## Load this dataset |
|
|
| This repo is a **pointer**. The raw EEG data lives at its canonical source |
| (OpenNeuro / NEMAR); [EEGDash](https://github.com/eegdash/EEGDash) streams it |
| on demand and returns a PyTorch / braindecode dataset. |
|
|
| ```python |
| # pip install eegdash |
| from eegdash import EEGDashDataset |
| |
| ds = EEGDashDataset(dataset="ds004865", cache_dir="./cache") |
| print(len(ds), "recordings") |
| ``` |
|
|
| You can also load it by canonical alias — these are registered classes in `eegdash.dataset`: |
|
|
| ```python |
| from eegdash.dataset import pyFR |
| ds = pyFR(cache_dir="./cache") |
| ``` |
|
|
| If the dataset has been mirrored to the HF Hub in braindecode's Zarr layout, |
| you can also pull it directly: |
|
|
| ```python |
| from braindecode.datasets import BaseConcatDataset |
| ds = BaseConcatDataset.pull_from_hub("EEGDash/ds004865") |
| ``` |
|
|
|
|
| ## Dataset metadata |
|
|
| | | | |
| |---|---| |
| | **Subjects** | 42 | |
| | **Age range** | 15–57 yrs, mean 34.1 | |
| | **Recordings** | 172 | |
| | **Tasks (count)** | 1 | |
| | **Sessions** | 5 | |
| | **Channels** | 100 (×7), 80 (×5), 74 (×5), 131 (×5), 46 (×4), 108 (×4), 62 (×4), 110 (×4), 54 (×4), 85 (×4), 86 (×4), 53 (×4), 32 (×3), 116 (×3), 47 (×3), 150 (×3), 121 (×3), 42 (×3), 55 (×3), 75 (×3), 78 (×3), 84 (×3), 109 (×3), 27 (×3), 82 (×3), 91 (×3), 72 (×3), 88 (×3), 105 (×3), 168 (×3), 48 (×3), 123 (×3), 96 (×3), 70 (×3), 104 (×3), 130 (×2), 63 (×2), 126 (×2), 68 (×2), 57 (×2), 52 (×2), 36 (×2), 102 (×2), 124 (×2), 76 (×2), 111 (×2), 58 (×2), 149 (×2), 144 (×2), 87 (×2), 119 (×2), 153 (×2), 142 (×2), 187 (×1), 95 (×1), 81 (×1), 90 (×1), 56 (×1), 94 (×1), 98 (×1), 160 (×1), 203 (×1), 120 (×1), 101 (×1), 97 (×1), 64 (×1) | |
| | **Sampling rate (Hz)** | 1000 (×102), 512 (×40), 2000 (×16), 400 (×8), 499.7071 (×6) | |
| | **Total duration (h)** | 180.6 | |
| | **Size on disk** | 97.8 GB | |
| | **Recording type** | IEEG | |
| | **Experimental modality** | Visual | |
| | **Paradigm type** | Memory | |
| | **Population** | Surgery | |
| | **BIDS version** | 1.7.0 | |
| | **Source** | openneuro | |
| | **License** | CC0 | |
| | **NEMAR citations** | 0 | |
|
|
| ## Tasks |
|
|
| - `pyFR` |
|
|
|
|
| ## Upstream README |
|
|
| _Verbatim from the dataset's authors — the canonical description._ |
|
|
| ### pyFR: Delayed Free Recall of Word Lists, Preliminary Cognitive Electrophysiology Study |
| #### Description |
| This dataset contains behavioral events and intracranial electrophysiological recordings from a delayed free recall task. The experiment consists of participants studying a list of words, presented visually one at a time, completing simple arithmetic problems that function as a distractor, and then freely recalled the words from the just-presented list in any order. The data was collected at clinical sites across the country as part of a collaboration with the Computational Memory Lab at the University of Pennsylvania. |
| This study was a preliminary cogntive electrophysiology study undertaken by the Computational Memory Lab, and is a predecessor to the following datasets: [FR1](https://openneuro.org/datasets/ds004789) & [CatFR1](https://openneuro.org/datasets/ds004809) |
| #### To Note |
| * The iEEG recordings are labeled either "monopolar" or "bipolar." The monopolar recordings are referenced (typically a mastoid reference), but should always be re-referenced before analysis. The bipolar recordings are referenced according to a paired scheme indicated by the accompanying bipolar channels tables. |
| * Each subject has a unique montage of electrode locations. MNI and Talairach coordinates are provided when available, along with brain region annotations. |
| * Recordings were made on multiple different systems, so we have done the scaling to provide all voltage values in V. |
| #### Contact |
| For questions or inquiries, please contact sas-kahana-sysadmin@sas.upenn.edu. |
|
|
|
|
| ## People |
|
|
| ### Authors |
| - Haydn G. Herrema |
| - Michael J. Kahana _(senior)_ |
|
|
| ### Contact |
| - Haydn Herrema |
|
|
| ## Funding |
|
|
| - NIH: MH055687 |
| - NIH: MH061975 |
|
|
| ## Links |
|
|
| - **DOI:** [10.18112/openneuro.ds004865.v2.0.1](https://doi.org/10.18112/openneuro.ds004865.v2.0.1) |
| - **OpenNeuro:** [ds004865](https://openneuro.org/datasets/ds004865) |
| - **Browse 700+ datasets:** [EEGDash catalog](https://huggingface.co/spaces/EEGDash/catalog) |
| - **Docs:** <https://eegdash.org> |
| - **Code:** <https://github.com/eegdash/EEGDash> |
|
|
| ## Provenance |
|
|
| - **Backend:** `s3` — `s3://openneuro.org/ds004865` |
| - **Exact size:** 104,999,471,870 bytes (97.8 GB) |
| - **Ingested:** 2026-04-06 |
| - **Stats computed:** 2026-04-04 |
|
|
| --- |
|
|
| _Auto-generated from [dataset_summary.csv](https://github.com/eegdash/EEGDash/blob/main/eegdash/dataset/dataset_summary.csv) and the [EEGDash API](https://data.eegdash.org/api/eegdash/datasets/summary/ds004865). Do not edit this file by hand — update the upstream source and re-run `scripts/push_metadata_stubs.py`._ |
|
|
