# REFED emotion dataset (EEG-fNIRS): EEG decoding results

Self-reported valence and arousal while watching videos: a stored-clip diagnostic

REFED (A Subject Real-time Dynamic Labeled EEG-fNIRS Synchronized Recorded Emotion Dataset) holds simultaneously recorded EEG and fNIRS from 32 healthy participants watching 15 emotion-eliciting video clips, with valence and arousal annotated continuously, in real time, by the participants themselves. Released on Hugging Face by Xiaojun Ning, Ziyu Jia and colleagues under CC BY-NC-SA 4.0, behind a gate that asks users to agree to non-commercial use and to cause no harm to human subjects, and described at NeurIPS 2025 (Datasets and Benchmarks Track). Only stored EEG clips from two nominal participant folders are used here.

**Also known as** REFED · A Subject Real-time Dynamic Labeled EEG-fNIRS Synchronized Recorded Emotion Dataset · REFED2025/REFED-dataset · Ning et al. (2025)

Description sources [huggingface.co](https://huggingface.co/datasets/REFED2025/REFED-dataset) · [papers.neurips.cc](https://papers.neurips.cc/paper_files/paper/2025/file/2bf0ed7c35d9d84128e7f7c72ab76402-Paper-Datasets_and_Benchmarks_Track.pdf)

## Where it appears

- [What can a small pilot show, and what can it not?](https://bci.report/topics/pilot-studies/#refed)

## Published results

Every figure below is copied from a reviewed download, not recomputed for this page.

### Pilot studies · REFED stored clips, a computational diagnostic

Read with its protocol: [Pilot studies](https://bci.report/topics/pilot-studies/#refed) · [pilot-studies-update.json](https://bci.report/data/pilot-studies-update.json)

| Method | Condition | Metric | Value | People |
| --- | --- | --- | --- | --- |
| EEG Ridge (relative band power) | Shared videos, a folder held out (familiar stimuli) | Equal-axis mean absolute error, raw self-report scale (lower is better) | 107.182 | 2 nominal participant folders |
| Source global mean — reference or comparator, not a decoding model | Shared videos, a folder held out (familiar stimuli) | Equal-axis mean absolute error, raw self-report scale (lower is better) | 40.287 | 2 nominal participant folders |
| Source video lookup — reference or comparator, not a decoding model | Shared videos, a folder held out (familiar stimuli) | Equal-axis mean absolute error, raw self-report scale (lower is better) | 27.325 | 2 nominal participant folders |
| Duration / numeric-video-ID ridge — reference or comparator, not a decoding model | Shared videos, a folder held out (familiar stimuli) | Equal-axis mean absolute error, raw self-report scale (lower is better) | 37.910 | 2 nominal participant folders |
| EEG Ridge (relative band power) | Folder and video IDs held out together | Equal-axis mean absolute error, raw self-report scale (lower is better) | 91.984 | 2 nominal participant folders |
| Source global mean — reference or comparator, not a decoding model | Folder and video IDs held out together | Equal-axis mean absolute error, raw self-report scale (lower is better) | 41.032 | 2 nominal participant folders |
| Source video lookup — reference or comparator, not a decoding model | Folder and video IDs held out together | Equal-axis mean absolute error, raw self-report scale (lower is better) | 41.032 | 2 nominal participant folders |
| Duration / numeric-video-ID ridge — reference or comparator, not a decoding model | Folder and video IDs held out together | Equal-axis mean absolute error, raw self-report scale (lower is better) | 47.098 | 2 nominal participant folders |

2 nominal participant folders with the same 15 videos: 30 clips, not as many independent people, so no interval or significance test is reported. EEG Ridge has a larger error than every source-only control in both conditions. With shared videos, the same-video lookup has the smallest error, because familiar stimuli carry the prediction; held out together, it has no matching video and equals the global mean. Targets are the mean of each clip’s stored valence and arousal labels on the published raw scale, not SAM scores. Stored EEG units, the EEG-to-rating clock and the crop end points are unresolved, and the rating means were seen before this design. No physiological, neural or population claim; outside every leaderboard.

## Source and licence

### REFED emotion dataset (EEG-fNIRS)

**Credit** Xiaojun Ning, Jing Wang, Zhiyang Feng, Tianzuo Xin, Shuo Zhang, Shaoqi Zhang, Zheng Lian, Yi Ding, Youfang Lin and Ziyu Jia · REFED: A Subject Real-time Dynamic Labeled EEG-fNIRS Synchronized Recorded Emotion Dataset, NeurIPS 2025 Datasets and Benchmarks Track. Data: REFED2025/REFED-dataset on Hugging Face, revision 0298355c2823946ac5800b2ec12a082bf2dcd01b, CC BY-NC-SA 4.0, gated. Derived analysis by BCI Report; not endorsed by the authors.

[CC BY-NC-SA 4.0 ↗](https://creativecommons.org/licenses/by-nc-sa/4.0/) · [Dataset record ↗](https://huggingface.co/datasets/REFED2025/REFED-dataset)

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data remain their creators’.

[All datasets →](https://bci.report/datasets/) · [All methods →](https://bci.report/methods/)

## Cite this page

BCI Report (2026). *REFED emotion dataset (EEG-fNIRS): EEG decoding results*. https://bci.report/datasets/refed/

Figures from release [`pilot-studies-update-20261012`](https://bci.report/releases/#pilot-studies-update-20261012) (2026-10-12). Cite the upstream dataset as well: its credit is on this page.

Every release is archived on Zenodo: [doi:10.5281/zenodo.23123296](https://doi.org/10.5281/zenodo.23123296). [BibTeX for the site and its releases →](https://bci.report/api/#cite-heading) · [CITATION.cff ↗](https://raw.githubusercontent.com/twu3202/bci-report/main/CITATION.cff)

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Markdown copy of https://bci.report/datasets/refed/, generated from the published page. Figures are aggregate results; terms of use: https://bci.report/data-use/