Longitudinal ERP dataset (RSVP): EEG decoding results

Name: BCI Report: results on Longitudinal ERP dataset (RSVP)
Creator: BCI Report
License: https://creativecommons.org/licenses/by/4.0/

RSVP face-target ERP, the same people at nominal Day 1, 7, 80 and 200 visits

Longitudinal ERP dataset (RSVP): EEG decoding results

A longitudinal EEG dataset of event-related potential (figshare 27201003) holds EEG from a rapid serial visual presentation task in which participants identified a target face: 15 people (Group A) recorded at four visits labelled Day 1, 7, 80 and 200, and 52 people (Group B) recorded once, with 57 EEG channels. Released by Chen Yang, Yufeng Zhang and colleagues (Beijing University of Posts and Telecommunications) under CC0 and described in Scientific Data (2025). Only Group A is used here.

Also known as A longitudinal EEG dataset of event-related potential · figshare 27201003 · Longitudinal ERP dataset · Zhang et al. (2025)

Description sources doi.org · doi.org · api.figshare.com

Where it appears

Does a decoder trained on an earlier session still work later?

Published results

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

Later sessions · RSVP target detection, first visit to later visits

Read with its protocol: Later sessions · later-sessions-update.json

Method	Condition	Metric	Value	People
Normalized ERP features + logistic/Platt (CPU baseline)	Trained at the first visit · nominal Day 7	AUROC	0.8880.864–0.911Targets: 1,794 of 72,000 events. AUROC ranks; it is not accuracy.	15
Normalized ERP features + logistic/Platt (CPU baseline)	Trained at the first visit · nominal Day 7	Average precision	0.359	15
Normalized ERP features + logistic/Platt (CPU baseline)	Trained at the first visit · nominal Day 80	AUROC	0.8790.854–0.903Targets: 1,786 of 72,000 events. AUROC ranks; it is not accuracy.	15
Normalized ERP features + logistic/Platt (CPU baseline)	Trained at the first visit · nominal Day 80	Average precision	0.310	15
Normalized ERP features + logistic/Platt (CPU baseline)	Trained at the first visit · nominal Day 200	AUROC	0.8530.827–0.879Targets: 1,793 of 72,000 events. AUROC ranks; it is not accuracy.	15
Normalized ERP features + logistic/Platt (CPU baseline)	Trained at the first visit · nominal Day 200	Average precision	0.240	15
Normalized ERP features + logistic/Platt (CPU baseline)	Day 200 minus Day 7, the same people	AUROC difference	−0.035−0.065–−0.0066 of 15 people lost 0.05 AUROC or more. Nominal visit labels: no claim that elapsed time caused it.	15

Source and licence

Longitudinal ERP dataset (RSVP)

Credit Chen Yang, Yufeng Zhang, Hongxin Zhang, Yixuan Li, Yijun Wang and Xiaorong Gao · A longitudinal EEG dataset of event-related potential, figshare, doi:10.6084/m9.figshare.27201003.v1, CC0. Paper: Yufeng Zhang, Hongxin Zhang, Yixuan Li, Yijun Wang, Xiaorong Gao and Chen Yang, A longitudinal EEG dataset of event-related potential, Scientific Data 12, 1069 (2025), doi:10.1038/s41597-025-05378-x. Derived analysis by BCI Report; not endorsed by the authors.

CC0-1.0 ↗ · Dataset record ↗

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data belong to the people credited.

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Cite this page

BCI Report (2026). Longitudinal ERP dataset (RSVP): EEG decoding results. https://bci.report/datasets/longitudinal-rsvp/

Figures from release later-sessions-update-20261008 (2026-10-08). Cite the upstream dataset as well: its credit is on this page.

Every release is archived on Zenodo: doi:10.5281/zenodo.23123296. BibTeX for the site and its releases → · CITATION.cff ↗