Early electrophysiological responses reflect precision-weighted prediction errors to face features.

Overview

1. Department of General Psychology, Università degli Studi di Padova, Padua, Italy
2. Department of Experimental Psychology, University College London, London, United Kingdom
3. IRCCS San Camillo Hospital, Venice, Italy
4. Functional Imaging Laboratory, University College London, London, United Kingdom

Abstract

Facial expressions serve as a key source of information about an individual’s emotional state, intentions, and the surrounding environment. Efficient error processing of facial features is therefore particularly important for successful social interaction. Nonetheless, while simple feature-selective error processing has been well documented, the literature on error processing in complex visual features, such as those of facial stimuli, that may not generate specific predictions at the fine-grained level of simple ones, presents mixed findings. The present study aimed to determine whether facial feature-related processing activity reflects precision-weighted prediction errors (pwPEs), and to investigate how rapidly these feature-selective error signals emerge within the EEG epoch. Using the Hierarchical Gaussian Filter to model pwPE evolution, a consistent relationship was observed between pwPE trajectories and neuronal activity, with peak effects emerging at approximately 140 ms post-stimulus onset. These findings provide evidence that facial expression prediction errors are computed early during face visual processing. During social interactions, this timely error signaling likely enables the continuous updating of predictive models about a social partner’s likely responses to environmental stimuli or interpersonal actions, facilitating rapid and adaptive behaviours that promote smooth social engagement.

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Data

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Data Availability

All scripts used in this study (i.e., the code for the experimental paradigm, the MATLAB pipeline for computing precision-weighted prediction errors with the Hierarchical Gaussian Filter, and the SPM12 analysis code) are openly available in the project’s associated OSF repository: https://osf.io/xhmcu/ The data are not publicly available due to institutional regulations at the data collection site designed to protect the privacy of biomedical data containing potentially identifying or sensitive information. Requests may be directed to the Data Protection Officer of IRCCS San Camillo Hospital () and will be considered in accordance with Italian regulations governing the privacy of biomedical data. This manuscript was written following the PECANS checklist [77] for transparent reporting, that can be found in the project’s associated OSF repository.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 6 MeSH terms, 1 funder, 69 references.

Cite

This paper

Costa, C., Ward, E. K., Pezzetta, R., Masina, F., Arcara, G., Press, C., & Scarpazza, C. (2026). Early electrophysiological responses reflect precision-weighted prediction errors to face features. PloS one, 21(9), e0357956. https://doi.org/10.1371/journal.pone.0357956

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