TraceLAB: A MATLAB Toolbox for Interindividual Synchrony Analysis of Facial Expression and Head Movement Data Acquired via Trace
Facial expressions transmit information about internal states, both during social interaction and in response to shared stimuli such as films. When individuals view the same content, synchrony in their expressions reflects shared information processing, and the degree to which their expressions correlate indicates how similarly their perceptual and affective systems are responding to the common input. This makes interindividual expression synchrony a potential marker of engagement and subjective experience. However, the acquisition and analysis of facial data pose both ethical and technical challenges to researchers. ‘Trace’ is a research media player implemented in PsychoPy’s online platform Pavlovia, which captures anonymised facial landmark coordinates through a webcam, without the ethical and technical constraints of capturing and storing video images of participants. Nonetheless, its usefulness is currently limited due to the lack of available preprocessing and analysis tools. This paper describes the functionality of TraceLAB, a MATLAB-based toolbox designed for the preprocessing of Trace data: specifically, the formatting, aligning, and filtering of data. In addition, TraceLAB implements some novel analysis techniques to allow researchers to quantify interindividual synchrony of expressions (through correlated component analysis) and head movements (through Surrogate Synchrony), which may be interpreted as measures of shared information processing. These techniques are demonstrated here on both simulated and real datasets.
Authors
- Iain D. Gilchrist (ORCID: https://orcid.org/0000-0003-2070-6679)
- Danaë Stanton Fraser
- Felix Carter (ORCID: https://orcid.org/0000-0002-1020-2939)
- Mike Richardson (ORCID: https://orcid.org/0000-0002-5433-6250)
Institutions
- University of Bristol (GB)
- University of Bath (GB)
Publication Details
- Journal
- Entropy
- Published
- 2026-04-29
- DOI
- https://doi.org/10.3390/e28050503
- Primary Topic
- Face Recognition and Perception
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- UK Research and Innovation