Inter-Subject Correlations of Pupillary Audience Responses

Decoding Visual Attention and Predicting Memory in a VR Media Setting

Bibliographic Data

ID17811433
AuthorsRalf Schmälzle (0000-0002-0179-1364, Michigan State University, corresponding author), Juncheng Wu (0000-0003-3884-6856, Communication University of China), Sue Lim (0000-0001-7559-1317, Michigan State University), Gary Bente (0009-0005-0819-8132, Michigan State University)
Year2025
Volume38
Issue3
Pages137-151
Publication date2025-02-19
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Media Psychology Theories Methods and Applications (JOURNAL)
Journal identifiersISSN: 1864-1105 • E-ISSN: 2151-2388
PublisherHogrefe Verlag (PUBLISHER • DE)
DOI10.1027/1864-1105/a000457
OpenAlexW4407721979
LanguageEN
References cited48

This study introduces a novel VR-based approach to measure pupillary responses during media consumption. Researchers exposed participants to 30 video messages in a virtual TV viewing room, capturing pupil dilation and constriction via VR-integrated eye-tracking. By analyzing cross-receiver similarity (inter-subject correlations) of pupillometric responses, we could identify which specific video an individual was watching. This method worked best under normal viewing conditions and was sensitive to attentional manipulations. This study also found that messages with the most robust pupil response signatures were more likely to be remembered. Theoretical implications for quantifying media exposure and developing signatures of perceptual attention in individuals and audiences are discussed. Practically, this pupillary audience response measurement could be applied to various media formats, including screen-based media, social media, and VR/AR environments. In sum, the study highlights the potential of pupillometry in understanding audience engagement and response dynamics in naturalistic media consumption settings

Pupil · World Wide Web · Color perception and design · Computer Science · Multisensory perception and integration · Neuroscience · Psychology · Visual perception and processing mechanisms

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