Investigating face processing in online interactions via UK–US hyperscanning using fNIRS

Videoconferencing technology has become a staple of everyday life and has found widespread use in business, education, and tele-medicine. Despite this, there have been few empirical studies investigating the neural correlates of interactions during this form of communication. This study investigates the neural mechanisms of face processing during online videoconferencing, employing functional near-infrared spectroscopy (fNIRS). We synchronised presentation and acquisition of fNIRS data across laboratories in the UK and US using custom Python software and a third-party computer system. Using this framework, we examine how different presentations of faces (live-online vs. static images) influence social cognition and inter-brain coupling (IBC) in a videoconferencing context. Forty participants (20 dyads) engaged in online sessions where they viewed either dynamic video feeds or static images of their partners' faces. Our findings did not show preferential activity in the right supramarginal gyrus during the observation of live on-line faces as expected from prior studies of live in-person face gaze. However, occipital-temporal and dorsal visual streams were more active for live-online faces than static-online faces. There was no observed evidence for increased cross-brain synchrony during the live face condition compared with the static face condition. Findings suggest that on-line studies of social interaction open a novel field of investigation that is differentiated from live interactions.

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Publication Details

Journal
Imaging Neuroscience
Published
2025-12-19
DOI
https://doi.org/10.1162/imag.a.1101
Primary Topic
Face Recognition and Perception
Type
article
Field-Weighted Citation Impact
0.00

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article

Investigating face processing in online interactions via UK–US hyperscanning using fNIRS

J. Adam Noah, Uzair Hakim, Paola Pinti, Xian Z. Zhang et al.
Imaging Neuroscience
Face Recognition and Perception
article

Investigating face processing in online interactions via UK–US hyperscanning using fNIRS

J. Adam Noah, Uzair Hakim, Paola Pinti, Xian Z. Zhang, Ilias Tachtsidis, Natalie Gunasekara, Joy Hirsch, Antonia Hamilton
article en

Abstract

Videoconferencing technology has become a staple of everyday life and has found widespread use in business, education, and tele-medicine. Despite this, there have been few empirical studies investigating the neural correlates of interactions during this form of communication. This study investigates the neural mechanisms of face processing during online videoconferencing, employing functional near-infrared spectroscopy (fNIRS). We synchronised presentation and acquisition of fNIRS data across laboratories in the UK and US using custom Python software and a third-party computer system. Using this framework, we examine how different presentations of faces (live-online vs. static images) influence social cognition and inter-brain coupling (IBC) in a videoconferencing context. Forty participants (20 dyads) engaged in online sessions where they viewed either dynamic video feeds or static images of their partners' faces. Our findings did not show preferential activity in the right supramarginal gyrus during the observation of live on-line faces as expected from prior studies of live in-person face gaze. However, occipital-temporal and dorsal visual streams were more active for live-online faces than static-online faces. There was no observed evidence for increased cross-brain synchrony during the live face condition compared with the static face condition. Findings suggest that on-line studies of social interaction open a novel field of investigation that is differentiated from live interactions.

Imaging NeuroscienceVol. 4
Yale University (US), University College London (GB), Birkbeck, University of London (GB)
Yale University, Wellcome Trust, National Institutes of Health, Engineering and Physical Sciences Research Council, National Institute of Mental Health
Quality Education
Openalex Percentile: Top 34%
Face Recognition and Perception
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