Quantification of inter-brain coupling: A review of current methods used in haemodynamic and electrophysiological hyperscanning studies.

Hyperscanning is a form of neuroimaging experiment where the brains of two or more participants are imaged simultaneously whilst they interact. Within the domain of social neuroscience, hyperscanning is increasingly used to measure inter-brain coupling (IBC) and explore how brain responses change in tandem during social interaction. In addition to cognitive research, some have suggested that quantification of the interplay between interacting participants can be used as a biomarker for a variety of cognitive mechanisms aswell as to investigate mental health and developmental conditions including schizophrenia, social anxiety and autism. However, many different methods have been used to quantify brain coupling and this can lead to questions about comparability across studies and reduce research reproducibility. Here, we review methods for quantifying IBC, and suggest some ways moving forward. Following the PRISMA guidelines, we reviewed 215 hyperscanning studies, across four different brain imaging modalities: functional near-infrared spectroscopy (fNIRS), functional magnetic resonance (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG). Overall, the review identified a total of 27 different methods used to compute IBC. The most common hyperscanning modality is fNIRS, used by 119 studies, 89 of which adopted wavelet coherence. Based on the results of this literature survey, we first report summary statistics of the hyperscanning field, followed by a brief overview of each signal that is obtained from each neuroimaging modality used in hyperscanning. We then discuss the rationale, assumptions and suitability of each method to different modalities which can be used to investigate IBC. Finally, we discuss issues surrounding the interpretation of each method.

Having a chat and then watching a movie: how social interaction synchronises our brains during co-watching.

How does co-presence change our neural experience of the world? Can a conversation change how we synchronise with our partner during later events? Using fNIRS hyperscanning, we measured brain activity from 27 pairs of familiar adults simultaneously over frontal, temporal and parietal regions bilaterally, as they co-watched two different episodes of a short cartoon. In-between the two episodes, each pair engaged in a face-to-face conversation on topics unrelated to the cartoon episodes. Brain synchrony was calculated using wavelet transform coherence and computed separately for real pairs and shuffled pseudo) pairs. Findings reveal that real pairs showed increased brain synchrony over right Dorso-Lateral Pre-Frontal cortex (DLPFC) and right Superior Parietal Lobe (SPL), compared to pseudo pairs (who had never seen each other and watched the same movie at different times; uncorrected for multiple comparisons). In addition, co-watching after a conversation was associated with greater synchrony over right TPJ compared to co-watching before a conversation, and this effect was significantly higher in real pairs (who engaged in conversation with each other) compared to pseudo pairs (who had a conversation with someone else; uncorrected for multiple comparisons). The present study has shed the light on the role of social interaction in modulating brain synchrony across people not just during social interaction, but even for subsequent non-social activities. These results have implications in the growing domain of naturalistic neuroimaging and interactive neuroscience.

Autistic adults benefit from and enjoy learning via social interaction as much as neurotypical adults do.

BACKGROUND: Autistic people show poor processing of social signals (i.e. about the social world). But how do they learn via social interaction? METHODS: 68 neurotypical adults and 60 autistic adults learned about obscure items (e.g. exotic animals) over Zoom (i) in a live video-call with the teacher, (ii) from a recorded learner-teacher interaction video and (iii) from a recorded teacher-alone video. Data were analysed via analysis of variance and multi-level regression models. RESULTS: Live teaching provided the most optimal learning condition, with no difference between groups. Enjoyment was the strongest predictor of learning: both groups enjoyed the live interaction significantly more than other condition and reported similar anxiety levels across conditions. LIMITATIONS: Some of the autistic participants were self-diagnosed-however, further analysis where these participants were excluded showed the same results. Recruiting participants over online platforms may have introduced bias in our sample. Future work should investigate learning in social contexts via diverse sources (e.g. schools). CONCLUSIONS: These findings advocate for a distinction between learning about the social versus learning via the social: cognitive models of autism should be revisited to consider social interaction not just as a puzzle to decode but rather a medium through which people, including neuro-diverse groups, learn about the world around them. Trial registration Part of this work has been pre-registered before data collection https://doi.org/10.17605/OSF.IO/5PGA3.