Collective rituals are present in all known societies, but their function is a matter of long-standing debates. Field observations suggest that they may enhance social cohesion and that their effects are not limited to those actively performing but affect the audience as well. Here we show physiological effects of synchronized arousal in a Spanish fire-walking ritual, between active participants and related spectators, but not participants and other members of the audience. We assessed arousal by heart rate dynamics and applied nonlinear mathematical analysis to heart rate data obtained from 38 participants. We compared synchronized arousal between fire-walkers and spectators. For this comparison, we used recurrence quantification analysis on individual data and cross-recurrence quantification analysis on pairs of participants' data. These methods identified fine-grained commonalities of arousal during the 30-min ritual between fire-walkers and related spectators but not unrelated spectators. This indicates that the mediating mechanism may be informational, because participants and related observers had very different bodily behavior. This study demonstrates that a collective ritual may evoke synchronized arousal over time between active participants and bystanders. It links field observations to a physiological basis and offers a unique approach for the quantification of social effects on human physiology during real-world interactions.

To study the mechanisms of coordination that are fundamental to successful interactions we carried out a joint finger tapping experiment in which pairs of participants were asked to maintain a given beat while synchronizing to an auditory signal coming from the other person or the computer. When both were hearing each other, the pair became a coupled, mutually and continuously adaptive unit of two “hyper-followers”, with their intertap intervals (ITIs) oscillating in opposite directions on a tap-to-tap basis. There was thus no evidence for the emergence of a leader–follower strategy. We also found that dyads were equally good at synchronizing with the irregular, but responsive other as with the predictable, unresponsive computer. However, they performed worse when the “other” was both irregular and unresponsive. We thus propose that interpersonal coordination is facilitated by the mutual abilities to (a) predict the other's subsequent action and (b) adapt accordingly on a millisecond timescale.

Measuring brain activity simultaneously from two people interacting is intuitively appealing if one is interested in putative neural markers of social interaction. However, given the complex nature of two-person interactions, it has proven difficult to carry out two-person brain imaging experiments in a methodologically feasible and conceptually relevant way. Only a small number of recent studies have put this into practice, using fMRI, EEG, or NIRS. Here, we review two main two-brain methodological approaches, each with two conceptual strategies. The first group has employed simultaneous fMRI recordings, studying a) turn-based interactions on the order of seconds, or b) pseudo-interactive scenarios, where only one person is scanned at a time, investigating the flow of information between brains. The second group of studies has recorded dual EEG/NIRS from two people interacting, in a) face-to-face turn-based interactions, investigating functional connectivity between theory-of-mind regions of interacting partners, or in b) continuous mutual interactions on millisecond timescales, to measure coupling between the activity in one person’s brain and the activity in the other’s brain. We discuss the questions these approaches have addressed, and consider scenarios when simultaneous two-brain recordings are needed. Furthermore, we suggest that a) quantification of inter-personal neural effects via measures of emergence, and b) multivariate decoding models that generalize source-specific features of interaction, may provide novel tools to study brains in interaction. This may allow for a better understanding of social cognition as both representation and participation.

Spontaneous interpersonal synchronization of rhythmic behavior such as gait or hand clapping is a ubiquitous phenomenon in human interactions, and is potentially important for social relationships and action understanding. Although several authors have suggested a role of the mirror neuron system in interpersonal coupling, the underlying brain mechanisms are not well understood. Here we argue that more general theories of neural computations, namely predictive coding and the Free Energy Principle, could explain interpersonal coordination dynamics. Each brain minimizes coding costs by reducing the mismatch between the representations of observed and own motor behavior. Continuous mutual prediction and alignment result in an overall minimization of free energy, thus forming a stable attractor state.

Human social behaviour is complex, and the biological and neural mechanisms underpinning it remain debated. A particularly interesting social phenomenon is our ability and tendency to fall into synchronization with other humans. Our ability to coordinate actions and goals relies on the ability to distinguish between and integrate self and other, which when impaired can lead to devastating consequences. Interpersonal synchronization has been a widely used framework for studying action coordination and self-other integration, showing that even in simple interactions, such as joint finger tapping, complex interpersonal dynamics emerge. Here we propose a computational model of self-other integration via within- and between-person action-perception links, implemented as a simple Kuramoto model with four oscillators. The model abstracts each member of a dyad as a unit consisting of two connected oscillators, representing intrinsic processes of perception and action. By fitting this model to data from two separate experiments we show that interpersonal synchronization strategies rely on the relationship between within- and between-unit coupling. Specifically, mutual adaptation exhibits a higher between-unit coupling than within-unit coupling; leading-following requires that the follower unit has a low within-unit coupling; and leading-leading occurs when two units jointly exhibit a low between-unit coupling. These findings are consistent with the theory of interpersonal synchronization emerging through self-other integration mediated by processes of action-perception coupling. Hence, our results show that chaotic human behaviour occurring on a millisecond scale may be modelled using coupled oscillators. Interacting with other people is crucial for our everyday life. We regularly and without much effort synchronize our movements with other people’s movements, across a wide range of interactions such as when dancing together and performing music. However, even a very simple interaction such as tapping a rhythm together can result in complex interaction dynamics. Two people tapping can choose different synchronization strategies, such as leading-following wherein one person is a leader and the other a follower, mutual adaptation where both adapt to each other, or leading-leading where both try to lead at the same time. In this paper we show how these strategies can be described using a mathematical model of coupled oscillators. Specifically, we show how the strategies rely on different coupling strengths between the oscillators in the model. This shows that even complex human behaviour may be modelled using simple mathematical terms.