A Kuramoto model of self-other integration across interpersonal synchronization strategies

Abstract

Human social behaviour is complex, and the biological and neural mechanisms underpinning it remain debated 1,2 . A particularly interesting social phenomenon is our ability and tendency to fall into synchrony with other humans 3,4 . 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 in simple interactions, such as joint finger tapping, complex interpersonal dynamics emerge. Here we propose a computational model of selfother 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

Transient brain networks underlying interpersonal strategies during synchronized action

“…In this framework, synchronization strategies can be described as resulting from the individual within the dyad either classifying the auditory feedback from the other as causally linked to the actions performed by the self or as distinct. In the case of the latter, where both dyad members segregate the auditory information from the other and the action produced by the self, a leading–leading interaction occurs ( Heggli et al., 2019a ). Hence, in a pure leading–leading interaction, there should be no directional information flow between the actions produced by one dyad member and those from the other dyad member.…”

“…This type of synchronization can emerge spontaneously, such as in the tendency for synchronized behaviour in walking, joke telling and general body movements, or with intention, such as in musical performance or dance ( Richardson et al., 2007 ; van Ulzen et al., 2008 ; Schmidt et al., 2014 ; Stupacher et al., 2017a ). In recent work, we have shown how interpersonal dynamics in synchronization tasks can be modelled using a network of coupled oscillators ( Heggli et al., 2019a ). We proposed that interpersonal synchronization strategies such as mutual adaptation, leading–following and leading–leading rely on action–perception links modulated by individual decisions to integrate or segregate information related to self-produced actions and the perception of other-produced actions ( Milward and Sebanz, 2016 ; Novembre et al., 2016 ; Koban et al., 2017 ; Heggli et al., 2019a ).…”

“…In recent work, we have shown how interpersonal dynamics in synchronization tasks can be modelled using a network of coupled oscillators ( Heggli et al., 2019a ). We proposed that interpersonal synchronization strategies such as mutual adaptation, leading–following and leading–leading rely on action–perception links modulated by individual decisions to integrate or segregate information related to self-produced actions and the perception of other-produced actions ( Milward and Sebanz, 2016 ; Novembre et al., 2016 ; Koban et al., 2017 ; Heggli et al., 2019a ). While there has been a considerate amount of research on the nature of these types of interpersonal synchronization strategies, we know little about the underlying neural mechanisms ( Konvalinka and Roepstorff, 2012 ; Koban et al., 2017 ).…”

Dyadic Entrainment. An Overwhelming and Modality-Dependent Phenomenon.

“…The cleaned timeseries were then interpolated with a sine function at 1kHz sampling rate, providing an estimate of the oscillators' positions on its cycle with a temporal resolution of 1ms. Conceptually, the choice of sinusoidal interpolation was supported by recent work on modelling of systems of coupled oscillators in joint finger-tapping studies 50 . Operationally, it guaranteed that all timeseries match in size without any loss of data, which was a requirement for the next steps of our analysis.…”

“…In conclusion, we want to highlight that the 'drifting metronomes' procedure is meant as a methodological contribution for the investigation of interpersonal coordination, in the hope that the community can build upon it with new research questions and experimental designs. We point at its adoption with simultaneous dual-electroencephalography recordings 49 , computational simulations 50 and replication on pathological populations [51][52][53] as potential sources of insight into the fundamentals of dyadic interactions.…”