Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties

Abstract

There is a growing consensus that a fuller understanding of social cognition depends on more systematic studies of real-time social interaction. Such studies require methods that can deal with the complex dynamics taking place at multiple interdependent temporal and spatial scales, spanning sub-personal, personal, and dyadic levels of analysis. We demonstrate the value of adopting an extended multi-scale approach by re-analyzing movement time-series generated in a study of embodied dyadic interaction in a minimal virtual reality environment (a perceptual crossing experiment). Reduced movement variability revealed an interdependence between social awareness and social coordination that cannot be accounted for by either subjective or objective factors alone: it picks out interactions in which subjective and objective conditions are convergent (i.e., elevated coordination is perceived as clearly social, and impaired coordination is perceived as socially ambiguous). This finding is consistent with the claim that interpersonal interaction can be partially constitutive of direct social perception. Clustering statistics (Allan Factor) of salient events revealed fractal scaling. Complexity matching defined as the similarity between these scaling laws was significantly more pronounced in pairs of participants as compared to surrogate dyads. This further highlights the multi-scale and distributed character of social interaction and extends previous complexity matching results from dyadic conversation to non-verbal social interaction dynamics. Trials with successful joint interaction were also associated with an increase in local coordination. Consequently, a local coordination pattern emerges on the background of complex dyadic interactions in the PCE task and makes joint successful performance possible.

A Sensorimotor Signature of the Transition to Conscious Social Perception: Co-regulation of Active and Passive Touch

“…This dyadic nature of the interaction was further supported by a re-analysis of the sensorimotor time series by Zapata-Fonseca et al (2016) . They revealed that the clustering statistics (Allan factor) of discrete movement events was characterized by fractal scaling, which highlights that the social interaction process operates in a distributed fashion across multiple timescales.…”

‘I Interact Therefore I Am’: The Self as a Historical Product of Dialectical Attunement

“…Conceptual and experimental practices should be developed hand-inhand with methods of analysis (e.g. Bahrami et al 2010;Konvalinka and Roepstorff 2012;Schilbach et al 2013;Abney et al 2014;Dumas et al 2014;Froese et al 2015;Friston and Frith 2015;Zapata-Fonseca et al 2016;Fusaroli and Tylén 2016;Sevgi et al 2016;Bolis and Schilbach 2017a). Here, we suggest a shift from an exclusive focus on the (Bayesian) brain in isolation, toward a multilevel understanding of intersubjectivity and psychopathology.…”

Complexity Matching and Requisite Variety

“…It is important to stress that there exists further research directed toward the foundation of social learning [9][10][11][12] that is even more closely connected to the ambitious challenge made by Ashby. In fact, this research aims at evaluating the transfer of information from the brain of one player to that of another, by way of the interaction the two players established through their avatars [10].…”