title: 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.
authors.affiliation: Plan de Estudios Combinados en Medicina (MD/PhD), Facultad de Medicina, Universidad Nacional Autónoma de MéxicoMexico City, Mexico; Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico.
authors.forename: Leonardo
authors.initials: L
authors.lastname: Zapata-Fonseca
authors.affiliation: Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México Mexico City, Mexico.
authors.forename: Dobromir
authors.initials: D
authors.lastname: Dotov
authors.affiliation: Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico; Departamento de Estructura de la Materia, Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de MéxicoMexico City, Mexico.
authors.forename: Ruben
authors.initials: R
authors.lastname: Fossion
authors.affiliation: Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de MéxicoMexico City, Mexico; Departamento de Ciencias de la Computación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de MéxicoMexico City, Mexico.
authors.forename: Tom
authors.initials: T
authors.lastname: Froese
keywords: complexity; embodied cognition; enactive; social cognition; social interaction; time-series analysis