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Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties
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-pers...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5149553/ https://www.ncbi.nlm.nih.gov/pubmed/28018274 http://dx.doi.org/10.3389/fpsyg.2016.01940 |
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author | Zapata-Fonseca, Leonardo Dotov, Dobromir Fossion, Ruben Froese, Tom |
author_facet | Zapata-Fonseca, Leonardo Dotov, Dobromir Fossion, Ruben Froese, Tom |
author_sort | Zapata-Fonseca, Leonardo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5149553 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-51495532016-12-23 Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties Zapata-Fonseca, Leonardo Dotov, Dobromir Fossion, Ruben Froese, Tom Front Psychol Psychology 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. Frontiers Media S.A. 2016-12-12 /pmc/articles/PMC5149553/ /pubmed/28018274 http://dx.doi.org/10.3389/fpsyg.2016.01940 Text en Copyright © 2016 Zapata-Fonseca, Dotov, Fossion and Froese. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Zapata-Fonseca, Leonardo Dotov, Dobromir Fossion, Ruben Froese, Tom Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties |
title | Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties |
title_full | Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties |
title_fullStr | Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties |
title_full_unstemmed | Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties |
title_short | Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties |
title_sort | time-series analysis of embodied interaction: movement variability and complexity matching as dyadic properties |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5149553/ https://www.ncbi.nlm.nih.gov/pubmed/28018274 http://dx.doi.org/10.3389/fpsyg.2016.01940 |
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