Medical College of Wisconsin
CTSIResearch InformaticsREDCap

Turn Taking, Team Synchronization, and Non-stationarity in Physiological Time Series. Nonlinear Dynamics Psychol Life Sci 2017 Jul;21(3):319-334

Date

06/12/2017

Pubmed ID

28601114

Scopus ID

2-s2.0-85020465434 (requires institutional sign-in at Scopus site)   13 Citations

Abstract

This study investigated the stationarity of electrodermal time series collected in situations where turn taking in human interactions are involved. In this context, the stationarity of the time series is the extent to which a simple model can be used to fit the entire time series. The experiment involved seven participants in an emergency response simulation against one opponent. They generated 48 time series across six simulations, which were split and re-spliced to separate the team's turns and the opponent's turns. Significant differences in R2 coefficients were found for both linear and nonlinear statistical models between experimental conditions, but the difference only amounted to 3% of the accuracy of those models relative to the original data. It was thus concluded that the impact of turn taking on stationarity was a small effect at most. A comparison of synchronization coefficients for the team data, which rely on the collective accuracy of the individual time series models, indicated stronger synchronization during periods when the team was watching the opponent's actions compared to when they took their own turns. It was thus concluded, furthermore, that the common focus of attention prevailed against any non-stationarity that was introduced by turn taking.

Author List

Guastello SJ, Marra DE, Castro J, Equi M, Peressini AF

Authors

Stephen Guastello BA,MA,PhD Professor in the Psychology department at Marquette University
David Marra in the CTSI department at Medical College of Wisconsin - CTSI




MESH terms used to index this publication - Major topics in bold

Attention
Decision Making
Emergencies
Humans
Interpersonal Relations
Nonlinear Dynamics