Cusp Catastrophe Models and the Role of Synchrony in Cognitive Workload and Fatigue in Teams.

This study evaluated autonomic synchrony and variability in synchrony as control variables in cusp catastrophe models of workload and fatigue for teams making dynamics decisions. In this experiment, 136 undergraduates were organized into 32 groups of three, four, and five members playing an online computer game while wearing electrodermal sensors. They also completed cognitive measures of elasticity-rigidity and situation awareness during the games. Synchrony was calculated using the SE coefficient from the driver-empath model. Analyses were constructed to determine whether SE or SE variability added value to the cusp catastrophe models for cognitive workload and fatigue that were determined previously in Guastello and McGuigan (2024). Results indicated that SE made a strong impact on changes in performance as a bifurcation variable in both the workload and fatigue models. The positive and negative impact on performance shown by SE variability suggested that team members were grappling with the best ways to coordinate with each other or that teams found an advantage to turning synchrony on and off. SE variability made a strong impact as a bifurcation variable in the workload load model, and a strong impact as a compensatory ability (asymmetry parameter) in the fatigue model. Practical implications are that synchrony could be functional or dysfunctional, depending on situational demands that could be momentary. The study opened new questions regarding the qualitative relationship between elasticity-rigidity variables and synchrony and the possible roles of strong vs. weak ties in a closed network of this type.

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PubMed
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2025-07-01
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Systems Engineering Methodologies and Applications
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article

Cusp Catastrophe Models and the Role of Synchrony in Cognitive Workload and Fatigue in Teams.

Laura M McGuigan, Stephen J. Guastello
PubMed
Systems Engineering Methodologies and Applications
article

Cusp Catastrophe Models and the Role of Synchrony in Cognitive Workload and Fatigue in Teams.

Laura M McGuigan, Stephen J. Guastello
article en

Abstract

This study evaluated autonomic synchrony and variability in synchrony as control variables in cusp catastrophe models of workload and fatigue for teams making dynamics decisions. In this experiment, 136 undergraduates were organized into 32 groups of three, four, and five members playing an online computer game while wearing electrodermal sensors. They also completed cognitive measures of elasticity-rigidity and situation awareness during the games. Synchrony was calculated using the SE coefficient from the driver-empath model. Analyses were constructed to determine whether SE or SE variability added value to the cusp catastrophe models for cognitive workload and fatigue that were determined previously in Guastello and McGuigan (2024). Results indicated that SE made a strong impact on changes in performance as a bifurcation variable in both the workload and fatigue models. The positive and negative impact on performance shown by SE variability suggested that team members were grappling with the best ways to coordinate with each other or that teams found an advantage to turning synchrony on and off. SE variability made a strong impact as a bifurcation variable in the workload load model, and a strong impact as a compensatory ability (asymmetry parameter) in the fatigue model. Practical implications are that synchrony could be functional or dysfunctional, depending on situational demands that could be momentary. The study opened new questions regarding the qualitative relationship between elasticity-rigidity variables and synchrony and the possible roles of strong vs. weak ties in a closed network of this type.

PubMedVol. 29(3)
Marquette University (US)
Openalex Percentile: Top 82%
Systems Engineering Methodologies and Applications
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Cusp Catastrophe Models and the Role of Synchrony in Cognitive Workload and Fatigue in Teams. — Laura M McGuigan, Stephen J. Guastello · PubMed (2025) | TGRS Research Map | TGRS