Cross-level effects suggest that measurements could be taken at one level (e.g., neural) to assess team experience (or skill) on another level (e.g., cognitive-behavioral).

By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area.

A multi-level framework for analyzing team cognition based on team communication content and team neurophysiology is described. The semantic content of team communication in submarine training crews is quantified using Latent Semantic Analysis (LSA), and their team neurophysiology is quantified using the previously described neurophysiologic synchrony method. In the current study, we validate the LSA communication metrics by demonstrating their sensitivity to variations in training segment and by showing that less experienced (novice) crews can be differentiated from more experienced crews based on the semantic relatedness of their communications. Cross-correlations between an LSA metric and a team neurophysiology metric are explored to examine fluctuations in the lead-lag relationship between team communication and team neurophysiology as a function of training segment and level of team experience. Finally, the implications of this research for team training and assessment are considered.

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