Approaches for Inserting Neurodynamics into the Training of Healthcare Teams

Abstract

Team neurodynamics is the study of the changing rhythms and organizations of teams from the perspective of neurophysiology. As a discipline, team neurodynamics is located at the intersection of collaborative learning, psychometrics, complexity theory, and neurobiology with the resulting principles and applications both drawing from and contributing to these specialties. This article describes the tools for studying team neurodynamics and illustrates the potential and the challenges these methods and models have for better understanding healthcare team training and performance. The fundamental metric is neurodynamic organization, which is the tendency of teams and its members to enter into prolonged metastable relationships when they experience and resolve uncertainty. The patterns of these relationships are resolved by symbolic modeling of electroencephalographic (EEG) power levels of the team members, and the information in these patterns are calculated using information theory tools. The topics discussed in this chapter anticipate the time when dynamic biometric data can contribute to our understanding of how to rapidly determine a team’s functional status, and how to use this information to optimize outcomes and training. The rapid, dynamic, and task neutral measures make the lessons learned in healthcare applicable to other complex group and team environments, and provide a foundation for incorporating these models into machines to support the training and performance of teams.