Can Neurophysiologic Synchronies Provide a Platform for Adapting Team Performance?

We have explored using neurophysiologic patterns as an approach for developing a deeper understanding of how teams collaborate when solving time-critical, complex real-world problems. Fifteen students solved substance abuse management simulations individually, and then in teams of three while measures of mental workload (WL) and engagement (E) were generated by electroencephalography (EEG). High and low workload and engagement levels were identified at each epoch for each team member and vectors of these measures were clustered by self organizing artificial neural networks. The resulting patterns, termed neurophysiologic synchronies, differed for the five teams reflecting the teams’ efficiency. When the neural synchronies were compared across the collaboration, segments were identified where different synchronies were preferentially expressed. This approach may provide an approach for monitoring the quality of team work during complex, real-world and possible one of a kind problem solving, and for adaptively modifying the teamwork flow when optimal synchronies are not frequent.