Developing Systems for the Rapid Modeling of Team Neurodynamics

We have been studying whether the simultaneous expression of EEG-derived cognitive measures by different members of a team could be used to complement verbal communication streams for constructing such teamwork models. In this approach the values of a cognitive measure at any point in time are aggregated across the team members into a vector that is then clustered / classified by artificial neural network (ANN) technologies (Stevens et al, 2009; Stevens et al, 2010a). The result is a series of symbolic patterns termed Neurophysiologic Synchronies (NS) defined as the second-by-second quantitative coexpression of the same neurophysiologic measure by different members of the team. The cognitive measures we have modeled include High Engagement and High Workload which have been derived from EEG data streams (Berka et al, 2005). If NS are meaningful constructs then their expression should: