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 chapter describes the tools for studying team neurodynamics and shows the potential of these methods and models for better understanding team formation and function. The models developed are reliable, sensitive and valid indicators of the changing neurodynamics of teams around which standardized quantitative models can begin to be developed. The technology is intended for documenting how rapidly teams are progressing towards proficiency and expertise and for understanding why some teams function better than others.
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It is not surprising that neurophysiologic events are the underpinnings of the social coordination dynamics seen in teams, yet it is only recently that their evolving dynamics in real-world teamwork settings have begun to be modeled (Stevens, Galloway, Berka & Sprang, 2009; Stephens, Silbert, & Hasson, 2010; Dumas, Nadal, Soussignan, Martinerie & Garnero, 2010; Dodel, Cohen, Mersmann, Luu, Forsythe, and Jirsa, 2011, Stevens, Galloway, Wang, Berka, 2012; Stevens, 2012). Equally important has been the extension of the neurophysiologic studies of teams from the relatively short and controlled environments with repetitive tasks, to continuous monitoring in real-world settings with longer-lasting tasks. Advances in both areas have led to the emerging field of team neurodynamics.
Electroencephalography is often the tool of choice for studying team neurodynamics. EEG is the recording of electrical activity of the brain at different regions along the scalp and the rhythmic patterns in the electrical oscillations from different brain regions contain signals representing complex facets of brain activity. While EEG has traditionally been viewed as a tool for studying individual cognition in the milliseconds to seconds range, multiple investigators are extending this range to include teams operating over minutes or hours in military, educational and corporate environments.
Two complementary approaches are steering these efforts. The first seeks to establish linkages between specific neuromarkers and different behavioral, cognitive or emotional states; an example is the phi complex that may distinguish states of effective and ineffective social coordination (Tognoli, Lagarde, DeGuzman, & Kelso, 2007). These high spectral EEG neuromarkers show a topology consistent with the neuroanatomical location of the human mirror neuron system that is activated during intentional social coordination. Unlike EEG signatures that appear and disappear in response to many stimuli (e.g. P300), neuromarkers like the phi complex exist at a higher level of abstraction and are more targeted to subsets of behaviors. Such neuromarkers may not be precise analogs of the multiple ways that can be used to describe interactions or aspects of cognition but are close enough approximations to be useful for a better understanding of teamwork.