Cross-Level Effects Between Neurophysiology and Communication During                     Team Training

Gorman, Jamie C.; Martin, Melanie; Dunbar, Terri A.; Stevens, Ronald H.; Galloway, Trysha; Amazeen, Polemnia G.; Likens, Aaron D.

doi:10.1177/0018720815602575

Cited by 42 publications

(60 citation statements)

References 40 publications

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“…As an example, Gorman et al (2016) showed that higher level structures of their team training task were reflected in changes in entropy values representing team neurophysiological states. Similarly, Strang et al (2015) showed that the coupling of team members' brain activity, measured with an entropy statistic, varied as a function of a task-load manipulation.…”

Section: Discussionmentioning

confidence: 99%

Problem‐Solving Phase Transitions During Team Collaboration

2017

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Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving (CPS) with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem were coded for occurrence of problem-solving processes. We applied a sliding window entropy technique to each team's communications and specified criteria for (a) identifying data points that qualify as peaks and (b) determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams' CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly.

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Section: Discussionmentioning

confidence: 99%

Problem‐Solving Phase Transitions During Team Collaboration

2017

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“…The additional measures may not always provide increased clarity. In a recent study the cross-level effects between the dynamics of communication and neurodynamics were modeled (Gorman et al, 2016). One interesting findings was a difference in the temporal lags between the neural and communication data streams between novices and experts, indicating that relating variables to each other at zero time lag may be insufficient to understand the interrelated system dynamics, and that changing time dimensions may also be needed during modeling.…”

Section: Discussionmentioning

confidence: 99%

“…While the three-person examples in Figures 8, 9 show the aggregated couplings among team members it is an easy extension to develop dynamic networks that show momentary relationships. These dynamical models enable comparisons with measures of team communication (Gorman et al, 2016) as well as behavioral models derived from expert raters (Stevens et al, 2015, 2016c), leading to dynamic multi-level, multi-modal and multi-entity snapshots of novice and expert teams in action.…”

Section: Discussionmentioning

confidence: 99%

Are Neurodynamic Organizations A Fundamental Property of Teamwork?

Stevens¹,

Galloway²

2017

Front. Psychol.

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When performing a task it is important for teams to optimize their strategies and actions to maximize value and avoid the cost of surprise. The decisions teams make sometimes have unintended consequences and they must then reorganize their thinking, roles and/or configuration into corrective structures more appropriate for the situation. In this study we ask: What are the neurodynamic properties of these reorganizations and how do they relate to the moment-by-moment, and longer, performance-outcomes of teams?. We describe an information-organization approach for detecting and quantitating the fluctuating neurodynamic organizations in teams. Neurodynamic organization is the propensity of team members to enter into prolonged (minutes) metastable neurodynamic relationships as they encounter and resolve disturbances to their normal rhythms. Team neurodynamic organizations were detected and modeled by transforming the physical units of each team member's EEG power levels into Shannon entropy-derived information units about the team's organization and synchronization. Entropy is a measure of the variability or uncertainty of information in a data stream. This physical unit to information unit transformation bridges micro level social coordination events with macro level expert observations of team behavior allowing multimodal comparisons across the neural, cognitive and behavioral time scales of teamwork. The measures included the entropy of each team member's data stream, the overall team entropy and the mutual information between dyad pairs of the team. Mutual information can be thought of as periods related to team member synchrony. Comparisons between individual entropy and mutual information levels for the dyad combinations of three-person teams provided quantitative estimates of the proportion of a person's neurodynamic organizations that represented periods of synchrony with other team members, which in aggregate provided measures of the overall degree of neurodynamic interactions of the team. We propose that increased neurodynamic organization occurs when a team's operating rhythm can no longer support the complexity of the task and the team needs to expend energy to re-organize into structures that better minimize the “surprise” in the environment. Consistent with this hypothesis, the frequency and magnitude of neurodynamic organizations were less in experienced military and healthcare teams than they were in more junior teams. Similar dynamical properties of neurodynamic organization were observed in models of the EEG data streams of military, healthcare and high school science teams suggesting that neurodynamic organization may be a common property of teamwork. The innovation of this study is the potential it raises for developing globally applicable quantitative models of team dynamics that will allow comparisons to be made across teams, tasks and training protocols.

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“…In this sense, the players should be challenged in unfamiliar environments with maximal pattern variations of the initial situation, for example, the players are instructed to perform movement errors instead of avoiding them (e.g. kick a ball with arms raised) (Schöllhorn et al, 2006). In fact, differential learning provides a highly improvisation demand, one of the most complex forms of creative behavior.…”

Section: Differential Learningmentioning

confidence: 99%

The Spawns of Creative Behavior in Team Sports: A Creativity Developmental Framework

et al. 2016

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Developing creativity in team sports players is becoming an increasing focus in sports sciences. The Creativity Developmental Framework is presented to provide an updated science based background. This Framework describes five incremental creative stages (beginner, explorer, illuminati, creator, and rise) and combines them into multidisciplinary approaches embodied in creative assumptions. In the first training stages, the emphasis is placed on the enrollment in diversification, deliberate play and physical literacy approaches grounded in nonlinear pedagogies. These approaches allow more freedom to discover different movement patterns increasing the likelihood of emerging novel, adaptive and functional solutions. In the later stages, the progressive specialization in sports and the differential learning commitment are extremely important to push the limits of the creative progress at higher levels of performance by increasing the range of skills configurations. Notwithstanding, during all developmental stages the teaching games for understanding, a game-centered approach, linked with the constraints-led approach play an important role to boost the tactical creative behavior. Both perspectives might encourage players to explore all actions possibilities (improving divergent thinking) and prevents the standardization in their actions. Overall, considering the aforementioned practice conditions the Creativity Developmental Framework scrutinizes the main directions that lead to a long-term improvement of the creative behavior in team sports. Nevertheless, this framework should be seen as a work in progress to be later used as the paramount reference in creativity training.

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Cross-Level Effects Between Neurophysiology and Communication During Team Training

Abstract: 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).

Cited by 42 publications

References 40 publications

Problem‐Solving Phase Transitions During Team Collaboration

Problem‐Solving Phase Transitions During Team Collaboration

Are Neurodynamic Organizations A Fundamental Property of Teamwork?

The Spawns of Creative Behavior in Team Sports: A Creativity Developmental Framework

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