Making Sense of Team Information

Stevens, Ronald H.; Galloway, Trysha; Willemson-Dunlap, Ann; Gorman, Jamie C.; Halpin, Donald J.

doi:10.1177/1541931218621026

Cited by 5 publications

(5 citation statements)

References 17 publications

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“…The team neurodynamics were separated into those of each team member (Stevens & Galloway, 2017; Stevens, Galloway, & Willemsen-Dunlap, 2018) which provided profiles of each persons’ neurodynamics. From Figure 4a, the AN and circulating nurse (CN) who had previously worked closely together were also well coordinated during the simulation with overlapping NI profiles during the ITB-1, Crash Cart, and ITB-2 segments.…”

Section: Resultsmentioning

confidence: 99%

“…This will enable cognitively informed task designs and accelerate the rates of team and team-member learning by focusing on the cognitively relevant properties of performance. They will likely shape the evolution of existing theories of teamwork and the creation of new performance measures and teaching practices; these data will also increase the transparency of human states enabling effective machine-human collaborations (Stevens, Galloway, Willemsen-Dunlap, Gorman, & Halpin, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Teaching Machines to Recognize Neurodynamic Correlates of Team and Team Member Uncertainty

Stevens

Galloway²

2019

Journal of Cognitive Engineering and Decision Making

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We describe efforts to make humans more transparent to machines by focusing on uncertainty, a concept with roots in neuronal populations that scales through social interactions. To be effective team partners, machines will need to learn why uncertainty happens, how it happens, how long it will last, and possible mitigations the machine can supply. Electroencephalography-derived measures of team neurodynamic organization were used to identify times of uncertainty in military, health care, and high school problem-solving teams. A set of neurodynamic sequences was assembled that differed in the magnitudes and durations of uncertainty with the goal of training machines to detect the onset of prolonged periods of high level uncertainty, that is, when a team might require support. Variations in uncertainty onset were identified by classifying the first 70 s of the exemplars using self-organizing maps (SOM), a machine architecture that develops a topology during training that separates closely related from desperate data. Clusters developed during training that distinguished patterns of no uncertainty, low-level and quickly resolved uncertainty, and prolonged high-level uncertainty, creating opportunities for neurodynamic-based systems that can interpret the ebbs and flows in team uncertainty and provide recommendations to the trainer or team in near real time when needed.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Teaching Machines to Recognize Neurodynamic Correlates of Team and Team Member Uncertainty

Stevens

Galloway²

2019

Journal of Cognitive Engineering and Decision Making

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“…This result suggests that signals other than verbal communication might be needed to track real-time implicit coordination. For instance, we detected the patient seizing perturbation in Figure 5 using neural and heart rate synchronization but not speech (Stevens, Galloway, Willemsen-Dunlap et al, 2018) and have observed that neural synchronization and speech are mutually entraining (Gorman et al, 2016). Thus, we think aligning communication dynamics with neurodynamics, heart rate variability, and other less overt coordination markers could help address the false negative observed in Figure 5.…”

Section: Discussionmentioning

confidence: 99%

Measuring Real-Time Team Cognition During Team Training

et al. 2019

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Objective A method for detecting real-time changes in team cognition in the form of significant communication reorganizations is described. We demonstrate the method in the context of scenario-based simulation training. Background We present the dynamical view that individual- and team-level aspects of team cognition are temporally intertwined in a team’s real-time response to challenging events. We suggest that this real-time response represents a fundamental team cognitive skill regarding the rapidity and appropriateness of the response, and methods and metrics are needed to track this skill. Method Communication data from medical teams (Study 1) and submarine crews (Study 2) were analyzed for significant communication reorganization in response to training events. Mutual information between team members informed post hoc filtering to identify which team members contributed to reorganization. Results Significant communication reorganizations corresponding to challenging training events were detected for all teams. Less experienced teams tended to show delayed and sometimes ineffective responses that more experienced teams did not. Mutual information and post hoc filtering identified the individual-level inputs driving reorganization and potential mechanisms (e.g., leadership emergence, role restructuring) underlying reorganization. Conclusion The ability of teams to rapidly and effectively reorganize coordination patterns as the situation demands is a team cognitive skill that can be measured and tracked. Application Potential applications include team monitoring and assessment that would allow for visualization of a team’s real-time response and provide individualized feedback based on team member’s contributions to the team response.

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“…We present neurodynamic examples from multiple tasks to show the generality of the findings. The subjects, and task details for the Map Navigation Task (Stevens & Galloway, 2015), Submarine Navigation, Healthcare (Stevens & Galloway, 2017;Stevens, Galloway, Halpin & Willemsen-Dunlap, 2016;Stevens, Galloway & Willemsen-Dunlap, 2018) and the live patient surgical operation have been previously described (Stevens & Galloway, 2017;. Brief task descriptions summaries are included when referring to new findings.…”

Section: Teams and Tasksmentioning

confidence: 99%

“…These periods of neurodynamic organization can be visualized as metastable attractor states and quantitated as described below, enabling comparisons across team members, teams and training situations (Stevens, Galloway & Willemsen-Dunlap, 2018). The temporal organizations seem to be a general property of teamwork being observed in military, healthcare and pre-college teaming (Stevens & Galloway, 2017), and their presence during important periods of a live patient surgery extends their significance to the real world .…”

Section: Introductionmentioning

confidence: 99%

The Gap Between The Micro And Macro Scales of Teamwork is Spanned By Neural Information But Not Neural Band Power

Stevens

Galloway²

2020

Proceedings of the Human Factors and Ergonomics Society Annual

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One of the more intriguing questions about teamwork is how macro-scale behaviors arise from the micro-scale neural dynamics of each team member. In this paper we show that the low-level dynamics of EEG band power, which themselves link poorly with behavioral teamwork measures can be transformed into information-based units of neurodynamic organization that link with macro-level constructs like experience and uncertainty. We suggest it is the frequency, magnitude and durations of the temporal organizations within the EEG band power that are important for linking to macro behaviors, and not exclusively EEG power levels. These studies provide an avenue for understanding how complex organizations arise from the dynamics of underlying micro-scale variables. The study also has practical implications for how micro-scale variables might be better represented, both conceptually and in terms of parsimony, for training machines to recognize human behaviors that span scales of teamwork.

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Making Sense of Team Information

Cited by 5 publications

References 17 publications

Teaching Machines to Recognize Neurodynamic Correlates of Team and Team Member Uncertainty

Teaching Machines to Recognize Neurodynamic Correlates of Team and Team Member Uncertainty

Measuring Real-Time Team Cognition During Team Training

The Gap Between The Micro And Macro Scales of Teamwork is Spanned By Neural Information But Not Neural Band Power

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