Parsing Neurodynamic Information Streams to Estimate the Frequency, Magnitude and Duration of Team Uncertainty.

Neurodynamic organizations are information-based abstractions, expressed in bits, of the structure of long duration EEG amplitude levels. Neurodynamic information (, the variable of neurodynamic organization) is thought to continually accumulate as EEG amplitudes cycle through periods of persistent activation and deactivation in response to the activities and uncertainties of teamwork. Here we show that (1) Neurodynamic information levels were a better predictor of uncertainty and novice and expert behaviors than were the EEG power levels from which was derived.

Analysis of Mirrored Psychophysiological Change of Cardiac Surgery Team Members During Open Surgery.

Objective: Mirrored psychophysiological change in cognitive workload indices may reflect shared mental models and effective healthcare team dynamics. In this exploratory analysis, we investigated the frequency of mirrored changes, defined as concurrent peaks in heart rate variability (HRV) across team members, during cardiac surgery.

Design: Objective cognitive workload was evaluated via HRV collected from the primary surgical team during cardiac surgery cases (N = 15).

Measuring Real-Time Team Cognition During Team Training.

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.

Neuroergonomics: Quantitative Modeling of Individual, Shared, and Team Neurodynamic Information.

Objective: The aim of this study was to use the same quantitative measure and scale to directly compare the neurodynamic information/organizations of individual team members with those of the team.

Background: Team processes are difficult to separate from those of individual team members due to the lack of quantitative measures that can be applied to both process sets.

Method: Second-by-second symbolic representations were created of each team member's electroencephalographic power, and quantitative estimates of their neurodynamic organizations were calculated from the Shannon entropy of the symbolic data streams.

Alternative Markers of Performance in Simulation: Where We Are and Where We Need To Go.

This article on alternative markers of performance in simulation is the product of a session held during the 2017 Academic Emergency Medicine Consensus Conference "Catalyzing System Change Through Health Care Simulation: Systems, Competency, and Outcomes." There is a dearth of research on the use of performance markers other than checklists, holistic ratings, and behaviorally anchored rating scales in the simulation environment. Through literature review, group discussion, and consultation with experts prior to the conference, the working group defined five topics for discussion: 1) establishing a working definition for alternative markers of performance, 2) defining goals for using alternative performance markers, 3) implications for measurement when using alternative markers, identifying practical concerns related to the use of alternative performance markers, and 5) identifying potential for alternative markers of performance to validate simulation scenarios.

Are Neurodynamic Organizations A Fundamental Property of Teamwork?

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?.

Cross-Level Effects Between Neurophysiology and Communication During Team Training.

Objective: We investigated cross-level effects, which are concurrent changes across neural and cognitive-behavioral levels of analysis as teams interact, between neurophysiology and team communication variables under variations in team training.

Background: When people work together as a team, they develop neural, cognitive, and behavioral patterns that they would not develop individually. It is currently unknown whether these patterns are associated with each other in the form of cross-level effects.

Modeling the neurodynamic organizations and interactions of teams.

Across-brain neurodynamic organizations arise when teams perform coordinated tasks. We describe a symbolic electroencephalographic (EEG) approach that identifies when team neurodynamic organizations occur and demonstrate its utility with scientific problem solving and submarine navigation tasks. Each second, neurodynamic symbols (NS) were created showing the 1-40 Hz EEG power spectral densities for each team member.

Toward a quantitative description of the neurodynamic organizations of teams.

The goal was to develop quantitative models of the neurodynamic organizations of teams that could be used for comparing performance within and across teams and sessions. A symbolic modeling system was developed, where raw electroencephalography (EEG) signals from dyads were first transformed into second-by-second estimates of the cognitive Workload or Engagement of each person and transformed again into symbols representing the aggregated levels of the team. The resulting neurodynamic symbol streams had a persistent structure and contained segments of differential symbol expression.

Cognitive neurophysiologic synchronies: what can they contribute to the study of teamwork?

Objective: Cognitive neurophysiologic synchronies (NS) are low-level data streams derived from electroencephalography (EEG) measurements that can be collected and analyzed in near real time and in realistic settings. The objective of this study was to relate the expression of NS for engagement to the frequency of conversation between team members during Submarine Piloting and Navigation (SPAN) simulations.

Background: If the expression of different NS patterns is sensitive to changes in the behavior of teams, they may be a useful tool for studying team cognition.

Exploring Alternative Models of Complex Patient Management with Artificial Neural Networks.

This study applied an unsupervised neural network modeling process to test data of the National Board of Medical Examiners (NBME) Computer-based Clinical Scenarios (CCS) to identify new performance categories and validate this process as a scoring technique. The classifications resulting from this neural network modeling were consistent with the NBME model in that highly rated NMBE performances (ratings of 7 or 8) were clustered together on the neural network output grid. Very low performance ratings appeared to share few common features and were accordingly classified at isolated nodes.