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

Journal of Defense Modeling & Simulation

2021

Uncertainty is a fundamental property of neural computation that becomes amplified when sensory information does not match a person’s expectations of the world. Uncertainty and hesitation are often early indicators of potential disruption, and the ability to rapidly measure uncertainty would have implications for future educational and training efforts by targeting reflective discussions about past actions, supporting in-progress corrections, and generating forecasts about future disruptions. An approach is described combining neurodynamics and machine learning to provide quantitative measures of uncertainty. Models of neurodynamic information derived from electroencephalogram (EEG) brainwaves have provided detailed neurodynamic histories of US Navy submarine navigation team members. Persistent periods (25–30 s) of neurodynamic information were seen as discrete peaks when establishing the submarine’s position and were identified as periods of uncertainty by an artificial intelligence (AI) system previously trained to recognize the frequency, magnitude, and duration of different patterns of uncertainty in healthcare and student teams. Transition matrices of neural network states closely predicted the future uncertainty of the navigation team during the three minutes prior to a grounding event. These studies suggest that the dynamics of uncertainty may have common characteristics across teams and tasks and that forecasts of their short-term evolution can be estimated.

“…This is consistent with novice healthcare teams having higher NI levels than experienced teams. 34,37…”

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: An Ai System's Perspective Of Navigation Uncertaintymentioning

confidence: 99%

See 2 more Smart Citations

Can machine learning be used to forecast the future uncertainty of military teams?

Stevens

Journal of Defense Modeling & Simulation

2021

“…Such sequence entrainment/synchrony in real-world settings was shown to occur with submarine navigation teams (Stevens and Galloway, 2014, 2019, 2021b. The submarine navigation team consists of one group responsible for keeping the ship on course and they do so by checking and reporting the position every 3 min through a timed sequence of activities called Rounds.…”

Section: Inter-brain Couplingmentioning

confidence: 99%

Exploring how healthcare teams balance the neurodynamics of autonomous and collaborative behaviors: a proof of concept

Stevens¹,

2022

Front. Hum. Neurosci.

Self Cite

Team members co-regulate their activities and move together at the collective level of behavior while coordinating their actions toward shared goals. In parallel with team processes, team members need to resolve uncertainties arising from the changing task and environment. In this exploratory study we have measured the differential neurodynamics of seven two-person healthcare teams across time and brain regions during autonomous (taskwork) and collaborative (teamwork) segments of simulation training. The questions posed were: (1) whether these abstract and mostly integrated constructs could be separated neurodynamically; and, (2) what could be learned about taskwork and teamwork by trying to do so? The taskwork and teamwork frameworks used were Neurodynamic Information (NI), an electroencephalography (EEG) derived measure shown to be a neurodynamic proxy for the pauses and hesitations associated with individual uncertainty, and inter-brain EEG coherence (IBC) which is a required component of social interactions. No interdependency was observed between NI and IBC, and second-by-second dynamic comparisons suggested mutual exclusivity. These studies show that proxies for fundamental properties of teamwork and taskwork can be separated neurodynamically during team performances of ecologically valid tasks. The persistent expression of NI and IBC were not simultaneous suggesting that it may be difficult for team members to maintain inter-brain coherence while simultaneously reducing their individual uncertainties. Lastly, these separate dynamics occur over time frames of 15–30 s providing time for real-time detection and mitigation of individual and collaborative complications during training or live patient encounters.

Team Members Show Decreased Inter-brain Coupling When Resolving Uncertainty

Stevens¹,

Proceedings of the Human Factors and Ergonomics Society Annual

2022

Team members regulate their activities and move together at the collective level of behavior while coordinating their actions toward shared goals. In parallel with team processes, team members need to resolve uncertainties arising from their changing task work and a shifting environment. We explored the neurodynamic tension between resolving individual uncertainty and participating in collaborative processes during high fidelity team training. Electroencephalography (EEG) was collected from five two-person medical flight teams and following pre-processing to remove non-brain signals, the inter-brain coherence ( IBC) were estimated by wavelet coherence and compared with the neurodynamic information ( NI) of each individual, a measure that maps closely with human uncertainty. Analysis of the second-by-second IBC and NI showed that the expressions of NI and IBC were not simultaneous and may be mutually exclusive, suggesting that the factors elevating and resolving NI levels are single person processes and that it may be difficult for team members to maintain IBC while reducing their uncertainties. Although preliminary, these studies provide a first step towards neurodynamically quantifying and modifying teamwork and task work processes.