Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty
Research on the microscale neural dynamics of social interactions has yet to be translated into improvements in the assembly, training and evaluation of teams. This is partially due to the scale of neural involvements in team activities, spanning the millisecond oscillations in individual brains to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-11-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1099-4300/18/12/427 |
| _version_ | 1828233566370136064 |
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| author | Ronald Stevens Trysha Galloway Donald Halpin Ann Willemsen-Dunlap |
| author_facet | Ronald Stevens Trysha Galloway Donald Halpin Ann Willemsen-Dunlap |
| author_sort | Ronald Stevens |
| collection | DOAJ |
| description | Research on the microscale neural dynamics of social interactions has yet to be translated into improvements in the assembly, training and evaluation of teams. This is partially due to the scale of neural involvements in team activities, spanning the millisecond oscillations in individual brains to the minutes/hours performance behaviors of the team. We have used intermediate neurodynamic representations to show that healthcare teams enter persistent (50–100 s) neurodynamic states when they encounter and resolve uncertainty while managing simulated patients. Each of the second symbols was developed situating the electroencephalogram (EEG) power of each team member in the contexts of those of other team members and the task. These representations were acquired from EEG headsets with 19 recording electrodes for each of the 1–40 Hz frequencies. Estimates of the information in each symbol stream were calculated from a 60 s moving window of Shannon entropy that was updated each second, providing a quantitative neurodynamic history of the team’s performance. Neurodynamic organizations fluctuated with the task demands with increased organization (i.e., lower entropy) occurring when the team needed to resolve uncertainty. These results show that intermediate neurodynamic representations can provide a quantitative bridge between the micro and macro scales of teamwork. |
| first_indexed | 2024-04-12T19:41:33Z |
| format | Article |
| id | doaj.art-0038a7185bc9447e899447f9ec39a532 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-12T19:41:33Z |
| publishDate | 2016-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-0038a7185bc9447e899447f9ec39a5322022-12-22T03:19:04ZengMDPI AGEntropy1099-43002016-11-01181242710.3390/e18120427e18120427Healthcare Teams Neurodynamically Reorganize When Resolving UncertaintyRonald Stevens0Trysha Galloway1Donald Halpin2Ann Willemsen-Dunlap3Brain Research Institute, University of California, Los Angeles School of Medicine, Culver City, CA 90230, USAIMMEX (Interactive Multi-Media Exercises), The Learning Chameleon, Inc., Culver City, CA 90230, USAJUMP Simulation and Education Center, 1306 N Berkeley Ave, Peoria, IL 61603, USAJUMP Simulation and Education Center, 1306 N Berkeley Ave, Peoria, IL 61603, USAResearch on the microscale neural dynamics of social interactions has yet to be translated into improvements in the assembly, training and evaluation of teams. This is partially due to the scale of neural involvements in team activities, spanning the millisecond oscillations in individual brains to the minutes/hours performance behaviors of the team. We have used intermediate neurodynamic representations to show that healthcare teams enter persistent (50–100 s) neurodynamic states when they encounter and resolve uncertainty while managing simulated patients. Each of the second symbols was developed situating the electroencephalogram (EEG) power of each team member in the contexts of those of other team members and the task. These representations were acquired from EEG headsets with 19 recording electrodes for each of the 1–40 Hz frequencies. Estimates of the information in each symbol stream were calculated from a 60 s moving window of Shannon entropy that was updated each second, providing a quantitative neurodynamic history of the team’s performance. Neurodynamic organizations fluctuated with the task demands with increased organization (i.e., lower entropy) occurring when the team needed to resolve uncertainty. These results show that intermediate neurodynamic representations can provide a quantitative bridge between the micro and macro scales of teamwork.http://www.mdpi.com/1099-4300/18/12/427team neurodynamicsShannon entropyEEGteamworkhealthcareuncertainty |
| spellingShingle | Ronald Stevens Trysha Galloway Donald Halpin Ann Willemsen-Dunlap Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty Entropy team neurodynamics Shannon entropy EEG teamwork healthcare uncertainty |
| title | Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty |
| title_full | Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty |
| title_fullStr | Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty |
| title_full_unstemmed | Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty |
| title_short | Healthcare Teams Neurodynamically Reorganize When Resolving Uncertainty |
| title_sort | healthcare teams neurodynamically reorganize when resolving uncertainty |
| topic | team neurodynamics Shannon entropy EEG teamwork healthcare uncertainty |
| url | http://www.mdpi.com/1099-4300/18/12/427 |
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