Task-related, intrinsic oscillatory and aperiodic neural activity predict performance in naturalistic team-based training scenarios

Date

2022

Authors

Cross, Z.R.
Chatburn, A.
Melberzs, L.
Temby, P.
Pomeroy, D.
Schlesewsky, M.
Bornkessel Schlesewsky, I.

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Scientific Reports, 2022; 12(1, article no. 16172):1-15

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Abstract

Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more individuals engaging cooperatively in real-world tasks, such as in operational training environments. In this exploratory study, we recruited forty individuals paired as twenty dyads and recorded dual-EEG at rest and during realistic training scenarios of increasing complexity using virtual simulation systems. We estimated markers of intrinsic brain activity (i.e., individual alpha frequency and aperiodic activity), as well as task-related theta and alpha oscillations. Using nonlinear modelling and a logistic regression machine learning model, we found that resting-state EEG predicts performance and can also reliably differentiate between members within a dyad. Task-related theta and alpha activity during easy training tasks predicted later performance on complex training to a greater extent than prior behaviour. These findings complement laboratory-based research on both oscillatory and aperiodic activity in higher-order cognition and provide evidence that theta and alpha activity play a critical role in complex task performance in team environments.

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Data source: Supplementary information, https://doi.org/10.1038/s41598-022-20704-8

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Copyright 2022 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. (http://creativecommons.org/licenses/by/4.0/)

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