ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task

Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlyi...

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Main Authors: Deepika Dasari, Guofa Shou, Lei Ding
Format: Article
Language:English
Published: Frontiers Media S.A. 2017-05-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/article/10.3389/fnins.2017.00297/full
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author Deepika Dasari
Guofa Shou
Lei Ding
Lei Ding
author_facet Deepika Dasari
Guofa Shou
Lei Ding
Lei Ding
author_sort Deepika Dasari
collection DOAJ
description Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.
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spelling doaj.art-a3d6c22797c04595af430625f28e02c12022-12-22T01:13:19ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2017-05-011110.3389/fnins.2017.00297252708ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control TaskDeepika Dasari0Guofa Shou1Lei Ding2Lei Ding3School of Electrical and Computer Engineering, University of OklahomaNorman, OK, United StatesSchool of Electrical and Computer Engineering, University of OklahomaNorman, OK, United StatesSchool of Electrical and Computer Engineering, University of OklahomaNorman, OK, United StatesStephenson School of Biomedical Engineering, University of OklahomaNorman, OK, United StatesElectroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.http://journal.frontiersin.org/article/10.3389/fnins.2017.00297/fullcognitive factorstime-on-task effectmental effortmental workloadEEGICA
spellingShingle Deepika Dasari
Guofa Shou
Lei Ding
Lei Ding
ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task
Frontiers in Neuroscience
cognitive factors
time-on-task effect
mental effort
mental workload
EEG
ICA
title ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task
title_full ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task
title_fullStr ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task
title_full_unstemmed ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task
title_short ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task
title_sort ica derived eeg correlates to mental fatigue effort and workload in a realistically simulated air traffic control task
topic cognitive factors
time-on-task effect
mental effort
mental workload
EEG
ICA
url http://journal.frontiersin.org/article/10.3389/fnins.2017.00297/full
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