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

• Published in: Frontiers in neuroscience Vol. 11; p. 297
• Main Authors: Dasari, Deepika, Shou, Guofa, Ding, Lei
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 30.05.2017; Frontiers Media S.A
• Subjects: Air traffic control; Aircraft; Cognitive ability; cognitive factors; Conduction; EEG; Electroencephalography; Fatigue; Human performance; ICA; Information processing; Interfaces; mental effort; mental workload; Neuroscience; Principal components analysis; Studies; time-on-task effect; Visual perception; Workloads; United States > US; mental effort; time-on-task effect; EEG; ICA; mental workload; cognitive factors
• ISSN: 1662-453X; 1662-4548; 1662-453X
• DOI: 10.3389/fnins.2017.00297

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.