Correlations of pilot trainees' brainwave dynamics with subjective performance evaluations: insights from EEG microstate analysis

Abstract

Objective: This study aims to investigate the relationship between the subjective performance evaluations on pilot trainees' aircraft control abilities and their brainwave dynamics reflected in the results from EEG microstate analysis. Specifically, we seek to identify correlations between distinct microstate patterns and each dimension included in the subjective flight control evaluations, shedding light on the neurophysiological mechanisms underlying aviation expertise and possible directions for future improvements in pilot training.

Background: Proficiency in aircraft control is crucial for aviation safety and modern aviation where pilots need to maneuver aircraft through an array of situations, ranging from routine takeoffs and landings to complex weather conditions and emergencies. However, the neurophysiological aspects of aviation expertise remain largely unexplored. This research bridges the gap by examining the relationship between pilot trainees' specific brainwave patterns and their subjective evaluations of flight control levels, offering insights into the cognitive underpinnings of pilot skill efficiency and development.

Method: EEG microstate analysis was employed to examine the brainwave dynamics of pilot trainees while they performed aircraft control tasks under a flight simulator-based pilot training process. Trainees' control performance was evaluated by experienced instructors across five dimensions and their EEG data were analyzed to investigate the associations between the parameters of specific microstates with successful aircraft control.

Results: The experimental results revealed significant associations between aircraft control levels and the parameters of distinct EEG microstates. Notably, these associations varied across control dimensions, highlighting the multifaceted nature of control proficiency. Noteworthy correlations included positive correlations between microstate class E and class G with aircraft control, emphasizing the role of attentional processes, perceptual integration, working memory, cognitive flexibility, decision-making, and executive control in aviation expertise. Conversely, negative correlations between microstate class C and class F with aircraft control indicated links between pilot trainees' cognitive control and their control performance on flight tasks.

Conclusion: The findings underscore the multidimensional nature of aircraft control proficiency and emphasize the significance of attentional and cognitive processes in achieving aviation expertise. These neurophysiological markers offer a basis for designing targeted pilot training programs and interventions to enhance trainees' aircraft control skills.

Keywords: EEG microstate analysis; aircraft control evaluations; brain dynamics; cognitive functions; correlation analysis; learning processes; pilot training.

Figure 1

Flight simulator and the experimental settings viewed from the top camera.

Figure 2

Information displayed on the primary flight display (PFD).

Figure 3

The spatial configuration of the seven microstate classes across STAGE (global) and for each training stage.

Figure 4

EEG microstate parameters of each microstate class during three stages: Training, PracticeA, and PracticeB.

Figure 5

Spearman correlation coefficients between the coverage of seven microstate classes and five aircraft control dimensions. Correlations with p-values satisfying p ≤ 0.05 are annotated by ^*.

Figure 6

Correlation coefficients between the duration of seven microstate classes and five aircraft control dimensions. Correlations with p-values satisfying p ≤ 0.05 are annotated by ^*.

Figure 7

Correlation coefficients between the occurrence of seven microstate classes and five aircraft control dimensions. Correlations with p-values satisfying p ≤ 0.05 are annotated by ^*.