Detection and Estimation of Working Memory States and Cognitive Functions Based on Neurophysiological Measures

There is growing interest for implementing tools to monitor cognitive performance in naturalistic work and everyday life settings. The emerging field of research, known as neuroergonomics, promotes the use of wearable and portable brain monitoring sensors such as functional near infrared spectroscopy (fNIRS) to investigate cortical activity in a variety of human tasks out of the laboratory. The objective of this study was to implement an on-line passive fNIRS-based brain computer interface to discriminate two levels of working memory load during highly ecological aircraft piloting tasks. Twenty eight recruited pilots were equally split into two groups (flight simulator vs. real aircraft). In both cases, identical approaches and experimental stimuli were used (serial memorization task, consisting in repeating series of pre-recorded air traffic control instructions, easy vs. hard). The results show pilots in the real flight condition committed more errors and had higher anterior prefrontal cortex activation than pilots in the simulator, when completing cognitively demanding tasks. Nevertheless, evaluation of single trial working memory load classification showed high accuracy (>76%) across both experimental conditions. The contributions here are two-fold. First, we demonstrate the feasibility of passively monitoring cognitive load in a realistic and complex situation (live piloting of an aircraft). In addition, the differences in performance and brain activity between the two experimental conditions underscore the need for ecologically-valid investigations.

Mind wandering is a pervasive threat to transportation safety, potentially accounting for a substantial number of crashes and fatalities. In the current study, mind wandering was induced through completion of the same task for 5 days, consisting of a 20-min monotonous freeway-driving scenario, a cognitive depletion task, and a repetition of the 20-min driving scenario driven in the reverse direction. Participants were periodically probed with auditory tones to self-report whether they were mind wandering or focused on the driving task. Self-reported mind wandering frequency was high, and did not statistically change over days of participation. For measures of driving performance, participant labeled periods of mind wandering were associated with reduced speed and reduced lane variability, in comparison to periods of on task performance. For measures of electrophysiology, periods of mind wandering were associated with increased power in the alpha band of the electroencephalogram (EEG), as well as a reduction in the magnitude of the P3a component of the event related potential (ERP) in response to the auditory probe. Results support that mind wandering has an impact on driving performance and the associated change in driver’s attentional state is detectable in underlying brain physiology. Further, results suggest that detecting the internal cognitive state of humans is possible in a continuous task such as automobile driving. Identifying periods of likely mind wandering could serve as a useful research tool for assessment of driver attention, and could potentially lead to future in-vehicle safety countermeasures.