Can Variability of Brain Activity serve as a Metric for Assessing Human Performance during UAS Dual-Task Training

Functional near infrared spectroscopy (fNIRS) is an emerging mobile neuroimaging technology that monitors brain function through measures of cerebral hemodynamics, i.e., concentration of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR). fNIRS measures are strongly associated with changes in cognitive effort and offer the ability to assess learning of complex tasks in realistic settings. However, much of this research has focused on investigating the effect of task load changes and training on average brain activity. Increasing empirical evidence has demonstrated that variability of brain activity changes can provide further understanding of cognitive effort and workload. However, there is limited research on evaluation of variability as a feature in fNIRS-related human factors studies, especially within the context of dual-task training. Therefore, this study aimed on evaluating variability of fNIRS measures during simulation-based training of a dual Unmanned Aerial System (UAS) operator task. fNIRS data was collected from 13 young adults who participated in five sessions of testing consisting of skill acquisition (three easy) and transfer (two hard) phases. Standard deviation (SD) and root mean squared successive differences (rMSSD) were used to represent variability. Firstly, variability increased within easy and hard sessions and decreased while transitioning from easy to hard sessions. Secondly, these changes were not only larger in magnitude, but were exactly opposite of those reported from average measures. Thirdly, variability was largest in left dorsolateral PFC (LDLPFC) and right anterior medial PFC (RAMPFC), which are the regions that are expected to have UAS task-evoked activity. Lastly, variability features did not differ between LDLPFC and RAMPFC, even though average did. In conclusion, these findings suggest that variability of fNIRS measures are not only sensitive to skill acquisition, practice, task load, transfer, and subject-specific differences in learning during UAS task training but offer complimentary information to that of typically reported average fNIRS measures.