In one experiment, EEG recordings were made during a daytime session while 16 well-rested participants performed versions of a PC flight simulator task that were either low, moderate, or high in difficulty. In another experiment, the same subjects repeatedly performed high difficulty versions of the same task during an all night session with total sleep deprivation. Multivariate EEG metrics of cortical activation were derived for frontal brain regions essential for working memory and executive control processes that are presumably important for maintaining situational awareness, central brain regions essential for sensorimotor control, and posterior parietal and occipital regions essential for visuoperceptual processing. During the daytime session each of these regional measures displayed greater activation during the high difficulty task than during the low difficulty task, and degree of cortical activation was positively correlated with subjective workload ratings in these well-rested subjects. During the overnight session, cortical activation declined with time-on-task, and the degree of this decline over frontal regions was negatively correlated with subjective workload ratings. Since participants were already highly skilled in the task, such changes likely reflect fatigue-related diminishment of frontal executive capability rather than practice effects. These findings suggest that the success of efforts to gauge mental workload via proxy cortical activation measures in the context of adaptive automation systems will likely depend on use of user models that take both task demands and the operator’s state of alertness into account. Further methodological development of the measurement approach outlined here would be required to achieve a practical, effective objective means for monitoring transient changes in cognitive brain function during performance of complex real-world tasks.