Sleep loss increases sleep propensity, destabilizes the wake state, impairs psychomotor and cognitive performance, and causes considerable social, financial and health-related costs. Although insufficient sleep is a risk factor for obesity, cardiovascular disease and diabetes, depression, and prospective mortality, about 20% to 40% of the US adults sleep less than the minimum sleep duration (7-8 hours per night) to prevent cumulative deterioration in cognitive performance. Neurobehavioral evidence from our previous studies and other groups has indicated robust and highly replicable (trait-like) individual differences in the magnitude of sleepiness and cognitive performance vulnerability to sleep deprivation. While some healthy adults show substantial cognitive deficits during sleep loss, others show few cognitive changes when sleep is deprived. However, little is known about why some sleep-deprived people are more prone to cognitive deficits that can result in costly errors and accidents. To answer this question, we propose to combine our interdisciplinary expertise in neuroimaging and neurobehavioral effects of sleep deprivation to elucidate the neural basis underlying this differential cognitive vulnerability. We will use a new technique of arterial spin labeling (ASL) perfusion functional magnetic resonance imaging (fMRI) for quantification of resting brain activity without task and tonic activation during performance of the psychomotor vigilance test (PVT) in a large sample of N=60 healthy subjects after normal sleep and following sleep deprivation. PVT is a simple, reliable and highly sensitive task for measuring attentional and performance deficits due to sleep deprivation. We will also use traditional BOLD fMRI for measuring phasic activation during fast and slow PVT responses and functional connectivity analysis for studying brain connectivity after normal sleep and following sleep deprivation. The findings from this project will elucidate the neural mechanisms by which sleep deprivation affects behavioral performance and how the effects of sleep deprivation vary across individuals of differential vulnerability. The new knowledge gained from this study will have relevance for understanding and managing excessive sleepiness due to a number of common sleep disorders (e.g., sleep apnea and other sleep disorders; affective disorders; shift work sleep disorder). The project also has the potential to yield brain-based biomarkers that can be used to predict individual responses to sleep deprivation and its treatment.