PROJECT SUMMARY Arousal regulatory systems are disrupted in a wide range of psychiatric and neurological disorders, yet we know surprisingly little about the fundamental brain network mechanisms underlying transitions between the sleep and wake arousal-states. Invasive animal studies have demonstrated the causal role of several deep-brain regions including nuclei of the brainstem and thalamus in arousal from sleep, and recently, human functional magnetic resonance imaging (fMRI) studies of arousal implicated such deep-brain regions as key contributors. While we know shifts in brain rhythms, connectivity, and behavior accompany arousal-state transitions, how brain-wide dynamics unfold across such key regions during this state-change remains unknown. Previous studies have been limited by the spatiotemporal resolution necessary to capture whole-brain network dynamics occurring at arousal. Invasive studies are limited by the number of regions they can record from simultaneously, and traditional non-invasive methods lack the temporal resolution necessary to capture the fast dynamics occurring at arousal. Our novel method will use encephalography (EEG) and behavioral response to detect arousal-state changes combined with simultaneous fast fMRI (sample rate < 1 s) at 7 Tesla to measure deep- brain activity in nuclei of the brainstem, individual nuclei of the thalamus, basal ganglia regions, and cortical regions during human arousal from sleep. Preliminary data suggests that this fMRI acquisition method can detect significant temporal differences in activity signatures between regions of interest. We hypothesize that activation of the brainstem’s locus coeruleus, followed by a distinct activation sequence across thalamic nuclei and the basal forebrain, will precede arousal, and deactivation of cortical regions will follow. We aim to build a fundamental understanding of the basic network mechanisms supporting arousal-state transitions in humans that will be necessary to ultimately understand how arousal regulatory system dynamics are altered in disorders. Delineating such temporal network dynamics using fMRI will provide a more precise understanding of how the brain switches between cognitive states by allowing us to link activity across dozens of subcortical nuclei simultaneously. Identifying these network mechanisms in humans will also provide the opportunity for future studies to identify fine-scale differences in neuropsychiatric disorders that was not previously possible.