ABSTRACT. Slow fluctuations in behavioral, cognitive, and neural states are an omnipresent feature of the brain across species and are aberrant in multiple disorders of the nervous system. Slow brain network fluctuations critically organize behavior across extended timescales: as drifts in arousal over minutes, as well as our ability to switch between attending externally versus turning internally to plan our future actions and dwell on recent experiences. Although the contribution of slow brain network fluctuations to behavior have typically been studied by linking one network measure to one behavior, this project seeks to more broadly understand slow fluctuations in healthy human participants by i) deeply characterizing their relationship across multiple measures of brain activity, physiology, behavior, and cognition measured simultaneously and ii) causally manipulating key factors of cognitive control and arousal which are hypothesized to orchestrate relationships between slow network fluctuations and ongoing behavior or switching between modes of externally versus internally oriented attention. To achieve these goals, Aim 1 will perform a deep characterization of slow network fluctuations by collecting extensive multimodal neural and physiological recordings in healthy human participants. Simultaneous fMRI, EEG, electrodermal activity, pupillometry, respiration, ECG, and EMG will be recorded as participants perform an extended array of tasks ranging from unstructured (rest) to highly structured attention-demanding tasks. Experience sampling will allow us to assess the contents of ongoing cognition. This rich dataset will allow us to, in an unprecedented manner, measure and link slow fluctuations across multiple modalities, map their relationship with behavior on externally-oriented tasks and to the contents of internal cognition. While Aim 1 will examine the relevance of slow fluctuations to performance on stimulus- driven tasks, our ability to direct attention internally likely has adaptive benefits, a feature not typically captured in externally-oriented lab-based tasks. Aim 2a will fill in this gap by directly assessing the contributions of slow brain network fluctuations to supporting internal processing that benefits our subsequent behavior. Specifically we will measure brain patterns associated with learning and goal planning tasks, and assess neural and behavioral markers of continued internal processing on these tasks during a subsequent time period. This will allow us to directly link slow network fluctuations to benefits associated with internally-oriented cognition, and measure trade-offs between internally- versus externally- oriented modes of cognition. Another major question relates to regulation of slow network fluctuations. Aim 2b will assess the potential causal contributions of two key factors, cognitive control and arousal, to slow fluctuations and their resulting impact on behavior and cognition. These factors will be inde...