QUASI-PERIODIC BRAIN PATTERNS AND SLEEP DURING REST AND N-BACK TASKS
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Rich, Cassandra
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Abstract
Quasi-periodic brain patterns (QPPs) provide a representation of functional architecture between the Default Mode Network (DMN) and Task Positive Network (TPN) during functional magnetic resonance imaging (fMRI). Previous research has identified fluctuations in QPPs during both rest and task performance that are affected by attentional focus and arousal (Abbas et al., 2019). Individual sleep duration with daytime sleepiness has been shown to affect arousal levels and reduce DMN connectivity in young adults (Ward et al., 2013), which alters connectivity between the DMN and the TPN. This study examines how fluctuations in arousal affect brain network patterns during both rest and working memory tasks in healthy college-age students. We monitored sleep quality using wrist actigraphy watches for three days before the scan. Participants were separated into good and poor sleepers based on sleep efficiency scores. Each participant underwent an fMRI and performed 0-back and 2-back tasks, as well as a rest scan. Overall we found that good sleepers were faster and more accurate in 0-back than 2-back compared to poor sleepers. The differences between poor and good sleepers in the 2-back task were less drastic, and this could be due to a more cognitively demanding task requiring more resources in both sleep groups. During rest and 0-back TPN subnetwork frontoparietal control network (FPCN) is positively correlated with DMN but decouples during the 2-back task. The data suggests that the network driving the differences between DMN and TPN is FPCN. Additionally, poor sleepers have lower FPCN amplitude and lower positive correlation with DMN than good sleepers during rest. Overall, our results suggest that the relationship between functional connectivity and brain networks changes with arousal and relates to task performance.
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Undergraduate Research Option Thesis