0170 Slow Oscillation Power and Heart Rate Variability During Sleep Predicts Next-day Subjective Sleepiness in Healthy, Young Adults

Abstract

Abstract Introduction High amplitude, slow oscillations in the electroencephalogram (EEG) often characterize the central nervous system’s homeostatic drive for sleep. Slow oscillations dominate the first part of the night and often dissipate as sleep need is satiated. These physiological changes are also reflected in next day subjective measures of sleepiness. Fluctuations in the autonomic nervous system, particularly parasympathetic activity, also coincide with slow wave sleep and are understood to represent bodily homeostasis. However, it is unclear if autonomic indicators effectively predict next-day sleepiness. Here, we investigated whether slow oscillatory (SO) power and cardiac autonomic activity during a night of sleep can predict next day subjective sleepiness. Methods 88 young (aged 18-35), healthy participants spent the night in a University sleep lab. Before and after sleep, participants completed the Karolinska Sleepiness Scale (KSS) to measure subjective sleepiness. Each participant slept with polysomnography, including electroencephalography and electrocardiography. From these measures, we assessed slow oscillation power (0.5-1Hz) and high frequency heart rate variability (HRV; 0.15-0.45 Hz) --an indicator of parasympathetic, vagally-mediated cardiac tone-- during the first quartile of slow wave sleep. Paired T-tests compared the differences in KSS scores pre- and post-sleep. Pearson’s correlations assessed bivariate associations between slow oscillatory power, high frequency HRV, and KSS scores. Mixed linear models assessed the ability of SO power and high frequency HRV to predict next day subjective sleepiness. Results No significant differences were found in KSS ratings pre- (M±SD = 4.23±1.92) and post-sleep (4.38±1.80). No bivariate correlations were present between pre-sleep KSS, SO, or high frequency HRV. A significant correlation between KSS-post sleep and SO power emerged (r=0.286, p=0.001). In Model 1, we found that SO power was a predictor of subjective sleepiness (p<0.001; AIC: 777.469). In Model 2, we included high frequency HRV and reduced the AIC to 515.588. Both slow oscillatory power (p<0.001) and high frequency HRV (p<0.001) were significant predictors of KSS after sleep in Model 2. Conclusion We found evidence that both central and autonomic indicators of sleep predict psychological measures of sleepiness. Using autonomic indicators to characterize physiological sleepiness, compared to in-lab polysomnography, may be a more generalizable and cost-effective approach. Support (If Any)