Abstract Introduction REM sleep is critical for health and cognitive functioning. Recent studies have identified electrophysiological REM burst events (REM bursts) in theta (4-8Hz) and alpha (8-16Hz) frequency bands associated with cognitive performance, suggesting REM bursts as neural markers of cognitive processes. Still, intra-individual characteristics of REM bursts are unknown. Here, we conducted an in-depth analysis of REM burst events across the night and examined their intra-subject reliability across four nights of sleep. Methods 86 healthy young adults (67F; 18-35 years) slept in-lab for four nights with polysomnography. A validated REM burst detection algorithm was used to identify EEG theta and alpha bursts. Using linear mixed models, we examined burst features (count, power, duration, density) across four quartiles of sleep and relations between time in REM and bursts in each night. We also calculated intraclass correlation coefficients (ICCs) for burst features and REM minutes across four nights of sleep per subject. Results Both REM theta and alpha burst count increased across each quartile, but burst power decreased over the night. Alpha burst density was lowest during quartile 1 compared with the rest of the night. Theta burst duration increased from quartile 1 and 2 to 3 and 4, while alpha burst duration did not vary. REM minutes positively predicted count and density measures, but negatively predicted power and duration measures. Exclusively in quartiles 1 and 2, REM minutes positively predicted alpha burst density and negatively predicted alpha burst power, indicating potential change in REM physiology from early to late night. Intraclass correlations from alpha and theta bursts showed that power and duration are highly reliable within-subject (ICC≈0.9), while counts, density, and REM minutes are moderately reliable (ICC≈0.5), showing similar levels of reliability levels as non-REM sleep spindles. Conclusion REM bursts were shorter, higher in power, and negatively correlated with the amount of REM sleep in the first half of night, while density increased across the night. We also identified burst features as trait-like, with intra-individual reliability comparable to existing spindles results. These results may provide foundational knowledge for studying REM bursts as neural markers of REM functions. Support (if any) RF1AG061355 (Baker/Mednick). K08HD107161 (Simon).
Chen et al. (Fri,) studied this question.