Abstract

Abstract Introduction The importance of human cortical theta-band power during REM is suggested by its association with aspects of emotional processing. Currently, this is measured first by visual-inspection of polysomnography to define REM-sleep (scored-REM) and then summing the total theta power within. However, activity attributed to scored-REM has been hypothesized to occur during some scored-NREM (“covert REM”) and total theta conflates different theta-band sources. Oscillatory theta-band activity (OTA) in the hippocampus and associated regions is the hallmark of REM-like sleep in invasive animal studies. We posit that an EEG assessment specifically targeting all-night OTA is a more accurate biomarker of theta-dependent REM functions than current methods. As a first step towards testing this hypothesis, we developed a sleep stage independent approach to isolate REM-like OTA from scalp-EEG. For validation, we compared this measure to conventional-staging and high-frequency activity. Methods Our method uses Irregular-Resampling Auto-Spectral Analysis to remove the aperiodic spectrum (a major source of theta-band power), followed by low-band power normalization to derive the relative oscillatory-theta activity (OTA). Covert REM-containing epochs were calculated based on OTA exceeding a threshold. We combined data from two in-laboratory studies resulting in a sample size of 42 healthy young adult subjects. Analyses used non-sleep restricted overnight EEG recordings from a frontal channel. Results A clear oscillatory-theta peak was observed after processing. Using all sleep stages, we found separation of OTA from total theta-band power evidenced by conventional staging (OTA: scored-REM>scored-NREM, p=0.003 vs total theta: scored-REM<scored-NREM, p<0.001) and correlation with beta-band activity (OTA: r=0.2, p<0.001 vs total theta: p=0.4). Supporting “covert REM”, OTA was present during scored-NREM (p<0.001). On average during a single sleep episode, covert REM was found in 28% of scored- NREM epochs (range=2-85%). Conclusion We developed a novel automated method for measuring REM-like oscillatory-theta activity, independent of conventional sleep staging methods. This method was used to measure REM-like activity across all sleep stages and, as reported in a companion abstract, test the hypothesis that this constitutes a better predictor of REM-dependent behavioral effects than current conventions. Support (If Any) This effort was fully supported by the Department of Defense Military Operational Medicine Research Program (MOMRP).

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