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Poster C131

Aperiodic vs. slow wave activity in rat sleep stages

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC

Quirine van Engen1 (, Alexandra Garcia1, Brad Voytek1,2,3; 1Department of Cognitive Science, UCSD, 2Halıcıoğlu Data Science Institute, UCSD, 3Department of Neuroscience, UCSD

Sleep is an important part of any animal's life. Humans spend a significant percentage each day sleeping; other mammals, such as cats, spend more than 50% of each day sleeping. Lack of sleep disrupts cognitive functioning, as well as emotional and physical health. Historically, sleep is divided into stages, differentiated based on electroencephalography (EEG) recordings, muscle activity, motion, and parasympathetic responses, with recent developments showing that the non-oscillatory, aperiodic EEG signal is a strong marker for sleep stage. This is interesting because, while deeper sleep stages are associated with increased EEG “slow-wave” activity, we have recently shown in clinical populations that EEG “slowing” is better explained by shifts in aperiodic activity compared to slow-wave oscillations. Therefore, we hypothesize that aperiodic activity is a better predictor of sleep stages than slow wave activity, and that not all slow “waves” in sleep are true oscillations. Here, we analyze a dataset consisting of rats' intracranial EEG going through sleep-wake cycles (Watson et al., 2016), to investigate whether they show a similar pattern in aperiodic activity over sleep stages as observed in other species (humans and mice). Preliminary results show the same pattern; deeper sleep stages are associated with steeper spectra compared to REM or awake. Aperiodic activity is related to E:I, which could inform future research to investigate this concept in relation to cognitive phenomena that require healthy sleep, and establish a potential causal relationship between aperiodic activity during sleep and cognition.

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April 13–16  |  2024