Abstract
Sleep–wake history, wake behaviors, lighting conditions, and circadian time influence sleep, but neither their relative contribution nor the underlying mechanisms are fully understood. The dynamics of electroencephalogram (EEG) slow-wave activity (SWA) during sleep can be described using the two-process model, whereby the parameters of homeostatic Process S are estimated using empirical EEG SWA (0.5–4 Hz) in nonrapid eye movement sleep (NREMS), and the 24 hr distribution of vigilance states. We hypothesized that the influence of extrinsic factors on sleep homeostasis, such as the time of day or wake behavior, would manifest in systematic deviations between empirical SWA and model predictions. To test this hypothesis, we performed parameter estimation and tested model predictions using NREMS SWA derived from continuous EEG recordings from the frontal and occipital cortex in mice. The animals showed prolonged wake periods, followed by consolidated sleep, both during the dark and light phases, and wakefulness primarily consisted of voluntary wheel running, learning a new motor skill or novel object exploration. Simulated SWA matched empirical levels well across conditions, and neither waking experience nor time of day had a significant influence on the fit between data and simulation. However, we consistently observed that Process S declined during sleep significantly faster in the frontal than in the occipital area of the neocortex. The striking resilience of the model to specific wake behaviors, lighting conditions, and time of day suggests that intrinsic factors underpinning the dynamics of Process S are robust to extrinsic influences, despite their major role in shaping the overall amount and distribution of vigilance states across 24 hr.
Highlights
The propensity for wake and sleep across the 24 hr day is thought to be determined by the time of day, lighting conditions, specific waking activities, preceding sleep–wake history, and homeostatically regulated needs such as hunger [1–7]
The intraepisodic dynamics of slow-wave activity (SWA) in mice can be described using the elaborated model First, we investigated the performance of the model based on recordings obtained in a group of animals well habituated to regular running wheels (RW)
We argue that rather than Process S building during θ-dominated waking, it is possible that other factors, which are manifested in more active waking behaviors, may in turn result in prolonged sustained wakefulness and a robust build-up of sleep need
Summary
The propensity for wake and sleep across the 24 hr day is thought to be determined by the time of day, lighting conditions, specific waking activities, preceding sleep–wake history, and homeostatically regulated needs such as hunger [1–7]. Homeostatic regulation involves a sensor and an effector, which monitor changes in regulated variables and trigger adequate responses to keep them within a given range [13]. How these relate to homeostatic regulation of sleep intensity is unknown, but evidence suggests that sleep is implicated in a variety of restorative processes related to energy homeostasis, synaptic homeostasis, and prophylactic cellular maintenance [14–19]. At the cellular and molecular levels, it has been shown that the levels of adenosine increase progressively in the basal forebrain and in some cortical areas during wake [14, 20, 21], which may influence activity in subcortical circuits responsible for sleep control [16], or directly inhibit specific neuronal populations in the cortex [14, 16]. Consistent with this, several molecular markers of synaptic strength or neuronal excitability change across waking and sleep [24–27], it is unclear whether they are directly regulated by states of vigilance, or merely represent an epiphenomenon of other processes not implicated directly in sleep regulation [28–31]
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