Modelling maintenance of wakefulness in rats: comparing potential non‐invasive sleep‐restriction methods and their effects on sleep and attentional performance

Abstract

Summary While several methods have been used to restrict the sleep of experimental animals, it is often unclear whether these different forms of sleep restriction have comparable effects on sleep–wake architecture or functional capacity. The present study compared four models of sleep restriction, using enforced wakefulness by rotation of cylindrical home cages over 11 h in male Wistar rats. These included an electroencephalographic‐driven ‘Biofeedback’ method and three non‐invasive methods where rotation was triggered according to a ‘Constant’, ‘Decreasing’ or random protocol based upon the ‘Weibull’ distribution fit to an archival Biofeedback dataset. Sleep–wake architecture was determined using polysomnography, and functional capacity was assessed immediately post‐restriction with a simple response latency task, as a potential homologue of the human psychomotor vigilance task. All sleep restriction protocols resulted in sleep loss, behavioural task disengagement and rebound sleep, although no model was as effective as real‐time electroencephalographic‐Biofeedback. Decreasing and Weibull protocols produced greater recovery sleep than the Constant protocol, mirrored by comparably poorer simple response latency task performance. Increases in urinary corticosterone levels following Constant and Decreasing protocols suggested that stress levels may differ between protocols. Overall, these results provide insight into the value of choosing a specific sleep restriction protocol, not only from the perspective of animal welfare and the use of less invasive procedures, but also translational validity. A more considered choice of the physiological and functional effects of sleep‐restriction protocols in rodents may improve correspondence with specific types of excessive daytime sleepiness in humans.

Sleep deprivation and stress: a reciprocal relationship

“…However, 10 h of total sleep deprivation using this novel paradigm did not prevent a significant rise of corticosterone [81]. Other methods, based on real-time EEG or EMG biofeedback systems triggering the rotation of cylindrical cages or running wheels when NREM sleep, REM sleep or inactivity are detected, were able to prevent sleep for 6-11 h in male rats and mice with a mild but non-significant increase in corticosterone [77,82].…”

“…Despite this study's conclusion stating that the overall low level of stress was unlikely to substantially alter sleep patterns during recovery, the immediate but transient effects of forced locomotion on corticosterone release, and thus subsequent effects on sleep parameters and underlying sleep-regulating mechanisms, cannot be ignored. Furthermore, other studies have shown that sleep deprivation, fragmentation or restriction by forced locomotion for 11-48 h in rats markedly increased the release of corticosterone [72][73][74][75][76][77]. In mice, 24 h of sleep deprivation using an activity wheel did not cause a significant increase in corticosterone [78], while another study showed that chronic sleep interruption during 14 days using a rotating drum induced an increase in corticosterone [79].…”

Food restriction induces functional resilience to sleep restriction in rats

“…The aim of the present study was to assess the effects of feeding condition (i.e. ad libitum-fed vs. food restriction) at baseline and on SR induced changes in performance of a simple response latency task (SRLT) in rats [26]. In addition, the effects of SR and food restriction on performance of a progressive ratio (PR) test were measured.…”

“…Breakpoint is considered to be an index of present state of motivation of the animal to obtain the reward. The EEG was recorded to quantify sleep and event-related potentials (ERP) during the SRLT to gain further insight into cognitive processes, and how they are affected by sleep loss and food restriction [26,28].…”

Characterisation of the Effects of Sleep Deprivation on the Electroencephalogram Using Permutation Lempel–Ziv Complexity, a Non-Linear Analysis Tool

“…These dynamic changes in the EEG display various amplitudes (i.e., low amplitude in wakefulness and REM sleep and high amplitude in NREM sleep) and specific spectral features. Analysis of the EEG is based on the visual and/or automated scoring of vigilance states on epochs of various durations using defined criteria both in humans [8,9] and rodents [10,11]. Fourier Transform-based signal analysis has provided essential information about the amplitude and frequency features of the EEG associated with the different vigilance states, characterised by power density spectra revealing frequency components of the signal [12].…”