Recent research has brought new insights into our sleep requirements - from the amount we need to when, where and how we do it. © 2012 Reed Business Information Ltd, England.

There is increasing evidence that sleep facilitates memory acquisition and consolidation. Moreover, the sleep-wake history preceding memory acquisition and retention as well as circadian timing may be important. We showed previously that sleep deprivation (SD) following learning in OF1 mice impaired their performance on an object recognition task. The learning task was scheduled at the end of the 12 h dark period and the test 24 h later. To investigate the influence of the prominent circadian sleep-wake distribution typical for rodents, we now scheduled the learning task at the beginning of the dark period. Wakefulness following immediately after the learning task was attained either by gentle interference (SD; n = 20) or by spontaneous wheel running (RW; n = 20). Two control groups were used: one had no RW throughout the experiment (n = 23), while the other group's wheel was blocked immediately after acquisition (n = 16), thereby preventing its use until testing. Recognition memory, defined as the difference in exploration of a novel and of familiar objects, was assessed 24 h later during the test phase. Motor activity and RW use were continuously recorded. Remarkably, performance on the object recognition task was not influenced by the protocols; the waking period following acquisition did not impair memory, independent of the method inducing wakefulness (i.e., sleep deprivation or spontaneous running). Thus, all groups explored the novel object significantly longer than the familiar ones during the test phase. Interestingly, neither the amount of rest lost during the SD interventions nor the amount of rest preceding acquisition influenced performance. However, the total amount of rest obtained by the control and SD mice subjected to acquisition at ?dark offset? correlated positively (r = 0.66) with memory at test, while no such relationship occurred in the corresponding groups tested at dark onset. Neither the amount of running nor intermediate rest correlated with performance at test in the RW group. We conclude that interfering with sleep during the dark period does not affect object recognition memory consolidation.

The hypothalamic neuropeptides hypocretins (orexins) play a crucial role in the stability of arousal and alertness. Recent data have raised the hypothesis that hypocretin neurons are also part of the circuitries that mediate the hypothalamic stress response. In particular, we have recently demonstrated that corticotrophin-releasing factor (CRF)immunoreactive terminals make direct synaptic contacts with hypocretin-expressing neurons and that numerous hypocretinergic neurons express the CRF-R1/2 receptors. Furthermore, CRF excites hypocretinergic cells ex vivo through CRF-R1 receptors. Activation of hypocretinergic neurons in response to acute stress is severely impaired in CRF-R1 knockout mice. Moreover, the stress response is impaired in hypocretin-deficient mice. We propose that upon stressor stimuli, CRF stimulates the release of hypocretins, and this circuit contributes to activation and maintenance of arousal associated with the stress response and addiction. (c) 2005 Prous Science. All rights reserved.

Sleep homeostasis and circadian rhythmicity interact to determine the timing of behavioral activity. Circadian clock genes contribute to circadian rhythmicity centrally and in the periphery, but some also have roles within sleep regulation. The clock gene Period3 (Per3) has a redundant function within the circadian system and is associated with sleep homeostasis in humans. This study investigated the role of PER3 in sleep/wake activity and sleep homeostasis in mice by recording wheel running activity under baseline conditions in wild-type (WT; n = 54) and in PER3-deficient (Per3(-/-); n = 53) mice, as well as EEG-assessed sleep before and after 6 hours of sleep deprivation in WT (n = 7) and Per3(-/-) (n = 8) mice. Whereas total activity and vigilance states did not differ between the genotypes, the temporal distribution of wheel running activity, vigilance states, and EEG delta activity was affected by genotype. In Per3(-/-) mice, running wheel activity was increased and REM sleep and NREM sleep were reduced in the middle of the dark phase, and delta activity was enhanced at the end of the dark phase. At the beginning of the baseline light period, there was less wakefulness and more REM and NREM in Per3(-/-) mice. Per3(-/-) mice spent less time in wakefulness and more time in NREM sleep in the light period immediately after sleep deprivation and REM sleep accumulated more slowly during the recovery dark phase. These data confirm a role for PER3 in sleep/wake timing and sleep homeostasis.

Caffeine, the most widely used psychoactive compound, is an adenosine receptor antagonist. It promotes wakefulness by blocking adenosine A(2A) receptors (A(2A)Rs) in the brain, but the specific neurons on which caffeine acts to produce arousal have not been identified. Using selective gene deletion strategies based on the Cre/loxP technology in mice and focal RNA interference to silence the expression of A(2A)Rs in rats by local infection with adeno-associated virus carrying short-hairpin RNA, we report that the A(2A)Rs in the shell region of the nucleus accumbens (NAc) are responsible for the effect of caffeine on wakefulness. Caffeine-induced arousal was not affected in rats when A(2A)Rs were focally removed from the NAc core or other A(2A)R-positive areas of the basal ganglia. Our observations suggest that caffeine promotes arousal by activating pathways that traditionally have been associated with motivational and motor responses in the brain.

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 sleepwake architecture or functional capacity. The present study compared four models of sleep restriction, using enforced wakefulness by rotation of cylindrical home cages over 11-hours in male Wistar rats. These included an electroencephalographic (EEG)-driven ?Biofeedback? method and three non-invasive methods where rotation was triggered according to a ?Constant?, ?Decreasing?, or a random protocol based upon the ?Weibull? distribution fit to an archival Biofeedback dataset. The sleep-wake architecture was determined using polysomnography and functional capacity was assessed immediately post-restriction with a simple response latency task (SRLT), 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 EEG-biofeedback. Decreasing and Weibull protocols produced greater recovery sleep than the Constant protocol, mirrored by comparably worse SRLT performance. Increases in urinary corticosterone levels following Constant and Decreasing protocols suggested that stress levels may differ between protocols. Overall, these results provide insights 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.

To test the hypothesis that sleep can reverse cognitive impairment during Alzheimer?s disease, we enhanced sleep in flies either co-expressing human amyloid precursor protein and Beta-secretase (APP:BACE), or in flies expressing human tau. The ubiquitous expression of APP:BACE or human tau disrupted sleep. The sleep deficits could be reversed and sleep could be enhanced when flies were administered the GABA-A agonist 4,5,6,7-tetrahydroisoxazolo-[5,4-c]pyridine-3-ol (THIP). Expressing APP:BACE disrupted both Short-term memory (STM) and Long-term memory (LTM) as assessed using Aversive Phototaxic Suppression (APS) and courtship conditioning. Flies expressing APP:BACE also showed reduced levels of the synaptic protein discs large (DLG). Enhancing sleep in memory-impaired APP:BACE flies fully restored both STM and LTM and restored DLG levels. Sleep also restored STM to flies expressing human tau. Using live-brain imaging of individual clock neurons expressing both tau and the cAMP sensor Epac1-camps, we found that tau disrupted cAMP signaling. Importantly, enhancing sleep in flies expressing human tau restored proper cAMP signaling. Thus, we demonstrate that sleep can be used as a therapeutic to reverse deficits that accrue during the expression of toxic peptides associated with Alzheimer?s disease.

The process of neurogenesis has been demonstrated to occur throughout life in the subgranular zone (SGZ) of the hippocampal dentate gyrus of several mammals, including humans. The basal rate of adult hippocampal neurogenesis can be altered by lifestyle and environmental factors. In this perspective review, the evidence for sleep as a modulator of adult hippocampal neurogenesis is first summarized. Following this, the impacts of sleep and sleep disturbances on hippocampal-dependent functions, including learning and memory, and depression are critically evaluated. Finally, we postulate that the effects of sleep on hippocampal-dependent functions may possibly be mediated by a change in adult hippocampal neurogenesis. This could provide a route to new treatments for cognitive impairments and psychiatric disorders.

Specific patterns of brain activity during sleep and waking are recorded in the electroencephalogram (EEG). Time-frequency analyses methods have been widely used to analyse the EEG and identified characteristic oscillations for each vigilance state (VS) i.e., wakefulness, rapid-eye movement (REM) and non-rapid-eye movement (NREM) sleep. However, other aspects such as change of patterns associated with brain dynamics may not be captured unless a non-linear-based analysis method is used. In this pilot study, Permutation Lempel-Ziv Complexity (PLZC), a novel symbolic dynamics analysis method, was used to characterise the changes in the EEG in sleep and wakefulness during baseline and recovery from sleep deprivation. The results obtained with PLZC were contrasted with a related non-linear method, Lempel-Ziv complexity (LZC). Both measure the emergence of new patterns. However, LZC is dependent on the absolute amplitude of the EEG, while PLZC is only dependent on the relative amplitude due to symbolisation procedure and thus, more resistant to noise. We showed that PLZC discriminates activated brain states associated with wakefulness and REM sleep, which both displayed higher complexity, compared to NREM sleep. Additionally, significantly lower PLZC values were measured in NREM sleep during the recovery period following SD compared to baseline, suggesting a reduced emergence of new activity patterns in the EEG. These findings were validated using PLZC on surrogate data. By contrast, LZC was merely reflecting changes in the spectral composition of the EEG. Overall, this study implies that PLZC is a robust non-linear complexity measure, which is not dependent on amplitude variations in the signal, and which may be useful to further assess EEG alterations induced by environmental or pharmacological manipulations.

Sleep is an essential physiological phenomenon which is regulated by fundamental sleep-wake cycles. Sleep is formed of non-rapid-eye-movement (NREM) and REM stages where NREM and REM sleep stages alternate with wakefulness in a whole night sleep (i.e., typically consists of several sleep-wake cycles). During sleep, brain is active and the activity also alters with changing vigilance states (VS). Furthermore, physiological or external changes in the brain structure might influence brain activity during sleep. Effects of ageing, sex differences, and pharmacological manipulations have been widely investigated in sleep research using Fourier Transform. However, the use of non-linear analysis techniques might be more suitable in analysing non-linear and non-stationary signals (e.g., electroencephalogram (EEG)). Therefore, non-linear analysis has been used within this PhD with the hypothesis that these methods might reveal hidden characteristics in the changing brain signals that are difficult to detect with traditional EEG power spectral density analysis. The use of non-linear analysis techniques (e.g., symbolic dynamic analysis (SDA)) will allow to further dissect the physiological significance of activity-dependent changes of neuronal networks across sleep-wake cycles, as well as the significance of brain activity patterns during waking, sleep, sleep deprivation (SD), or induced by sleep-promoting drugs and pharmacological treatments.
In this PhD, rodent and human sleep EEG recordings were analysed using SDA methods: Lempel-Ziv complexity (LZC), Permutation Entropy (PE) and Permutation Lempel-Ziv complexity (PLZC). All the methods were able characterise different VS with wakefulness and REM sleep resulting in higher measures of complexity compared to NREM sleep suggesting an active state of the brain in these VS. This was measured in all datasets assisting the hypothesis on the usefulness of these techniques in sleep research by providing the minimum requirement for sleep analysis. In addition to this, SD significantly reduced complexity in the following sleep period supporting the compensation process for the lost sleep by the increased in slow wave activity which was reflected as reduced complexity in this study. Furthermore, a low dose tiagabine administration?s sleep compensation promoting effect was found in mice.
Moreover, ageing was identified as a main effect on changes in brain activity. These changes were more pronounced in the old age where complexity was significantly lower compared to young age. On the one hand, this was found with all three methods and contributing to the hypothesis that these techniques reveal structural dynamic changes due to physiological alterations. On the other hand, no significant differences in complexity across genders were found suggesting the underlying mechanisms to maintain sleep-wake cycles are similar for men and women. This finding with further investigation might corroborate to question the need to use both genders in drug trials. Furthermore, significant changes in brain activity were found at different times of the sleep period highlighting the changes occurring within VS as sleep progresses. This also has an impact on the way sleep stages are scored and investigated which are influenced by different brain activity levels within each VS throughout the entire sleep.
All in all, this study achieved to support its hypothesis of determining the changes in brain activity as a complexity measure by characterising sleep under physiological and pharmacologically induced EEG datasets in mice and in humans. The study was a novel application to analyse sleep in these conditions. However, with further analysis performed on larger datasets, its findings together with surrogate data analysis proved SDA techniques? robust usability which can complement the gold standard FT analysis in sleep research.

Human and rodent vigilance states have evolutionarily conserved control mechanisms, which suggests that measures of sleep can translate from the laboratory to the clinic. Continuity is an essential aspect of sleep architecture that facilitates the restoration of both body and mind. Current measures of vigilance state continuity do not align well between species and this prevents accurate translation. Throughout this thesis, survival and transition probability analyses were evaluated for their ability to quantify vigilance state continuity in humans and rats. These techniques produced more effective quantification of sleep architecture than metrics such as wake after sleep onset, number of awakenings and average bout lengths.
Two methods for defining a bout were first investigated. In both humans and rats, statistical properties of bouts were characterized using different bout-duration thresholds. It was found that bouts are best modelled with distributions that include a time component. Biological relevance of sleep continuity was also investigated in rats, where bouts of NREM sleep as short as 20 seconds reduced the homeostatic pressure, yet awakenings as short as 10 seconds were enough to disrupt the restorative processes of sleep. Short bouts were therefore an important component of sleep architecture and must be considered when evaluating continuity. Continuity metrics were next used to evaluate sleep restriction in rats and circadian rhythmicity in humans. Both homeostatic and circadian influences exerted significant control of NREM sleep continuity, whilst REM continuity was mostly unaffected. Finally, pharmacological agents were tested and their impact on state continuity effectively translated between species. NREM sleep continuity was not altered by the REM sleep inhibition of SSRI?s which differed to the deficits induced by REM sleep restriction. The main contribution of this thesis is to demonstrate that accurate quantification of vigilance state continuity can improve understanding of sleep architecture and the evaluation of pharmacological agents to deliver better patient outcomes.

Symbolic dynamic analysis (SDA) methods have been applied to biomedical signals and have been proven efficient in characterising differences in the electroencephalogram (EEG) in various conditions (e.g., epilepsy, Alzheimer?s and Parkinson?s diseases). In this study, we investigated the use of SDA on EEGs recorded during sleep. Lempel-Ziv Complexity (LZC), Permutation Entropy (PE), Permutation Lempel-Ziv Complexity (PLZC), as well as power spectral analysis based on the fast Fourier transform (FFT), were applied to 8-h sleep EEG recordings in healthy men (n=31) and women (n=29), aged 20-74 years. The results of the SDA methods and FFT analysis were compared and the effects of age and sex were investigated. Surrogate data were used to determine whether the findings with SDA methods truly reflected changes in non-linear dynamics of the EEG and not merely changes in the power spectrum. The surrogate data analysis showed that LZC merely reflected spectral changes in EEG activity, whereas PE and PLZC reflected genuine changes in the non-linear dynamics of the EEG. All three SDA techniques distinguished the vigilance states (i.e. wakefulness, REM sleep, NREM sleep and its sub stages: stage 1, stage 2 and slow wave sleep). Complexity of the sleep EEG increased with ageing. Sex on the other hand did not affect the complexity values assessed with any of these three SDA methods, even though FFT detected sex differences. This study shows that SDA provides additional insights into the dynamics of sleep EEG and how it is affected by ageing.

Symbolic dynamic analysis (SDA) methods have been applied to biomedical signals and have been proven efficient in characterising differences in the electroencephalogram (EEG) in various conditions (e.g., epilepsy, Alzheimer?s, and Parkinson?s diseases). In this study, we investigated the use of SDA on EEGs recorded during sleep. Lempel-Ziv complexity (LZC), permutation entropy (PE), and permutation Lempel-Ziv complexity (PLZC), as well as power spectral analysis based on the fast Fourier transform (FFT), were applied to 8-h sleep EEG recordings in healthy men (n=31) and women (n=29), aged 20-74 years. The results of the SDA methods and FFT analysis were compared and the effects of age and sex were investigated. Surrogate data were used to determine whether the findings with SDA methods truly reflected changes in nonlinear dynamics of the EEG and not merely changes in the power spectrum. The surrogate data analysis showed that LZC merely reflected spectral changes in EEG activity, whereas PE and PLZC reflected genuine changes in the nonlinear dynamics of the EEG. All three SDA techniques distinguished the vigilance states (i.e., wakefulness, REM sleep, NREM sleep, and its sub-stages: stage 1, stage 2, and slow wave sleep). Complexity of the sleep EEG increased with ageing. Sex on the other hand did not affect the complexity values assessed with any of these three SDA methods, even though FFT detected sex differences. This study shows that SDA provides additional insights into the dynamics of sleep EEG and how it is affected by ageing.

One of sleep?s putative functions is mediation of adaptation to waking experiences. Chronic stress is a common waking experience, however, which specific aspect of sleep is most responsive, and how sleep changes relate to behavioral disturbances and molecular correlates remain unknown. We quantified sleep, physical, endocrine and behavioral variables, as well as the brain and blood transcriptome in mice exposed to nine weeks of unpredictable chronic mild stress (UCMS). Comparing 46 phenotypical variables revealed that rapid-eye-movement sleep (REMS), corticosterone regulation and coat state were most responsive to UCMS. REMS theta oscillations were enhanced whereas delta oscillations in non-REMS were unaffected. Transcripts affected by UCMS in the prefrontal cortex, hippocampus, hypothalamus and blood were associated with inflammatory and immune responses. A machine learning approach controlling for unspecific UCMS effects identified transcriptomic predictor sets for REMS parameters which were enriched in 193 pathways, including some involved in stem cells, immune response, apoptosis and survival. Only 3 pathways were enriched in predictor sets for non-REMS. Transcriptomic predictor sets for variation in REMS continuity and theta activity shared many pathways with corticosterone regulation, in particular pathways implicated in apoptosis and survival, including mitochondrial apoptotic machinery. Predictor sets for REMS and anhedonia shared pathways involved in oxidative stress, cell proliferation and apoptosis. These data identify REMS as a core and early element of the response to chronic stress, and identify apoptosis and survival pathways as a putative mechanism by which REMS may mediate the response to stressful waking experiences.

Alzheimer?s disease (AD) is a significant public health concern. The incidence continues to rise, and it is set to be over one million in the UK by 2025. The processes involved in the pathogenesis of AD have been shown to overlap with those found in cognitive decline in patients with Obstructive Sleep Apnoea (OSA). Currently, the standard treatment for OSA is Continuous Positive Airway Pressure. Adherence to treatment can, however, be an issue, especially in patients with dementia. Also, not all patients respond adequately, necessitating the use of additional treatments. Based on the body of data, we here suggest that excessive and prolonged neuronal activity might contribute to genesis and acceleration of both AD and OSA in the absence of appropriately structured sleep. Further, we argue that external factors, including systemic inflammation and obesity, are likely to interfere with immunological processes of the brain, and further promote disease progression. If this hypothesis is proven in future studies, it could have far-reaching clinical translational implications, as well as implications for future treatment strategies in OSA.

The high prevalence of sleep disturbance in neurodegenerative and psychiatric conditions is often interpreted as evidence for both sleep?s sensitivity to and causal involvement in brain pathology. Nevertheless, how and which aspects of sleep contribute to brain function remains largely unknown. This review provides a critical evaluation of clinical and animal literature describing sleep and circadian disturbances in two distinct conditions and animal models thereof: Alzheimer?s disease (AD) and schizophrenia. Its goal is to identify commonalities and distinctiveness of specific aspects of sleep disturbance and their relationship to symptoms across conditions. Despite limited standardisation, data imply that reductions in sleep continuity and alterations in sleep timing are common to AD and schizophrenia, whereas reductions in REM sleep and sleep spindle activity appear more specific to AD and schizophrenia, respectively. Putative mechanisms underlying these alterations are discussed. A standardised neuroscience based quantification of sleep and disease-independent assessment of symptoms in patients and animal models holds promise for furthering the understanding of mechanistic links between sleep and brain function in health and disease.