The effects of sleep inertia on decision-making performance.
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Sleep inertia, the performance impairment that occurs immediately after awakening, has not been studied previously in relation to decision-making performance. Twelve subjects were monitored in the sleep laboratory for one night and twice awoken by a fire alarm (slow wave sleep, SWS and REM sleep). Decision making was measured over 10 3-min trials using the 'Fire Chief' computer task under conditions of baseline. SWS and REM arousal. The most important finding was that sleep inertia reduces decision-making performance for at least 30 min with the greatest impairments (in terms of both performance and subjective ratings) being found within 3 min after abrupt nocturnal awakening. Decision-making performance was as little as 51% of optimum (i.e. baseline) during these first few minutes. However, after 30 min. performance may still be as much as 20% below optimum. The initial effects of sleep inertia during the first 9 min are significantly greater after SWS arousal than after REM arousal, but this difference is not sustained. Decision-making performance after REM arousal showed more variability than after SWS arousal. Subjects reported being significantly sleepier and less clear-headed following both SWS and REM awakenings compared with baseline and this was sustained across the full 30 min. In order to generalize this finding to real-life situations, further research is required on the effects of continuous noise, emotional arousal and physical activity on the severity and duration of sleep inertia. (+info)
Cardiac autonomic nervous system activity during presleep wakefulness and stage 2 NREM sleep.
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Previous research has found that cardiac parasympathetic nervous system (PNS) activity increases and cardiac sympathetic nervous system (SNS) activity decreases during night-time sleep. This study aimed to examine in greater detail the time course of these changes in cardiac autonomic nervous system (ANS) activity. In the week prior to the experimental night, nine subjects maintained a constant sleep-wake schedule and experienced an adaptation night. Each subject's experimental night consisted of 2 h of presleep wakefulness, followed by a night of sleep, commencing at each subject's normal sleep onset time. One hundred and twenty beat blocks of presleep wakefulness and stable Stage 2 non-rapid eye movement (NREM) sleep across the night were selected. SNS activity was assessed using pre-ejection period, the amplitude of the T-wave in the ECG and the 0.1 Hz peak from the spectral analysis of the ECG. PNS activity was assessed using respiratory sinus arrhythmia (spectral analysis). Heart rate and respiratory rate were also measured. The results indicated a progressive decrease in SNS activity throughout sleep and a rise in PNS activity during the first half of the normal sleep period. The changes in PNS activity were similar, while the changes in SNS activity were altered, compared with a previous study in which stage of sleep was not controlled. This indicates a likely sleep stage influence on SNS activity, but not on cardiac PNS activity. These results are consistent with the concept of a primarily circadian, but not sleep, influence on PNS activity, and primarily a sleep, but not circadian, influence on SNS activity. (+info)
Respiratory-related evoked potentials during the transition from alpha to theta EEG activity in stage 1 NREM sleep.
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It has been argued previously that evoked potential components during Stage 1 sleep in response to both auditory and respiratory stimuli are intermediate between those of wakefulness and Stage 2 sleep. However, state fluctuations in the ECG between alpha and theta during Stage 1 sleep have been linked to changes in a number of respiratory functions including ventilation, upper airway resistance and chemical drive. It was therefore hypothesized that if respiratory related evoked potentials (RREP) were averaged separately for alpha and theta EEG periods during Stage 1 sleep, the alpha RREP would resemble wakefulness and the theta RREP would resemble Stage 2 sleep. RREPs were produced by 250 ms occlusions in 10 subjects. EEG was recorded from 29 scalp sites, referenced to linked ears, together with EOG and EMG. The N1 component was not specifically associated with alpha vs. theta activity, but appeared to be sensitive to any decrease in arousal level, suggesting that it was more related to attention than to changes in the EEG. The late N2 and P300 components were present during wake and Stage 1 alpha. However, in Stage 1 theta, different late components emerged (N300 and P450) that differed in latency, amplitude or topographical distribution from those seen in wakefulness. The P2 proved difficult to interpret, whereas the N550 did not appear until Stage 2 sleep, and as such, was not dependent on alpha/theta state. The results indicate that RREP components are differentially affected by the transition into sleep. (+info)
Prion protein: a role in sleep regulation?
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The prion protein (PrP) is a glycoprotein anchored to cell membranes and expressed in most cell types. Its structural features indicate possible relations to signal peptidases (Glockshuber et al. 1998). Since mutations in this protein lead to severe neurodegeneration and death in humans and animals, it is possible that the loss of its normal function contributes to the development of the pathology. Little is known about its normal function, but there are indications that it may play a role in circadian rhythm and sleep regulation in mice. We explored further whether PrP plays a role in sleep regulation by comparing sleep and the effects of 6 h sleep deprivation in PrP knockout mice and isogenic wild-type mice of the 129/Ola strain. The mice did not differ in the amount and distribution of the vigilance states or in the power spectra. The most remarkable difference was the larger and long-lasting increase of slow-wave activity (mean EEG power density 0.75-4.0 Hz) in non-rapid-eye-movement (NREM) sleep during recovery from sleep deprivation in the null mice. The results confirm our previous findings in mice with a mixed background. This observation applies also to slow-wave activity in NREM sleep episodes following spontaneous waking bouts of different duration. Sleep fragmentation in both genotypes was larger than in mice with the mixed background. A new aspect was revealed by the spectral analysis of the EEG, where the null mice had a lower peak frequency within the theta band in REM sleep and waking, and not in NREM sleep. Behavioural observations concomitant with the EEG indicated that the EEG difference in waking may be attributed to the smaller amount of exploratory behaviour in the null mice. The difference between the genotypes in theta peak frequency was not an overall effect on the EEG, since it was absent in NREM sleep. PrP therefore may be affecting the theta-generating mechanisms in the hippocampus during waking and REM sleep. It remains unresolved whether PrP plays a role in sleep consolidation, nevertheless the data suggest that it is involved in sleep regulation. A passive avoidance test showed a difference between the genotypes. It is not probable that this was due to memory differences, since the genotypes reacted similarly in a delayed T-maze alternation procedure. The behavioural differences need to be pursued further. (+info)
Differences in brain gene expression between sleep and waking as revealed by mRNA differential display and cDNA microarray technology.
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The consequences of sleep and sleep deprivation at the molecular level are largely unexplored. Knowledge of such molecular events is essential to understand the restorative processes occurring during sleep as well as the cellular mechanisms of sleep regulation. Here we review the available data about changes in neural gene expression across different behavioural states using candidate gene approaches such as in situ hybridization and immunocytochemistry. We then describe new techniques for systematic screening of gene expression in the brain, such as subtractive hybridization, mRNA differential display, and cDNA microarray technology, outlining advantages and disadvantages of these methods. Finally, we summarize our initial results of a systematic screening of gene expression in the rat brain across behavioural states using mRNA differential display and cDNA microarray technology. The expression pattern of approximately 7000 genes was analysed in the cerebral cortex of rats after 3 h of spontaneous sleep, 3 h of spontaneous waking, or 3 h of sleep deprivation. While the majority of transcripts were expressed at the same level among these three conditions, 14 mRNAs were modulated by sleep and waking. Six transcripts, four more expressed in waking and two more expressed in sleep, corresponded to novel genes. The eight known transcripts were all expressed at higher levels in waking than in sleep and included transcription factors and mitochondrial genes. A possible role for these known transcripts in mediating neural plasticity during waking is discussed. (+info)
Prostaglandin D2 and sleep--a molecular genetic approach.
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Prostaglandin (PG) D2 is the major prostanoid in the mammalian brain, and is the endogenous sleep-promoting substance in mice, rats, and monkeys, and probably in humans as well. When PGD synthase (PGDS), the enzyme responsible for the biosynthesis of PGD2 in the brain, was inhibited in vivo by its selective inhibitors, tetravalent selenium compounds, both slow-wave sleep and rapid-eye-movement sleep were reduced almost completely but reversibly, indicating that PGDS is a key enzyme in sleep regulation. Experiments with transgenic mice also support this contention. In situ hybridization, immunoperoxidase staining, and direct enzyme assay of tissue samples revealed that PGDS is mainly, if not exclusively, localized in the arachnoid membrane and choroid plexus, from which it is secreted into the cerebrospinal fluid to become beta-trace protein. PGD2 exerts its somnogenic activity by binding with PGD2 receptors, exclusively localized at the ventro-rostral surface of the basal forebrain. CGS21680, an adenosine A2a agonist, mimicked the somnogenic activity of PGD2 when applied to the PGD2-sensitive zone. This effect was dose-dependently and selectively abolished by the prior i.p. application of the adenosine A2a antagonist KF17837. Furthermore, the somnogenic activity of PGD2 was also dose-dependently and selectively attenuated by KF17837, indicating the possibility that the sleep induction by PGD2 may be mediated by adenosine through A2a receptors under these conditions. When PGD2 was infused into the subarachnoid space below the rostral basal forebrain, concurrent with sleep induction, striking expression of Fos immunoreactivity was observed in the ventrolateral preoptic area. Fos expression in the ventrolateral preoptic area was positively correlated with the preceding amount of sleep and negatively correlated with Fos expression in the tuberomammillary nucleus. PGD2 also increased Fos IR in the basal leptomeninges and several regions implicated in autonomic regulation. These observations suggest that PGD2 may induce sleep via leptomeningeal PGD2 receptors with subsequent activation of the ventrolateral preoptic area neurons. (+info)
Human insulin gene insertion in mice. Effects on the sleep-wake cycle?
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Recently, insulin synthesis and the presence of an insulin receptor have been demonstrated in the brain. Intracerebroventricular infusion of insulin causes a selective increase in the amount of slow-wave sleep. In the present study, the sleep-wake cycle of transgenic mice, with or without habenular neuronal expression of the human insulin gene, was studied to investigate the possible role of brain insulin as a sleep modulator. Slow-wave sleep duration was increased in those mice expressing human insulin in the habenula. However, it is possible that this effect was not due to expression of the insulin transgene, but to the genetic background of one of the parental strains (CBA) used for insertion of the transgene. Users of transgenic mice should be aware of this possibility and be cautious in interpreting results when hybrid embryos are used as transgene recipients. (+info)
Interdependence of multiple theta generators in the hippocampus: a partial coherence analysis.
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The extracellularly recorded theta oscillation reflects a dynamic interaction of various synaptic and cellular mechanisms. Because the spatially overlapping dipoles responsible for the generation of theta field oscillation may represent different mechanisms, their separation might provide clues with regard to their origin and significance. We used a novel approach, partial coherence analysis, to reveal the various components of the theta rhythm and the relationship among its generators. Hippocampal field activity was recorded by a 16-site silicon probe in the CA1-dentate gyrus axis of the awake rat. Field patterns, recorded from various intrahippocampal or entorhinal cortex sites, were used to remove activity caused by a common source by the partialization procedure. The findings revealed highly coherent coupling between theta signals recorded (1) from the hippocampal fissure and stratum (str.) oriens of the CA1 region and (2) between CA1 stratum radiatum and the dentate molecular layer. The results of partial coherence analysis indicated that rhythmic input from the entorhinal cortex explained theta coherence between signals recorded from the hippocampal fissure and str. oriens but not the coherence between signals derived from str. radiatum and the dentate molecular layer. After bilateral lesions of the entorhinal cortex, all signals recorded from both below and above the CA1 hippocampal pyramidal cell layer became highly coherent. These observations indicate the presence of two, relatively independent, theta generators in the hippocampus, which are mediated by the entorhinal cortex and the CA3-mossy cell recurrent circuitry, respectively. The CA3-mossy cell theta generator is partially suppressed by the dentate gyrus interneuronal output in the intact brain. We suggest that timing of the action potentials of pyramidal cells during the theta cycle is determined by the cooperation between the active CA3 neurons and the entorhinal input. (+info)