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Anecdotal reports recount of individuals obtaining insights during sleep. For instance, various acclaimed scientists have attributed some of their greatest insights to sleep-related mentation. To date, this phenomenon has not been systematically investigated. The current study explored the occurrence and characteristics of Sleep-Related Insights (SRIs) in a large population sample, using a questionnaire approach. We found that a large majority of participants (~80%) experienced SRIs at some point in their lives and about 40% obtained SRIs regularly. Most of these subjects could link SRIs to remembered sleep mentation. SRIs were reported to occur in both sleep and half-sleep states, and at any point of the sleep period. Furthermore, SRIs regarded emotional preoccupations about twice as often as theoretical problems. Finally, SRIs were not robustly related to subjective sleep-quality, but small positive correlations with insomnia and narcolepsy-like symptoms were observed. In conclusion, SRIs are much more common than might have been expected, manifest in several forms and appear to be part of normal, healthy sleep. Importantly, the strong link of SRIs with sleep mentation suggests they result from some form of higher-order information processing during sleep, rather than being (fully) secondary to general restorative effects of sleep. Finally, our findings show that a large portion of the sampled population is aware of sleep's benefits for real life problem solving and experiences such benefits on a regular basis.

INTRODUCTION: Post Traumatic Stress Disorder (PTSD) is a significant health problem with as key symptoms aversive memory intrusions and overgeneralization of the traumatic event, as well as sleep disturbances. Interestingly, sleep has an important role in memory consolidation. In particular, sleep spindles in different cortical areas reflect reprocessing and consolidation of specific memory traces. Given their strong relationship with memory reprocessing during sleep and reported memory and sleep alterations in PTSD, sleep spindles may play a role in the aetiology of PTSD. The current study assesses sigma fluctuations in PTSD patients. METHODS: Several parameters of sigma fluctuations were analysed and compared between traumatized police officers and combat veterans with (N=13) and without (N=14) PTSD. An automated detection method, free of a-priori assumptions regarding spindle characteristic, was used to obtain an unbiased representation of all sigma fluctuations. The standard deviation of the filtered sleep EEG (11-16 Hz) was computed (moving window: 0.2s), and all waxing/waning couplets with an amplitude over 5 microvolt were detected. For each detected sigma fluctuation, several variables were computed (e.g. duration, amplitude etc). RESULTS: Increased spindling activity was found in PTSD patients compared to trauma controls. This despite SSRI use in a small subsample of patients, which decreased spindling. The assumption free analyses revealed details regarding spindle abnormalities in PTSD that would have been missed by analysing only heuristically detected spindles. CONCLUSION: The spindle abnormalities in PTSD may reflect excessive reprocessing and consolidation of trauma-related memories and may in this way contribute to the emotional memory problems. memory problems.

OBJECTIVES: A spindle reflects neurophysiological mechanisms of interactions between inhibitory cells in the thalamic reticular nucleus (RE) and bursting thalamocortical (TC) relay neurons. A gradual cell recruitment in RE-TC-RE loops is linked to the waxing of spindles. The cause of spindle waning is less clear, but a depolarizing action by the thalamic IH current may be involved. The influence of these neurophysiological mechanisms on spindle morphology inthe scalp EEG is still to be clarified. The transient nature of spindling and the lack of knowledge of the precise mechanism behind spindles require that the analysis of scalp EEG spindles should be performed with a minimum of assumptions and a high temporal resolution. This paper presents a statistical approach for the analysis of scalp EEG to determine the dynamics of spindle power. METHODS: The algorithm, developed in the Galaxy sleep system, has a very high timeresolution and deploys a minimum of assumptions. EEG is band-pass filtered (11.0-16.0 Hz) using a FIR-filter. The standard deviation of the signal is computed with a moving window of 0.2 second. The resulting power has a time resolution of the sample rate of the signal. Waxing and waning characteristics of a spindle are represented by the time-variant characteristics of the power. A pattern recognition algorithm detects all waxing/waning couplets. Various characteristics like peak power, total intensity, duration, symmetry, polarization/depolarization speed etc. are calculated for each waxing and waning couplet. In addition power dynamics in different spindle bands are calculated. RESULTS: Sleep EEG data of previously published studies on sleep and memory were reanalyzed to compare the statistics of the waxing/waning dynamics with spindles detected heuristically by visual criteria. The statistical analysis without prior assumptions provided more details of a spindle that could not be detected by visual heuristics (even with automated detection). The power dynamics showed that the power within the slow band (10-13 Hz) increased during the waxing part whereas the power in the fast band (13-16Hz) increased during the waning part of the spindle. CONCLUSION: Detecting all waxing/waning patterns without prior criteria like amplitude, duration etc. is useful. Subsequent analysis of waxing/waning parameters reveals more details missed by analyzing only heuristically detected spindles.

Normal sleep consists of two states: NREM (light and deep sleep) and REM, alternating in a cyclical pattern. The sleep/wake rhythm is regulated by two processes: the sleep propensity, building up during wake, and the circadian rhythm, imposed by the suprachiasmatic nucleus. The arousal pathways in the brainstem regulate the wake state. The ventrolateral preoptic nucleus in the hypothalamus (VLPO) is important for the control of NREM sleep. The VLPO neurons and the arousal pathways mutually inhibit each other, resulting in the alternation between sleeping and waking. Orexin from the lateral hypothalamus may stabilize the switching between these states. Cells in the pons and mesencephalon bring about the main phenomena of REM sleep. Although the regulation of the alternation between REM and NREM is not yet clear a mutually inhibitory interaction has been proposed between NREM active (REM-off) neurons and REM active (REM-on) neurons in brainstem and midbrain.

OBJECTIVES: Many insomnia patients complain about a disturbance by even minimal sounds from the environment. However, the concept of noise sensitivity is still poorly understood. Noise sensitive people are more affected by a noisy environment, but they do not seem to have an increased auditory sensitivity. Nevertheless noise sensitivity can have a large impact on daily life and in general they seem to have more sleep problems and more psychological problems. In this study noise sensitivity is studied in relation to individual sleep patterns, sleep quality and symptoms of sleep problems. In addition the association between noise sensitivity with personality traits is studied. METHODS: A group of 450 first year students in completed a noise sensitivity questionnaire (NoiSeQ) and a questionnaire for general sensitivity to environmental stimuli. In addition individual sleep patterns were measured with a general sleep questionnaire and subjective sleep quality was assessed with the Dutch Sleep Quality Scale. The Sleep50 scale was used to measure presence of symptoms of sleep problems. Two personality tests were administered: the 5 PVT (neuroticism and extraversion) and the ZBV to measure the tendency for anxiety. A group of low noise sensitive persons (LO) and a group of high sensitive persons (HI) were selected from NoiSeQ scores for the sleep subscale. RESULTS: More than a third of this student sample (36.5%) judged their chronotype as ‘extreme evening types’. This can be explained by the fact that these young students were still adolescents. 14.1% of the subjects had subjective symptoms of insomnia, 12.8% had symptoms of apnea, whereas 9.4% claimed to have parasomnias like sleepwalking or nightmares. The HI group had a longer sleep latency (p

Contains fulltext : 129669.pdf (Publisher’s version ) (Closed access) The posterior midline region (PMR)-considered a core of the default mode network-is deactivated during successful performance in different cognitive tasks. The extent of PMR-deactivations is correlated with task-demands and associated with successful performance in various cognitive domains. In the domain of episodic memory, functional MRI (fMRI) studies found that PMR-deactivations reliably predict learning (successful encoding). Yet it is unclear what explains this relation. One intriguing possibility is that PMR-deactivations are partially mediated by respiratory artifacts. There is evidence that the fMRI signal in PMR is particularly prone to respiratory artifacts, because of its large surrounding blood vessels. As respiratory fluctuations have been shown to track changes in attention, it is critical for the general interpretation of fMRI results to clarify the relation between respiratory fluctuations, cognitive performance, and fMRI signal. Here, we investigated this issue by measuring respiration during word encoding, together with a breath-holding condition during fMRI-scanning. Stimulus-locked respiratory analyses showed that respiratory fluctuations predicted successful encoding via a respiratory phase-locking mechanism. At the same time, the fMRI analyses showed that PMR-deactivations associated with learning were reduced during breath-holding and correlated with individual differences in the respiratory phase-locking effect during normal breathing. A left frontal region-used as a control region-did not show these effects. These findings indicate that respiration is a critical factor in explaining the link between PMR-deactivation and successful cognitive performance. Further research is necessary to demonstrate whether our findings are restricted to episodic memory encoding, or also extend to other cognitive domains. 12 p.

Effects of emotional experience on sleep depend on circadian phase

People who consider themselves sensitive to noise, experience more noise annoyance, sleep disturbance and reduced daytime performance. Besides psychological factors, an association with cardiovascular reactions during noise has been established in noise sensitives. Decreased efficiency of the parasympathetic nervous system in the regulation of heart rate has been hypothesized. In this study the effect of background noise (65 dB(A)) on cortical arousal levels and heart rate variability was studied in a group of high and low Noise Sensitivity (NS). Subjects (N=30) were selected based on their score on the NSS. EEG and ECG were recorded during task performance with and without background noise. The results showed a non-significant trend: high NS subjects seemed to have slightly higher baseline arousal levels. When controlling for baseline arousal levels high NS subjects showed more high arousal activity during noise condition than during silence. This was not the case for low NS subjects, who remained at intermediate levels during both conditions. Mean heartbeat variation was significantly higher within the high NS group compared to the low NS group. Even moderate background noise levels resulted in different physiological responses between groups. When exploring the association between NS and personality traits, neuroticism appeared to be a predictor for NS. High correlations were found with introversion and overall sensitivity to (non-acoustical) stimuli. This led us to conclude that NS might not be a single construct, but part of a more generic sensitivity to environmental stimuli as has been suggested previously.