891 resultados para night sleep


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ABSTRACT Maria Peltola Electrical status epilepticus during sleep – Continuous spikes and waves during sleep Department of Clinical Neurophysiology, University of Turku Department of Clinical Neurophysiology and Department of Pediatric Neurology, Children’s Hospital, Helsinki University Central Hospital Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Finland, 2014 Background: Electrical status epilepticus during sleep (ESES) is an EEG phenomenon of frequent spikes and waves occurring in slow sleep. ESES relates to cognitive deterioration in heterogeneous childhood epilepsies. Validated methods to quantitate ESES are missing. The clinical syndrome, called epileptic encephalopathy with continuous spikes and waves during sleep (CSWS) is pharmacoresistant in half of the patients. Limited data exists on surgical treatment of CSWS. Aims and methods: The effects of surgical treatment were studied by investigating electroclinical outcomes in 13 operated patients (nine callosotomies, four resections) with pharmacoresistant CSWS and cognitive decline. Secondly, an objective paradigm was searched for assessing ESES by the semiautomatic quantification of spike index (SI) and measuring spike strength from EEG. Results: Postoperatively, cognitive deterioration was stopped in 12 (92%) patients. Three out of four patients became seizure-free after resective surgery. Callosotomy resulted in greater than 90% reduction of atypical absences in six out of eight patients. The preoperative propagation of ESES from one hemisphere to the other was associated with a good response. Semiautomatic quantification of SI was a robust method when the maximal interspike interval of three seconds was used to determine the “continuous” discharge in ten EEGs. SI of the first hour of sleep appeared representative of the whole night SI. Furthermore, the spikes’ root mean square was found to be a stable measure of spike strength when spatially integrated over multiple electrodes during steady NREM sleep. Conclusions: Patients with pharmacoresistant CSWS, based on structural etiology, may benefit from resective surgery or corpus callosotomy regarding both seizure outcome and cognitive prognosis. The semiautomated SI quantification, with proper userdefined settings and the new spatially integrated measure of spike strength, are robust and promising tools for quantifying ESES. Keywords: Electrical status epilepticus during sleep, ESES, continuous spikes and waves during sleep, CSWS, epilepsy surgery, spike index, spike strength, RMS TIIVISTELMÄ Maria Peltola Unenaikainen sähköinen status epilepticus Kliininen neurofysiologia, Turun yliopisto Kliininen neurofysiologia ja lastenneurologia, Lasten ja nuorten sairaala, Helsingin yliopistollinen keskussairaala Annales Universitatis Turkuensis, Medica-Odontologica, Turku, Suomi, 2014 Tausta: Sähköinen status epilepticus unessa (ESES) on aivosähkökäyrä (EEG)-ilmiö, jossa hidasaaltounen aikana esiintyy tiheä piikkihidasaaltopurkaus. ESES:n kvantifioimiseen ei ole olemassa validoituja menetelmiä. ESES on liitetty kognitiivisen tason laskuun ja tällöin puhutaan CSWS (continuous spikes and waves during sleep) - oireyhtymästä. CSWS ei vastaa lääkehoitoon puolella potilaista ja sen epilepsiakirurgisesta hoidosta on olemassa vain vähän tietoa. Tavoitteet ja menetelmät: Selvitimme retrospektiivisesti epilepsiakirurgian vaikusta elektrokliinisiin löydöksiin 13:lla lääkeresistenttiä CSWS-oireyhtymää sairastavalla lapsella, joilla oli rakenteellinen aivojen poikkeavuus. Toinen tavoite oli löytää objektiivinen puoliautomaattinen tapa mitata purkauksen määrää ja piikkien voimakkuutta EEG:stä. Tulokset: Kognitiivisen tason jatkuva heikentyminen loppui 12 (92 %) potilaalla leikkauksen jälkeen. Kolme neljästä resektiopotilaasta tuli kohtauksettomaksi. Kallosotomian jälkeen kuudella kahdeksasta potilaasta päivittäiset kohtaukset vähenivät yli 90 %:lla. Purkauksen leviäminen leikkausta edeltävästi vain yhdestä hemisfääristä toiseen liittyi hyvään leikkaushoitovasteeseen. Piikki-indeksi, jossa käytetään jatkuvan purkauksen määritelmänä maksimissaan kolmea sekuntia piikkien välillä, osoittautui luotettavaksi menetelmäksi ESES:n kvantifioimiseen. Useammasta elektrodista integroitu piikkien neliöllinen keskiarvo oli piikin voimakkuuden vakaa mitta häiriintymättömässä NREM-unessa. Päätelmät: Lääkehoidolle vastaamatonta CSWS:ää sairastavat potilaat, joilla on rakenteellinen aivopoikkeavuus ja yhdensuuntainen purkauksen leviämismalli, näyttävät kohtausten vähenemisen lisäksi hyötyvän epilepsiakirurgiasta kognitiivisesti. Puoliautomaattinen piikki-indeksin kvantifiointi sopivilla käyttäjäasetuksilla ja uusi spatiaalisesti integroitu piikin voimakkuuden mittari ovat stabiileja ja lupaavia ESES:n kvantitatiivisia mittareita. Avainsanat: Unenaikainen sähköinen status epilepticus, ESES, CSWS, epilepsiakirurgia, piikki-indeksi, piikin voimakkuus, neliöllinen keskiarvo

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We sought to examine the possible participation of dopaminergic receptors in the phasic events that occur during rapid eye movement (REM) sleep, known as sawtooth waves (STW). These phasic phenomena of REM sleep exhibit a unique morphology and, although they represent a characteristic feature of REM sleep, little is known about the mechanisms which generate them and which are apparently different from rapid eye movements. STW behavior was studied in 10 male volunteers aged 20 to 35 years, who were submitted to polysomnographic monitoring (PSG). On the adaptation night they were submitted to the first PSG and on the second night, to the basal PSG. On the third night the volunteers received placebo or haloperidol and spent the whole night awake. On the fourth night they were submitted to the third PSG. After a 15-day rest period, the volunteers returned to the sleep laboratory and, according to a double-blind crossover randomized design, received haloperidol or placebo and spent the whole night awake, after which they were submitted to the fourth PSG. The volunteers who were given haloperidol combined with sleep deprivation exhibited an elevation of the duration and density of the STW, without significant alterations of the other REM sleep phasic phenomena such as rapid eye movement. These findings suggest that sawtooth waves must have their own generating mechanisms and that the dopaminergic receptors must exert a modulating role since REM sleep deprivation, as well as administration of neuroleptics, produces supersensitivity of dopaminergic receptors.

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The effects of haloperidol and olanzapine on polysomnographic measures made in bipolar patients during manic episodes were compared. Twelve DSM-IV mania patients were randomly assigned to receive either haloperidol (mean ± SD final dosage: 5.8 ± 3.8 mg) or olanzapine (mean ± SD final dosage: 13.6 ± 6.9 mg) in a 6-week, double-blind, randomized, controlled clinical trial. One-night polysomnographic evaluation was performed before and after the haloperidol or olanzapine treatment. Psychopathology and illness severity were rated respectively with the Young Mania Rating Scale (YMRS) and the Clinical Global Impressions - Bipolar version (CGI-BP). There was a significant improvement in the YMRS and CGI-BP scores at the end of the study for both groups. Mixed ANOVA used to compare the polysomnographic measures of both drugs demonstrated significant improvement in sleep measures with olanzapine. In the olanzapine group, statistically significant time-drug interaction effects on sleep continuity measures were observed: sleep efficiency (mean ± SEM pre-treatment value: 6.7 ± 20.3%; after-treatment: 85.7 ± 10.9%), total wake time (pre-treatment: 140.0 ± 92.5 min; after-treatment: 55.2 ± 44.2 min), and wake time after sleep onset (pre-treatment: 109.7 ± 70.8 min; after-treatment: 32.2 ± 20.7 min). Conversely, improvement of polysomnographic measures was not observed for the haloperidol group (P > 0.05). These results suggest that olanzapine is more effective than haloperidol in terms of sleep-promoting effects, although olanzapine is comparatively as effective as haloperidol in treating mania. Polysomnography records should provide useful information on how manic states can be affected by psychopharmacological agents.

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Sleep loss is both common and critically relevant to our society and might lead to the abuse of psychostimulants such as amphetamines, cocaine and modafinil. Since psychoactive substance abuse often occurs within a scenario of sleep deficit, the purpose of this investigation was to compare the sleep patterns of rats challenged with cocaine (7 mg/kg, ip), methamphetamine (7 mg/kg, ip), or modafinil (100 mg/kg, ip) subsequent to paradoxical sleep deprivation (PSD) for 96 h. Our results show that, immediately after 96 h of PSD, rats (10 per group) that were injected with a psychostimulant presented lower percentages of paradoxical sleep compared to those injected with saline (P < 0.01). Regarding slow wave sleep (SWS), rats injected with psychostimulants after PSD presented a late rebound (on the second night subsequent to the injection) in the percentage of this phase of sleep when compared to PSD rats injected with saline (P < 0.05). In addition, the current study has produced evidence of the characteristic effect of each drug on sleep architecture. Home cage control rats injected with modafinil and methamphetamine showed a reduction in SWS compared with the saline group. Methamphetamine affected sleep patterns most, since it significantly reduced paradoxical sleep, SWS and sleep efficiency before and after PSD compared to control (P < 0.05). Cocaine was the psychostimulant causing the least changes in sleep pattern in relation to those observed after saline injection. Therefore, our results suggest that abuse of these psychostimulants in a PSD paradigm aggravates their impact on sleep patterns.

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Gastroesophageal reflux (GER) is common in asthma patients and can contribute to sleep disruption. The aim of the present study was to determine the time-related distribution of GER events together with their impact on sleep in asthmatic subjects with GER disease symptoms. The inclusion criteria were: 18-65 years, controlled moderate to severe asthma and GER-compatible clinical evidence. The exclusion criteria were: chronic obstructive lung disease, smoking, infections of the upper airways, use of oral corticosteroids, other co-morbidities, pregnancy, sleep-related disorders, night-time shift work, and the use of substances with impact on sleep. Asthmatic patients with nocturnal symptoms were excluded. All-night polysomnography and esophageal pH monitoring were recorded simultaneously. Of the 147 subjects selected, 31 patients and 31 controls were included. Seventeen patients were classified as DeMeester positive and 14 as DeMeester negative. Both groups displayed similar outcomes when general variables were considered. Sleep stage modification one minute prior to GER was observed in the DeMeester-positive group. Awakening was the most frequent occurrence at GER onset and during the 1-min period preceding 38% of the nocturnal GER. Sleep stage 2 was also prevalent and preceded 36% of GER events. In the DeMeester-negative group, awakening was the most frequent response before and during GER. Modifications in sleep stages, arousals or awakenings were associated with 75% of the total GER events analyzed during the period of one minute before and after the fall of esophageal pH below 4 in the DeMeester-positive group. These data provide evidence that sleep modifications precede the GER events in asthmatic patients.

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The objective of the present study was to evaluate the expression of a cyclic alternating pattern (CAP) in slow wave sleep (SWS) in children with the well-defined chronic syndrome juvenile idiopathic arthritis (JIA). Twelve patients (9-17 years of age), 7 girls, with JIA were compared to matched controls by age, pubertal stage and gender. After one night of habituation in the sleep laboratory, sleep measurements were obtained by standard polysomnography with conventional sleep scoring and additional CAP analyses. The sleep parameters of the JIA and control groups were similar for sleep efficiency (91.1 ± 6.7 vs 95.8 ± 4.0), sleep stage in minutes: stage 1 (16.8 ± 8.5 vs 17.8 ± 4.0), stage 2 (251.9 ± 41 vs 262.8 ± 38.1), stage 3 (17.0 ± 6.0 vs 15.1 ± 5.7), stage 4 (61.0 ± 21.7 vs 77.1 ± 20.4), and rapid eye movement sleep (82.0 ± 27.6 vs 99.0 ± 23.9), respectively. JIA patients presented nocturnal disrupted sleep, with an increase in short awakenings, but CAP analyses showed that sleep disruption was present even during SWS, showing an increase in the overall CAP rate (P < 0.01). Overall CAP rate during non-rapid eye movement sleep was significantly higher in pediatric patients who were in chronic pain. This is the first study of CAP in pediatric patients with chronic arthritis showing that CAP analyses can be a powerful tool for the investigation of disturbance of SWS in children, based on sleep EEG visual analysis.

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Cardiovascular diseases (CVDs) are known to be associated with poor sleep quality in general populations, but they have not been consistently associated with specific work schedules. Studies of CVD generally do not simultaneously consider sleep and work schedules, but that approach could help to disentangle their effects. We investigated the association between insomnia and a self-reported physician diagnosis of CVD in day and night workers, considering all sleep episodes during nocturnal and diurnal sleep. A cross-sectional study was conducted in 1307 female nursing professionals from 3 public hospitals, using baseline data from the “Health and Work in Nursing - a Cohort Study.” Participants were divided into two groups: i) day workers with no previous experience in night shifts (n=281) and whose data on insomnia were related to nocturnal sleep and ii) those who worked exclusively at night (n=340) and had data on both nocturnal and diurnal sleep episodes, as they often sleep at daytime. Multiple logistic regression analysis was performed. Among day workers, insomnia complaints increased the odds of CVD 2.79-fold (95% CI=1.01-6.71) compared with workers who had no complaints. Among night workers, reports of insomnia during both nocturnal and diurnal sleep increased the odds of reported CVD 3.07-fold (95% CI=1.30-7.24). Workers with insomnia had similar probabilities of reporting CVD regardless of their work schedule, suggesting a relationship to insomnia and not to night work per se. The results also highlighted the importance of including evaluation of all sleep episodes (diurnal plus nocturnal sleep) for night workers.

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The present thesis study is a systematic investigation of information processing at sleep onset, using auditory event-related potentials (ERPs) as a test of the neurocognitive model of insomnia. Insomnia is an extremely prevalent disorder in society resulting in problems with daytime functioning (e.g., memory, concentration, job performance, mood, job and driving safety). Various models have been put forth in an effort to better understand the etiology and pathophysiology of this disorder. One of the newer models, the neurocognitive model of insomnia, suggests that chronic insomnia occurs through conditioned central nervous system arousal. This arousal is reflected through increased information processing which may interfere with sleep initiation or maintenance. The present thesis employed event-related potentials as a direct method to test information processing during the sleep-onset period. Thirteen poor sleepers with sleep-onset insomnia and 1 2 good sleepers participated in the present study. All poor sleepers met the diagnostic criteria for psychophysiological insomnia and had a complaint of problems with sleep initiation. All good sleepers reported no trouble sleeping and no excessive daytime sleepiness. Good and poor sleepers spent two nights at the Brock University Sleep Research Laboratory. The first night was used to screen for sleep disorders; the second night was used to investigate information processing during the sleep-onset period. Both groups underwent a repeated sleep-onsets task during which an auditory oddball paradigm was delivered. Participants signalled detection of a higher pitch target tone with a button press as they fell asleep. In addition, waking alert ERPs were recorded 1 hour before and after sleep on both Nights 1 and 2.As predicted by the neurocognitive model of insomnia, increased CNS activity was found in the poor sleepers; this was reflected by their smaller amplitude P2 component seen during wake of the sleep-onset period. Unlike the P2 component, the Nl, N350, and P300 did not vary between the groups. The smaller P2 seen in our poor sleepers indicates that they have a deficit in the sleep initiation processes. Specifically, poor sleepers do not disengage their attention from the outside environment to the same extent as good sleepers during the sleep-onset period. The lack of findings for the N350 suggest that this sleep component may be intact in those with insomnia and that it is the waking components (i.e., Nl, P2) that may be leading to the deficit in sleep initiation. Further, it may be that the mechanism responsible for the disruption of sleep initiation in the poor sleepers is most reflected by the P2 component. Future research investigating ERPs in insomnia should focus on the identification of the components most sensitive to sleep disruption. As well, methods should be developed in order to more clearly identify the various types of insomnia populations in research contexts (e.g., psychophysiological vs. sleep-state misperception) and the various individual (personality characteristics, motivation) and environmental factors (arousal-related variables) that influence particular ERP components. Insomnia has serious consequences for health, safety, and daytime functioning, thus research efforts should continue in order to help alleviate this highly prevalent condition.

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The EEG of the sleep onset period of psychophysiological insomniacs, psychiatric insomniacs and controls was compared using power spectral analysis (FFT). Eighteen drug-free subjects were equally divided into three groups according to their responses in the Brock Sleep and Insomnia Questionnaire, the Minnesota Multiphasic Personality Inventory and the Sleep Disorders Questionnaire. Group 1 consisted of psychophysiological insomniacs, group 2 included insomniacs with an indication of psychiatric disturbances, and group 3 was a control group. EEG, EOG and EMG were recorded for two consecutive nights. Power spectral analysis (FFT) of EEG at C4 from the sleep onset period (defined as lights out to the first five minutes of stage 2) was performed on all standard frequency bands, delta: .5-4 Hz; theta: 4-8 Hz; alpha: 8-12 Hz; sigma: 12-15 Hz beta: 15-25 Hz. Psychophysiological insomniacs had less alpha during wakefulness than the other two groups and did not show the dramatic drop in alpha across the sleep onset period, which characterizes normal sleep. They also had less delta, especially during stage 2 on night 2. They also showed less delta in the last quartile of the chronological analysis of the sleep onset period. Psychiatric insomniacs showed lower relative beta power values overall while psychophysiological insomniacs showed higher relative beta power values during wakefulness. This microanalysis 11 confirms that the sleep onset period is generally similar for psychiatric insomniacs and normal sleepers. This may be due to the sample of psychiatric insomniacs being heterogeneous or may reflect a sleep onset system that is essentially intact. Psychophysiological insomniacs have higher cortical arousal during the sleep onset period than do the psychiatric insomniacs and the controls. Clear differences in the sleep onset period of psychophysiological insomniacs exist. The dramatic changes in power values in these two groups are not seen in the psychophysiological insomniacs, which may make the discrimination between wakefulness and sleep more difficult.

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The main purpose ofthis study was to examine the effect ofintention on the sleep onset process from an electrophysiological point ofview. To test this, two nap conditions, the Multiple Sleep Latency Test (MSLT) and the Repeated Test of Sustained Wakefulness (RTSW) were used to compare intentional and inadvertent sleep onset. Sixteen female participants (aged 19-25) spent two non-consecutive nights in the sleep lab; however, due to physical and technical difficulties only 8 participants produced compete sets of data for analysis. Each night participants were given six nap opportunities. For three ofthese naps they were instructed to fall asleep (MSLT), for the remaining three naps they were to attempt to remain awake (RTSW). These two types of nap opportunities represented the conditions ofintentional (MSLT) and inadvertent (RTSW) sleep onset. Several other sleepiness, performance, arousal and questionnaire measures were obtained to evaluate and/or control for demand characteristics, subjective effort and mental activity during the nap tests. The nap opportunities were scored using a new 9 stage scoring system developed by Hori et al. (1994). Power spectral analyses (FFT) were also performed on the sleep onset data provided by the two nap conditions. Longer sleep onset latencies (approximately 1.25 minutes) were obseIVed in the RTSW than the MSLT. A higher incidence of structured mental activity was reported in the RTSW and may have been reflected in higher Beta power during the RTSW. The decent into sleep was more ragged in the RTSW as evidenced by an increased number shifts towards higher arousal as measured using the Hori 9 stage sleep scoring method. 1ll The sleep onset process also appears to be altered by the intention to remain awake, at least until the point ofinitial Stage 2 sleep (i.e. the first appearance of spindle activity). When only examining the final 4.3 minutes ofthe sleep onset process (ending with spindle activity), there were significant interactions between the type ofnap and the time until sleep onset for Theta, Alpha and Beta power. That is to say, the pattern of spectral power measurements in these bands differed across time as a function ofthe type ofnap. The effect ofintention however, was quite small (,,2 < .04) when compared to the variance which could be accounted for by the passage oftime (,,2 == .10 to .59). These data indicate that intention alone cannot greatly extend voluntary wakefulness if a person is sleepy. This has serious implications for people who may be required to perform dangerous tasks while sleepy, particularly for people who are in a situation that does not allow them the opportunity to engage in behavioural strategies in order to maintain their arousal.

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Sleep spindles have been found to increase following an intense period of learning on a combination of motor tasks. It is not clear whether these changes are task specific, or a result of learning in general. The current study investigated changes in sleep spindles and spectral power following learning on cognitive procedural (C-PM), simple procedural (S-PM) or declarative (DM) learning tasks. It was hypothesized that S-PM learning would result in increases in Sigma power during Non-REM sleep, whereas C-PM and DM learning would not affect Sigma power. It was also hypothesized that DM learning would increase Theta power during REM sleep, whereas S-PM and C-PM learning would not affect Theta power. Thirty-six participants spent three consecutive nights in the sleep laboratory. Baseline polysomnographic recordings were collected on night 2. Participants were randomly assigned to one of four conditions: C-PM, S-PM, DM or control (C). Memory task training occurred on night 3 followed by polysomnographic recording. Re-testing on respective memory tasks occurred one-week following training. EEG was sampled at 256Hz from 16 sites during sleep. Artifact-free EEG from each sleep stage was submitted to power spectral analysis. The C-PM group made significantly fewer errors, the DM group recalled more, and the S-PM improved on performance from test to re-test. There was a significant night by group interaction for the duration of Stage 2 sleep. Independent t-tests revealed that the S-PM group had significantly more Stage 2 sleep on the test night than the C group. The C-PM and the DM group did not differ from controls in the duration of Stage 2 sleep on test night. There was no significant change in the duration of slow wave sleep (SWS) or REM sleep. Sleep spindle density (spindles/minute) increased significantly from baseline to test night following S-PM learning, but not for C-PM, DM or C groups. This is the first study to have shown that the same pattern of results was found for spindles in SWS. Low Sigma power (12-14Hz) increased significantly during SWS following S-PM learning but not for C-PM, DM or C groups. This effect was maximal at Cz, and the largest increase in Sigma power was at Oz. It was also found that Theta power increased significantly during REM sleep following DM learning, but not for S-PM, C-PM or C groups. This effect was maximal at Cz and the largest change in Theta power was observed at Cz. These findings are consistent with the previous research that simple procedural learning is consolidated during Stage 2 sleep, and provide additional data to suggest that sleep spindles across all non-REM stages and not just Stage 2 sleep may be a mechanism for brain plasticity. This study also provides the first evidence to suggest that Theta activity during REM sleep is involved in memory consolidation.

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The present study has both theoretical and practical aspects. The theoretical intent of the study was to closely examine the relationship between muscle activity (EMG) and EEG state during the process of falling asleep. Sleep stages during sleep onset (SO) have been generally defined with regards to brain wave activity (Recht schaff en & Kales (1968); and more precisely by Hori, Hayashi, & Morikawa (1994)). However, no previous study has attempted to quantify the changes in muscle activity during this same process. The practical aspect of the study examined the reliability ofa commercially developed wrist-worn alerting device (NovAlert™) that utilizes changes in muscle activity/tension in order to alert its user in the event that he/she experiences reduced wakefulness that may result in dangerous consequences. Twelve female participants (aged 18-42) sp-ent three consecutive nights in the sleep lab ("Adaptation", "EMG", and "NOVA" nights). Each night participants were given 5, twenty-minute nap opportunities. On the EMG night, participants were allowed to fall asleep freely. On the NOV A night, participants wore the Nov Alert™ wrist device that administered a Psychomotor Vigilance Test (PVT) when it detected that muscle activity levels had dropped below baseline. Nap sessions were scored using Hori's 9-stage scoring system (Hori et aI, 1994). Power spectral analyses (FFT) were also performed. Effects ofthe PVT administration on EMG and EEG frequencies were also examined. Both chin and wrist EMG activity showed reliable and significant decline during the early stages ofHori staging (stages HO to H3 characterized by decreases in alpha activity). All frequency bands studied went through significant changes as the participants progressed through each ofHori's 9 SO stages. Delta, theta, and sigma activity increased later in the SO continuum while a clear alpha dominance shift was noted as alpha activity shifted from the posterior regions of the brain (during Hori stages HO to H3) to the anterior portions (during Hori stages H7 to H9). Administration of the PVT produced significant increases in EMG activity and was effective in reversing subjective drowsiness experienced during the later stages of sleep onset. Limitations of the alerting effects of the PVTs were evident following 60 to 75 minutes of use in that PVTs delivered afterwards were no longer able to significantly increase EMG levels. The present study provides a clearer picture of the changes in EMG and EEG during the sleep onset period while testing the efficacy of a commercially developed alerting device. EMG decreases were found to begin during Hori stage 0 when EEG was - dominated by alpha wave activity and were maximal as Hori stages 2 to 5 were traversed (coincident with alpha and beta activity). This signifies that EMG decrements and the loss of resting alpha activity are closely related. Since decreased alpha has long been associated with drowsiness and impending sleep, this investigation links drops in muscle tone with sleepiness more directly than in previous investigations. The EMG changes were reliably demonstrated across participants and the NovAlert™ detected the EMG decrements when Hori stage 3 was entered. The alerting vibrations produced by the NovAlert™ occurred early enough in the SO process to be of practical importance as a sleepiness monitoring and alerting device.

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Imaging studies have shown reduced frontal lobe resources following total sleep deprivation (TSD). The anterior cingulate cortex (ACC) in the frontal region plays a role in performance monitoring and cognitive control; both error detection and response inhibition are impaired following sleep loss. Event-related potentials (ERPs) are an electrophysiological tool used to index the brain's response to stimuli and information processing. In the Flanker task, the error-related negativity (ERN) and error positivity (Pe) ERPs are elicited after erroneous button presses. In a Go/NoGo task, NoGo-N2 and NoGo-P3 ERPs are elicited during high conflict stimulus processing. Research investigating the impact of sleep loss on ERPs during performance monitoring is equivocal, possibly due to task differences, sample size differences and varying degrees of sleep loss. Based on the effects of sleep loss on frontal function and prior research, it was expected that the sleep deprivation group would have lower accuracy, slower reaction time and impaired remediation on performance monitoring tasks, along with attenuated and delayed stimulus- and response-locked ERPs. In the current study, 49 young adults (24 male) were screened to be healthy good sleepers and then randomly assigned to a sleep deprived (n = 24) or rested control (n = 25) group. Participants slept in the laboratory on a baseline night, followed by a second night of sleep or wake. Flanker and Go/NoGo tasks were administered in a battery at 1O:30am (i.e., 27 hours awake for the sleep deprivation group) to measure performance monitoring. On the Flanker task, the sleep deprivation group was significantly slower than controls (p's <.05), but groups did not differ on accuracy. No group differences were observed in post-error slowing, but a trend was observed for less remedial accuracy in the sleep deprived group compared to controls (p = .09), suggesting impairment in the ability to take remedial action following TSD. Delayed P300s were observed in the sleep deprived group on congruent and incongruent Flanker trials combined (p = .001). On the Go/NoGo task, the hit rate (i.e., Go accuracy) was significantly lower in the sleep deprived group compared to controls (p <.001), but no differences were found on false alarm rates (i.e., NoGo Accuracy). For the sleep deprived group, the Go-P3 was significantly smaller (p = .045) and there was a trend for a smaller NoGo-N2 compared to controls (p = .08). The ERN amplitude was reduced in the TSD group compared to controls in both the Flanker and Go/NoGo tasks. Error rate was significantly correlated with the amplitude of response-locked ERNs in control (r = -.55, p=.005) and sleep deprived groups (r = -.46, p = .021); error rate was also correlated with Pe amplitude in controls (r = .46, p=.022) and a trend was found in the sleep deprived participants (r = .39, p =. 052). An exploratory analysis showed significantly larger Pe mean amplitudes (p = .025) in the sleep deprived group compared to controls for participants who made more than 40+ errors on the Flanker task. Altered stimulus processing as indexed by delayed P3 latency during the Flanker task and smaller amplitude Go-P3s during the Go/NoGo task indicate impairment in stimulus evaluation and / or context updating during frontal lobe tasks. ERN and NoGoN2 reductions in the sleep deprived group confirm impairments in the monitoring system. These data add to a body of evidence showing that the frontal brain region is particularly vulnerable to sleep loss. Understanding the neural basis of these deficits in performance monitoring abilities is particularly important for our increasingly sleep deprived society and for safety and productivity in situations like driving and sustained operations.

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While sleep has been shown to be involved in memory consolidation and the selective enhancement of newly acquired memories of future relevance (Wilhelm, et al., 2011), limited research has investigated the role of sleep or future relevance in processes of memory reconsolidation. The current research employed a list-method directed forgetting procedure in which participants learned two lists of syllable pairs on Night 1 and received directed forgetting instructions on Night 2. On Night 2, one group (Labile; n = 15) received a memory reactivation treatment consisting of reminders designed to return memories of the learned lists to a labile state. A second group (Stable, n = 16) received similar reminders designed to leave memories of the learned lists in their stable state. No differences in forgetting were found across the two lists or groups. However, a negative correlation between frontal delta (1 – 4 Hz) electroencephalographic (EEG) power during Early Stage 2 non-rapid eye movement (NREM) sleep and forgetting of to-beremembered material was found exclusively in the Labile group (r = -.61, p < .05). Further, central theta (4 – 8 Hz ) EEG power during rapid eye movement (REM) sleep was found to correlate with directed forgetting exclusively in the Labile group (r = .81, p < .001) and total forgetting in the Stable group (r = .50, p < .05). These observed relationships support the proposed hypothesis suggesting that sleep processes are involved in the reconsolidation of labile memories, and that this reconsolidation may be selective for memories of future relevance. A role for sleep in the beneficial reprocessing of memories through the selective reconsolidation of labile memories in NREM sleep and the weakening of memories in REM sleep is discussed.

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Objectifs : Le bruxisme survenant au cours du sommeil est un trouble du mouvement caractérisé par du grincement de dents et l’activité rythmique des muscles masticateurs (ARMM). Le bruxisme/ARMM est souvent associé à des mouvements du corps et des à éveils corticaux. Une séquence d’activation précède le ARMM/bruxisme. Ces événements incluent une augmentation des variables suivants : l’activité sympathique (-4 minutes), les activités encéphalographique (-4 second), le fréquence cardiaque, l’amplitude de la respiration (-1 second) et l’activité des muscle suprahyoïdiens (-0.8 second). La présente étude a examiné l’association entre le bruxisme et les changements de la pression artérielle. Méthodes: Dix sujets avec le bruxisme (5 hommes, 5 femmes, âge moyen = 26 ± 1,8) ont complétés 3 nuits de polysomnographie qui comprenait l'enregistrement non invasive de la pression artérielle. La première nuit a servi de dépistage et d’habituation au laboratoire. L'analyse a été réalisée sur les deuxièmes et troisièmes nuits enregistrements. Seuls les épisodes de bruxisme isolés survenant au cours du stade 2 du sommeil ont été utilisés pour l’analyse, pour un total de 65 épisodes. Les mesures des pressions systolique et diastolique ont été prises 20 battements avant et 23 battements après l'apparition de chaque épisode bruxisme lors du sommeil. Les épisodes de bruxisme ont été classés comme suit: 1) bruxisme avec éveil cortical; 2) bruxisme avec mouvement du corps (MC), 3) bruxisme avec éveil cortical et MC. Une quatrième catégorie, bruxisme seul, a également été analysée, mais utilisée comme donnée préliminaire puisque la catégorie se composait de seulement 4 épisodes de bruxisme. Résultats: Les deux pressions systolique et diastolique ont augmenté avec les épisodes de bruxisme. Cette augmentation a été statistiquement significative pour la pression systolique et diastolique pour les épisodes de bruxisme avec éveil cortical et/ou MC (p ≤ 0,05). L’augmentation moyenne de la pression (systolique / diastolique ± SE) a été : 28,4 ± 2,4/13,2 ± 1,5 mm Hg pour le bruxisme avec éveil cortical; 30,7 ± 1,6/19.4 ± 2.3 mm Hg pour bruxisme avec MC; 26.4 ± 2,8 / 14,6 ± 2.0mm Hg pour bruxisme avec éveil cortical et MC; 22,9 ± 5,2/12,4 ± 3,3mm Hg pour les épisodes de bruxisme seuls. Conclusion: Le bruxisme du sommeil est associé à des hausses de la pression artérielle pendant le sommeil. Cette hausse est supérieure dans les épisodes de bruxisme associés à un éveil cortical et / ou MC, qui sont souvent associés avec les événements bruxisme. Ces résultats sont en accord avec nos observations antérieures, où le bruxisme est précédé par une augmentation de l'activité sympathique et de la tachycardie sinusale.