Search

Sleep and memory studies often focus on overnight rather than long‐term memory changes, traditionally associating overnight memory change (OMC) with sleep architecture and sleep patterns such as spindles. In addition, (para‐)sympathetic innervation has been associated with OMC after a daytime nap using heart rate variability (HRV). In this study we investigated overnight and long‐term performance changes for procedural memory and evaluated associations with sleep architecture, spindle activity (SpA) and HRV measures (R‐R interval [RRI], standard deviation of R‐R intervals [SDNN], as well as spectral power for low [LF] and high frequencies [HF]). All participants (N = 20, Mage = 23.40 ± 2.78 years) were trained on a mirror‐tracing task and completed a control (normal vision) and learning (mirrored vision) condition. Performance was evaluated after training (R1), after a full‐night sleep (R2) and 7 days thereafter (R3). Overnight changes (R2‐R1) indicated significantly higher accuracy after sleep, whereas a significant long‐term (R3‐R2) improvement was only observed for tracing speed. Sleep architecture measures were not associated with OMC after correcting for multiple comparisons. However, individual SpA change from the control to the learning night indicated that only "SpA enhancers" exhibited overnight improvements for accuracy and long‐term improvements for speed. HRV analyses revealed that lower SDNN and LF power was associated with better OMC for the procedural speed measure. Altogether, this study indicates that overnight improvement for procedural memory is specific for spindle enhancers, and is associated with HRV during sleep following procedural learning. [ABSTRACT FROM AUTHOR]

Background: Seltorexant is a potent and selective antagonist of the orexin-2 receptor that is being developed for the treatment of insomnia and major depressive disorder.Aims: The primary objective was to investigate the effect of seltorexant on sleep efficiency after single and multiple dose administration in subjects with insomnia disorder without psychiatric comorbidity. Secondary objectives included evaluation of total sleep time, latency to persistent sleep, and wake after sleep onset. Subjects received 40 mg of seltorexant for five days during Period 1 and placebo during Period 2 or vice versa in this randomized, two-way crossover study. Objective sleep parameters were evaluated by polysomnography over 8 h on Day 1/2 (single dose) and on Day 5/6 (multiple doses). Subjective sleep parameters were assessed by questionnaires.Results: Twenty-seven subjects completed the study. The mean changes in sleep efficiency (% (SD)) of seltorexant from placebo at Day 1/2 were 5.8 (9.2), and 7.9 (9.8) at Day 5/6 ( p < 0.001 at both time points); in total sleep time (min (SD)) 27.7 (44.3) and 37.9 (47.1), respectively; in latency to persistent sleep (min (SD)) -18.8 (21.3) and -29.9 (27.7), respectively; and in wake after sleep onset (min (SD)) -11.1 (36.4) and -11.3 (46.5). The most common adverse events were headache and somnolence.Conclusions: Sleep efficiency was increased with seltorexant treatment compared with placebo. Treatment with seltorexant resulted in a prolonged total sleep time, shorter latency to persistent sleep and wake after sleep onset. There were no unexpected safety findings. [ABSTRACT FROM AUTHOR]

Background: In 2007, the AASM Manual for the Scoring of Sleep and Associated Events was published by the American Academy of Sleep Medicine (AASM). Concerning the visual classification of sleep stages, these new rules are intended to replace the rules by Rechtschaffen and Kales (R&K). Methods: We adapted the automatic R&K sleep scoring system Somnolyzer 24 × 7 to comply with the AASM rules and subsequently performed a validation study based on 72 polysomnographies from the Siesta database (56 healthy subjects, 16 patients, 38 females, 34 males, aged 21-86 years). Scorings according to the AASM rules were performed manually by experienced sleep scorers and semi-automatically by the AASM version of the Somnolyzer. Manual scorings and Somnolyzer reviews were performed independently by at least 2 out of 8 experts from 4 sleep centers. Results: In the quality control process, sleep experts corrected 4.8 and 3.7% of the automatically assigned epochs, resulting in a reliability between 2 Somnolyzer-assisted scorings of 99% (Cohen's kappa: 0.99). In contrast, the reliability between the 2 manual scorings was 82% (kappa: 0.76). The agreement between the 2 Somnolyzer-assisted and the 2 visual scorings was between 81% (kappa: 0.75) and 82% (kappa: 0.76). Conclusion: The AASM version of the Somnolyzer revealed an agreement between semi-automated and human expert scoring comparable to that published for the R&K version with a validity comparable to that of human experts, but with a reliability close to 1, thereby reducing interrater variability as well as scoring time to a minimum. Copyright © 2010 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Objectives: Sleep bruxism (SB) is a parasomnia defined as a stereotyped movement disorder characterized by grinding or clenching of the teeth during sleep. Pathophysiologically, SB is the result of biological and psychosocial influences. Treatment comprises behavioral, orthodontic and pharmacological interventions. While benzodiazepines and muscle relaxants have been reported by clinicians to reduce bruxism-related motor activity, placebo-controlled studies are lacking. Thus, the aim of the present study was to investigate the acute effects of clonazepam (Rivotril®) as compared with placebo, utilizing polysomnography and psychometry. Method: Ten drug-free outpatients (6 females, 4 males), aged 46.5 ± 13.1 years, suffering from SB (ICD-10: F45.8; ICSD: 306.8) and having been treated by bite splints were included in the trial. Comorbidity was high: 7 patients presented nonorganic insomnia related to adjustment or anxiety disorders (5 patients) or depression (2 patients); all patients had a concomitant movement disorder (6 restless legs syndrome, 4 periodic leg movement disorder). After one adaptation night, patients received placebo and 1 mg clonazepam 1/2 hour before lights out in a single-blind, nonrandomized study design. Objective sleep quality was determined by polysomnography, subjective sleep and awakening quality by rating scales, objective awakening quality by psychometric tests. Clinical evaluation was based on the Pittsburgh Sleep Quality Index (PSQI), the Zung Depression (SDS) and Anxiety (SAS) Scales, the Quality of Life Index, the Epworth Sleepiness Scale and the International Restless Legs Syndrome Study Group (IRLSSG) Scale. Results: On admission, SB patients exhibited deteriorated PSQI, SAS, SDS and IRLSSG measures. As compared with placebo, 1 mg clonazepam significantly improved the mean bruxism index from 9.3 to 6.3/h of sleep. Furthermore, it significantly improved the total sleep period, total sleep time, sleep efficiency, sleep latency and time awake during the total sleep period, and increased stage 2 sleep and movement time. Periodic leg movements decreased significantly, while the apnea index and apnea-hypopnea index increased marginally, but remained within normal limits. Subjective sleep quality improved as well, while in mood, performance and psychophysiology no changes were observed. Conclusion: Acute clonazepam therapy significantly improved not only the bruxism index but also objective and subjective sleep quality, with unchanged mood, performance and psychophysiological measures upon awakening, suggesting good tolerability of the drug. Copyright © 2005 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 × 7™) consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report™). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20–95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen’s kappa: 0.72) between the Somnolyzer 24 × 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen’s kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 × 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen’s kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 × 7 and demonstrated its applicability in clinical routine and sleep studies. Copyright © 2005 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Utilizing polysomnography (PSG) and psychometry, objective and subjective sleep and awakening quality was investigated in 11 patients (mean age 50 ± 14) with nonorganic insomnia (F 51.0) related to dysthymia (F 34.1) as compared with 11 age- and sex-matched normal controls. Patients demonstrated decreased sleep efficiency and sleep stage S2 as well as increased sleep latency to S1, S2 and S3, wakefulness within the total sleep period, number of awakenings, S1 and REM sleep. There was no intergroup difference in REM latency. Subjective sleep quality and the total score of the Self-Assessment Scale for Sleep and Awakening Quality (SSA) were deteriorated as were evening and morning well-being, mood, affectivity and drowsiness. Noopsychic measures showed deteriorated numerical memory, fine motor activity and reaction time variability. In a placebo-controlled crossover design study, the acute effects of 100 mg trazodone[sup 1] , a serotonin reuptake inhibitor with a sedative action due to 5HT[sub 2] and α[sub 1] receptor blockade, were investigated in the patients. As compared with placebo, trazodone induced an increase in slow-wave sleep (S3 + 4), a lengthening of REM latency, a decrease in REM sleep and a normalization of the periodic leg movement (PLM) index. In the morning, there was a minimal increase in somatic complaints and a decrease in critical flicker frequency and systolic blood pressure. In conclusion, our study demonstrated that dysthymia induced significant changes in objective and subjective sleep and awakening quality, which were counteracted by 100 mg trazodone, thus suggesting a key-lock principle in the treatment of nonorganic insomnia related to dysthymia with this drug.Copyright © 2001 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Abstract: We reported earlier that overnight change in explicit memory is positively related to the change in sleep spindle activity (between a control and a learning night). However, it remained unclear whether this effect was restricted to good memory performers and whether a general association of sleep spindles and a “sleep-related learning trait” may not account for this effect. Here we now present a secondary and more detailed analysis of our randomized multicenter study. Subjects were studied over a 4-week study period (including actigraphy and daily sleep diaries), including three overnight stays in the sleep laboratory. In the course of the study, subjects completed test-batteries of memory (Wechsler-Memory-Scale-revised; WMS) and other cognitive abilities (Raven''s Advanced-Progressive-Matrices; APM) and were asked to study 160 word pairs in the evening before being tested by cued-recall. Afterwards, subjects went to bed in the laboratory with full polysomnographic montages. Additionally, subjects participated on another occasion in a non-learning control (perceptual priming) task that was counterbalanced either before or after the learning condition. Slow as well as fast spindle activities were analyzed at frontopolar and central topographies. Although it was found that spindle activity is generally (in learning as well as control nights) elevated in highly gifted subjects, spindle analyses revealed that spindle increase (control to learning night) is specifically related to explicit memory improvement overnight, independent of individual learning traits. Together these findings suggest that the spindle increase after learning is related to elaborate encoding before sleep, whereas an individual''s general learning ability is well reflected in interindividual (and trait-like) differences of absolute sleep spindle activity. [Copyright &y& Elsevier]

Study Objective: To investigate differences between visual sleep scoring according to the classification developed by Rechtschaffen and Kales (R&K, 1968) and scoring based on the new guidelines of the American Academy of Sleep Medicine (AASM, 2007)., Design: All-night polysomnographic recordings were scored visually according to the R&K and AASM rules by experienced sleep scorers. Descriptive data analysis was used to compare the resulting sleep parameters., Participants: Healthy subjects and patients (38 females and 34 males) aged between 21 and 86 years., Interventions: N/A., Measurement and Results: While sleep latency and REM latency, total sleep time, and sleep efficiency were not affected by the classification standard, the time (in minutes and in percent of total sleep time) spent in sleep stage 1 (S1/N1), stage 2 (S2/N2) and slow wave sleep (S3+S4/N3) differed significantly between the R&K and the AASM classification. While light and deep sleep increased (S1 vs. N1 [+10.6 min, (+2.8%)]: P<0.01; S3+S4 vs. N3 [+9.1 min (+2.4%)]: P<0.01), stage 2 sleep decreased significantly according to AASM rules (S2 vs. N2 [-20.5 min, (-4.9%)]: P<0.01). Moreover, wake after sleep onset was significantly prolonged by approximately 4 minutes (P<0.01) according to the AASM standard. Interestingly, the effects on stage REM were age-dependent (intercept at 20 years: -7.5 min; slope: 1.6 min for 10-year age increase). No effects of sex and diagnosis were observed., Conclusion: The study shows significant and age-dependent differences between sleep parameters derived from conventional visual sleep scorings on the basis of R&K rules and those based on the new AASM rules. Thus, new normative data have to be established for the AASM standard.

Conventionally, polysomnographic recordings are classified according to the rules published in 1968 by Rechtschaffen and Kales (R&K). The present paper describes an automatic classification system embedded in an e-health solution that has been developed and validated in a large database of healthy controls and sleep disturbed patients. The Somnolyzer 24x7 adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, slow and rapid eye movements), a feature matrix plausibility check, a classifier designed as an expert system and a rule-based smoothing procedure for the start and the end of stages REM and 2. The validation based on 286 recordings in both normal healthy subjects aged 20 to 95 years and patients suffering from organic or nonorganic sleep disorders demonstrated an overall epoch-by-epoch agreement of 80% (Cohen's Kappa: 0.72) between the Somnolyzer 24x7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's Kappa: 0.68) between two human experts. Two Somnolyzer 24x7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's Kappa: 0.991). Moreover, correlation analysis in R&K derived target variables revealed similar -- in 36 out of 38 variables even higher -- relationships between Somnolyzer 24x7 and expert evaluations as compared to the concordance between two human experts. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24x7 both, on the epoch-by-epoch and on the target variable level. These results demonstrate the applicability of the Somnolyzer 24x7 evaluation in clinical routine and sleep studies.

To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 x 7) consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20-95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen's kappa: 0.72) between the Somnolyzer 24 x 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 x 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 x 7 and demonstrated its applicability in clinical routine and sleep studies.

Study Objectives: Functional significance of stage 2 sleep spindle activity for declarative memory consolidation., Design: Randomized, within-subject, multicenter., Setting: Weekly sleep laboratory visits, actigraphy, and sleep diary (4 weeks)., Participants: Twenty-four healthy subjects (12 men) aged between 20 and 30 years., Interventions: Declarative memory task or nonlearning control task before sleep., Measurement and Results: This study measured spindle activity during stage 2 sleep following a (declarative) word-pair association task as compared to a control task. Participants performed a cued recall in the evening after learning (160 word pairs) as well as in the subsequent morning after 8 hours of undisturbed sleep with full polysomnography. Overnight change in the number of recalled words, but not absolute memory performance, correlated significantly with increased spindle activity during the experimental night (r24 = .63, P < .01). Time spent in each sleep stage could not account for this relationship., Conclusion: A growing body of evidence supports the active role of sleep for information reprocessing. Whereas past research focused mainly on the distinct rapid eye movement and slow-wave sleep, these results indicate that increased sleep stage 2 spindle activity is related to an increase in recall performance and, thus, may reflect memory consolidation.