Recent epidemiologic studies have found that sleep duration is associated with obesity, diabetes, hypertension and mortality. These studies have used self-reported habitual sleep duration, which has not been well validated. We model the extent to which self-reported habitual sleep reflects average objectively measured sleep. Eligible participants at the Chicago site of Coronary Artery Risk Development in Young Adults Study were invited to participate in a 2003-2004 ancillary sleep study; 82% (n=669) agreed. Sleep measurements collected in two waves included: 3-days of wrist actigraphy, a sleep log, and standard questions about usual sleep duration. Average measured sleep was 6 hours, and subjective reports averaged 0.80 hours longer than measured sleep. Subjective reports were not well calibrated, increasing on average by 31 minutes for each additional hour of measured sleep. Our model suggests that persons sleeping 5 and 7 hours over-reported, on average, by 1.3 and 0.3 hours respectively. Overall, there was a correlation of 0.45 between reported and measured sleep duration. The extent of overestimation, calibration and correlation varied by personal and sleep characteristics. Although asking about sleep duration seems uncomplicated, the correlation between self-reported and objectively-measured sleep in this population was moderate and systematically biased.

/pdf/self-reported-and-measured-sleep-duration-how-similar-are-297jfipp10.pdf

Self-reported and measured sleep duration: how similar are they?

In this study, a new scheme was presented for detecting epileptic seizures from electro-encephalo-gram (EEG) data recorded from normal subjects and epileptic patients. The new scheme was based on approximate entropy (ApEn) and discrete wavelet transform (DWT) analysis of EEG signals. Seizure detection was accomplished in two stages. In the first stage, EEG signals were decomposed into approximation and detail coefficients using DWT. In the second stage, ApEn values of the approximation and detail coefficients were computed. Significant differences were found between the ApEn values of the epileptic and the normal EEG allowing us to detect seizures with over 96% accuracy. Without DWT as preprocessing step, it was shown that the detection rate was reduced to 73%. The analysis results depicted that during seizure activity EEG had lower ApEn values compared to normal EEG. This suggested that epileptic EEG was more predictable or less complex than the normal EEG. The data was further analyzed with surrogate data analysis methods to test for evidence of nonlinearities. It was shown that epileptic EEG had significant nonlinearity whereas normal EEG behaved similar to Gaussian linear stochastic process.

Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy

Adaptive servo-ventilation (ASV) is a novel method of ventilatory support designed for Cheyne-Stokes respiration (CSR) in heart failure. The aim of our study was to compare the effect of one night of ASV on sleep and breathing with the effect of other treatments. Fourteen subjects with stable cardiac failure and receiving optimal medical treatment were tested untreated and on four treatment nights in random order: nasal oxygen (2 L/min), continuous positive airway pressure (CPAP) (mean 9.25 cm H(2)O), bilevel (mean 13.5/5.2 cm H(2)O), or ASV largely at the default settings (mean pressure 7 to 9 cm H(2)O) during polysomnography. Thermistor apnea + hypopnea index (AHI) declined from 44.5 +/- 3.4/h (SEM) untreated to 28.2 +/- 3.4/h oxygen and 26.8 +/- 4.6/h CPAP (both p < 0.001 versus control), 14.8 +/- 2.3/h bilevel, and 6.3 +/- 0.9/h ASV (p < 0.001 versus bilevel). Effort band AHI behaved similarly. Arousal index decreased from 65.1 +/- 3.9/h untreated to 29.8 +/- 2.8/h oxygen and 29.9 +/- 3.2/h CPAP, to 16.0 +/- 1.3/h bilevel and 14.7 +/- 1.8/h ASV (p < 0.01 versus all except bilevel). There were large increases in slow-wave and rapid eye movement (REM) sleep with ASV but not with oxygen or CPAP. All subjects preferred ASV to CPAP. One night ASV suppresses central sleep apnea and/or CSR (CSA/CSR) in heart failure and improves sleep quality better than CPAP or 2 L/min oxygen.

https://www.atsjournals.org/doi/pdf/10.1164/ajrccm.164.4.9908114

Adaptive pressure support servo-ventilation: a novel treatment for Cheyne-Stokes respiration in heart failure

Several theories claim that dreaming is a random by-product of REM sleep physiology and that it does not serve any natural function. Phenomenal dream content, however, is not as disorganized as such views imply. The form and content of dreams is not random but organized and selective: during dreaming, the brain constructs a complex model of the world in which certain types of elements, when compared to waking life, are underrepresented whereas others are over represented. Furthermore, dream content is consistently and powerfully modulated by certain types of waking experiences. On the basis of this evidence, I put forward the hypothesis that the biological function of dreaming is to simulate threatening events, and to rehearse threat perception and threat avoidance. To evaluate this hypothesis, we need to consider the original evolutionary context of dreaming and the possible traces it has left in the dream content of the present human population. In the ancestral environment human life was short and full of threats. Any behavioral advantage in dealing with highly dangerous events would have increased the probability of reproductive success. A dream-production mechanism that tends to select threatening waking events and simulate them over and over again in various combinations would have been valuable for the development and maintenance of threat-avoidance skills. Empirical evidence from normative dream content, children's dreams, recurrent dreams, nightmares, post traumatic dreams, and the dreams of hunter-gatherers indicates that our dream-production mechanisms are in fact specialized in the simulation of threatening events, and thus provides support to the threat simulation hypothesis of the function of dreaming.

https://www.unil.ch/files/live/sites/ln/files/shared/Revonsuo_1.pdf

The reinterpretation of dreams: An evolutionary hypothesis of the function of dreaming

Postgraduate Education CornerContemporary Reviews in Sleep MedicineWrist Actigraphy

The goal of the present study was to evaluate the first-night effect in psychiatric inpatients using large subject samples (n > 30) in order to obtain a good statistical evaluation. Thirty-two normal subjects and 94 psychiatric inpatients (38 depressives and 56 insomniacs) were studied for three consecutive nights in the hospital sleep laboratory. Our results showed clearly that there was a first-night effect in normal subjects, similar to that reported in previously published data, characterized by a longer rapid eye movement (REM) sleep latency (p < 0.05), increased wakefulness (p < 0.01) and total sleep time (p < 0.02) and a decreased sleep efficiency (p < 0.01). REM sleep latency and stage REM in the first third of the night were still altered in the second night. Both clinical groups had a less marked first-night effect than normal subjects, showing alterations only observed in REM sleep (p < 0.01) (decreased REM sleep, longer REM sleep latency, increased REM sleep gravity center). However, the first-night effect was more pronounced in insomniacs than in depressed patients. No statistical differences between the second and third nights' recordings were found in sleep parameters. It is suggested that first-night data should not be simply discarded but could be used in subsequent analyses.

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First-night effect in normal subjects and psychiatric inpatients.

In this paper, we compare and analyze the results from automatic analysis and visual scoring of nocturnal sleep recordings. The validation is based on a sleep recording set of 60 subjects (33 males and 27 females), consisting of three groups : 20 normal control subjects, 20 depressed patients and 20 insomniac patients treated with a benzodiazepine. The inter-expert variability estimated from these 60 recordings (61,949 epochs) indicated an average agreement rate of 87.5% between two experts on the basis of 30-second epochs. The automatic scoring system, compared in the same way with one expert, achieved an average agreement rate of 82.3%, without expert supervision. By adding expert supervision for ambiguous and unknown epochs, detected by computation of an uncertainty index and unknown rejection, the automatic/expert agreement grew from 82.3% to 90%, with supervision over only 20% of the night. Bearing in mind the composition and the size of the test sample, the automated sleep staging system achieved a satisfactory performance level and may be considered a useful alternative to visual sleep stage scoring for large-scale investigations of human sleep.

/pdf/sleep-stage-scoring-using-the-neural-network-model-2ppjr0o5q0.pdf

Sleep Stage Scoring Using the Neural Network Model: Comparison Between Visual and Automatic Analysis in Normal Subjects and Patients

Summary: First- and second-night effects on the electroencephalogram (EEG) were investigated by means of polygraphic sleep recordings and all-night spectral analysis. Eighteen normal subjects were studied for three con­ secutive nights in a hospital sleep laboratory. Visual sleep scoring showed that there was a first-night effect in normal subjects similar to that reported previously [increased wakefulness; decreased total sleep time, sleep effi­ ciency, and rapid eye movement (REM) sleep]. Spectral analysis of the sleep EEG revealed important changes, most of which occurred in REM sleep. Increased delta, theta, and betal power densities accompanied by decreased mean frequency were seen in REM sleep in the second night. On the basis of REM sleep deprivation results previously published, our data suggest that the second night could be affected by partial REM sleep deprivation that occurred in the first night. Delta and theta power density values decreased in the first non-rapid eye movement episode of nights I and 2; this could result from increased REM sleep pressure. The overall consistency of spectral data in the first and second night with REM sleep findings derived from visual scoring in the first night lends further support to this hypothesis. The sleep disturbance experienced during the first night in a sleep laboratory may be a useful and valid model of transient insomnia. Therefore, we conclude that data from all nights recorded should be included in assessing a

/pdf/changes-in-eeg-power-density-during-sleep-laboratory-52pv8fpdcr.pdf

Gabriella Carelli

Papers

First-night effect in normal subjects and psychiatric inpatients.

Sleep Stage Scoring Using the Neural Network Model: Comparison Between Visual and Automatic Analysis in Normal Subjects and Patients

Changes In EEG Power Density During Sleep Laboratory Adaptation