See Morris and Weil (doi: ) for a scientific commentary on this article. In a prospective multicentre study involving 1280 patients with idiopathic RBD, Postuma et al. show that approximately 6% of patients each year (>73.5% over 12 years) convert to full neurodegenerative disease. They test the predictive power of 21 prodromal markers of neurodegeneration, providing a template for planning neuroprotective trials.

Human beings exhibit wide variation in their timing of daily behavior. We and others have suggested previously that such differences might arise because of alterations in the period length of the endogenous human circadian oscillator. Using dermal fibroblast cells from skin biopsies of 28 subjects of early and late chronotype (11 ''larks'' and 17 ''owls''), we have studied the circadian period lengths of these two groups, as well as their ability to phase-shift and entrain to environmental and chemical signals. We find not only period length differences between the two classes, but also significant changes in the amplitude and phaseshifting properties of the circadian oscillator among individuals with identical ''normal'' period lengths. Mathematical modeling shows that these alterations could also account for the extreme behavioral phenotypes of these subjects. We conclude that human chronotype may be influenced not only by the period length of the circadian oscillator, but also by cellular components that affect its amplitude and phase. In many instances, these changes can be studied at the molecular level in primary dermal cells.chronotype ͉ circadian ͉ fibroblast ͉ genetics

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.

This study was supported by the Bundesministerium für Bildung und Forschung, Germany (FKZ: 13N13160 and 13N13162) and Intellux GmbH, Germany.