Spontaneous attentional failures reflect multiplicative interactions of chronic sleep loss with acute sleep loss and circadian misalignment

Objectives: Acute and chronic sleep loss and circadian timing interact such that, depending on their combination, small or very large performance decrements are observed in tasks of attention. Here, we tested whether such nonlinear interactions extend to a physiological measure of spontaneous visual attentional failures, indicating a fundamental principle of sleep-wake regulation. Methods: Nine healthy volunteers completed an in-laboratory 3-week forced desynchrony protocol consisting of 12 consecutive 42.85-hour cycles with a sleep-wake ratio of 1:3.3. The protocol induced increasing chronic sleep loss, while extended wake (32.85 hours) and sleep episodes (10 hours) occurred at multiple circadian phases. Attentional failure rate was quantified from continuous electrooculograms (number of 30-second epochs with slow eye movements/h of wakefulness) as a function of time since scheduled wake (acute sleep loss), week of study (chronic sleep loss), and circadian (melatonin) phase. Results: During the first ∼8 hours awake, attentional failure rate was low, irrespective of the week. During the following wake hours, attentional failure rate increased steadily but at a faster rate in weeks 2 and 3 compared to week 1. The effects of acute and chronic sleep loss on attentional failure rate were magnified during the biological night compared to the biological day. Conclusions: A single extended sleep episode can only temporarily reverse attentional impairment associated with chronic sleep loss. Multiplicative effects of acute and chronic sleep loss-further amplified during the biological night-substantiate the interaction of 2 homeostatic response mechanisms and caution against underestimating their disproportionate combined impact on performance, health, and safety

Dawn simulation light: a potential cardiac events protector

Objective/Background: Major cardiovascular events frequently increase in the morning due to abrupt changes in the sympatho-vagal cardiac control during the transition from sleep to wakefulness. These neural changes are translated into stepwise increases in cardiac functions, resulting in a potential cardiovascular stress. Here, we explored whether light can "optimize" heart rate and its neural control, by actively promoting a less steep transition from sleep to wakefulness, thus minimizing morning cardiovascular vulnerability. Methods: Seventeen healthy young men were awakened 2-hours before their habitual wake-time. In a counterbalanced within-subject design, we applied a control condition (darkness during sleep and dim light during wakefulness) or dawn-simulation-light (DSL) starting 30-minutes before and ending 30-minutes after scheduled wake-up time. Results: Our data reveal a significantly gradient reduction in heart rate during the transition from sleep to wakefulness, when applying DSL as compared to a control condition. Likewise, cardiac sympathovagal control smoothly increased throughout the 30-min sleep episode preceding scheduled wake-up under DSL and remained stable for the first 30-min of wakefulness. Interestingly, these effects were mostly driven by changes in the parasympathetic cardiac control. Conclusions: Our data demonstrate for the first time that a non-invasive strategy, as light exposure surrounding the wake-up process, can significantly reduce the deleterious sleep-to-wake evoked cardiac modulation in healthy young men awakened under conditions of increased sleep pressure. A translational approach of this light exposure, which closely resembles natural lighting conditions in the morning, may therefore act as a potential protector for cardiac vulnerability in the critical morning hours

Automatic artifacts and arousals detection in whole-night sleep EEG recordings

In sleep electroencephalographic (EEG) signals, artifacts and arousals marking are usually part of the processing. This visual inspection by a human expert has two main drawbacks: it is very time consuming and subjective. To detect artifacts and arousals in a reliable, systematic and reproducible automatic way, we developed an automatic detection based on time and frequency analysis with adapted thresholds derived from data themselves. The automatic detection performance is assessed using 5 statistic parameters, on 60 whole night sleep recordings coming from 35 healthy volunteers (male and female) aged between 19 and 26. The proposed approach proves its robustness against inter- and intra-, subjects and raters’ scorings, variability. The agreement with human raters is rated overall from substantial to excellent and provides a significantly more reliable method than between human raters. Existing methods detect only specific artifacts or only arousals, and/or these methods are validated on short episodes of sleep recordings, making it difficult to compare with our whole night results. The method works on a whole night recording and is fully automatic, reproducible, and reliable. Furthermore the implementation of the method will be made available online as open source code

Privacy-Enhanced Web Personalization

Abstract. Consumer studies demonstrate that online users value personalized content. At the same time, providing personalization on websites seems quite profitable for web vendors. This win-win situation is however marred by privacy concerns since personalizing people's interaction entails gathering considerable amounts of data about them. As numerous recent surveys have consistently demonstrated, computer users are very concerned about their privacy on the Internet. Moreover, the collection of personal data is also subject to legal regulations in many countries and states. Both user concerns and privacy regulations impact frequently used personalization methods. This article analyzes the tension between personalization and privacy, and presents approaches to reconcile the both. It has been tacitly acknowledged for many years that personalized interaction and user modeling have significant privacy implications, due to the fact that large amounts of personal information about users needs to be collected to perform personalization. Fo