Sylvia Frey

Cortical activation patterns herald successful dream recall after NREM and REM sleep

Dreaming pertains to both REM and NREM sleep. However, frequency and regional specific differences in EEG activity remains controversial. We investigated NREM and REM sleep EEG power density associated with and without dream recall in 17 young subjects during a 40-h multiple nap protocol under constant routine conditions. NREM sleep was associated with lower EEG power density for dream recall in the delta range, particularly in frontal derivations, and in the spindle range in centro-parietal derivations. REM sleep was associated with low frontal alpha activity and with high alpha and beta activity in occipital derivations. Our data indicate that specific EEG frequency- and topography changes underlie differences between dream recall and no recall after both NREM and REM sleep awakening. This dual NREM-REM sleep modulation holds strong implications for the mechanistic understanding of this complex ongoing cognitive process.

Estimation of human circadian phase via a multi-channel ambulatory monitoring system and a multiple regression model

Reliable detection of circadian phase in humans using noninvasive ambulatory measurements in real-life conditions is challenging and still an unsolved problem. The masking effects of everyday behavior and environmental input such as physical activity and light on the measured variables need to be considered critically. Here, we aimed at developing techniques for estimating circadian phase with the lowest subject burden possible, that is, without the need of constant routine (CR) laboratory conditions or without measuring the standard circadian markers, (rectal) core body temperature (CBT), and melatonin levels. In this validation study, subjects (N = 16) wore multi-channel ambulatory monitoring devices and went about their daily routine for 1 week. The devices measured a large number of physiological, behavioral, and environmental variables, including CBT, skin temperatures, cardiovascular and respiratory function, movement/posture, ambient temperature, and the spectral composition and intensity of light received at eye level. Sleep diaries were logged electronically. After the ambulatory phase, subjects underwent a 32-h CR procedure in the laboratory for measuring unmasked circadian phase based on the “midpoint” of the salivary melatonin profile. To overcome the complex masking effects of confounding variables during ambulatory measurements, multiple regression techniques were applied in combination with the cross-validation approach to subject-independent prediction of circadian phase. The most accurate estimate of circadian phase was achieved using skin temperatures, irradiance for ambient light in the blue spectral band, and motion acceleration as predictors with lags of up to 24 h. Multiple regression showed statistically significant improvement of variance of prediction error over the traditional approaches to determining circadian phase based on single predictors (motion acceleration or sleep log), although CBT was intentionally not included as the predictor. Compared to CBT alone, our method resulted in a 40% smaller range of prediction errors and a nonsignificant reduction of error variance. The proposed noninvasive measurement method could find applications in sleep medicine or in other domains where knowing the exact endogenous circadian phase is important (e.g., for the timing of light therapy).

An Improved Method for Estimating Human Circadian Phase Derived From Multichannel Ambulatory Monitoring and Artificial Neural Networks

Recently, we developed a novel method for estimating human circadian phase with noninvasive ambulatory measurements combined with subject-independent multiple regression models and a curve-fitting approach. With this, we were able to estimate circadian phase under real-life conditions with low subject burden, i.e., without need of constant routine (CR) laboratory conditions, and without measuring standard circadian markers, such as core body temperature (CBT) or pineal hormone melatonin rhythms. The precision of ambulatory-derived estimated circadian phase was within an error of 12 ± 41 min (mean ± SD) in comparison to melatonin phase during a CR protocol. The physiological measures could be reduced to a triple combination: skin temperatures, irradiance in the blue spectral band of ambient light, and motion acceleration. Here, we present a nonlinear regression model approach based on artificial neural networks for a larger data set (25 healthy young males), including both the original data and additional data collected in the same protocol and using the same equipment. Throughout our validation study, subjects wore multichannel ambulatory monitoring devices and went about their daily routine for 1 wk. The devices collected a large number of physiological, behavioral, and environmental variables, including CBT, skin temperatures, cardiovascular and respiratory functions, movement/posture, ambient temperature, spectral composition and intensity of light perceived at eye level, and sleep logs. After the ambulatory phase, study volunteers underwent a 32-h CR protocol in the laboratory for measuring unmasked circadian phase (i.e., “midpoint” of the nighttime melatonin rhythm). To overcome the complex masking effects of many different confounding variables during ambulatory measurements, neural network–based nonlinear regression techniques were applied in combination with the cross-validation approach to subject-independent prediction of circadian phase. The most accurate estimate of circadian phase with a prediction error of −3 ± 23 min (mean ± SD) was achieved using only two types of the measured variables: skin temperatures and irradiance for ambient light in the blue spectral band. Compared to our previous linear multiple regression modeling approach, motion acceleration data can be excluded and prediction accuracy, nevertheless, improved. Neural network regression showed statistically significant improvement of variance of prediction error over traditional approaches in determining circadian phase based on single predictors (CBT, motion acceleration, or sleep logs), even though none of these variables was included as predictor. We, therefore, have identified two sets of noninvasive measures that, combined with the prediction model, can provide researchers and clinicians with a precise measure of internal time, in spite of the masking effects of daily behavior. This method, here validated in healthy young men, requires testing in a clinical or shiftwork population suffering from circadian sleep-wake disorders. (Author correspondence: vitaliy.kolodyazhniy@sbg.ac.at)

Young Women With Major Depression Live on Higher Homeostatic Sleep Pressure Than Healthy Controls

There is mounting evidence for the involvement of the sleep-wake cycle and the circadian system in the pathogenesis of major depression. However, only a few studies so far focused on sleep and circadian rhythms under controlled experimental conditions. Thus, it remains unclear whether homeostatic sleep pressure or circadian rhythms, or both, are altered in depression. Here, the authors aimed at quantifying homeostatic and circadian sleep-wake regulatory mechanisms in young women suffering from major depressive disorder and healthy controls during a multiple nap paradigm under constant routine conditions. After an 8-h baseline night, 9 depressed women, 8 healthy young women, and 8 healthy older women underwent a 40-h multiple nap protocol (10 short sleep-wake cycles) followed by an 8-h recovery night. Polysomnographic recordings were done continuously, and subjective sleepiness was assessed. In order to measure circadian output, salivary melatonin samples were collected during scheduled wakefulness, and the circadian modulation of sleep spindles was analyzed with reference to the timing of melatonin secretion. Sleep parameters as well as non-rapid eye movement (NREM) sleep electroencephalographic (EEG) spectra were determined for collapsed left, central, and right frontal, central, parietal, and occipital derivations for the night and nap-sleep episodes in the frequency range .75–25 Hz. Young depressed women showed higher frontal EEG delta activity, as a marker of homeostatic sleep pressure, compared to healthy young and older women across both night sleep episodes together with significantly higher subjective sleepiness. Higher delta sleep EEG activity in the naps during the biological day were observed in young depressed women along with reduced nighttime melatonin secretion as compared to healthy young volunteers. The circadian modulation of sleep spindles between the biological night and day was virtually absent in healthy older women and partially impaired in young depressed women. These data provide strong evidence for higher homeostatic sleep pressure in young moderately depressed women, along with some indications for impairment of the strength of the endogenous circadian output signal involved in sleep-wake regulation. This finding may have important repercussions on the treatment of the illness as such that a selective suppression of EEG slow-wave activity could promote acute mood improvement. (Author correspondence: Christian.cajochen@upkbs.ch)

Extraocular light via the ear canal does not acutely affect human circadian physiology, alertness and psychomotor vigilance performance

We aimed at testing potential effects of extraocular bright light via the ear canals on human evening melatonin levels, sleepiness and psychomotor vigilance performance. Twenty healthy young men and women (10/10) kept a regular sleep–wake cycle during the 2-week study. The volunteers reported to the laboratory on three evenings, 2 h 15 min before usual bedtime, on average at 21:45 h. They were exposed to three different light conditions, each lasting for 12 min: extraocular bright light via the ear canal, ocular bright light as an active control condition and a control condition (extraocular light therapy device with completely blacked out LEDs). The timing of exposure was on average from 22:48 to 23:00 h. During the 2-h protocol, saliva samples were collected in 15-min intervals for melatonin assays along with subjective sleepiness ratings, and the volunteers performed a 10-min visual psychomotor vigilance task (PVT) prior to and after each light condition. The evening melatonin rise was significantly attenuated after the 12-min ocular bright light exposure while no significant changes were observed after the extraocular bright light and sham light condition. Subjective sleepiness decreased immediately over a short period only after ocular light exposure. No significant differences were observed for mean reaction times and the number of lapses for the PVT between the three light conditions. We conclude that extraocular transcranial light exposure in the late evening does not suppress melatonin, reduce subjective sleepiness or improve performance, and therefore, does not acutely influence the human circadian timing system.

Challenging the sleep homeostat: Sleep in depression is not premature aging

OBJECTIVES The close relationship between major depression and sleep disturbances led to the hypothesis of a deficiency in homeostatic sleep pressure in depression (S-deficiency hypothesis). Many observed changes of sleep characteristics in depression are also present in healthy aging, leading to the premise that sleep in depression resembles premature aging. In this study, we aimed at quantifying the homeostatic sleep-wake regulation in young women with major depression and healthy young and older controls under high sleep pressure conditions. METHODS After an 8-h baseline night nine depressed women, eight healthy young, and eight healthy older women underwent a 40-h sustained wakefulness protocol followed by a recovery night under constant routine conditions. Polysomnographic recordings were carried out continuously. Sleep parameters as well as the time course of EEG slow-wave activity (SWA) (EEG spectra range: 0.75-4.5 Hz), as a marker of homeostatic sleep pressure, were analyzed during the recovery night. RESULTS Young depressed women exhibited higher absolute mean SWA levels and a stronger response to sleep deprivation, particularly in frontal brain regions. In contrast, healthy older women exhibited not only attenuated SWA values compared to the other two groups, but also an absence of the frontal SWA predominance. CONCLUSIONS Homeostatic sleep regulation and sleep architecture in young depressed women are not equal to premature aging. Moreover, our findings demonstrate that young moderately depressed women exhibit no deficiency in the sleep homeostatic process S as predicted by the S-deficiency hypothesis, but, rather, live on an elevated level of homeostatic sleep pressure.

Higher Frontal EEG Synchronization in Young Women with Major Depression: A Marker for Increased Homeostatic Sleep Pressure?

STUDY OBJECTIVES Major depressive disorder (MDD) is often associated with disturbances in circadian and/or sleep-wake dependent processes, which both regulate daytime energy and sleepiness levels. DESIGN Analysis of continuous electroencephalographic (EEG) recordings during 40 h of extended wakefulness under constant routine conditions. Artifact-free EEG samples derived from 12 locations were subjected to spectral analysis. Additionally, half-hourly ratings of subjective tension and sleepiness levels and salivary melatonin measurements were collected. SETTING Centre for Chronobiology, Psychiatric Hospitals of the University of Basel, Switzerland. PARTICIPANTS Eight young healthy women and 8 young untreated women with MDD. INTERVENTIONS N/A. MEASUREMENTS AND RESULTS MDD women exhibited higher frontal low-frequency (FLA) EEG activity (0.5-5.0 Hz) during extended wakefulness than controls, particularly during the night. Enhanced FLA was paralleled by higher levels of subjective sleepiness and tension. In MDD women, overall FLA levels correlated positively with depression scores. The timing of melatonin onset did not significantly differ between the two groups, but the nocturnal secretion of salivary melatonin was significantly attenuated in MDD women. CONCLUSIONS Our data imply that young women with MDD live on a higher homeostatic sleep pressure level, as indexed by enhanced FLA during wakefulness. Its positive correlation with depression scores indicates a possible functional relationship. High FLA could reflect a use-dependent phenomenon in depression (enhanced cognitive rumination or tension) and/or an attenuated circadian arousal signal.

Subjective Mood in Young Unmedicated Depressed Women under High and Low Sleep Pressure Conditions

Diurnal mood variations are one of the core symptoms in depression, and total sleep deprivation (SD) can induce rapid, short-lasting clinical improvement in depressed patients. Here, we investigated if differential sleep pressure conditions impact on subjective mood levels in young women with major depressive disorder (MDD) without sleep disturbances, and in healthy controls. Eight healthy and eight MDD women underwent 40-h SD (high sleep pressure) and 40-h multiple NAP (low sleep pressure) protocols under constant routine conditions during which subjective mood was assessed every 30-min. MDD women rated overall significantly worse mood than controls, with minimal values for both groups during the biological night (ca. 4 a.m.), under high and low sleep pressure conditions. During SD, nighttime mood ratings in MDD women were lower than in controls and partially recovered during the second day of SD, but never attained control levels. The degree of this diurnal time-course in mood under SD correlated positively with sleep quality in MDD women. Our data indicate that MDD women without sleep disturbances did not exhibit a SD-induced antidepressant response, suggesting that the mood enhancement response to sleep deprivation might be related to the co-existence of sleep disturbances, which is an association that remains to be fully established.

Reply to Cordi et al.

In their paper on the influence of the moon on sleep, Cordi et al.[1] have analyzed a large number of subjects and found no significant effects, as opposed to our positive study findings with a smaller cohort [2]. More is not necessarily better. There are two main reasons why we think the comparison of these two data sets is not just comparing a small with a big sample size, since increasing the number of study volunteers in a sleep study does not automatically increase data quality.