Studies on sleep patterns and sleep homeostasis in birds:An ecological approach

Sleep is a complex phenomenon that consists of two completely different and alternating states, slow-wave sleep (SWS) and rapid-eye-movement sleep (REM sleep). Each of these two states is thought to play an important role in supporting brain and bodily functions. Yet, how exactly sleep fulfills these functions is a topic of ongoing research and debate. Most of what is known about sleep is derived from studies that were done in mammals under strictly controlled laboratory conditions. However, sleep is not restricted to mammals but is thought to be present in all living animals. Moreover, studies in a laboratory setting may not provide a complete picture of the regulatory processes and functions of sleep under natural conditions. For that reason, I measured sleep in three bird species under both laboratory conditions and semi-natural conditions: the European jackdaw (Coloeus monedula), the European starling (Sturnus vulgaris) and the barnacle goose (Branta leucopsis). The results provide evidence for homeostatic regulation of SWS in birds similar to what has been reported for mammals, but also produced unexpected findings. For example, the geese only showed a rebound of SWS after brief sleep deprivation in summer but not in winter. Also, both geese and starlings displayed strong seasonal variation in the overall amount of sleep. The starling in particular slept 5h per day less in summer than they did in winter. Moreover, both geese and starlings slept about 2h less during full moon nights than new moon nights. Another intriguing finding was the strong variation in REM sleep between the 3 species, which ranged from hardly any REM sleep in starlings to a much higher, mammalian-like amount of REM sleep in jackdaws. Such findings are difficult to reconcile with current theories in the function of REM sleep that are largely based on studies in mammals. Together, these findings in birds indicate that sleep is highly sensitive to environmental factors and suggest a great deal of flexibility in the regulation of sleep under natural conditions

Seasonal variation in rest-activity patterns in barnacle geese:Are measurements of activity a good indicator of sleep-wake patterns?

Sleep is a widely spread phenomenon in the animal kingdom and is thought to serve important functions. Yet, the function of sleep remains an enigma. Studies in non-model animal species in their natural habitat might provide more insight into the evolution and function of sleep. However, polysomnography in the wild may not always be an option or first choice and some studies may need to rely on rest–activity recordings as a proxy for sleep and wakefulness. In the current paper, we analyzed how accelerometry-based activity data correlate with electroencephalogram (EEG)-based sleep–wake patterns in barnacle geese under seminatural conditions across different seasons. In winter, the geese had pronounced daily rhythms in rest and activity, with most activity occurring during the daytime. In summer, activity was more spread out over the 24 h cycle. Hourly activity scores strongly correlated with EEG-determined time awake, but the strength of the correlation varied with phase of the day and season. In winter, the correlations between activity and waking time were weaker for daytime than for night-time. Furthermore, the correlations between activity and waking during daytime were weaker in winter than in summer. During daytime in winter, there were many instances where the birds were awake but not moving. Experimental sleep deprivation had no effect on the strength of the correlation between activity scores and EEG-based wake time. Overall, hourly activity scores also showed significant inverse correlation with the time spent in non-rapid eye movement (NREM) sleep. However, correlation between activity scores and time spent in REM sleep was weak. In conclusion, accelerometry-based activity scores can serve as a good estimate for time awake or even the specific time spent in NREM sleep. However, activity scores cannot reliably predict REM sleep and sleep architecture

A comparison of continuous and intermittent EEG recordings in geese:How much data are needed to reliably estimate sleep-wake patterns?

Recent technological advancements allow researchers to measure electrophysiological parameters of animals, such as sleep, in remote locations by using miniature dataloggers. Yet, continuous recording of sleep might be constrained by the memory and battery capacity of the recording devices. These limitations can be alleviated by recording intermittently instead of continuously, distributing the limited recording capacity over a longer period. We assessed how reduced sampling of sleep recordings affected measurement precision of NREM sleep, REM sleep, and Wake. We analysed a dataset on sleep in barnacle geese that we resampled following 12 different recording schemes, with data collected for 1 min per 5 min up to 1 min per 60 min in steps of 5 min. Recording 1 min in 5 min still yielded precise estimates of hourly sleep-wake values (correlations of 0.9) while potentially extending the total recording period by a factor of 5. The correlation strength gradually decreased to 0.5 when recording 1 min per 60 min. For hourly values of Wake and NREM sleep, the correlation strength in winter was higher compared with summer, reflecting more fragmented sleep in summer. Interestingly for hourly values of REM sleep, correlations were unaffected by season. Estimates of total 24 h sleep-wake values were similar for all intermittent recording schedules compared to the continuous recording. These data indicate that there is a large safe range in which researchers can periodically record sleep. Increasing the sample size while maintaining precision can substantially increase the statistical power, and is therefore recommended whenever the total recording time is limited

The European starling (<i>Sturnus vulgaris</i>) shows signs of NREM sleep homeostasis but has very little REM sleep and no REM sleep homeostasis

Most of our knowledge about the regulation and function of sleep is based on studies in a restricted number of mammalian species, particularly nocturnal rodents. Hence, there is still much to learn from comparative studies in other species. Birds are interesting because they appear to share key aspects of sleep with mammals, including the presence of two different forms of sleep, i.e. non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. We examined sleep architecture and sleep homeostasis in the European starling, using miniature dataloggers for electroencephalogram (EEG) recordings. Under controlled laboratory conditions with a 12:12 h light–dark cycle, the birds displayed a pronounced daily rhythm in sleep and wakefulness with most sleep occurring during the dark phase. Sleep mainly consisted of NREM sleep. In fact, the amount of REM sleep added up to only 1~2% of total sleep time. Animals were subjected to 4 or 8 h sleep deprivation to assess sleep homeostatic responses. Sleep deprivation induced changes in subsequent NREM sleep EEG spectral qualities for several hours, with increased spectral power from 1.17 Hz up to at least 25 Hz. In contrast, power below 1.17 Hz was decreased after sleep deprivation. Sleep deprivation also resulted in a small compensatory increase in NREM sleep time the next day. Changes in EEG spectral power and sleep time were largely similar after 4 and 8 h sleep deprivation. REM sleep was not noticeably compensated after sleep deprivation. In conclusion, starlings display signs of NREM sleep homeostasis but the results do not support the notion of important REM sleep functions

Cloud cover amplifies the sleep-suppressing effect of artificial light at night in geese

In modern society the night sky is lit up not only by the moon but also by artificial light devices. Both of these light sources can have a major impact on wildlife physiology and behaviour. For example, a number of bird species were found to sleep several hours less under full moon compared to new moon and a similar sleep-suppressing effect has been reported for artificial light at night (ALAN). Cloud cover at night can modulate the light levels perceived by wildlife, yet, in opposite directions for ALAN and moon. While clouds will block moon light, it may reflect and amplify ALAN levels and increases the night glow in urbanized areas. As a consequence, cloud cover may also modulate the sleep-suppressing effects of moon and ALAN in different directions. In this study we therefore measured sleep in barnacle geese (Branta leucopsis) under semi-natural conditions in relation to moon phase, ALAN and cloud cover. Our analysis shows that, during new moon nights stronger cloud cover was indeed associated with increased ALAN levels at our study site. In contrast, light levels during full moon nights were fairly constant, presumably because of moonlight on clear nights or because of reflected artificial light on cloudy nights. Importantly, cloud cover caused an estimated 24.8% reduction in the amount of night-time NREM sleep from nights with medium to full cloud cover, particularly during new moon when sleep was unaffected by moon light. In conclusion, our findings suggest that cloud cover can, in a rather dramatic way, amplify the immediate effects of ALAN on wildlife. Sleep appears to be highly sensitive to ALAN and may therefore be a good indicator of its biological effects.ISSN:0269-7491ISSN:1878-2450ISSN:1873-642

Seasonal variation in sleep homeostasis in migratory geese:A rebound of NREM sleep following sleep deprivation in summer but not in winter

Sleep is a behavioral and physiological state that is thought to serve important functions. Many animals go through phases in the annual cycle where sleep time might be limited, for example, during the migration and breeding phases. This leads to the question whether there are seasonal changes in sleep homeostasis. Using electroencephalogram (EEG) data loggers, we measured sleep in summer and winter in 13 barnacle geese (Branta leucopsis) under semi-natural conditions. During both seasons, we examined the homeostatic regulation of sleep by depriving the birds of sleep for 4 and 8 h after sunset. In winter, barnacle geese showed a clear diurnal rhythm in sleep and wakefulness. In summer, this rhythm was less pronounced, with sleep being spread out over the 24-h cycle. On average, the geese slept 1.5 h less per day in summer compared with winter. In both seasons, the amount of NREM sleep was additionally affected by the lunar cycle, with 2 h NREM sleep less during full moon compared to new moon. During summer, the geese responded to 4 and 8 h of sleep deprivation with a compensatory increase in NREM sleep time. In winter, this homeostatic response was absent. Overall, sleep deprivation only resulted in minor changes in the spectral composition of the sleep EEG. In conclusion, barnacle geese display season-dependent homeostatic regulation of sleep. These results demonstrate that sleep homeostasis is not a rigid phenomenon and suggest that some species may tolerate sleep loss under certain conditions or during certain periods of the year.ISSN:1550-9109ISSN:0161-810

Shift in Food Intake and Changes in Metabolic Regulation and Gene Expression during Simulated Night-Shift Work:A Rat Model

Night-shift work is linked to a shift in food intake toward the normal sleeping period, and to metabolic disturbance. We applied a rat model of night-shift work to assess the immediate effects of such a shift in food intake on metabolism. Male Wistar rats were subjected to 8 h of forced activity during their rest (ZT2-10) or active (ZT14-22) phase. Food intake, body weight, and body temperature were monitored across four work days and eight recovery days. Food intake gradually shifted toward rest-work hours, stabilizing on work day three. A subgroup of animals was euthanized after the third work session for analysis of metabolic gene expression in the liver by real-time polymerase chain reaction (PCR). Results show that work in the rest phase shifted food intake to rest-work hours. Moreover, liver genes related to energy storage and insulin metabolism were upregulated, and genes related to energy breakdown were downregulated compared to non-working time-matched controls. Both working groups lost weight during the protocol and regained weight during recovery, but animals that worked in the rest phase did not fully recover, even after eight days of recovery. In conclusion, three to four days of work in the rest phase is sufficient to induce disruption of several metabolic parameters, which requires more than eight days for full recovery.publishedVersio

Automated entire thrombus density measurements for robust and comprehensive thrombus characterization in patients with acute ischemic stroke

Background and Purpose: In acute ischemic stroke (AIS) management, CT-based thrombus density has been associated with treatment success. However, currently used thrombus measurements are prone to inter-observer variability and oversimplify the heterogeneous thrombus composition. Our aim was first to introduce an automated method to assess the entire thrombus density and then to compare the measured entire thrombus density with respect to current standard manual measurements. Materials and Method: In 135 AIS patients, the density distribution of the entire thrombus was determined. Density distributions were described usingmedians, interquartile ranges (IQR), kurtosis, and skewedness. Differences between themedian of entire thrombusmeasurements and commonly applied manualmeasurements using 3 regions of interest were determined using linear regression. Results: Density distributions varied considerably with medians ranging from 20.0 to 62.8 HU and IQRs ranging from 9.3 to 55.8 HU. The average median of the thrombus density distributions (43.5 ± 10.2 HU) was lower than the manual assessment (49.6 ± 8.0 HU) (p<0.05). The difference between manual measurements and median density of entire thrombus decreased with increasing density (r = 0.64; p<0.05), revealing relatively higher manual measurements for low density thrombi such that manual density measurement tend overestimates the real thrombus density. Conclusions: Automatic measurements of the full thrombus expose a wide variety of thrombi density distribution, which is not grasped with currently used manual measurement. Furthermore, d

Two-year clinical follow-up of the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in The Netherlands (MR CLEAN): Design and statistical analysis plan of the extended follow-up study

Background: MR CLEAN was the first randomized trial to demonstrate the short-term clinical effectiveness of endovascular treatment in patients with acute ischemic stroke caused by large vessel occlusion in the anterior circulation. Several other trials confirmed that endovascular treatment improves clinical outcome at three months. However, limited data are available on long-term clinical outcome. We aimed to estimate the effect of endovascular treatment on functional outcome at two-year follow-up in patients with acute ischemic stroke. Secondly, we aimed to assess the effect of endovascular treatment on major vascular events and mortality during two years of follow-up. Methods: MR CLEAN is a multicenter clinical trial with randomized treatment allocation, open-label treatment, and blinded endpoint evaluation. Patients included were 18 years or older with acute ischemic stroke caused by a proven anterior proximal artery occlusion who could be treated within six hours after stroke onset. The intervention contrast was endovascular treatment and usual care versus no endovascular treatment and usual care. The current study extended the follow-up duration from three months to two years. The primary outcome is the score on the modified Rankin scale at two years. Secondary outcomes include all-cause mortality and the occurrence of major vascular events within two years of follow-up. Discussion: The results of our study provide information on the long-term clinical effectiveness of endovascular treatment, which may have implications for individual treatment decisions and estimates of cost-effectiveness. Trial registration:NTR1804. Registered on 7 May 2009; ISRCTN10888758. Registered on 24 July 2012 (main MR CLEAN trial); NTR5073. Registered on 26 February 2015 (extended follow-up study)