Ostriches Sleep like Platypuses

Mammals and birds engage in two distinct states of sleep, slow wave sleep (SWS) and rapid eye movement (REM) sleep. SWS is characterized by slow, high amplitude brain waves, while REM sleep is characterized by fast, low amplitude waves, known as activation, occurring with rapid eye movements and reduced muscle tone. However, monotremes (platypuses and echidnas), the most basal (or ‘ancient’) group of living mammals, show only a single sleep state that combines elements of SWS and REM sleep, suggesting that these states became temporally segregated in the common ancestor to marsupial and eutherian mammals. Whether sleep in basal birds resembles that of monotremes or other mammals and birds is unknown. Here, we provide the first description of brain activity during sleep in ostriches (Struthio camelus), a member of the most basal group of living birds. We found that the brain activity of sleeping ostriches is unique. Episodes of REM sleep were delineated by rapid eye movements, reduced muscle tone, and head movements, similar to those observed in other birds and mammals engaged in REM sleep; however, during REM sleep in ostriches, forebrain activity would flip between REM sleep-like activation and SWS-like slow waves, the latter reminiscent of sleep in the platypus. Moreover, the amount of REM sleep in ostriches is greater than in any other bird, just as in platypuses, which have more REM sleep than other mammals. These findings reveal a recurring sequence of steps in the evolution of sleep in which SWS and REM sleep arose from a single heterogeneous state that became temporally segregated into two distinct states. This common trajectory suggests that forebrain activation during REM sleep is an evolutionarily new feature, presumably involved in performing new sleep functions not found in more basal animals

The cascading pathogenic consequences of Sarcoptes scabiei infection that manifest in host disease

Sarcoptic mange, caused by the parasitic mite Sarcoptes scabiei, causes a substantive burden of disease to humans, domestic animals and wildlife, globally. There are many effects of S. scabiei infection, culminating in the disease which hosts suffer. However, major knowledge gaps remain on the pathogenic impacts of this infection. Here, we focus on the bare-nosed wombat host (Vombatus ursinus) to investigate the effects of mange on: (i) host heat loss and thermoregulation, (ii) field metabolic rates, (iii) foraging and resting behaviour across full circadian cycles, and (iv) fatty acid composition in host adipose, bone marrow, brain and muscle tissues. Our findings indicate that mange-infected V. ursinus lose more heat to the environment from alopeciaaffected body regions than healthy individuals. Additionally, mange-infected individuals have higher metabolic rates in the wild. However, these metabolic demands are difficult to meet, because infected individuals spend less time foraging and more time inactive relative to their healthy counterparts, despite being outside of the burrow for longer

Network Physiology reveals relations between network topology and physiological function

The human organism is an integrated network where complex physiologic systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here, we develop a framework to probe interactions among diverse systems, and we identify a physiologic network. We find that each physiologic state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiologic states the network undergoes topological transitions associated with fast reorganization of physiologic interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.Comment: 12 pages, 9 figure

Differences in pre-sleep activity and sleep location are associated with variability in daytime/nighttime sleep electrophysiology in the domestic dog

The domestic dog (Canis familiaris) is a promising animal model. Yet, the canine neuroscience literature is predominantly comprised of studies wherein (semi-)invasive methods and intensive training are used to study awake dog behavior. Given prior findings with humans and/or dogs, our goal was to assess, in 16 family dogs (1.5–7 years old; 10 males; 10 different breeds) the effects of pre-sleep activity and timing and location of sleep on sleep electrophysiology. All three factors had a main and/or interactive effect on sleep macrostructure. Following an active day, dogs slept more, were more likely to have an earlier drowsiness and NREM, and spent less time in drowsiness and more time in NREM and REM. Activity also had location- and time of day-specific effects. Time of day had main effects; at nighttime, dogs slept more and spent less time in drowsiness and awake after first drowsiness, and more time in NREM and in REM. Location had a main effect; when not at home, REM sleep following a first NREM was less likely. Findings are consistent with and extend prior human and dog data and have implications for the dog as an animal model and for informing future comparative research on sleep

Evaluation of two minimally invasive techniques for electroencephalogram recording in wild or freely behaving animals.

Insight into the function of sleep may be gained by studying animals in the ecological context in which sleep evolved. Until recently, technological constraints prevented electroencephalogram (EEG) studies of animals sleeping in the wild. However, the recent development of a small recorder (Neurologger 2) that animals can carry on their head permitted the first recordings of sleep in nature. To facilitate sleep studies in the field and to improve the welfare of experimental animals, herein, we test the feasibility of using minimally invasive surface and subcutaneous electrodes to record the EEG in barn owls. The EEG and behaviour of four adult owls in captivity and of four chicks in a nest box in the field were recorded. We scored a 24-h period for each adult bird for wakefulness, slow-wave sleep (SWS), and rapid-eye movement (REM) sleep using 4 s epochs. Although the quality and stability of the EEG signals recorded via subcutaneous electrodes were higher when compared to surface electrodes, the owls' state was readily identifiable using either electrode type. On average, the four adult owls spent 13.28 h awake, 9.64 h in SWS, and 1.05 h in REM sleep. We demonstrate that minimally invasive methods can be used to measure EEG-defined wakefulness, SWS, and REM sleep in owls and probably other animals

Validation of 'Somnivore', a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, SomnivoreTM, for automated wake-sleep stage classification. We designed an algorithm that extracts features from various input channels, following a brief session of manual scoring, and provides automated wake-sleep stage classification for each recording. For algorithm validation, polysomnography data was obtained from independent laboratories, and include normal, cognitively-impaired, and alcohol-treated human subjects (total n = 52), narcoleptic mice and drug-treated rats (total n = 56), and pigeons (n = 5). Training and testing sets for validation were previously scored manually by 1-2 trained sleep technologists from each laboratory. F-measure was used to assess precision and sensitivity for statistical analysis of classifier output and human scorer agreement. The algorithm gave high concordance with manual visual scoring across all human data (wake 0.91 ± 0.01; N1 0.57 ± 0.01; N2 0.81 ± 0.01; N3 0.86 ± 0.01; REM 0.87 ± 0.01), which was comparable to manual inter-scorer agreement on all stages. Similarly, high concordance was observed across all rodent (wake 0.95 ± 0.01; NREM 0.94 ± 0.01; REM 0.91 ± 0.01) and pigeon (wake 0.96 ± 0.006; NREM 0.97 ± 0.01; REM 0.86 ± 0.02) data. Effects of classifier learning from single signal inputs, simple stage reclassification, automated removal of transition epochs, and training set size were also examined. In summary, we have developed a polysomnography analysis program for automated sleep-stage classification of data from diverse species. Somnivore enables flexible, accurate, and high-throughput analysis of experimental and clinical sleep studies

Walking Behavior of Zoo Elephants: Associations between GPS-Measured Daily Walking Distances and Environmental Factors, Social Factors, and Welfare Indicators

Research with humans and other animals suggests that walking benefits physical health. Perhaps because these links have been demonstrated in other species, it has been suggested that walking is important to elephant welfare, and that zoo elephant exhibits should be designed to allow for more walking. Our study is the first to address this suggestion empirically by measuring the mean daily walking distance of elephants in North American zoos, determining the factors that are associated with variations in walking distance, and testing for associations between walking and welfare indicators. We used anklets equipped with GPS data loggers to measure outdoor daily walking distance in 56 adult female African (n = 33) and Asian (n = 23) elephants housed in 30 North American zoos. We collected 259 days of data and determined associations between distance walked and social, housing, management, and demographic factors. Elephants walked an average of 5.3 km/day with no significant difference between species. In our multivariable model, more diverse feeding regimens were correlated with increased walking, and elephants who were fed on a temporally unpredictable feeding schedule walked 1.29 km/day more than elephants fed on a predictable schedule. Distance walked was also positively correlated with an increase in the number of social groupings and negatively correlated with age. We found a small but significant negative correlation between distance walked and nighttime Space Experience, but no other associations between walking distances and exhibit size were found. Finally, distance walked was not related to health or behavioral outcomes including foot health, joint health, body condition, and the performance of stereotypic behavior, suggesting that more research is necessary to determine explicitly how differences in walking may impact elephant welfare