Somnotate: A probabilistic sleep stage classifier for studying vigilance state transitions.

Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and current computational annotation methods ignore intermediate states because the classification features become ambiguous, even though intermediate states contain important information regarding vigilance state dynamics. To address this problem, we have developed "Somnotate"-a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). First we demonstrate that Somnotate sets new standards in polysomnography, exhibiting annotation accuracies that exceed human experts on mouse electrophysiological data, remarkable robustness to errors in the training data, compatibility with different recording configurations, and an ability to maintain high accuracy during experimental interventions. However, the key feature of Somnotate is that it quantifies and reports the certainty of its annotations. We leverage this feature to reveal that many intermediate vigilance states cluster around state transitions, whereas others correspond to failed attempts to transition. This enables us to show for the first time that the success rates of different types of transition are differentially affected by experimental manipulations and can explain previously observed sleep patterns. Somnotate is open-source and has the potential to both facilitate the study of sleep stage transitions and offer new insights into the mechanisms underlying sleep-wake dynamics.

Chronic Exposure to Dim Light at Night or Irregular Lighting Conditions Impact Circadian Behavior, Motor Coordination, and Neuronal Morphology.

Mistimed exposure to light has been demonstrated to negatively affect multiple aspects of physiology and behavior. Here we analyzed the effects of chronic exposure to abnormal lighting conditions in mice. We exposed mice for 1 year to either: a standard light/dark cycle, a "light-pollution" condition in which low levels of light were present in the dark phase of the circadian cycle (dim light at night, DLAN), or altered light cycles in which the length of the weekday and weekend light phase differed by 6 h ("social jetlag"). Mice exhibited several circadian activity phenotypes, as well as changes in motor function, associated particularly with the DLAN condition. Our data suggest that these phenotypes might be due to changes outside the core clock. Dendritic spine changes in other brain regions raise the possibility that these phenotypes are mediated by changes in neuronal coordination outside of the clock. Given the prevalence of artificial light exposure in the modern world, further work is required to establish whether these negative effects are observed in humans as well.

Dim light in the evening causes coordinated realignment of circadian rhythms, sleep, and short-term memory.

Light provides the primary signal for entraining circadian rhythms to the day/night cycle. In addition to rods and cones, the retina contains a small population of photosensitive retinal ganglion cells (pRGCs) expressing the photopigment melanopsin (OPN4). Concerns have been raised that exposure to dim artificial lighting in the evening (DLE) may perturb circadian rhythms and sleep patterns, and OPN4 is presumed to mediate these effects. Here, we examine the effects of 4-h, 20-lux DLE on circadian physiology and behavior in mice and the role of OPN4 in these responses. We show that 2 wk of DLE induces a phase delay of ∼2 to 3 h in mice, comparable to that reported in humans. DLE-induced phase shifts are unaffected in Opn4-/- mice, indicating that rods and cones are capable of driving these responses in the absence of melanopsin. DLE delays molecular clock rhythms in the heart, liver, adrenal gland, and dorsal hippocampus. It also reverses short-term recognition memory performance, which is associated with changes in preceding sleep history. In addition, DLE modifies patterns of hypothalamic and cortical cFos signals, a molecular correlate of recent neuronal activity. Together, our data show that DLE causes coordinated realignment of circadian rhythms, sleep patterns, and short-term memory process in mice. These effects are particularly relevant as DLE conditions-due to artificial light exposure-are experienced by the majority of the populace on a daily basis.

Continuous and non-invasive thermography of mouse skin accurately describes core body temperature patterns, but not absolute core temperature.

Body temperature is an important physiological parameter in many studies of laboratory mice. Continuous assessment of body temperature has traditionally required surgical implantation of a telemeter, but this invasive procedure adversely impacts animal welfare. Near-infrared thermography provides a non-invasive alternative by continuously measuring the highest temperature on the outside of the body (Tskin), but the reliability of these recordings as a proxy for continuous core body temperature (Tcore) measurements has not been assessed. Here, Tcore (30 s resolution) and Tskin (1 s resolution) were continuously measured for three days in mice exposed to ad libitum and restricted feeding conditions. We subsequently developed an algorithm that optimised the reliability of a Tskin-derived estimate of Tcore. This identified the average of the maximum Tskin per minute over a 30-min interval as the optimal way to estimate Tcore. Subsequent validation analyses did however demonstrate that this Tskin-derived proxy did not provide a reliable estimate of the absolute Tcore due to the high between-animal variability in the relationship between Tskin and Tcore. Conversely, validation showed that Tskin-derived estimates of Tcore reliably describe temporal patterns in physiologically-relevant Tcore changes and provide an excellent measure to perform within-animal comparisons of relative changes in Tcore.

Telling the Time with a Broken Clock: Quantifying Circadian Disruption in Animal Models.

Circadian rhythms are approximately 24 h cycles in physiology and behaviour that enable organisms to anticipate predictable rhythmic changes in their environment. These rhythms are a hallmark of normal healthy physiology, and disruption of circadian rhythms has implications for cognitive, metabolic, cardiovascular and immune function. Circadian disruption is of increasing concern, and may occur as a result of the pressures of our modern 24/7 society-including artificial light exposure, shift-work and jet-lag. In addition, circadian disruption is a common comorbidity in many different conditions, ranging from aging to neurological disorders. A key feature of circadian disruption is the breakdown of robust, reproducible rhythms with increasing fragmentation between activity and rest. Circadian researchers have developed a range of methods for estimating the period of time series, typically based upon periodogram analysis. However, the methods used to quantify circadian disruption across the literature are not consistent. Here we describe a range of different measures that have been used to measure circadian disruption, with a particular focus on laboratory rodent data. These methods include periodogram power, variability in activity onset, light phase activity, activity bouts, interdaily stability, intradaily variability and relative amplitude. The strengths and limitations of these methods are described, as well as their normal ranges and interrelationships. Whilst there is an increasing appreciation of circadian disruption as both a risk to health and a potential therapeutic target, greater consistency in the quantification of disrupted rhythms is needed.

Light and Cognition: Roles for Circadian Rhythms, Sleep, and Arousal.

Light exerts a wide range of effects on mammalian physiology and behavior. As well as synchronizing circadian rhythms to the external environment, light has been shown to modulate autonomic and neuroendocrine responses as well as regulating sleep and influencing cognitive processes such as attention, arousal, and performance. The last two decades have seen major advances in our understanding of the retinal photoreceptors that mediate these non-image forming responses to light, as well as the neural pathways and molecular mechanisms by which circadian rhythms are generated and entrained to the external light/dark (LD) cycle. By contrast, our understanding of the mechanisms by which lighting influences cognitive processes is more equivocal. The effects of light on different cognitive processes are complex. As well as the direct effects of light on alertness, indirect effects may also occur due to disrupted circadian entrainment. Despite the widespread use of disrupted LD cycles to study the role circadian rhythms on cognition, the different experimental protocols used have subtly different effects on circadian function which are not always comparable. Moreover, these protocols will also disrupt sleep and alter physiological arousal, both of which are known to modulate cognition. Studies have used different assays that are dependent on different cognitive and sensory processes, which may also contribute to their variable findings. Here, we propose that studies addressing the effects of different lighting conditions on cognitive processes must also account for their effects on circadian rhythms, sleep, and arousal if we are to fully understand the physiological basis of these responses.

Light and the laboratory mouse.

Light exerts widespread effects on physiology and behaviour. As well as the widely-appreciated role of light in vision, light also plays a critical role in many non-visual responses, including regulating circadian rhythms, sleep, pupil constriction, heart rate, hormone release and learning and memory. In mammals, responses to light are all mediated via retinal photoreceptors, including the classical rods and cones involved in vision as well as the recently identified melanopsin-expressing photoreceptive retinal ganglion cells (pRGCs). Understanding the effects of light on the laboratory mouse therefore depends upon an appreciation of the physiology of these retinal photoreceptors, including their differing sens itivities to absolute light levels and wavelengths. The signals from these photoreceptors are often integrated, with different responses involving distinct retinal projections, making generalisations challenging. Furthermore, many commonly used laboratory mouse strains carry mutations that affect visual or non-visual physiology, ranging from inherited retinal degeneration to genetic differences in sleep and circadian rhythms. Here we provide an overview of the visual and non-visual systems before discussing practical considerations for the use of light for researchers and animal facility staff working with laboratory mice.