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Sleep homeostasis reflects temporally integrated local cortical neuronal activity
AbstractThe homeostatic regulation of sleep manifests as a relative constancy of its daily amount and intensity. Theoretical descriptions of this phenomenon define “Process S”, a variable with dynamics dependent only on sleep-wake history, whose levels are reflected in electroencephalogram (EEG) slow wave activity (0.5 – 4 Hz) during sleep. Here we developed novel mathematical models of Process S in mice, assuming that its dynamics are a function of the deviation of cortical neuronal firing rates from a locally defined set-point, crucially without explicit knowledge of sleep-wake state. Our results suggest that Process S tracks global sleep-wake history through an integration of local cortical neuronal activity levels over time. We posit that, instead of reflecting sleep-wake-dependent changes in specific variables and serving their homeostatic regulation, Process S may be a time-keeping mechanism which enables individuals to obtain a species-specific and ecologically-relevant quantity of sleep, even in the absence of external temporal information.
Ultrasonic vocalisation rate tracks the diurnal pattern of activity in winter phenotype Djungarian hamsters (Phodopus sungorus).
Vocalisations are increasingly being recognised as an important aspect of normal rodent behaviour yet little is known of how they interact with other spontaneous behaviours such as sleep and torpor, particularly in a social setting. We obtained chronic recordings of the vocal behaviour of adult male and female Djungarian hamsters (Phodopus sungorus) housed under short photoperiod (8 h light, 16 h dark, square wave transitions), in different social contexts. The animals were kept in isolation or in same-sex sibling pairs, separated by a grid which allowed non-physical social interaction. On approximately 20% of days hamsters spontaneously entered torpor, a state of metabolic depression that coincides with the rest phase of many small mammal species in response to actual or predicted energy shortages. Animals produced ultrasonic vocalisations (USVs) with a peak frequency of 57 kHz in both social and asocial conditions and there was a high degree of variability in vocalisation rate between subjects. Vocalisation rate was correlated with locomotor activity across the 24-h light cycle, occurring more frequently during the dark period when the hamsters were more active and peaking around light transitions. Solitary-housed animals did not vocalise whilst torpid and animals remained in torpor despite overlapping with vocalisations in social-housing. Besides a minor decrease in peak USV frequency when isolated hamsters were re-paired with their siblings, changing social contexts did not influence vocalisation behaviour or structure. In rare instances, temporally overlapping USVs occurred when animals were socially-housed and were grouped in such a way that could indicate coordination. We did not observe broadband calls (BBCs) contemporaneous with USVs in this paradigm, corroborating their correlation with physical aggression which was absent from our experiment. Overall, we find little evidence to suggest a direct social function of hamster USVs. We conclude that understanding the effects of vocalisations on spontaneous behaviours, such as sleep and torpor, will inform experimental design of future studies, especially where the role of social interactions is investigated.
Rodent models in translational circadian photobiology.
Over the last decades remarkable advances have been made in the understanding of the photobiology of circadian rhythms. The identification of a third photoreceptive system in the mammalian eye, in addition to the rods and cones that mediate vision, has transformed our appreciation of the role of light in regulating physiology and behavior. These photosensitive retinal ganglion cells (pRGCs) express the blue-light sensitive photopigment melanopsin and project to the suprachiasmatic nuclei (SCN)-the master circadian pacemaker-as well as many other brain regions. Much of our understanding of the fundamental mechanisms of the pRGCs, and the processes that they regulate, comes from mouse and other rodent models. Here we describe the contribution of rodent models to circadian photobiology, including both their strengths and limitations. In addition, we discuss how an appreciation of both rodent and human data is important for translational circadian photobiology. Such an approach enables a bi-directional flow of information whereby an understanding of basic mechanisms derived from mice can be integrated with studies from humans. Progress in this field is being driven forward at several levels of analysis, not least by the use of personalized light measurements and photoreceptor specific stimuli in human studies, and by studying the impact of environmental, rather than laboratory, lighting on different rodent models.
Penguins snatch seconds-long microsleeps.
Chinstrap penguins fall asleep thousands of times per day in the wild.
Does the claustrum have a function? Lessons from human lesion and animal studies point to divergent multifunctionality
The claustrum is the most densely interconnected region in the human brain. Despite the accumulating data from clinical and experimental studies, the functional role(s) of the claustrum remain unknown. Here, we systematically review claustrum lesion studies and discuss their functional implications. Claustral lesions are associated with an array of signs and symptoms, including changes in cognitive, perceptual and motor abilities; electrical activity; mental state; and sleep. The wide range of symptoms observed following claustral lesions suggests that the claustrum may either have a number of distinct functions, or a global function that impacts many neural processes. We further discuss the implications of these lesions in the context of recent evidence linking the claustrum to sensory perception, sleep, and salience as well as highlighting an underexplored link between the claustrum and pain. We hypothesize that the claustrum is connected to multiple brain networks, both ancient and advanced, which underly fundamental functions as well as higher cognitive processes. Extensive evidence derived from human lesion studies and animal experiments provides unequivocal evidence for a key function of the claustrum as a multifunctional node in numerous networks.
Methods to estimate body temperature and energy expenditure dynamics in fed and fasted laboratory mice: effects of sleep deprivation and light exposure.
Monitoring body temperature and energy expenditure in freely-moving laboratory mice remains a powerful methodology used widely across a variety of disciplines-including circadian biology, sleep research, metabolic phenotyping, and the study of body temperature regulation. Some of the most pronounced changes in body temperature are observed when small heterothermic species reduce their body temperature during daily torpor. Daily torpor is an energy saving strategy characterized by dramatic reductions in body temperature employed by mice and other species when challenged to meet energetic demands. Typical measurements used to describe daily torpor are the measurement of core body temperature and energy expenditure. These approaches can have drawbacks and developing alternatives for these techniques provides options that can be beneficial both from an animal-welfare and study-complexity perspective. First, this paper presents and assesses a method to estimate core body temperature based on measurements of subcutaneous body temperature, and second, a separate approach to better estimate energy expenditure during daily torpor based on core body temperature. Third, the effects of light exposure during the habitual dark phase and sleep deprivation during the light period on body temperature dynamics were tested preliminary in fed and fasted mice. Together, the here-published approaches and datasets can be used in the future to assess body temperature and metabolism in freely-moving laboratory mice.
An integrated approach identifies the molecular underpinnings of murine anterior visceral endoderm migration.
The anterior visceral endoderm (AVE) differs from the surrounding visceral endoderm (VE) in its migratory behavior and ability to restrict primitive streak formation to the opposite side of the mouse embryo. To characterize the molecular bases for the unique properties of the AVE, we combined single-cell RNA sequencing of the VE prior to and during AVE migration with phosphoproteomics, high-resolution live-imaging, and short-term lineage labeling and intervention. This identified the transient nature of the AVE with attenuation of "anteriorizing" gene expression as cells migrate and the emergence of heterogeneities in transcriptional states relative to the AVE's position. Using cell communication analysis, we identified the requirement of semaphorin signaling for normal AVE migration. Lattice light-sheet microscopy showed that Sema6D mutants have abnormalities in basal projections and migration speed. These findings point to a tight coupling between transcriptional state and position of the AVE and identify molecular controllers of AVE migration.
Figure 4 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to <i>Vhl</i> Inactivation in the Kidney
<p>Renal cortex, but not the papilla, is permissive to long-term survival of <i>Vhl</i>-null cells. <b>A,</b> Representative tdTomato IHC counterstained with hematoxylin in different renal anatomical regions of Control or KO mice harvested at the early or late time points. Scale bar, 100 μm. Magnification, ×20. <b>B,</b> Proportion of cells that are tdTomato-positive in different regions of the kidney as quantified by tdTomato IHC in kidneys from Control or KO mice harvested at different intervals after recombination. <i>n</i> = 7F, 16M for all regions for KO; <i>n</i> = 9F, 15M; 9F, 15M; 9F, 14M; 8F, 14M for cortex, outer medulla, inner medulla, and papilla, respectively, for Control. Line denotes linear regression. Significance testing performed for slope and intercept of linear regression by <i>t</i> test.</p>
Figure 5 from Oncogenic Cell Tagging and Single-Cell Transcriptomics Reveal Cell Type–Specific and Time-Resolved Responses to <i>Vhl</i> Inactivation in the Kidney
<p><i>Vhl</i>-null cells specifically undergo time-dependent alterations in gene expression. <b>A,</b> Density plot depicting UMAP distribution of tdTomato-positive cells from kidneys of Control and KO mice harvested at the early or late time points. <b>B,</b> Left, UMAP plot depicting tdTomato-positive cells from Control and KO mice harvested at the early and late time points colored by UMAP cluster. Right, proportion of cells from each condition belonging to any cluster. <b>C,</b> Scatter plot depicting frequency of expression in tdTomato-positive cells from KO mice at the late time point against log<sub>2</sub>-fold change (log<sub>2</sub>FC) between cells from KO mice at the late versus early time points for all genes. Orange, significantly regulated genes. Genes explicitly mentioned in the main text are labeled. <b>D,</b> Gene set enrichment plots depicting upregulation of genes regulated early after <i>Vhl</i> inactivation (left) or genes known to be HIF targets (right) in <i>Vhl</i>-null cells at the late versus early time points. NES, normalized enrichment score. <i>P</i> value adjusted by Bonferroni correction for multiple testing. <b>E,</b> UMAP plot depicting “PT like” cells among tdTomato-positive cells from Control and KO mice harvested at the early and late time points. Black, PT-like cells. <b>F,</b> Proportion of cells inferred to be “PT like” within tdTomato-positive (top) or tdTomato-negative (bottom) cells across conditions. Median and interquartile range plotted. Pairwise comparisons tested by one-way ANOVA with Holm–Šídák correction. <b>G,</b> Representative CD45 IHC on kidneys from Control (<i>n</i> = 1F, 4M) and KO (<i>n</i> = 6M) mice harvested at the late time point. Scale bar, 50 μm. Magnification, ×40. <b>A–F</b>, scRNA-seq data shown for <i>n</i> = 3F, 1M mice for Control early and Control late samples; <i>n</i> = 2F, 2M mice for KO early and KO late samples.</p>