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Daily rhythms are disrupted in patients with mood disorders. The lateral habenula (LHb) and dorsal raphe nucleus (DRN) contribute to circadian timekeeping and regulate mood. Thus, pathophysiology in these nuclei may be responsible for aberrations in daily rhythms during mood disorders. Using the 15-day chronic social defeat stress (CSDS) paradigm and in vitro slice electrophysiology, we measured the effects of stress on diurnal rhythms in firing of LHb cells projecting to the DRN (cellsLHb→DRN) and unlabeled DRN cells. We also performed optogenetic experiments to investigate if increased firing in cellsLHb→DRN during exposure to a weak 7-day social defeat stress (SDS) paradigm induces stress-susceptibility. Last, we investigated whether exposure to CSDS affected the ability of mice to photoentrain to a new light–dark (LD) cycle. The cellsLHb→DRN and unlabeled DRN cells of stress-susceptible mice express greater blunted diurnal firing compared to stress-näive (control) and stress-resilient mice. Daytime optogenetic activation of cellsLHb→DRN during SDS induces stress-susceptibility which shows the direct correlation between increased activity in this circuit and putative mood disorders. Finally, we found that stress-susceptible mice are slower, while stress-resilient mice are faster, at photoentraining to a new LD cycle. Our findings suggest that exposure to strong stressors induces blunted daily rhythms in firing in cellsLHb→DRN, DRN cells and decreases the initial rate of photoentrainment in susceptible-mice. In contrast, resilient-mice may undergo homeostatic adaptations that maintain daily rhythms in firing in cellsLHb→DRN and also show rapid photoentrainment to a new LD cycle., Daily rhythms are disrupted in patients suffering from mood disorders, and it is known that the lateral habenula and dorsal raphe nucleus contribute to circadian timekeeping and regulate mood. This study shows that stress-susceptible mice have blunted and inverted diurnal firing rhythms in lateral habenula cells that project to the dorsal raphe nucleus, and have a slow rate of photoentrainment to a new light cycle.

Circadian clocks orchestrate multiple different physiological rhythms in a well-synchronized manner. However, how these separate rhythms are interconnected is not exactly understood. Here, we developed a method that allows for the real-time simultaneous measurement of locomotor activity and body temperature of mice using infrared video camera imaging. As expected from the literature, temporal profiles of body temperature and locomotor activity were positively correlated with each other. Basically, body temperatures were high when animals were in locomotion. However, interestingly, increases in body temperature were not always associated with the appearance of locomotor activity. Video imaging revealed that mice exhibit non-locomotor activities such as grooming and postural adjustments, which alone induce considerable elevation of body temperature. Noticeably, non-locomotor movements always preceded the initiation of locomotor activity. Nevertheless, non-locomotor movements were not always accompanied by locomotor movements, suggesting that non-locomotor movements provide a mechanism of thermoregulation independent of locomotor activity. In addition, in the current study, we also report the development of a machine learning-based recording method for the detection of circadian feeding and drinking behaviors of mice. Our data illustrate the potential utility of thermal video imaging in the investigation of different physiological rhythms.

Purpose Intraocular pressure (IOP) is known to have a strong circadian rhythm, yet how light/dark cycles entrain this rhythm is unknown. The purpose of this study was to assess whether, like the retina, the mammalian ciliary body and IOP clocks have an intrinsic ability to entrain to light/dark cycles. Methods Iris-ciliary body complexes were obtained from period2:luciferase (PER2::LUC) mice and cultured to measure bioluminescence rhythmicity. Pairs of the iris-ciliary body complex were exposed to antiphasic 9:15 h light/dark cycle in vitro. After 4 days of exposure to light/dark cycles, bioluminescence was recorded to establish their circadian phases. In addition, pairs of the iris-ciliary body complex co-cultured with the retinas or corneas of wild-type mice were also investigated. The IOP circadian changes of free-running Opn4-/-;rd1/rd1 mice whose behavior was antiphasic to wild-type were measured by a rebound tonometry, and compared with wild-type mice. Opn3, Opn4, and Opn5 mRNA expression in the iris-ciliary body were analyzed using RT-PCR. Results The iris/ciliary body complex expressed Opn3, Opn4, and Opn5 mRNA; however, unlike in retina and cornea, neither the iris-CB complex nor the co-cultured complex was directly entrained by light-dark cycle in vitro. The diurnal IOP change of Opn4-/-;rd1/rd1 mice showed an antiphasic pattern to wild-type mice and their rhythms followed the whole-animal behavioral rhythm. Conclusions Despite expressing mRNA for several non-visual opsins, circadian rhythms of the iris-ciliary body complex of mice do not entrain directly to light-dark cycles ex vivo. Unlike retina, the iris/ciliary body clocks of blind mice remain synchronized to the organismal behavioral rhythm rather than local light-dark cycles. These results suggest that IOP rhythm entrainment is mediated by a systemic rather than local signal in mice.

For animals living in temperate latitudes, seasonal changes in day length are an important cue for adaptations of their physiology and behavior to the altered environmental conditions. The suprachiasmatic nucleus (SCN) is known as the central circadian clock in mammals, but may also play an important role in adaptations to different photoperiods. The SCN receives direct light input from the retina and is able to encode day-length by approximating the waveform of the electrical activity rhythm to the duration of daylight. Changing the overall waveform requires a reorganization of the neuronal network within the SCN with a change in the degree of synchrony between the neurons; however, the underlying mechanisms are yet unknown. In the present study we used PER2::LUC bioluminescence imaging in cultured SCN slices to characterize network dynamics on the single-cell level and we aimed to provide evidence for a role of modulations in coupling strength in the photoperiodic-induced phase dispersal. Exposure to long photoperiod (LP) induced a larger distribution of peak times of the single-cell PER2::LUC rhythms in the anterior SCN, compared to short photoperiod. Interestingly, the cycle-to-cycle variability in single-cell period of PER2::LUC rhythms is also higher in the anterior SCN in LP, and is positively correlated with peak time dispersal. Applying a new, impartial community detection method on the time series data of the PER2::LUC rhythm revealed two clusters of cells with a specific spatial distribution, which we define as dorsolateral and ventromedial SCN. Post hoc analysis of rhythm characteristics of these clusters showed larger cycle-to-cycle single-cell period variability in the dorsolateral compared to the ventromedial cluster in the anterior SCN. We conclude that a change in coupling strength within the SCN network is a plausible explanation to the observed changes in single-cell period variability, which can contribute to the photoperiod-induced phase distribution.

The level of activity of many animals including humans rises and falls with a period of ~ 24 hours. The intrinsic biological oscillator that gives rise to this circadian oscillation is driven by a molecular feedback loop with an approximately 24 hour cycle period and is influenced by the environment, most notably the light:dark cycle. In addition to the circadian oscillations, behavior of many animals is influenced by multiple oscillations occurring at faster-ultradian-time scales. These ultradian oscillations are also thought to be driven by feedback loops. While many studies have focused on identifying such ultradian oscillations, less is known about how the ultradian behavioral oscillations interact with each other and with the circadian oscillation. Decoding the coupling among the various physiological oscillators may be important for understanding how they conspire together to regulate the normal activity levels, as well in disease states in which such rhythmic fluctuations in behavior may be disrupted. Here, we use a wavelet-based cross-frequency analysis to show that different oscillations identified in spontaneous mouse behavior are coupled such that the amplitude of oscillations occurring at higher frequencies are modulated by the phase of the slower oscillations. The patterns of these interactions are different among different individuals. Yet this variability is not random. Differences in the pattern of interactions are confined to a low dimensional subspace where different patterns of interactions form clusters. These clusters expose the differences among individuals-males and females are preferentially segregated into different clusters. These sex-specific features of spontaneous behavior were not apparent in the spectra. Thus, our methodology reveals novel aspects of the structure of spontaneous animal behavior that are not observable using conventional methodology.