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Environment shapes sleep patterns in a wild nocturnal primate.
Among primates, the suborder Haplorhini is considered to have evolved a consolidated monophasic sleep pattern, with diurnal species requiring a shorter sleep duration than nocturnal species. Only a few primate species have been systematically studied in their natural habitat where environmental variables, including temperature and light, have a major influence on sleep and activity patterns. Here we report the first sleep study on a nocturnal primate performed in the wild. We fitted seven wild Javan slow lorises (Nycticebus javanicus) in West Java, Indonesia with accelerometers that collected activity data, and installed climate loggers in each individual's home range to collect ambient temperature readings (over 321 days in total). All individuals showed a strictly nocturnal pattern of activity and displayed a striking synchronisation of onset and cessation of activity in relation to sunset and sunrise. The longest consolidated rest episodes were typically clustered near the beginning and towards the end of the light period, and this pattern was inversely related to daily fluctuations of the ambient temperature. The striking relationship between daily activity patterns, light levels and temperature suggests a major role of the environment in shaping the daily architecture of waking and sleep. We concluded that well-known phenotypic variability in daily sleep amount and architecture across species may represent an adaptation to changes in the environment. Our data suggest that the consolidated monophasic sleep patterns shaped by environmental pressures observed in slow lorises represent phylogenetic inertia in the evolution of sleep patterns in humans.
In vivo MRI characterization of progressive cardiac dysfunction in the mdx mouse model of muscular dystrophy.
AIMS: The mdx mouse has proven to be useful in understanding the cardiomyopathy that frequently occurs in muscular dystrophy patients. Here we employed a comprehensive array of clinically relevant in vivo MRI techniques to identify early markers of cardiac dysfunction and follow disease progression in the hearts of mdx mice. METHODS AND RESULTS: Serial measurements of cardiac morphology and function were made in the same group of mdx mice and controls (housed in a non-SPF facility) using MRI at 1, 3, 6, 9 and 12 months after birth. Left ventricular (LV) and right ventricular (RV) systolic and diastolic function, response to dobutamine stress and myocardial fibrosis were assessed. RV dysfunction preceded LV dysfunction, with RV end systolic volumes increased and RV ejection fractions reduced at 3 months of age. LV ejection fractions were reduced at 12 months, compared with controls. An abnormal response to dobutamine stress was identified in the RV of mdx mice as early as 1 month. Late-gadolinium-enhanced MRI identified increased levels of myocardial fibrosis in 6, 9 and 12-month-old mdx mice, the extent of fibrosis correlating with the degree of cardiac remodeling and hypertrophy. CONCLUSIONS: MRI could identify cardiac abnormalities in the RV of mdx mice as young as 1 month, and detected myocardial fibrosis at 6 months. We believe these to be the earliest MRI measurements of cardiac function reported for any mice, and the first use of late-gadolinium-enhancement in a mouse model of congenital cardiomyopathy. These techniques offer a sensitive and clinically relevant in vivo method for assessment of cardiomyopathy caused by muscular dystrophy and other diseases.
Modulation of recognition memory performance by light and its relationship with cortical EEG theta and gamma activities.
Acute exposure to light exerts widespread effects on physiology, in addition to its key role in photoentrainment. Although the modulatory effect of light on physiological arousal is well demonstrated in mice, its effect on memory performance is inconclusive, as the direction of the effect depends on the nature of the behavioural task employed and/or the type of stimulus utilised. Moreover, in all rodent studies that reported significant effects of light on performance, brain activity was not assessed during the task and thus it is unclear how brain activity was modulated by light or the exact relationship between light-modulated brain activity and performance. Here we examine the modulatory effects of light of varying intensities on recognition memory performance and frontoparietal waking electroencephalography (EEG) in mice using the spontaneous recognition memory task. We report a light-intensity-dependent disruptive effect on recognition memory performance at the group level, but inspection of individual-level data indicates that light-intensity-dependent facilitation is observed in some cases. Using linear mixed-effects models, we then demonstrate that EEG fast theta (θ) activity at the time of encoding negatively predicts recognition memory performance, whereas slow gamma (γ) activity at the time of retrieval positively predicts performance. These relationships between θ/γ activity and performance are strengthened by increasing light intensity. Thus, light modulates θ and γ band activities involved in attentional and mnemonic processes, thereby affecting recognition memory performance. However, extraneous factors including the phase of the internal clock at which light is presented and homeostatic sleep pressure may determine how photic input is translated into behavioural performance.
Effects of circadian misalignment on sleep in mice.
Circadian rhythms and sleep-wake history determine sleep duration and intensity, and influence subsequent waking. Previous studies have shown that T cycles - light-dark (LD) cycles differing from 24 h - lead to acute changes in the daily amount and distribution of waking and sleep. However, little is known about the long-term effects of T cycles. Here we performed continuous 10 day recording of electroencephalography (EEG), locomotor activity and core body temperature in C57BL/6 mice under a T20 cycle, to investigate spontaneous sleep and waking at baseline compared with when the circadian clock was misaligned and then re-aligned with respect to the external LD cycle. We found that the rhythmic distribution of sleep was abolished during misalignment, while the time course of EEG slow wave activity (1-4 Hz) was inverted compared to baseline. Although the typical light-dark distribution of NREM sleep was re-instated when animals were re-aligned, slow wave activity during NREM sleep showed an atypical increase in the dark phase, suggesting a long-term effect of T cycles on sleep intensity. Our data show that circadian misalignment results in previously uncharacterised long-term effects on sleep, which may have important consequences for behaviour.
Global sleep homeostasis reflects temporally and spatially integrated local cortical neuronal activity.
Sleep homeostasis manifests as a relative constancy of its daily amount and intensity. Theoretical descriptions define 'Process S', a variable with dynamics dependent on global sleep-wake history, and reflected in electroencephalogram (EEG) slow wave activity (SWA, 0.5-4 Hz) during sleep. The notion of sleep as a local, activity-dependent process suggests that activity history must be integrated to determine the dynamics of global Process S. Here, we developed novel mathematical models of Process S based on cortical activity recorded in freely behaving mice, describing local Process S as a function of the deviation of neuronal firing rates from a locally defined set-point, independent of global sleep-wake state. Averaging locally derived Processes S and their rate parameters yielded values resembling those obtained from EEG SWA and global vigilance states. We conclude that local Process S dynamics reflects neuronal activity integrated over time, and global Process S reflects local processes integrated over space.
Sleep homeostasis, habits and habituation.
The importance of sleep for behavioural performance during waking is long-established, but the underlying reasons and mechanisms remain elusive. Waking and sleep are associated with changes in the levels of GluA1 AMPAR subunit in synaptic membranes, while studies using genetically-modified mice have identified an important role for GluA1-dependent synaptic plasticity in a non-associative form of memory that underlies short-term habituation to recently experienced stimuli. Here we posit that sleep may play a role in dishabituation, which restores attentional capacity and maximises the readiness of the animal for learning and goal-directed behaviour during subsequent wakefulness. Furthermore we suggest that sleep disturbance may fundamentally change the nature of behaviour, making it more model-free and habitual as a result of reduced attentional capacity.
The Interplay between Long- and Short-Range Temporal Correlations Shapes Cortex Dynamics across Vigilance States.
Increasing evidence suggests that cortical dynamics during wake exhibits long-range temporal correlations suitable to integrate inputs over extended periods of time to increase the signal-to-noise ratio in decision making and working memory tasks. Accordingly, sleep has been suggested as a state characterized by a breakdown of long-range correlations. However, detailed measurements of neuronal timescales that support this view have so far been lacking. Here, we show that the cortical timescales measured at the individual neuron level in freely behaving male rats change as a function of vigilance state and time awake. Although quiet wake and rapid eye movement (REM) sleep are characterized by similar, long timescales, these long timescales are abrogated in non-REM sleep. We observe that cortex dynamics exhibits rapid transitions between long-timescale states and sleep-like states governed by short timescales even during wake. This becomes particularly evident during sleep deprivation, when the interplay between these states can lead to an increasing disruption of long timescales that are restored after sleep. Experiments and modeling identify the intrusion of neuronal offline periods as a mechanism that disrupts the long timescales arising from reverberating cortical network activity. Our results provide novel mechanistic and functional links among behavioral manifestations of sleep, wake, and sleep deprivation and specific measurable changes in the network dynamics relevant for characterizing the brain's changing information-processing capabilities. They suggest a network-level function of sleep to reorganize cortical networks toward states governed by long timescales to ensure efficient information integration for the time awake.SIGNIFICANCE STATEMENT Lack of sleep deteriorates several key cognitive functions, yet the neuronal underpinnings of these deficits have remained elusive. Cognitive capabilities are generally believed to benefit from a neural circuit's ability to reliably integrate information. Persistent network activity characterized by long timescales may provide the basis for this integration in cortex. Here, we show that long-range temporal correlations indicated by slowly decaying autocorrelation functions in neuronal activity are dependent on vigilance states. Although wake and rapid eye movement (REM) sleep exhibit long timescales, these long-range correlations break down during non-REM sleep. Our findings thus suggest two distinct states in terms of timescale dynamics. During extended wake, the rapid switching to sleep-like states with short timescales can lead to an overall decline in cortical timescales.
Differences in electroencephalographic non-rapid-eye movement sleep slow-wave characteristics between young and old mice.
Changes in sleep pattern are typical for the normal aging process. However, aged mice show an increase in the amount of sleep, whereas humans show a decrease when aging. Mice are considered an important model in aging studies, and this divergence warrants further investigation. Recently, insights into the network dynamics of cortical activity during sleep were obtained by investigating characteristics of individual electroencephalogram (EEG) slow waves in young and elderly humans. In this study, we investigated, for the first time, the parameters of EEG slow waves, including their incidence, amplitude, duration and slopes, in young (6 months) and older (18-24 months) C57BL/6J mice during undisturbed 24 h, and after a 6-h sleep deprivation (SD). As expected, older mice slept more but, in contrast to humans, absolute NREM sleep EEG slow-wave activity (SWA, spectral power density between 0.5-4 Hz) was higher in the older mice, as compared to the young controls. Furthermore, slow waves in the older mice were characterized by increased amplitude, steeper slopes and fewer multipeak waves, indicating increased synchronization of cortical neurons in aging, opposite to what was found in humans. Our results suggest that older mice, in contrast to elderly humans, live under a high sleep pressure.
Effects of Aging on Cortical Neural Dynamics and Local Sleep Homeostasis in Mice.
Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture.SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex.
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.
Cortical region-specific sleep homeostasis in mice: effects of time of day and waking experience.
Sleep-wake history, wake behaviors, lighting conditions, and circadian time influence sleep, but neither their relative contribution nor the underlying mechanisms are fully understood. The dynamics of electroencephalogram (EEG) slow-wave activity (SWA) during sleep can be described using the two-process model, whereby the parameters of homeostatic Process S are estimated using empirical EEG SWA (0.5-4 Hz) in nonrapid eye movement sleep (NREMS), and the 24 hr distribution of vigilance states. We hypothesized that the influence of extrinsic factors on sleep homeostasis, such as the time of day or wake behavior, would manifest in systematic deviations between empirical SWA and model predictions. To test this hypothesis, we performed parameter estimation and tested model predictions using NREMS SWA derived from continuous EEG recordings from the frontal and occipital cortex in mice. The animals showed prolonged wake periods, followed by consolidated sleep, both during the dark and light phases, and wakefulness primarily consisted of voluntary wheel running, learning a new motor skill or novel object exploration. Simulated SWA matched empirical levels well across conditions, and neither waking experience nor time of day had a significant influence on the fit between data and simulation. However, we consistently observed that Process S declined during sleep significantly faster in the frontal than in the occipital area of the neocortex. The striking resilience of the model to specific wake behaviors, lighting conditions, and time of day suggests that intrinsic factors underpinning the dynamics of Process S are robust to extrinsic influences, despite their major role in shaping the overall amount and distribution of vigilance states across 24 hr.
Assessment of left atrial volumes at 1.5 Tesla and 3 Tesla using FLASH and SSFP cine imaging.
PURPOSE: To investigate left atrial volumes and function and their variability in healthy volunteers using steady state free precession (SSFP) and fast low angle shot (FLASH) sequences at both 1.5 and 3 T using both the short-axis and biplane area-length methods. MATERIALS AND METHODS: Ten healthy volunteers underwent CMR at both 1.5 and 3 Tesla. The biplane area-length method utilized volumes from the horizontal and vertical long axis images. RESULTS: There were no significant differences between left atrial short-axis volumes or function between 1.5 and 3 T assessed using either FLASH or SSFP sequences. The biplane area-length method underestimated maximal left atrial volume using FLASH by 12 mL at 3 T (18%) and by 10 mL (14%) at 1.5 T (p = 0.003 and p = 0.05 respectively). Variability was larger for left atrial measurements using the biplane area-length method. CONCLUSION: Field strength had no effect on left atrial volume and function assessment using either FLASH or SSFP. The use of the short-axis method for the acquisition of left atrial parameters is more reproducible than the biplane area-length for serial measurements.