Gina Johnson
Sleep is a biological rhythm that arises from multiple brain structures and neurotransmitter systems. Despite extensive research, many of the mechanisms underlying this complex behaviour remain poorly understood. Sleep in mice consists of three stages: WAKE, non-REM, and REM. These stages can be identified by inspecting electroencephalogram (EEG) and electromyogram (EMG) signals. Traditionally, sleep stage scoring has been conducted through manual inspection by human experts, which is time-consuming and requires specialised knowledge. To address this issue, automated sleep stage scoring methods have been proposed, such as MC-SleepNet, which combines two types of deep neural networks to achieve higher accuracy. Additionally, video-tracking methods have been employed to assess sleep/wake behaviour in mice, providing a non-invasive approach that can be easily incorporated into ongoing screening programmes. By studying the sleep patterns of mice, researchers aim to understand the common features and possible functions of sleep across different species, as well as identify any unique characteristics that may have evolved in specific environments.
| Characteristics | Values |
|---|---|
| Method | Video-tracking, EEG/EMG, MC-SleepNet |
| Equipment | Cameras, digital hard drive recorder, monitor, ANY-maze software |
| Sleep Stages | WAKE, non-REM, REM |
| Factors Affecting Sleep | Age, sex, light, sedatives, stimulants, species, group size |
| Sleep Architecture | Slow-wave sleep (SWS), rapid eye movement (REM) sleep |
| Sleep Duration | Older mice sleep more than younger mice |
| Sleep Quality | Sleep fragmentation occurs in older mice |
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What You'll Learn
Video-tracking methods
In one study, mice were housed in light-tight chambers with light provided by a halogen light source through fibre optic cables. Miniature NIR cameras were mounted above each individual cage and connected to a digital hard drive recorder and monitor. Video data was then extracted and analysed offline using commercially available video-tracking software. This method allows for the simultaneous evaluation of additional behavioural repertoires associated with changes in sleep and wakefulness, such as the distance travelled or the time spent in certain areas of the cage.
Another study used a similar video-tracking approach to discriminate rapid eye movement (REM) from non-REM (NREM) sleep. Mouse behaviour was continuously recorded by digital video at 10 frames per second, and six variables were extracted from the video for each 10-second epoch. These variables included the intra-epoch mean of velocity, aspect ratio, and area of the mouse, as well as the intra-epoch standard deviation of the same variables.
A novel automated scoring method named "MC-SleepNet" combines two types of deep neural networks and has been shown to accurately score sleep stages in mice with an accuracy of 96.6%. This method has been evaluated using a large-scale dataset containing the sleep records of 4,200 phenotypically wild-type healthy mice, demonstrating its robustness and accuracy.
In addition to these video-tracking methods, there are also non-invasive methods for tracking eye movements during sleep in mice, such as electrooculography (EOG) and video-oculography. These methods can be used to track eye movements in head-fixed animals, but they have limitations such as the need for the eye to be open during recording or the inability to directly measure eye movements.
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EEG/EMG recordings
Electroencephalography (EEG) and electromyography (EMG) are pivotal techniques used to study the homeodynamics and circuitry of sleep-wake regulation in mice. The EEG/EMG recording setup is used to determine the sleep amount and sleep/wake profile of mice under baseline conditions or after treatment with substances like caffeine.
EEG is a technique that involves recording epidural electroencephalograms to detect different sleep-wake states in animals. In the case of mice, steel screws are implanted over the frontal cortical area and the parietal area of one hemisphere for monitoring EEG signals. This allows for the detection of brain waves and the differentiation between non-rapid eye movement (Non-REM or NREM) sleep and REM sleep. NREM sleep is characterised by large, slow brain waves with delta activity below 4 Hz, while REM sleep exhibits a shift to a rapid low-voltage EEG in the theta range between 6 and 10 Hz.
EMG activity is monitored through the bilateral placement of wires in the neck muscles of the mice. This measures muscle activity, which helps differentiate between active and inactive states, providing additional context to the EEG data.
EEG and EMG recordings can be performed over multiple days to assess the effects of substances or interventions on the sleep-wake behaviour of mice. For example, a study may involve recording EEG and EMG for two consecutive days, with the administration of a substance on the second day, to evaluate its impact on sleep patterns.
Furthermore, high-density EEG (HD-EEG) recordings have been performed over nine continuous days in mice under chronic sleep restriction conditions. These HD-EEG recordings provide detailed data on frontal and parietal EEG activity, allowing for the investigation of oscillatory activities, such as slow waves and spindles, across different cortical regions.
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Sleep patterns in young vs old mice
Sleep patterns in mice, as in humans, change throughout life. In humans, the highest density of slow waves moves from the occipital cortex in preschoolers to centro-parietal areas during adolescence, and to frontal areas in adulthood. Middle-aged humans show a reduced sleep efficiency, duration, slow-wave density, and a reduced amplitude of slow waves compared to young adults.
In mice, studies have shown conflicting results. One study compared EEG recordings of the somatosensory cortex of 6-month-old and 18-24-month-old male mice and found an increase in sleep quantity and delta-range power in the older group. Another study found that mice of the same strain showed only a non-significant trend for an increase in their daily amount of non-REM sleep from 3 to 6 to 12 months, with a significant decline at 2 years compared to 1 year.
Another study performed in C57BL/6J mice with LFP recordings from motor and visual cortices in 4-and-a-half-month-old, 1-year-old, and 2-year-old mice showed a linear increase in total sleep time with age. The same study also showed that the amplitude of slow waves was larger in the younger group compared to the older groups, but the slow wave incidence was only significantly increased in the 2-year-old group.
In the light phase, 3-month-old and 1-year-old mice spent similar amounts of time in sleep and wake states, except that the 1-year-old mice spent significantly less time in REM sleep at the beginning and end of each period. In the dark phase, older mice spent less time awake and more time in SWS. The increase in total sleep duration was mainly due to an increase in the number of short (less than a minute) sleep episodes during the dark phase.
Different mouse strains show different sleep patterns and are affected differently by age, so it is important to compare results of studies performed in the same mouse strain.
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Sleep patterns in male vs female mice
Sleep studies in mice are important to understand the common features and functions of sleep, as well as the differences in sleep patterns between species. The house mouse (Mus musculus) and the spiny mouse (Acomys cahirinus) are two species that have been extensively studied for their sleep and diurnal patterns.
When it comes to sleep patterns in male versus female mice, there are some differences to note. In a study on spiny mice, it was observed that male mice exhibited higher activity with a running wheel during the late night when in a group of 5, compared to smaller groups or when alone. On the other hand, female spiny mice were more active with the wheel during the late night when alone, as compared to being in groups. This indicates that the presence of other mice influenced the sleep patterns of these mice, with males being more active in larger groups and females being more active when alone.
Additionally, it has been found that male mice whose mothers had a low-protein diet during pregnancy slept longer at night compared to normal mice. This suggests that maternal diet can impact the sleep patterns of male offspring, and further research is needed to understand the effect on female offspring.
To track and study sleep patterns in male and female mice, various methods can be employed:
- Video-tracking: This involves using digital cameras to record mouse behaviour over a period of time. The absence of locomotor activity is one indicator of sleep, but it is not equivalent to sleep, and more advanced methods are often used in conjunction.
- EEG (electroencephalogram) and EMG (electromyogram): These tools measure brain activity and muscle activity, respectively, and can provide more accurate data on sleep patterns by distinguishing between REM (rapid eye movement) and non-REM sleep.
- Piezoelectric systems: This non-invasive method has been used to monitor sleep in mice and can provide insights into sleep amounts and sleep bout length.
By utilizing these methods and studying sleep patterns in both male and female mice, researchers can gain a better understanding of the variability in mammalian sleep and the factors that influence it.
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Sleep patterns in house mice vs spiny mice
Sleep patterns in mice can be studied using a variety of methods, including non-invasive piezoelectric systems, EEG/EMG, and infrared (IR) cameras. These methods allow for the analysis of sleep architecture, which includes the characterization of sleep and wake states, as well as the identification of unique phenomena and behaviours associated with sleep and circadian rhythms.
One such study compared the sleep and diurnal patterns of house mice (Mus musculus) and spiny mice (Acomys cahirinus). The house mice used in the study were specifically the outbred Swiss Webster (SW) and the inbred C57BL/6J (BL6) strains, while the spiny mice were A. cahirinus. The study found that both species were primarily nocturnal, but exhibited distinct behavioural patterns. The activity of A. cahirinus increased sharply at dark onset but decreased sharply just two hours later under group and individual housing conditions. This decrease in activity two hours after dark onset was widespread in A. cahirinus and was consistent across different methods of sleep analysis. One possible explanation for this shorter period of consolidated wakefulness is the natural high foraging ability of A. cahirinus relative to other rodents.
In terms of sex differences, male spiny mice (A. cahirinus) exhibited differences in activity levels compared to male house mice (M. musculus), while female spiny mice showed highly variable activity levels with no significant differences between species. Additionally, spiny mice were observed to be more social than house mice, often sitting huddled together in large groups during periods of low activity or sleep.
Overall, these findings suggest that A. cahirinus has differing sleep physiology compared to house mice, highlighting the importance of studying sleep diversity among murid rodents to better understand the common features and possible functions of sleep across different species.
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Frequently asked questions
Sleep in mice consists of three stages: WAKE, non-REM (non-rapid eye movement sleep), and REM (rapid eye movement sleep). These stages are identified by electroencephalogram (EEG) and electromyogram (EMG) signals.
Older adult mice sleep more than young ones, but only during the dark phase of the sleep-wake cycle. Sleep fragmentation and sleep during the active phase (dark phase) were higher in older mice.
Yes, sex differences in activity were observed between A. cahirinus females and males. However, these differences were not observed in the house mouse (Mus musculus).
Several methods can be used, including non-invasive piezoelectric systems, EEG/EMG, infrared (IR) cameras, and video-tracking.
Manual sleep stage scoring requires considerable time, expertise, and effort. Automated scoring methods have been proposed, but they have limitations in accuracy and robustness against individual differences and noise.
