The authors would like to acknowledge the NIH Fellows Editorial Board for their editorial assistance. This research was funded by the Intramural Research Program of the NIMH (ZIA MH00889). RMS was also supported by a FRAXA Postdoctoral Fellowship.

All the procedures were approved by the National Institute of Mental Health Animal Care and Use Committee and performed in accordance with the National Institutes of Health Guidelines on the Care and Use of Animals.
1. Setting up the Sleep Detection Units
<ol>
	<li>Purchase the desired number of units and software.</li>
	<li>Follow the instructions to set up the monitoring systems.
	<ol>
		<li>Align a detector opposite to an emitter. Make sure the infrared beams are facing inwards and are aligned at the same height.</li>
		<li>Use the provided screws to position the detectors and emitters at the desired height on the metal stand. This height should be adjusted so that the bedding of the cage is below the level of the infrared beams, but the beam is at the proper height to detect the animal&#39;s activity. This creates an internal area of 27 cm &#215; 32 cm (10.625 in &#215; 12.75 in).
		<ol>
			<li>If more screws are needed, purchase more at a hardware store (6-32 &#188; in Pan Head Screw).</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Connect each detector with each emitter. Connect the emitter to the provided hub linked to the receiver. Perform this for both the x and the y planes. Repeat this step for all setups.</li>
	<li>Connect the receiver to a computer with the provided USB hub.</li>
</ol>
2. Software Setup
<ol>
	<li>Install the analysis software and select the provided hardware configuration file as the default. The hardware configuration file should only be changed by the company.</li>
	<li>Click File | Open Experiment Configuration. Open the default experiment configuration.</li>
	<li>Click Experiment | Properties.</li>
	<li>Click the Scan tab. Change the Scan Rate to 10 s.</li>
	<li>Click the Activity tab. Change the activity sampling rate to 10 s.</li>
	<li>Click File | Save Experiment As to save these configuration settings for future experiments.</li>
</ol>
3. Animal Setup
<ol>
	<li>Singly house the mice in clean cages that are 31 cm (12.25 in) long and 16.5 cm (6.5 in) wide. To prevent the mouse from building up the bedding and obstructing the beams, use bedding at a depth of 3 mm. Do not provide additional nesting material for the mice.</li>
	<li>Provide the mice with access to food and water ad libitum by means of a wire feeder that rests in the top of the cage out of the way of the beams. If necessary, refill the food and change the water bottles when cages are changed every 3-5 days throughout the duration of the study.</li>
	<li>Align the mouse cage inside the infrared beam set up, ensuring that it rests in approximately the middle of the beams for full coverage.</li>
	<li>Ensure the light dark cycle of the room is set to mirror the light dark cycle of the normal housing conditions of the mice, or change as desired based on the experiment.</li>
</ol>
4. Drug Preparation and Injections
<ol>
	<li>Obtain sterile water and sterile cyclodextrin.</li>
	<li>For all injections, use a 1 mL syringe with a 25.5-30.5 G hypodermic needle. A new sterile needle and syringe should be used for each mouse.</li>
	<li>To reduce the time between injections, assemble all syringes in advance.</li>
	<li>For cyclodextrin injections: prepare cyclodextrin solution by adding 3 g of cyclodextrin to 10 mL of water to make a 30% cyclodextrin solution.</li>
	<li>Administer 0.3 mL of either saline or cyclodextrin via IP injection.</li>
</ol>
5. Software to Record Sleep
<ol>
	<li>Open the default hardware configuration file.</li>
	<li>Click File | Open Experiment Configuration. Open the desired or default experiment configuration.</li>
	<li>Click Experiment | Setup.
	<ol>
		<li>Designate the location to save the data file as well as a location to save the backup file. The software requires that the data file be stored in the Program Files under the specific program folder. 
		NOTE: Given that some computers view the Program Files as sensitive, access to the data file may not be possible after the experiment. Therefore, it is recommended to save the backup file to another, non-sensitive area on the local computer.</li>
		<li>Designate the animal ID to each sleep chamber and enter the weight of the animal if desired. If a chamber is not being used in the experiment, unchecking the box will deactivate that chamber. Once the identification information is entered, click Done.</li>
	</ol>
	</li>
	<li>Click File | Save Experiment As to save the current experiment configuration under the desired file name.</li>
	<li>Click Experiment | Run or F5 to start the recording. Wait for a 10 s epoch to make sure that all chambers are picking up activity. As the animals were just injected, it is highly likely that the animals will be moving enough to be detected by the infrared beams.
	<ol>
		<li>If no activity is detected, try to move the mouse cage manually to ensure the beams pick up the movement. Continue troubleshooting or move to a working chamber if the activity is still not recorded. 
		NOTE: Run the experiment as soon as the injections are finished.</li>
	</ol>
	</li>
	<li>Cover the computer screens with an opaque cover to block the light. Cover the flashing lights on the activity meter.</li>
	<li>Run the experiment for 24 h. 
	NOTE: Because of the time necessary to perform the injections, it will not be a full 24 h. The injections should be performed at the same time daily. Sleep should not be recorded during injections.</li>
	<li>The following day, at the time of injections, click Experiment | Stop to end the recording. Click File | Export | Generate Subject CSVs to collect the raw data for each mouse. 
	NOTE: It may take some time to export, so do this immediately and then proceed to injections while the computer is processing.</li>
	<li>Click File | Export | Sleep to export the sleep file for each experiment by opening the raw .CDTA data file on any computer that has the software installed.
	<ol>
		<li>Under Detection Parameters Activity Source, ensure that both the x-axis and y-axis boxes are checked.</li>
		<li>Under Sleep Threshold Epochs, ensure that 4 epochs are selected.</li>
		<li>Under Sleep Threshold Activity Threshold, ensure that 0 counts are selected.</li>
		<li>Under Light/Dark Cycle, check the appropriate time for the light/dark cycle.</li>
		<li>Under Analysis Window, select the desired time for analysis. In the case of the injection studies, leave the Day as default. Set the Start Time as ExpSTART. Set the Duration as 24:00 for 24 h. Analysis using the software can be done for a maximum of 72 h.</li>
		<li>Save the configuration to save time for exporting data.</li>
		<li>Click Update.</li>
		<li>Click Generate CSV File and save the file to the desired location.</li>
	</ol>
	</li>
</ol>
6. Data Analysis
<ol>
	<li>For each recording session, open the sleep file. To assign the subject ID, open the individual CSV file for each chamber to determine the subject ID. Record the TOT sleep hh:mm:ss for both the light and the dark phases for all animals.
	<ol>
		<li>Check the Individual subject CSV file for inconsistencies indicating the failure of recording. If high beam counts are detected in one plane, but no counts are observed on the other plane, this indicates beam failure. 
		NOTE: The &#34;% sleeping&#34; for the light and dark phases is calculated over the total recording period, which includes both light and dark phases. For 12 h light/dark cycles, multiply this number by 2 to get the &#34;% sleeping&#34; in the 12 h light or dark phase. Given that the injection studies did not go for a full 24 h, the calculated &#34;% sleeping&#34; is not accurate. To generate the correct &#34;% sleeping&#34;, divide the &#34;TOT sleep hh:mm:ss&#34; by the &#34;Experiment elapsed time: hh:mm:ss,&#34; multiply by 2, and then multiply by 100 to get the percent. If injections were performed in the light phase, then only the light phase needs to be adjusted in this manner.</li>
	</ol>
	</li>
	<li>Since different days and phases are being compared with each other, analyze the percent sleep duration for each phase and each day.</li>
</ol>

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	<li>Picchioni, D., Reith, R. M., Nadel, J. L., Smith, C. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sleep,+plasticity+and+the+pathophysiology+of+neurodevelopmental+disorders:+the+potential+roles+of+protein+synthesis+and+other+cellular+processes.">Sleep, plasticity and the pathophysiology of neurodevelopmental disorders: the potential roles of protein synthesis and other cellular processes.</a> Brain sciences. 4, 150-201 (2014).</li><li>Ingvar, M. C., Maeder, P., Sokoloff, L., Smith, C. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+aging+on+local+rates+of+cerebral+protein+synthesis+in+rats.">The effects of aging on local rates of cerebral protein synthesis in rats.</a> Monographs in neural sciences. 11, 47-50 (1984).</li><li>Pack, A. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Novel+method+for+high-throughput+phenotyping+of+sleep+in+mice.">Novel method for high-throughput phenotyping of sleep in mice.</a> Physiological genomics. 28, 232-238 (2007).</li><li>Sare, R. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deficient+Sleep+in+Mouse+Models+of+Fragile+X+Syndrome.">Deficient Sleep in Mouse Models of Fragile X Syndrome.</a> Front Mol Neurosci. 10, (2017).</li><li>Alvarez, G. G., Ayas, N. 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V., Burgess, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+MusD+retrotransposon+insertion+in+the+mouse+Slc6a5+gene+causes+alterations+in+neuromuscular+junction+maturation+and+behavioral+phenotypes.">A MusD retrotransposon insertion in the mouse Slc6a5 gene causes alterations in neuromuscular junction maturation and behavioral phenotypes.</a> PloS one. 7, e30217 (2012).</li><li>Angelakos, C. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hyperactivity+and+male-specific+sleep+deficits+in+the+16p11.2+deletion+mouse+model+of+autism.">Hyperactivity and male-specific sleep deficits in the 16p11.2 deletion mouse model of autism.</a> Autism research: official journal of the International Society for Autism Research. 10, 572-584 (2017).</li><li>Fisher, S. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+assessment+of+sleep-wake+behavior+in+mice.">Rapid assessment of sleep-wake behavior in mice.</a> Journal of biological rhythms. 27, 48-58 (2012).</li><li>Mang, G. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+a+piezoelectric+system+as+an+alternative+to+electroencephalogram/+electromyogram+recordings+in+mouse+sleep+studies.">Evaluation of a piezoelectric system as an alternative to electroencephalogram/ electromyogram recordings in mouse sleep studies.</a> Sleep. 37, 1383-1392 (2014).</li><li>Chen, L., Toth, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fragile+X+mice+develop+sensory+hyperreactivity+to+auditory+stimuli.">Fragile X mice develop sensory hyperreactivity to auditory stimuli.</a> Neuroscience. 103, 1043-1050 (2001).</li></ol>

The authors have nothing to disclose.

Here, we present a noninvasive, high-throughput method for determination of sleep duration based on activity monitoring in the home-cage. This method of assessment of total sleep time has been validated against EEG studies3. Activity-based home-cage monitoring is simple, noninvasive, and applicable to population studies in large numbers of animals. It is limited in that it cannot give detailed information about sleep (such as sleep bout duration and sleep stages).
Pitfa...

Sleep has important functions for the restoration of the body and brain following the daily burden of wakefulness1. It has been shown that sleep plays a role in memory retention and general brain plasticity1. The EEG is the gold standard to detect sleep2. In rodents, EEG monitoring requires surgical implantation of electrodes affixed to a head-mount, after which the animal needs a period of time to recover2. After the recovery, the animal is attached to the recording device and is given another period of habituation2. Because of these necessary periods of recovery and habituation, EEG is time consuming and laborious and cannot be reasonably performed on a large scale. Additionally, the surgical procedure of electrode implantation carries an inherent risk to the animal. Finally, the data analysis for scoring sleep in EEG studies is also very laborious. An alternative, non-invasive, high-throughput method of sleep monitoring would greatly aid rodent sleep research.
An activity-based home-cage monitoring system used to detect sleep addresses the limitations of EEG studies. The simple premise is that an inactive animal is likely a sleeping animal. It has been shown that 40 s of continuous inactivity (binned in 10 s epochs) is a reliable measure of sleep as measured with an EEG (shown to have 88-94% agreement)3. Home-cage monitoring systems can be used to study large groups of animals with minimal setup time. We have shown that it takes animals approximately one day to habituate to individual housing in the home-cage monitoring system4 in contrast to the weeks of recovery needed for EEG studies2. In addition, some setups can also detect physiological parameters such as core body temperature, heart rate, activity, and feeding. Temperature and heart rate are determined from the implantation of a small transmitter. These parameters can provide more information about the mouse and may be used in parallel with the sleep recording to further add to our understanding of sleep and how it is affected.
While it is a powerful tool, there are some limitations to the types of data that can be acquired from activity-based home-cage monitoring. EEG studies can differentiate between REM and non-REM sleep, which may be important for a deeper understanding of sleep architecture. Activity-based home-cage monitoring systems can only provide data for total sleep duration. In addition, although the output for activity-based home-cage monitoring gives information about sleep bout duration, we cannot accurately assess bout duration because of the inherent limitation of 40 s intervals3. Despite these limitations, home-cage monitoring of sleep duration provides an important biological measure that may influence many downstream factors including the animal&#39;s health and behavior5.
Activity-based home-cage monitoring has been used to detect sleep in many studies indicating its versatility. We cite a sample of these studies4,6,7,8,9,10,11,12. In addition to the method presented, there are other methods of detecting sleep via activity-based monitoring, each containing its own limitations13,14. Some of these studies examine long periods of uninterrupted sleep (72 h) while some examine sleep in blocks of 24 h. In this study, we present sleep analysis for each 24 h period after the response to daily intraperitoneal (IP) injections and to periodic cage changes in a mouse model of fragile X syndrome (Fmr1 KO mice). We chose Fmr1 KO mice because they have reduced sleep4 and are hypothesized to be hyper-reactive to sensory information15. Our data highlight the ability to detect changes in sleep patterns in response to a stressful event. This method is ideal for obtaining general information about sleep in large cohorts of mice. The method can be useful for understanding the effects of specific genetic alterations on sleep, the effects of pharmacological treatments, or responses to events, such as a stressor. In addition, the method provides a simple means of screening for a response before initiating more involved studies.

<table><tbody><tr><td>Comprehensive Lab Animal Monitoring System (CLAMS)</td><td>Columbus Instruments</td><td></td><td>Equipment and software to analyze sleep duration</td></tr><tr><td>Captisol Research Grade</td><td>Captisol</td><td>RC-0C7-100</td><td>Captisol for dissolving hydrophobic compounds</td></tr><tr><td>30 G BD Needle 1/2 inch</td><td>BD</td><td>305106</td><td>Needle for injections</td></tr><tr><td>BD Disposable Syringes</td><td>Fisher</td><td>14-823-30</td><td>Syringes for injections</td></tr><tr><td>B6.129P2-Fmr1tm1Cgr/J</td><td>Jackson Labs</td><td>3025</td><td>Fmr1 KO mice</td></tr><tr><td>Super Mouse 750 Mouse Cage</td><td>Lab Products, Inc.&amp;nbsp;</td><td></td><td>Homecages for the mice</td></tr><tr><td>SANI-Chips Bedding</td><td>PJ Murphys</td><td></td><td>Bedding for the mice</td></tr></tbody></table>

noninvasive, high-throughput determination of sleep duration in rodents

Traditionally, sleep is monitored by an electroencephalogram (EEG). EEG studies in rodents require surgical implantation of the electrodes followed by a long recovery period. To perform an EEG recording, the animal is connected to a receiver, creating an unnatural tether to the head-mount. EEG monitoring is time consuming, carries risk to the animal, and is not a completely natural setting for the measurement of sleep. Alternative methods to detect sleep, particularly in a high-throughput fashion, would greatly advance the field of sleep research. Here, we describe a validated method for detecting sleep via activity-based home-cage monitoring. Previous studies have shown that sleep assessed via this method has a high degree of agreement with sleep defined by traditional EEG-based measures. Whereas this method is validated for total sleep time, it is important to note that sleep bout duration should be assessed by an EEG which has better temporal resolution. The EEG can also differentiate rapid eye movement (REM) and non-REM sleep, giving more detail about the exact nature of sleep. Nevertheless, activity-based sleep determination can be used to analyze multiple days of undisturbed sleep and to assess sleep as a response to an acute event (like stress). Here, we show the power of this system to detect the response of mice to daily intraperitoneal injections.

To determine the effect of daily injections on sleep and whether animals habituate to the injections, we performed daily IP injections for 14 consecutive days at 9:00 AM (light cycle began at 6:00 AM) and recorded sleep duration in 12 Fmr1 KO C57Bl/6J mice. We used a within subjects&#39; design, injecting each animal with normal saline for 4 consecutive days (Days 1-4) and then 30% cyclodextrin for the following ten consecutive days (Days 5-14). Cyclodextrin was selected because ...

Watch this Scientific Journal Video about Noninvasive, High-throughput Determination of Sleep Duration in Rodents at JoVE.com

Noninvasive, High-throughput Determination of Sleep Duration in Rodents

We describe a high-throughput method of measuring sleep by means of activity-based home-cage monitoring. This method offers advantages over traditional EEG-based methods. It is well validated for the determination of total sleep duration and can be a powerful tool to monitor sleep in rodent models of human disease.

Traditionally, sleep is monitored by an electroencephalogram (EEG). EEG studies in rodents require surgical implantation of the electrodes followed by a ...

noninvasive-high-throughput-determination-of-sleep-duration-in-rodents

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Behavior

7.8K Views.  National Institutes of Health. We describe a high-throughput method of measuring sleep by means of activity-based home-cage monitoring. This method offers advantages over traditional EEG-based methods. It is well validated for the determination of total sleep duration and can be a powerful tool to monitor sleep in rodent models of human disease.

Video: Noninvasive, High-throughput Determination of Sleep Duration in Rodents

Measuring Circadian and Acute Light Responses in Mice using Wheel Running Activity

Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day)1, 2. They are responsible for timing our sleep/wake cycles and hormone secretion. Since this timing is not precisely 24-hours, it is synchronized to the solar day by light input. This is accomplished via photic input from the retina to the suprachiasmatic nucleus (SCN) which serves as the master pacemaker synchronizing peripheral clocks in other regions of the brain and peripheral tissues to the environmental light dark cycle3-7. The alignment of rhythms to this environmental light dark cycle organizes particular physiological events to the correct temporal niche, which is crucial for survival8. For example, mice sleep during the day and are active at night. This ability to consolidate activity to either the light or dark portion of the day is referred to as circadian photoentrainment and requires light input to the circadian clock9. Activity of mice at night is robust particularly in the presence of a running wheel. Measuring this behavior is a minimally invasive method that can be used to evaluate the functionality of the circadian system as well as light input to this system. Methods that will covered here are used to examine the circadian clock, light input to this system, as well as the direct influence of light on wheel running behavior.

This article will review methods that can be used to determine circadian function and light responsiveness in mice.

Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day)1, 2.  They ...

Neuroscience

Chronic Sleep Deprivation in Mouse Pups by Means of Gentle Handling

Sleep is critical for proper development and neural plasticity. Moreover, abnormal sleep patterns are characteristic of many neurodevelopmental disorders. Studying how chronic sleep restriction during development can affect adult behavior may add to our understanding of the emergence of behavioral symptoms of neurodevelopmental disorders. While there are many methods that can be used to restrict sleep in rodents including forced locomotion, constant disruption, presentation of an aversive stimulus, or electric shock, many of these methods are very stressful and cannot be used in neonatal mice. Here, we describe gentle handling, a sleep deprivation technique that can be used chronically throughout development and into adulthood to achieve sleep restriction. Gentle handling involves close observation of the mice throughout the sleep deprivation period and requires the researcher to gently prod the animals whenever they are inactive or display behaviors associated with sleep. Coupled with EEG recordings, gentle handling could be used to selectively disrupt a specific phase of sleep such as rapid eye movement (REM) sleep. The technique of gentle handling is a powerful tool for the study of the effects of chronic sleep restriction even in neonatal mice that circumvents many of the more stressful procedures used for sleep deprivation.

We describe a sleep deprivation technique known as gentle handling where investigators gently prod mice any time sleep behavior is observed. This method is a powerful tool that allows researchers to study the effects that chronic sleep restriction throughout development can have on future brain physiology and behavior.

Sleep is critical for proper development and neural plasticity. Moreover, abnormal sleep patterns are characteristic of many neurodevelopmental disorders. ...

Simultaneous Electroencephalography, Real-time Measurement of Lactate Concentration and Optogenetic Manipulation of Neuronal Activity in the Rodent Cerebral Cortex

Although the brain represents less than 5% of the body by mass, it utilizes approximately one quarter of the glucose used by the body at rest1. The function of non rapid eye movement sleep (NREMS), the largest portion of sleep by time, is uncertain. However, one salient feature of NREMS is a significant reduction in the rate of cerebral glucose utilization relative to wakefulness2-4. This and other findings have led to the widely held belief that sleep serves a function related to cerebral metabolism. Yet, the mechanisms underlying the reduction in cerebral glucose metabolism during NREMS remain to be elucidated.
	One phenomenon associated with NREMS that might impact cerebral metabolic rate is the occurrence of slow waves, oscillations at frequencies less than 4 Hz, in the electroencephalogram5,6. These slow waves detected at the level of the skull or cerebral cortical surface reflect the oscillations of underlying neurons between a depolarized/up state and a hyperpolarized/down state7. During the down state, cells do not undergo action potentials for intervals of up to several hundred milliseconds. Restoration of ionic concentration gradients subsequent to action potentials represents a significant metabolic load on the cell8; absence of action potentials during down states associated with NREMS may contribute to reduced metabolism relative to wake.
	Two technical challenges had to be addressed in order for this hypothetical relationship to be tested. First, it was necessary to measure cerebral glycolytic metabolism with a temporal resolution reflective of the dynamics of the cerebral EEG (that is, over seconds rather than minutes). To do so, we measured the concentration of lactate, the product of aerobic glycolysis, and therefore a readout of the rate of glucose metabolism in the brains of mice. Lactate was measured using a lactate oxidase based real time sensor embedded in the frontal cortex. The sensing mechanism consists of a platinum-iridium electrode surrounded by a layer of lactate oxidase molecules. Metabolism of lactate by lactate oxidase produces hydrogen peroxide, which produces a current in the platinum-iridium electrode. So a ramping up of cerebral glycolysis provides an increase in the concentration of substrate for lactate oxidase, which then is reflected in increased current at the sensing electrode. It was additionally necessary to measure these variables while manipulating the excitability of the cerebral cortex, in order to isolate this variable from other facets of NREMS.
	We devised an experimental system for simultaneous measurement of neuronal activity via the elecetroencephalogram, measurement of glycolytic flux via a lactate biosensor, and manipulation of cerebral cortical neuronal activity via optogenetic activation of pyramidal neurons. We have utilized this system to document the relationship between sleep-related electroencephalographic waveforms and the moment-to-moment dynamics of lactate concentration in the cerebral cortex. The protocol may be useful for any individual interested in studying, in freely behaving rodents, the relationship between neuronal activity measured at the electroencephalographic level and cellular energetics within the brain.

A procedure is described for manipulating the activity of cerebral cortical pyramidal neurons optogenetically while the electroencephalogram, electromyogram, and cerebral lactate concentration are monitored. Experimental recordings are performed on cable-tethered mice while they undergo spontaneous sleep/wake cycles. Optogenetic equipment is assembled in our laboratory; recording equipment is commercially available.

Although the brain represents less than 5% of the body  by mass, it utilizes approximately one quarter of the glucose used by the body  at rest1. The ...

Advancing Sleep Disorder Treatments: A Drosophila-Based Screening Approach

High-Throughput Small Molecule Drug Screening For Age-Related Sleep Disorders Using Drosophila melanogaster

Sleep, an essential component of health and overall well-being, often presents challenges for older individuals who frequently experience sleep disorders characterized by shortened sleep duration and fragmented patterns. These sleep disruptions also correlate with an increased risk of various illnesses in the elderly, including diabetes, cardiovascular diseases, and psychological disorders. Unfortunately, existing drugs for sleep disorders are associated with significant side effects such as cognitive impairment and addiction. Consequently, the development of new, safer, and more effective sleep disorder medications is urgently needed. However, the high cost and lengthy experimental duration of current drug screening methods remain limiting factors.
This protocol describes a cost-effective and high-throughput screening method that utilizes Drosophila melanogaster, a species with a highly conserved sleep regulation mechanism compared to mammals, making it an ideal model for studying sleep disorders in the elderly. By administering various small compounds to aged flies, we can assess their effects on sleep disorders. The sleep behaviors of these flies are recorded using an infrared monitoring device and analyzed with the open-source data package Sleep and Circadian Analysis MATLAB Program 2020 (SCAMP2020). This protocol offers a low-cost, reproducible, and efficient screening approach for sleep regulation. Fruit flies, due to their short life cycle, low husbandry cost, and ease of handling, serve as excellent subjects for this method. As an illustration, Reserpine, one of the tested drugs, demonstrated the ability to promote sleep duration in elderly flies, highlighting the effectiveness of this protocol.

Author Spotlight: Overcoming Challenges in Drosophila Sleep Measurement Using DAM System 

Presented is a protocol for high-throughput drug screening to improve sleep by monitoring the sleep behavior of fruit flies in an elderly Drosophila model.

Sleep, an essential component of health and overall well-being, often presents challenges for older individuals who frequently experience sleep disorders ...

Polygraphic Recording Procedure for Measuring Sleep in Mice

Recording of the epidural electroencephalogram (EEG) and electromyogram (EMG) in small animals, like mice and rats, has been pivotal to study the homeodynamics and circuitry of sleep-wake regulation. In many laboratories, a cable-based sleep recording system is used to monitor the EEG and EMG in freely behaving mice in combination with computer software for automatic scoring of the vigilance states on the basis of power spectrum analysis of EEG data. A description of this system is detailed herein. Steel screws are implanted over the frontal cortical area and the parietal area of 1 hemisphere for monitoring EEG signals. In addition, EMG activity is monitored by the bilateral placement of wires in both neck muscles. Non-rapid eye movement (Non-REM; NREM) sleep is characterized by large, slow brain waves with delta activity below 4 Hz in the EEG, whereas a shift from low-frequency delta activity to a rapid low-voltage EEG in the theta range between 6 and 10 Hz can be observed at the transition from NREM to REM sleep. By contrast, wakefulness is identified by low- to moderate-voltage brain waves in the EEG trace and significant EMG activity.

The recording of electroencephalogram (EEG) and electromyogram (EMG) in freely behaving mice is a critical step to correlate behavior and physiology with sleep and wakefulness. The experimental protocol described herein provides a cable-based system for acquiring EEG and EMG recordings in mice.

Recording of the epidural electroencephalogram (EEG) and electromyogram (EMG) in small animals, like mice and rats, has been pivotal to study the ...

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Three vigilance states dominate mammalian life: wakefulness, non-rapid eye movement (non-REM) sleep, and REM sleep. As more neural correlates of behavior are identified in freely moving animals, this three-fold subdivision becomes too simplistic. During wakefulness, ensembles of global and local cortical activities, together with peripheral parameters such as pupillary diameter and sympathovagal balance, define various degrees of arousal. It remains unclear the extent to which sleep also forms a continuum of brain states-within which the degree of resilience to sensory stimuli and arousability, and perhaps other sleep functions, vary gradually-and how peripheral physiological states co-vary. Research advancing the methods to monitor multiple parameters during sleep, as well as attributing to constellations of these functional attributes, is central to refining our understanding of sleep as a multifunctional process during which many beneficial effects must be executed. Identifying novel parameters characterizing sleep states will open opportunities for novel diagnostic avenues in sleep disorders.
We present a procedure to describe dynamic variations of mouse non-REM sleep states via the combined monitoring and analysis of electroencephalogram (EEG)/electrocorticogram (ECoG), electromyogram (EMG), and electrocardiogram (ECG) signals using standard polysomnographic recording techniques. Using this approach, we found that mouse non-REM sleep is organized into cycles of coordinated neural and cardiac oscillations that generate successive 25-s intervals of high and low fragility to external stimuli. Therefore, central and autonomic nervous systems are coordinated to form behaviorally distinct sleep states during consolidated non-REM sleep. We present surgical manipulations for polysomnographic (i.e., EEG/EMG combined with ECG) monitoring to track these cycles in the freely sleeping mouse, the analysis to quantify their dynamics, and the acoustic stimulation protocols to assess their role in the likelihood of waking up. Our approach has already been extended to human sleep and promises to unravel common organizing principles of non-REM sleep states in mammals.

Here, we present experimental and analytical procedures to describe the temporal dynamics of the neural and cardiac variables of non-REM sleep in mice, which modulate sleep responsiveness to acoustic stimuli.

Three vigilance states dominate mammalian life: wakefulness, non-rapid eye movement (non-REM) sleep, and REM sleep. As more neural correlates of behavior ...

Optogenetic Manipulation of Neural Circuits During Monitoring Sleep/wakefulness States in Mice

In recent years, optogenetics has been widely used in many fields of neuroscientific research. In many cases, an opsin, such as channel rhodopsin 2 (ChR2), is expressed by a virus vector in a particular type of neuronal cells in various Cre-driver mice. Activation of these opsins is triggered by application of light pulses which are delivered by laser or LED through optic cables, and the effect of activation is observed with very high time resolution. Experimenters are able to acutely stimulate neurons while monitoring behavior or another physiological outcome in mice. Optogenetics can enable useful strategies to evaluate function of neuronal circuits in the regulation of sleep/wakefulness states in mice. Here we describe a technique for examining the effect of optogenetic manipulation of neurons with a specific chemical identity during electroencephalogram (EEG) and electromyogram (EMG) monitoring to evaluate the sleep stage of mice. As an example, we describe manipulation of GABAergic neurons in the bed nucleus of the stria terminalis (BNST). Acute optogenetic excitation of these neurons triggers a rapid transition to wakefulness when applied during NREM sleep. Optogenetic manipulation along with EEG/EMG recording can be applied to decipher the neuronal circuits that regulate sleep/wakefulness states.

Here, we describe methods of optogenetic manipulation of particular types of neurons during monitoring of sleep/wakefulness states in mice, presenting our recent work on the bed nucleus of the stria terminalis as an example.

In recent years, optogenetics has been widely used in many fields of neuroscientific research. In many cases, an opsin, such as channel rhodopsin 2 ...

The Sleep Nullifying Apparatus: A Highly Efficient Method of Sleep Depriving Drosophila

Sleep homeostasis, the increase in sleep observed following sleep loss, is one of the defining criteria used to identify sleep throughout the animal kingdom. As a consequence, sleep deprivation and sleep restriction are powerful tools that are commonly used to provide insight into sleep function. Nonetheless, sleep deprivation experiments are inherently problematic in that the deprivation stimulus itself may be the cause of observed changes in physiology and behavior. Accordingly, successful sleep deprivation techniques should keep animals awake and, ideally, result in a robust sleep rebound without also inducing a large number of unintended consequences. Here, we describe a sleep deprivation technique for Drosophila melanogaster. The Sleep Nullifying Apparatus (SNAP) administers a stimulus every 10s to induce negative geotaxis. Although the stimulus is predictable, the SNAP effectively prevents &#62;95% of nighttime sleep even in flies with high sleep drive. Importantly, the subsequent homeostatic response is very similar to that achieved using hand-deprivation. The timing and spacing of the stimuli can be modified to minimize sleep loss and thus examine non-specific effects of the stimulus on physiology and behavior. The SNAP can also be used for sleep restriction and to assess arousal thresholds. The SNAP is a powerful sleep disruption technique that can be used to better understand sleep function.

The Sleep Nullifying Apparatus: A Highly Efficient Method of Sleep Depriving Drosophila

Sleep deprivation is a powerful tool to investigate sleep function and regulation. We describe a protocol to sleep deprive Drosophila using the Sleep Nullifying Apparatus, and to determine the extent of rebound sleep induced by deprivation.

Sleep homeostasis, the increase in sleep observed following sleep loss, is one of the defining criteria used to identify sleep throughout the animal ...

Establishing a Device for Sleep Deprivation in Mice

Circadian rhythm disruption refers to the desynchronization between the external environment or behavior and the endogenous molecular clock, which significantly impairs health. Sleep deprivation is one of the most common causes of circadian rhythm disruption. Various modalities (e.g., platforms on the water, gentle handling, sliding bar chambers, rotating drums, orbital shakers, etc.) have been reported for inducing sleep deprivation in mice to investigate its effects on health. The current study introduces an alternative method for sleep deprivation in mice. An automated rocker platform-based device was designed that is cost-effective and efficiently disrupts sleep in group-housed mice at adjustable time intervals. This device induces characteristic changes of sleep deprivation with minimal stress response. Consequently, this method may prove useful for investigators interested in studying the effects and underlying mechanisms of sleep deprivation on the pathogenesis of multiple diseases. Moreover, it offers a cost-effective solution, particularly when multiple sleep deprivation devices are required to run in parallel.

The present protocol outlines a method for setting up a cost-effective rocker platform-based device used for inducing sleep deprivation in mice. This device has proven to be effective in causing disruptions in electroencephalogram (EEG)-evidenced sleep patterns, as well as inducing metabolic and molecular changes associated with sleep deprivation.

Circadian rhythm disruption refers to the desynchronization between the external environment or behavior and the endogenous molecular clock, which ...

Medicine

Automated Sleep Stage Scoring Tool for Rodents Using LightGBM

IntelliSleepScorer, a Software Package with a Graphic User Interface for Mice Automated Sleep Stage Scoring

Sleep stage scoring in rodents is the process of identifying the three stages: nonrapid eye movement sleep (NREM), rapid eye movement sleep (REM), and wake. Sleep stage scoring is crucial for studying sleep stage-specific measures and effects. 
Sleep patterns in rodents differ from those in humans, characterized by shorter episodes of NREM and REM interspaced by waking, and traditional manual sleep stage scoring by human experts is time-consuming. To address this issue, previous studies have used machine learning-based approaches to develop algorithms to automatically categorize sleep stages, but high-performing models with great generalizability are often not publicly available/cost-free nor user-friendly for non-trained sleep researchers. 
Therefore, we developed a machine learning-based LightGBM algorithm trained with a large dataset. To make the model available to sleep researchers without coding experience, a software tool named IntelliSleepScorer (v1.2- newest version) was developed based on the model, which features an easy-to-use graphic user interface. In this manuscript, we present step-by-step instructions for using the software to demonstrate a convenient and effective automatic sleep stage scoring tool in mice for sleep researchers.

Author Spotlight: IntelliSleepScorer &#8212; A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research

We present a software package with a graphic user interface for researchers without coding experience to score sleep stages in mice with a simple download and operation.

Sleep stage scoring in rodents is the process of identifying the three stages: nonrapid eye movement sleep (NREM), rapid eye movement sleep (REM), and ...

Noninvasive, High-throughput Determination of Sleep Duration in Rodents

Summary

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The Sleep Nullifying Apparatus: A Highly Efficient Method of Sleep Depriving Drosophila

Establishing a Device for Sleep Deprivation in Mice

IntelliSleepScorer, a Software Package with a Graphic User Interface for Mice Automated Sleep Stage Scoring