We thank Dr. Larry D. Frye for editorial help with this manuscript. This work was supported by Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research 24300129 (to M.L.), 25890005 (to Y.O.) and 26640025 (to Y.T.), the National Agriculture and Food Research Organization (to Y.U.), the World Premier International Research Center Initiative (WPI) from the Ministry of Education, Culture, Sports, Science, and Technology (to Y.O., Y.T., Y.U. and M.L.) and the Nestl&#233; Nutrition Council, Japan (to M.L.).

Ethics Statement: Procedures involving animal subjects have been approved by the Institutional Animal Experiment Committee at the University of Tsukuba.
1. Preparation of Electrodes and Cables for EEG/EMG Recordings
<ol>
	<li>Prepare EEG/EMG recording electrode according to the following procedure. 
	Note: The electrode is disposable and can be used only for 1 animal. Plan carefully the wiring configuration for all connectors. Place marks on the connectors for the correct orientation.
	<ol>
		<li>Solder each pin of a 4-pin header to a 2-cm stainless steel wire. In brief, hold one end of the wire to the pin, place a hot soldering iron onto the wire-pin joint, and melt some solder to ensure that just enough solder runs smoothly into the joint. Be careful not to apply too much heat to the pin; otherwise, the plastic around the pins will melt.</li>
		<li>Solder the free end of each of 2 wires attached to the pin header to the head of a 1.0-mm-diameter stainless steel screw. In brief, hold the free end of the wire to the thread below the screw head, place a hot soldering iron onto the wire-screw joint, and melt some solder to ensure that just enough solder runs smoothly into the joint. The 2 wires with screws serve as EEG recording electrodes, whereas the 2 wires without screws serve as EMG recording electrodes.</li>
		<li>Use scissors to strip off 1 mm of the insulation at the end of the EMG electrodes to increase the quality of the EMG signal.</li>
		<li>Completely cover all soldered pins with epoxy adhesive by using a thin wooden stick or tooth pick to reduce the electrical noise during EEG/EMG recordings.</li>
	</ol>
	</li>
	<li>Prepare a cable for connecting the electrode with the slip ring as described below. This cable can be reused.
	<ol>
		<li>Solder each pin of a 4-pin FFC/FPC connector with a wire of a 30-cm flat cable. In brief, hold the stripped end of the wire to the pin, place a hot soldering iron onto the wire-pin joint, and melt some solder to ensure that just enough solder runs smoothly into the joint. 
		Note: Choose the length of the flat cable which is appropriate for the height of the experimental animal cage used for EEG/EMG recordings.</li>
		<li>Solder crimp sockets to a tip of the wires on the other end of the flat cable. In brief, hold a crimp socket to the stripped free end of the wire, place a hot soldering iron onto the wire-socket joint, and melt some solder to ensure that just enough solder runs smoothly into the joint.</li>
		<li>Insert each crimp socket into a 4-position crimp housing.</li>
		<li>Completely cover the crimp sockets with epoxy adhesive by using a thin wooden stick or tooth pick.</li>
	</ol>
	</li>
</ol>
2. Implantation of Electrodes in the Mouse Head (Duration: Approx. 20 min)
<ol>
	<li>Sterilize all surgical tools in a hot bead sterilizer before the surgery. Anesthetize a male mouse (10 - 20 weeks old, 20 - 30 g) with an intraperitoneal injection of pentobarbital (50 mg/kg). After checking that the mouse is deeply anesthetized by pinching a toe, shave the hair on the head and neck with clippers.</li>
	<li>Move the mouse to the stereotaxic frame, and fix the head between the 2 ear bars. Apply petroleum jelly on the eyes to prevent dryness. Cleanse the shaved-skin with alcohol and cut it along the midline with a scalpel to expose the skull. Clip the skin to keep the surgical area open.</li>
	<li>By using a carbide cutter (drill size: 0.8-mm diameter), drill 2 holes into the skull, one over the frontal cortical area (1 mm anterior to bregma, 1.5 mm lateral to the midline) and the other over the parietal area (1 mm anterior to lambda, 1.5 mm lateral to midline) of the right hemisphere, according to stereotaxic coordinates of Paxinos and Franklin.23</li>
	<li>By using a jeweler&#39;s screw driver, place stainless steel EEG recording screws in the holes and make 2 - 2.5 turns for each screw for epidural positioning over the cortex. 
	Note: Do not insert screws too deep to prevent damage to the brain tissue. Check that the screws are tightly fixed on the skull. This is important to have stable EEG signals during a long period of multiple recordings (typically, more than 1 month). Wiggly screws produce EEG artifacts and may come off before the end of the experimental schedule.</li>
	<li>Fix the electrode assembly (cf. Section 1.1, pins turned upward) with instant glue to the skull and cover with dental cement. Make bilaterally small holes with forceps in the trapezius (neck) muscles and insert the stainless steel wires that serve as EMG electrodes into the holes. Suture the skin with a silk thread (0.1 mm diameter) to avoid exposure of the muscle.</li>
	<li>Remove the mouse from the stereotaxic frame. Administer ampicillin (100 mg/kg) and meloxicam (1 mg/kg) intraperitoneally to the mouse to avoid bacterial infection and to reduce post-surgical pain, respectively. Keep the mouse on a heat pad and monitor it until it has regained sufficient consciousness to maintain sternal recumbency. House the mouse individually during recovery to avoid removal of electrodes by other animals, and administer meloxicam (1 mg/kg) intraperitoneally on the first day after the surgery.</li>
</ol>
3. Recording and Acquiring EEG/EMG Data
<ol>
	<li>After a 1-week recovery period, house each mouse individually in an experimental cage placed in a soundproof recording chamber. Maintain an ambient temperature of 23 &#177; 1 &#176;C and automatically control cycles of 12-hr light/12-hr dark (lights on at 08:00, illumination intensity ~ 100 lux).</li>
	<li>Connect the EEG/EMG electrode assembly on the mouse head to a recording cable. Ensure that the recording cable is connected to a slip ring (which is designed so that movements of the mouse are not restricted by twisting of the cable) and an EEG/EMG signal amplifier. Filter EEG/EMG signals (EEG, 0.5-64 Hz; EMG, 16-64 Hz), digitize at a sampling rate of 128 Hz by an analog-to-digital converter (A/D) and finally record on a computer running EEG/EMG recording software (Table &#39;Materials&#39;, 4th entry from bottom).</li>
	<li>Habituate the mouse for 2 - 3 days in the recording chamber. If the EEG/EMG recording includes intraperitoneal drug administrations, gently handle the mouse on each habituation day at the time of the drug administration.</li>
	<li>Subsequently, start EEG/EMG recording software (Table &#39;Materials&#39;, 4th entry from bottom).
	<ol>
		<li>Select the &#39;Data file information&#39; tab and click the box next to the file name. Enter a file name and click &#39;Save&#39;.</li>
		<li>Select the &#39;Recording condition&#39; tab and select all EEG/EMG channels which will be recorded.</li>
		<li>Select the sampling frequency (128 Hz) in the &#39;Recording condition&#39; tab.</li>
		<li>Check if the selected channels are displayed properly in the &#39;Channel information&#39; tab.</li>
		<li>Select the &#39;Timer setting&#39; tab and click &#39;Monitor&#39; to display EEG and EMG.</li>
		<li>Check if EEG/EMG signals are displayed correctly.</li>
		<li>Select the &#39;Timer setting&#39; tab and set the clock time for the beginning and end of the recording in the &#39;Main Timer&#39; area.</li>
		<li>Click &#39;Monitor&#39; in the &#39;Timer setting&#39; tab to start the recording.</li>
	</ol>
	</li>
	<li>Record EEG/EMG signals under baseline (i.e., sleep/wake behavior of a freely behaving mouse) and different treatment conditions (e.g., caffeine administration or sham treatment) over several days. Euthanize the mouse with an intraperitoneal injection of pentobarbital (200 mg/kg) after the last experimental day.</li>
</ol>
4. Scoring of Behavioral State Based on EEG/EMG Data
<ol>
	<li>Start the software for EEG/EMG analysis (Table &#39;Materials&#39;, 4th entry from bottom). Open the EEG/EMG raw data (.kcd file) produced under the step 3. Click the &#39;Sleep&#39; tab and select Epoch time. Select 10 sec.</li>
	<li>Click the &#39;Sleep&#39; tab and select &#39;Multi-screening&#39; to automatically score all 10-sec epochs into 3 stages (i.e., NREM and REM sleep, and wakefulness) on the basis of the amplitudes of EEG and EMG and power spectral analysis of the EEG.3</li>
	<li>Click &#39;FFT condition for EEG&#39;.</li>
	<li>Set the parameters for the power spectral analysis [256 datum points (corresponding to 2 sec of the EEG), Hanning window function, and the average of 5 spectra per epoch].3 Click &#39;OK&#39;.</li>
	<li>Click &#39;Start Screening&#39; to begin the automatic screening. Open the scored data (.raf file).</li>
	<li>Check the results of the automatic screening and, if necessary, correct them manually based on the standard criteria (see the Representative Results, Figure 1B and Table 1).2, 3 Briefly, click and hold left mouse button on an incorrectly scored epoch and drag the cursor across the string of incorrectly scored epochs. Release the left mouse button and select the correct behavioral state in the pop-up window. 
	Note: Occasionally, epochs at the transition between two vigilant states are difficult to score unambiguously to one state. In such cases, the epoch should be scored to the ostensible state and the same criteria should be applied to similar epochs throughout the experiment to ensure data reproducibility.</li>
</ol>

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The authors Yujiro Tauguchi and Sayaka Kohtoh are employees of Kissei Comtech Co., Ltd that develops SleepSign software for acquisition and automatic scoring of EEG/EMG data used in this article.

This protocol describes a set-up for EEG/EMG recordings that allows the assessment of sleep and wakefulness under low-noise, cost-effective, and high-throughput conditions. Due to the small size of the EEG/EMG electrode head assembly, this system can be combined with other implants for intra-brain experiments, including optogenetics (optical fiber implantation) or, in conjunction with simultaneous cannula implantation, microinfusion of drugs into the mouse brain.31 Moreover, the design of the electrode head assembly with respect to multi-pin headers offers flexibility in the number of recording channels, if the measurement of additional electrical signals (e.g., contralateral EEG, electrooculogram or local field potential) is required.
However, individual housing is required for the cable-based design described in this protocol, which therefore limits the assessment of behavioral states, i.e., sleep and wakefulness, in combination with social interaction or complex behavioral testing. In these cases, a wireless sleep monitoring system is likely more suitable, although telemetric devices are not without&#12288;their own limiting features, especially battery cost and life.
The quality of EEG/EMG signals is important for the scoring of behavioral states according to the criteria shown in Figure 1 and Table 1. Wiggly electrodes (i.e., screws) are often the reason for electric noise resulting in artifacts in the EEG and FFT analysis. Moreover, it is important for the quality of the EEG signal to completely cover the electrode screws with dental cement to avoid air bubbles between the screws and cement, resulting in increased electric noise. The quality of EEG signals can be checked in an obviously sleeping mouse by visually confirming that they have a high amplitude and low frequency.
Cost and time to implant electrodes are critical factors for many sleep research laboratories and are considered a major drawback for large-scale screening of sleep-wake behavior in mice. The EEG/EMG recording system described here can be established and operated at low-to-moderate cost, including recurring cost for electrode materials and medical supplies (approximately 2 USD per mouse) and investments for EEG/EMG recording equipment (slip ring, amplifier, and A/D converter; approximately 2,000 USD per mouse).
With respect to time, a skilled researcher can conclude the electrode implantation for 1 mouse in less than 20 min; and thus, it is possible to operate on more than 20 mice per day. Another key factor for the overall efficiency of the assessment of sleep on the basis of EEG/EMG measurement is the use of software for acquisition and automatic scoring of EEG/EMG data. For these purposes, a variety of commercial and in-house developed software is available with a high variability in pricing or scoring accuracy.

Technical advances have often precipitated quantum leaps in the understanding of neurobiological processes. For example, Hans Berger&#39;s discovery in 1929 that electrical potentials recorded from the human scalp took the form of sinusoidal waves, the frequency of which was directly related to the level of wakefulness of the subject, led to rapid advances in the understanding of sleep-wake regulation, in both animals and humans alike.1 To this day the electroencephlogram (EEG), in conjunction with the electromyogram (EMG), i.e., electrical activity produced by skeletal muscles, represents the data &#34;backbone&#34; of nearly every experimental and clinical assessment that seeks to correlate behavior and physiology with the activity of cortical neurons in behaving animals, including humans. In most basic sleep research laboratories these EEG recordings are performed by using a cable-based system (Figure 1) wherein acquired data is subjected off-line to pattern and spectrum analysis [e.g., applying a fast Fourier transform (FFT) algorithm] to determine the vigilance state of the subject being recorded.2, 3 Sleep consists of rapid-eye movement (REM) and non-REM (NREM) sleep. REM sleep is characterized by a rapid low-voltage EEG, random eye movement, and muscle atonia, a state in which the muscles are effectively paralyzed. REM sleep is also known as paradoxical sleep, because the brain activity resembles that of wakefulness, whereas the body is largely disconnected from the brain and appears to be in deep sleep. By contrast, motor neurons are stimulated during NREM sleep but there is no eye movement. Human NREM sleep can be divided into 4 stages, whereby stage 4 is called deep sleep or slow-wave sleep and is identified by large, slow brain waves with delta activity between 0.5 - 4 Hz in the EEG. On the other hand, a subdivision between phases of NREM sleep in smaller animals, like rats and mice, has not been established, mostly because they do not have long consolidated periods of sleep as seen in humans.
Over the years, and on the basis of EEG interpretation, several models of sleep-wake regulation, both circuit- and humoral-based, have been proposed. The neural and cellular basis of the need for sleep or, alternatively, &#34;sleep drive,&#34; remains unresolved, but has been conceptualized as a homeostatic pressure that builds during the waking period and is dissipated by sleep. One theory is that endogenous somnogenic factors accumulate during wakefulness and that their gradual accumulation is the underpinning of sleep homeostatic pressure. While the first formal hypothesis that sleep is regulated by humoral factors has been credited to Rosenbaum&#39;s work published in 18924, it was Ishimori5, 6 and Pieron7 who independently, and over 100 years ago, demonstrated the existence of sleep-promoting chemicals. Both researchers proposed, and indeed proved, that hypnogenic substances or &#39;hypnotoxins&#39; were present in the cerebral spinal fluid (CSF) of sleep-deprived dogs.8 Over the past century several additional putative hypnogenic substances implicated in the sleep homeostatic process have been identified (for review, see ref. 9), including prostaglandin (PG) D2,10 cytokines,11 adenosine,12 anandamide,13 and the urotensin II peptide.14
Experimental work by Economo15, 16, Moruzzi and Magoun17, and others in the early and mid-20th century produced findings that inspired circuit-based theories of sleep and wakefulness and, to a certain degree, overshadowed the then prevailing humoral theory of sleep. To date, several &#34;circuit models&#34; have been proposed, each informed by data of varying quality and quantity (for review, see ref. 18). One model, for example, proposes that slow-wave sleep is generated through adenosine-mediated inhibition of acetylcholine release from cholinergic neurons in the basal forebrain, an area mainly consisiting of the nucleus of the horizontal limb of the diagonal band of Broca and the substantia inominata.19 Another popular model of sleep/wake regulation describes a flip-flop switch mechanism on the basis of mutually inhibitory interactions between sleep-inducing neurons in the ventrolateral preoptic area and wake-inducing neurons in the hypothalamus and brain stem.18, 20, 21 Moreover, for the switching in and out of REM sleep, a similar reciprocally inhibitory interaction has been proposed for areas in the brain stem, that is the ventral periaqueductal gray, lateral pontine tegmentum, and sublaterodorsal nucleus.22 Collectively, these models have proven valuable heuristics and afforded important interpretative frameworks for studies in sleep research; however, a yet fuller understanding of the molecular mechanisms and circuits regulating the sleep-wake cycle will require a more complete knowledge of its components. The system for polygraphic recording detailed below should aid in this goal.

<table><tbody><tr><td>4-pin header</td><td>Hirose</td><td>A3B-4PA-2DSA(71)</td><td></td></tr><tr><td>Ampicillin</td><td>Meiji Seika</td><td></td><td></td></tr><tr><td>Analog-to-digital converter</td><td>Contec</td><td>AD16-16U(PCIEV)</td><td></td></tr><tr><td>Caffeine</td><td>Sigma</td><td>C0750</td><td></td></tr><tr><td>Carbide cutter</td><td>Minitor</td><td>B1055</td><td></td></tr><tr><td>Crimp housing</td><td>Hirose</td><td>DF11-4DS-2C</td><td></td></tr><tr><td>Crimp socket</td><td>Hirose</td><td>DF11-30SC</td><td></td></tr><tr><td>Dental cement (Toughron Rebase)</td><td>Miki Chemical Product</td><td></td><td></td></tr><tr><td>Epoxy adhesive</td><td>Konishi</td><td>#16351</td><td></td></tr><tr><td>FFC/FPC connector</td><td>Honda Tsushin Kogyo</td><td>FFC-10BMEP1(B)</td><td></td></tr><tr><td>Flat cable</td><td>Hitachi Cable</td><td>20528-ST LF</td><td></td></tr><tr><td>Instant glue (Aron Alpha A)</td><td>Toagosei</td><td>N/A</td><td></td></tr><tr><td>Meloxicam</td><td>Boehringer Ingelheim</td><td>N/A</td><td></td></tr><tr><td>Pentobarbital</td><td>Kyoritsu Seiyaku</td><td>N/A</td><td></td></tr><tr><td>Signal amplifier</td><td>Biotex</td><td>N/A</td><td></td></tr><tr><td>Sleep recording chamber</td><td>APL</td><td>N/A</td><td></td></tr><tr><td>SleepSign software</td><td>Kissei Comtec</td><td>N/A</td><td>for EEG/EMG recording/analysis</td></tr><tr><td>Slip ring</td><td>Biotex</td><td>N/A</td><td></td></tr><tr><td>Stainless steel screw</td><td>Yamazaki</td><td>N/A</td><td>&amp;phi;1.0 &amp;times; 2.0</td></tr><tr><td>Stainless steel wire</td><td>Cooner Wire</td><td>AS633</td><td></td></tr></tbody></table>

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.

Figure 1B illustrates examples of the mouse EEG in the different vigilance states. As shown in Table 1, epochs are classified as NREM sleep if the EEG shows large, slow brain waves with a delta rhythm below 4 Hz and the EMG has only a weak or no signal. Epochs are classified as REM sleep if the EEG shows rapid low-voltage brain waves in the theta range between 6 and 10 Hz and the EMG shows low amplitude. Other epochs should be classified as wakefulness (i.e., low-to-moderate voltage EEG and occurrence of EMG activity).
For instance, the EEG/EMG recording set-up described in this protocol can be used to determine the sleep amount and sleep/wake profile of C57BL/6 mice under baseline conditions or after treatment with caffeine (Figures 2 and 3).
Under baseline conditions, mice, which are nocturnal animals, exhibited a clear circadian sleep-wake rhythm, as seen in these figures, with larger amounts of sleep during the light period than during the dark one (Figure 2A). During the 12-hr light period, the mice showed 6.7 hr and 0.9 hr of NREM and REM sleep, respectively; whereas during the 12-hr dark period, wakefulness was predominant (Figure 2B). On the other hand, the quality of sleep can be evaluated on the basis of the vigilance state and EEG power spectrum analysis (Figure 2C-F). Typically, polygraphic recordings of EEG and EMG can be used to determine episode duration distribution, mean duration, and stage transition number for each vigilance state (Figure 2C-E). Moreover, the EEG power spectrum for NREM and REM sleep in mice during the light and dark period (Figure 2F) shows strong EEG power density in the frequency range of 0.5 - 4 Hz and 6 - 10 Hz, respectively. It should be noted that the EEG during REM sleep includes small amounts of delta waves (0.5 - 4 Hz), since the intermingled states of NREM and REM sleep are sometimes a contaminant.
To assess drug effects on the sleep-wake behavior of mice,24-30 EEG and EMG are typically recorded for 2 consecutive days. To determine, for example, the arousal effect of caffeine on C57BL/6 mice,24 the mice were treated with vehicle (10 ml/kg saline; intraperitoneally) on day 1 at 10:00 A.M. in the early phase of the light period. The animals were then treated with caffeine (15 mg/kg) 24 hr later, and the vigilance states were classified offline into waking, REM sleep, and NREM sleep. Figure 3A shows typical examples of EEG, EMG, and hypnograms after the administration of caffeine (lower polysomnographic panels) or vehicle (upper polysomnographic panels) in a C57BL/6 mouse. Caffeine increased the amount of wakefulness in C57BL/6 mice 2.8-fold for 3 hr after the injection (Figure 3B).
<img alt="Figure 1" src="/files/ftp_upload/53678/53678fig1.jpg" /> 
Figure 1. Sleep Bioassay System for Mice.
(A)&#160;To monitor EEG signals, stainless steel screws are implanted epidurally over the frontal cortical and parietal areas of 1 hemisphere. In addition, EMG activity is monitored by stainless steel wires placed bilaterally within the trapezius muscles. (B) Typical examples of EEG, EMG, and EEG power density for 10 sec during NREM or REM sleep or wakefulness in a mouse. In NREM sleep, EEG shows high-amplitude waves; and the delta band (0.5 - 4 Hz) is dominant (left). In REM sleep, EEG shows low amplitude waves, with the theta band (6 - 10 Hz) being dominant (middle). In wakefulness, the EEG shows low-amplitude waves, with no frequency being dominant (right). EMG signals are lower in both NREM and REM sleep than in wakefulness. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53678/53678fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/53678/53678fig2.jpg" /> 
Figure 2. Sleep-wake Profiles under Baseline Conditions in C57BL/6 Mice Assessed by EEG/EMG Recordings. 
(A) Time-course changes in the hourly amount of each behavioral stage. White and black bars above the x-axes indicate the light and dark periods, respectively. (B) Total amount of each stage for 12 hr shows a larger amount of NREM and REM sleep during the light period compared with that in the dark period. (C) Distribution of episode duration of each stage. (D) Mean duration of each stage is longer for wakefulness in the dark period. (E) Stage-transition number of each stage shows more frequent transitions during the light period. (F) EEG power spectrum during NREM and REM sleep shows essentially no power-density differences between light and dark periods. Data are presented as the mean &#177; SEM (n = 5). *p &#60;0.05, **p &#60;0.01, as assessed by paired two-tailed Student&#39;s t test. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53678/53678fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" height="890" src="/files/ftp_upload/53678/53678fig3.jpg" width="700" /> 
Figure 3. Arousal Effect of Caffeine Assessed by EEG/EMG Recordings. 
(A) Typical examples of EEG, EMG, and hypnograms after administration of vehicle (upper panel) or caffeine at a dose of 15 mg/kg (lower panel). (B) Time courses of wakefulness in mice treated with caffeine. (C) Wakefulness over a 3-hr period after injection of caffeine. Data are presented as the mean &#177; SEM (n = 5). **p &#60;0.01 compared to vehicle injection, as assessed by paired two-tailed Student&#39;s t test. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53678/53678fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="0" cellpadding="0" cellspacing="0" width="519">
	<colgroup>
		<col />
		<col span="2" />
		<col />
	</colgroup>
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:156px;"></td>
			<td style="width:139px;">NREM sleep</td>
			<td style="width:139px;">REM sleep</td>
			<td style="width:87px;">Wakefulness</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">EEG amplitude</td>
			<td>High</td>
			<td>Low</td>
			<td>Low</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Dominant EEG frequency</td>
			<td>Delta band (0.5 - 4 Hz)</td>
			<td>Theta band (6 - 10 Hz)</td>
			<td>None</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">EMG amplitude</td>
			<td>Low</td>
			<td>Low</td>
			<td>High</td>
		</tr>
	</tbody>
</table>
Table 1:General Criteria to Score Behavioral States by EEG/EMG Signals.

Watch this Scientific Journal Video about Polygraphic Recording Procedure for Measuring Sleep in Mice at JoVE.com

Polygraphic Recording Procedure for Measuring Sleep in Mice

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 ...

polygraphic-recording-procedure-for-measuring-sleep-in-mice

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Neuroscience

Unit 1

Functions of the Central and Peripheral Nervous System

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23.4K Views.  University of Tsukuba. 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.

Video: Polygraphic Recording Procedure for Measuring Sleep in Mice

Manipulation of Epileptiform Electrocorticograms (ECoGs) and Sleep in Rats and Mice by Acupuncture

Ancient Chinese literature has documented that acupuncture possesses efficient therapeutic effects on epilepsy and insomnia. There is, however, little research to reveal the possible mechanisms behind these effects. To investigate the effect of acupuncture on epilepsy and sleep, several issues need to be addressed. The first is to identify the acupoints, which correspond between humans, rats, and mice. Furthermore, the depth of insertion of the acupuncture needle, the degree of needle twist in manual needle acupuncture, and the stimulation parameters for electroacupuncture (EA) need to be determined. To evaluate the effects of acupuncture on epilepsy and sleep, a feasible model of epilepsy in rodents is required. We administer pilocarpine into the left central nucleus of the amygdala (CeA) to simulate focal temporal lobe epilepsy (TLE) in rats. Intraperitoneal (IP) injection of pilocarpine induces generalized epilepsy and status epilepticus (SE) in rats. Five IP injections of pentylenetetrazol (PTZ) with a one-day interval between each injection successfully induces spontaneous generalized epilepsy in mice. Recordings of electrocorticograms (ECoGs), electromyograms (EMGs), brain temperature, and locomotor activity are used for sleep analysis in rats, while ECoGs, EMGs, and locomotor activity are employed for sleep analysis in mice. ECoG electrodes are implanted into the frontal, parietal, and contralateral occipital cortices, and a thermistor is implanted above the cerebral cortex by stereotactic surgery. EMG electrodes are implanted into the neck muscles, and an infrared detector determines locomotor activity. The criteria for categorizing vigilance stages, including wakefulness, rapid eye movement (REM) sleep, and non-REM (NREM) sleep are based on information from ECoGs, EMGs, brain temperature, and locomotor activity. Detailed classification criteria are stated in the text.

Manipulation of Epileptiform Electrocorticograms ECoGs and Sleep in Rats and Mice by Acupuncture

This paper demonstrates the performance of acupuncture, epilepsy models, and the analysis of sleep in rodents. The acupuncture procedure and the identification of acupoints are described. Pilocarpine or pentylenetetrazol (PTZ) is used to induce epilepsy. Electrocorticogram (ECoG), electromyogram (EMG), brain temperature, and locomotor activity recordings are employed for sleep analysis.

Ancient Chinese literature has documented that acupuncture possesses efficient therapeutic effects on epilepsy and insomnia. There is, however, little ...

Behavior

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.

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 ...

A High-performance Liquid Chromatography Measurement of Kynurenine and Kynurenic Acid: Relating Biochemistry to Cognition and Sleep in Rats

The kynurenine pathway (KP) of tryptophan degradation has been implicated in psychiatric disorders. Specifically, the astrocyte-derived metabolite kynurenic acid (KYNA), an antagonist at both N-methyl-d-aspartate (NMDA) and &#945;7 nicotinic acetylcholine (&#945;7nACh) receptors, has been implicated in cognitive processes in health and disease. As KYNA levels are elevated in the brains of patients with schizophrenia, a malfunction at the glutamatergic and cholinergic receptors is believed to be causally related to cognitive dysfunction, a core domain of the psychopathology of the illness. KYNA may play a pathophysiologically significant role in individuals with schizophrenia. It is possible to elevate endogenous KYNA in the rodent brain by treating animals with the direct bioprecursor kynurenine, and preclinical studies in rats have demonstrated that acute elevations in KYNA may impact their learning and memory processes. The current protocol describes this experimental approach in detail and combines a) a biochemical analysis of blood kynurenine levels and brain KYNA formation (using high-performance liquid chromatography), b) behavioral testing to probe the hippocampal-dependent contextual memory (passive avoidance paradigm), and c) an assessment of sleep-wake behavior [telemetric recordings combining electroencephalogram (EEG) and electromyogram (EMG) signals] in rats. Taken together, a relationship between elevated KYNA, sleep, and cognition is studied, and this protocol describes in detail an experimental approach to understanding function outcomes of kynurenine elevation and KYNA formation in vivo in rats. Results obtained through variations of this protocol will test the hypothesis that the KP and KYNA serve pivotal roles in modulating sleep and cognition in health and disease states.

Alterations in the kynurenine pathway (KP) neuroactive metabolites are implicated in psychiatric illnesses. Investigating the functional outcomes of an altered kynurenine pathway metabolism in vivo in rodents may help elucidate novel therapeutic approaches. The current protocol combines biochemical and behavioral approaches to investigate the impact of an acute kynurenine challenge in rats.

The kynurenine pathway (KP) of tryptophan degradation has been implicated in psychiatric disorders. Specifically, the astrocyte-derived metabolite ...

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 ...

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Current web resources provide limited, user friendly tools to compute spectrograms for visualizing and quantifying electroencephalographic (EEG) data. This paper describes a Windows-based, open source code for creating EEG multitaper spectrograms. The compiled program is accessible to Windows users without software licensing. For Macintosh users, the program is limited to those with a MATLAB software license. The program is illustrated via EEG spectrograms that vary as a function of states of sleep and wakefulness, and opiate-induced alterations in those states. The EEGs of C57BL/6J mice were wirelessly recorded for 4 h after intraperitoneal injection of saline (vehicle control) and antinociceptive doses of morphine, buprenorphine, and fentanyl. Spectrograms showed that buprenorphine and morphine caused similar changes in EEG power at 1&#8722;3 Hz and 8&#8722;9 Hz. Spectrograms after administration of fentanyl revealed maximal average power bands at 3 Hz and 7 Hz. The spectrograms unmasked differential opiate effects on EEG frequency and power. These computer-based methods are generalizable across drug classes and can be readily modified to quantify and display a wide range of rhythmic biological signals.

This protocol provides an open source, compiled MATLAB program that generates multitaper spectrograms for electroencephalographic data.

Current web resources provide limited, user friendly tools to compute spectrograms for visualizing and quantifying electroencephalographic (EEG) data. ...

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Arrhythmias are common, affecting millions of patients worldwide. Current treatment strategies are associated with significant side effects and remain ineffective in many patients. To improve patient care, novel and innovative therapeutic concepts causally targeting arrhythmia mechanisms are needed. To study the complex pathophysiology of arrhythmias, suitable animal models are necessary, and mice have been proven to be ideal model species to evaluate the genetic impact on arrhythmias, to investigate fundamental molecular and cellular mechanisms, and to identify potential therapeutic targets.
Implantable telemetry devices are among the most powerful tools available to study electrophysiology in mice, allowing continuous ECG recording over a period of several months in freely moving, awake mice. However, due to the huge number of data points (&gt;1 million QRS complexes per day), analysis of telemetry data remains challenging. This article describes a step-by-step approach to analyze ECGs and to detect arrhythmias in long-term telemetry recordings using the software, Ponemah, with its analysis modules, ECG Pro and Data Insights, developed by Data Sciences International (DSI). To analyze basic ECG parameters, such as heart rate, P wave duration, PR interval, QRS interval, or QT duration, an automated attribute analysis was performed using Ponemah to identify P, Q, and T waves within individually adjusted windows around detected R waves. 
Results were then manually reviewed, allowing adjustment of individual annotations. The output from the attribute-based analysis and the pattern recognition analysis was then used by the Data Insights module to detect arrhythmias. This module allows an automatic screening for individually defined arrhythmias within the recording, followed by a manual review of suspected arrhythmia episodes. The article briefly discusses challenges in recording and detecting ECG signals, suggests strategies to improve data quality, and provides representative recordings of arrhythmias detected in mice using the approach described above.

Here we present a step-by-step protocol for a semiautomated approach to analyze murine long-term electrocardiography (ECG) data for basic ECG parameters and common arrhythmias. Data are obtained by implantable telemetry transmitters in living and awake mice and analyzed using Ponemah and its analysis modules.

Arrhythmias are common, affecting millions of patients worldwide. Current treatment strategies are associated with significant side effects and remain ...

Medicine

LFP Recording in Mouse Brain for Cognitive Research and Drug Analysis

Dual Extracellular Recordings in the Mouse Hippocampus and Prefrontal Cortex

The technique of recording local field potentials (LFPs) is an electrophysiological method used to measure the electrical activity of localized neuronal populations. It serves as a crucial tool in cognitive research, particularly in brain regions like the hippocampus and prefrontal cortex. Dual LFP recordings between these areas are of particular interest as they allow the exploration of interregional signal communication. However, methods for performing these recordings are rarely described, and most commercial recording devices are either expensive or lack adaptability to accommodate specific experimental designs. This study presents a comprehensive protocol for performing dual-electrode LFP recordings in the mouse hippocampus and the prefrontal cortex to investigate the effects of antipsychotic drugs and potassium channel modulators on LFP properties in these areas. The technique enables the measurement of LFP properties, including power spectra within each brain region and coherence between the two. Additionally, a low-cost, custom-designed recording device has been developed for these experiments. In summary, this protocol provides a means to record signals with high signal-to-noise ratios in different brain regions, facilitating the investigation of interregional information communication within the brain.

Author Spotlight: Studying Drug Impacts on Brain Signals Using Dual LFP Recording Protocol in Mice

This protocol outlines the use of a custom-designed recording device and electrodes to record local field potentials and investigate information flow in the mouse hippocampus and prefrontal cortex.

The technique of recording local field potentials (LFPs) is an electrophysiological method used to measure the electrical activity of localized neuronal ...

Enhancing Brain Drainage During Sleep with Transcranial Photobiomodulation

Photobiomodulation Under Electroencephalographic Controls of Sleep for Stimulation of Lymphatic Removal of Toxins from Mouse Brain

The meningeal lymphatic vessels (MLVs) play an important role in the removal of toxins from the brain. The development of innovative technologies for the stimulation of MLV functions is a promising direction in the progress of the treatment of various brain diseases associated with MLV abnormalities, including Alzheimer&#39;s and Parkinson&#39;s diseases, brain tumors, traumatic brain injuries, and intracranial hemorrhages. Sleep is a natural state when the brain&#39;s drainage processes are most active. Therefore, stimulation of the brain&#39;s drainage and MLVs during sleep may have the most pronounced therapeutic effects. However, such commercial technologies do not currently exist.
This study presents a new portable technology of transcranial photobiomodulation (tPBM) under electroencephalographic (EEG) control of sleep designed to photo-stimulate removal of toxins (e.g., soluble amyloid beta (A&#946;)) from the brain of aged BALB/c mice with the ability to compare the therapeutic effectiveness of different optical resources. The technology can be used in the natural condition of a home cage without anesthesia, maintaining the motor activity of mice. These data open up new prospects for developing non-invasive and clinically promising photo-technologies for the correction of age-related changes in the MLV functions and brain&#39;s drainage processes and for effectively cleansing brain tissues from metabolites and toxins. This technology is intended both for preclinical studies of the functions of the sleeping brain and for developing clinically relevant treatments for sleep-related brain diseases.

Author Spotlight: Developing Photo-Stimulation Technology for Toxin Removal in Sleep-Related Brain Diseases

This study presents an original and portable tPBM technology under electroencephalographic (EEG) control of deep or non-rapid eye movement (NREM) sleep in non-anesthetized male C57BL/6 mice of different ages to stimulate lymphatic clearance of A&#946; from the brain into the peripheral lymphatic system (the deep cervical lymph nodes, dcLNs).

The meningeal lymphatic vessels (MLVs) play an important role in the removal of toxins from the brain. The development of innovative technologies for the ...

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 ...