We thank all lab members for their contribution to the writing and careful reading of this manuscript. We are grateful to Paul Franken for stimulating discussions, Dr. Gis&#232;le Ferrand for helpful comments on the surgical protocol, and Dr. Jean-Yves Chatton for providing the original Labview executable files for the noise exposure. Funding was provided by the Swiss National Science Foundation (Grants 31003A_146244 and 31003A_166318) and the Etat de Vaud.

<ol>
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The authors declare that they have no competing financial interest.

Here, we show how to establish a continuous temporal profile of non-REM sleep that integrates EEG, EMG, and ECG variables. This is a first step towards developing an integrative description of mouse sleep, which can help to identify the previously unrecognized timescale over which high and low resilience to noise are organized during non-REM sleep1. A similar temporal structure was also described in human non-REM sleep through an analogous analysis1.
The procedure presented here fulfills two goals. First, we bring to attention that polysomnographic techniques can reliably provide both EEG and EMG-ECG signals during the entirety of the non-REM sleep periods in mice. The heartbeat is most evident in EMG traces during REM sleep due to muscle atonia, and it becomes more hidden in non-REM sleep because of increased muscle tone and occasional muscle twitches. Inserting EMG-ECG electrodes more deeply into the muscle and keeping them as distant as possible increases the amplitude of the R-waves of the heart, such that they emerge clearly from the background muscle tonus. Routines for peak detection then extract the heart rate from the non-REM sleep EMG-ECG signal and allow for the quantification of its variability.
Telemetry-based technologies to simultaneously monitor EEG/EMG and ECG are increasingly used, but the quality of the signals required for thorough spectral analysis remains inferior in terms of bandwidth and stability. Furthermore, even single-channel transmitters are of considerable size, and their implantation in the cervical subcutaneous region or in the body cavity may affect the animal&#39;s well-being and perturb sleep. Nevertheless, further developing such devices is necessary to expand the range of central and autonomic parameters that can be simultaneously followed during undisturbed sleep in mice, which is the animal model of choice for sleep studies. In combination with techniques such as head restraint, which allows for the collection of data from both non-REM and REM sleep in mice with unaltered spectral profiles1,19, multiparametric measurements during sleep can now be combined with controlled behavioral testing.
Second, the analytical approach we present here can also be applied to local field potentials to define the brain area involved in generating the hallmark of interest1. Moreover, it is applicable to imaging techniques fast enough to report on the spectral behavior of neuronal populations and for both continuous (e.g., spectral bands) and discrete (e.g. heart rate or respiration) variables. Its time resolution is only limited by the duration of the epoch chosen for scoring the vigilance state. Essentially, standard spectral analyses of the signals derived from non-REM sleep bouts are followed by an alignment of the power density values of individual signals for every epoch. Then, a spectral analysis of these power dynamics is used to quantify periodicities in the structure. In both mice and humans, our approach yielded a 0.02-Hz oscillation, with comparable properties1, which qualified it as a unifying hallmark for mammalian sleep structure.
A critical step was the functional validation of the observed periodicity by scoring non-REM sleep retrospectively based on the behavioral reactivity of the sleeping mouse to noise. Here, the choice of a noise stimulus that led to a variable behavioral outcome, causing wake-up or sleep-through, was decisive. Strong sensory stimuli that cause wake-up in most exposures would not unravel the 0.02-Hz oscillation, because wake-up would be enforced from all its phases. In contrast, a too-weak stimulus would not consistently reveal the phase relation to the 0.02-Hz oscillation. Similarly, any&#160;observed periodicity in a measured parameter set would need to go along with the variable outcome. For example, in the case presented here, we have only distinguished between wake-up or sleep-through events, not considering the exact moment of wake-up during the noise exposure or the duration of the ensuing wake state (however, see1). Using short stimuli at various intensities24,25,28 could help to delineate the exact phase relationships between the 0.02-Hz oscillation and wake-up. Furthermore, varying the frequency composition of the sounds could modulate arousability as a function of the recent history of sleep-wake behavior, the gender, the presence of nestlings, or other forms of recent experience. Another possibility could be to probe whether the prevalence of microarousals or full arousals depends upon a given momentary sleep state.
The scoring of sleep based on a variable behavioral outcome could illuminate the functional microarchitecture of sleep more generally. While we and others have tested reactivity to noise exposure1,28, wake-up in response to other sensory modalities, vigilance state transitions14, or dream reports could be assessed to extract the corresponding correlates of the preceding sleep. Furthermore, it will be very interesting to test sleep disorder patients with respect to their sensibility to external disturbance and to a potential disruption of the 0.02-Hz oscillation. Sleep disorders may lead to cardiovascular disturbance, whereas cardiovascular risk can lead to sleep dysregulation31,32, rendering investigations on the brain-heart coordination during 0.02-Hz oscillation potentially relevant for understanding this bidirectional dependence.

Mammalian sleep is a behavioral state of rest and of resilience to environmental stimuli. In spite of this apparent uniformity, polysomnographic and autonomic parameters indicate that sleep moves between qualitatively and quantitatively different neural and somatic states on various temporal and spatial scales1. Over minutes to tens of minutes, the switch between non-REM and REM sleep occurs. Non-REM sleep is accompanied by large-amplitude, low-frequency activity in the EEG, with a spectral peak around ~0.5 - 4 Hz, whereas REM sleep shows regular EEG activity in the theta band (6 - 10 Hz), together with muscle atonia2. Within non-REM sleep, humans cycle through light (S2) and deep slow-wave sleep (SWS). As their naming indicates, these two stages show lower and higher arousal thresholds3,4, respectively, and they differ primarily in the density of low-frequency cortical EEG power, referred to as slow-wave activity (SWA; 0.75 - 4 Hz). Non-uniformity persists throughout individual bouts of S2 and SWS on the minute- to sub-second-timescale, as extensively documented by the variable presence of SWA over the course of a bout5,6, but also by EEG and field potential rhythms at higher frequencies, including spindle waves in the sigma band (10-15 Hz) and gamma rhythms (80 - 120 Hz) (for a review, see7,8,9,10).
Rather than being subtle, these variations do shift the sleeping cortical state in humans to the extremes of the spectrum. For non-REM sleep, these range from a predominance of SWA to states that approximate wake-like activity because they contain a substantial proportion of high-frequency components11,12. In rodents and cats, although non-REM sleep is not subdivided into stages, a brief period called intermediate sleep (IS) emerges prior to REM sleep onset13. During IS, REM sleep features such as hippocampal theta activity and ponto-geniculo-occipital waves initiate, while non-REM sleep signatures, such as spindle waves and SWA, are still present, indicating a mix between the two sleep states14,15. Nevertheless, IS could be functionally distinct because it is modulated by antidepressants16 and through novel object presentation during prior waking17, and it contributes to setting the arousal threshold18. Furthermore, state space plots of EEG and EMG parameters of freely moving rats show a cluster of points14 that is continuous between non-REM sleep, REM sleep, and wakefulness. There are also sporadic declines in SWA, without entering wakefulness or REM sleep, which leads to substantial fluctuations in the relative presence of the low- and high-frequency components during a consolidated non-REM sleep bout14,19,20. Finally, variable ratios of SWA and higher frequency rhythms during non-REM sleep occur not only in time, but also show regional differences in amplitude and synchronization between cortical areas19.
Mammalian non-REM sleep is far from uniform. However, whether such non-uniformity leads to states that differ in function and behavioral attributes is not clear. In several types of sleep disorders, continuous sleep is disrupted by spontaneous awakenings and inappropriate motor behavior. Moreover, spectral analyses show alterations in the relative presence of higher frequencies in the EEG21 and in autonomic parameters, such as rates of breathing and cardiac beating22. The orderly sequence of stable sleep states is thus perturbed, and elements of cortical and/or autonomic arousal intrude in an uncontrolled manner. Therefore, understanding the continuum of sleep states is of possible relevance for disease. Additionally, the perturbance of sleep by environmental noise in urban environments is associated with general health risks, rendering it crucial to identify moments of heightened vulnerability during sleep23.
Behavioral arousal experiments in sleeping humans indicate that it is hardest to wake up from SWA-dominated non-REM sleep (stage S3), whereas light non-REM sleep (stage S2) and REM sleep show comparable and lower arousal thresholds4. The cortical processing of short sound stimuli varies substantially between REM sleep, S2, and S324,25, indicating that state-specific cortical activity patterns modulate the first stages of sensory processing. For non-REM sleep in humans, the propensity to wake up in response to noise varies with the presence of spindle waves and alpha rhythms in the EEG26,27,28. Thalamocortical rhythmicity during spindles is accompanied by enhanced synaptic inhibition at both the thalamic and cortical levels, which is thought to contribute to the attenuation of sensory processing7.
How are noise-resistant and vulnerable periods of sleep organized in time, and what are their determinants? In both mice and human, we recently identified an infra-slow, 0.02-Hz oscillation in neural rhythms. Depending upon the phase of this 0.02-Hz oscillation, mice showed variable reactivity to external stimuli, either waking up or sleeping through the noise. Interestingly, this oscillation was correlated with the rate of the heartbeat, indicating that the autonomic nervous system participates in the modulation of sleep&#39;s vulnerability to external stimuli1. Memory-related hippocampal rhythms were also organized within this rhythm, and, most strikingly, its strength correlated with the quality of memory consolidation in humans. The 0.02-Hz oscillation thus appears to be an organizing principle of rodent and human non-REM sleep that modulates both sensitivity to the environment and internal memory processing. This again highlights the need for multiparametric and continuous assessments of sleep states to recognize their functionality and to identify sites of potential vulnerability.
Here, we present a procedure to extract the waveform of these dynamics, including the surgical implantation of mice for combined EEG/ECoG and EMG-ECG measurements, exposure to sensory stimuli, and analysis routines. This procedure provides a basis for viewing sleep as a continuously varying yet highly organized vigilance state during which different fundamental sleep functions are sequentially executed. More generally, the procedure is applicable to approaches aiming to extract the spectral and autonomic features that precede a behavioral outcome during sleep in both health and disease states.

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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.

Figure 2A (top panel) shows 100-min stretches of spontaneous sleep-wake behavior, recorded through polysomnographic electrodes implanted as described (see Figure 1). The increases and decreases of the EEG and EMG amplitude at non-REM sleep onset are clearly visible. Intermittent REM sleep is marked by a decrease in EEG amplitude and a further decrease in EMG tone that is not visible on this compressed time scale. Zooming in on one non-REM sleep bout reveals the high-amplitude slow waves in the EEG and, in the EMG-ECG trace, the low muscle activity, onto which the RR intervals of the heart rate superimpose as vertical deflections (Figure 2A, middle and lower panels). An FFT reveals the dominance of SWA throughout all 4-s epochs (Figure 2B). Plotting the mean sigma power (10 - 15 Hz, red shadowed bar) for each of these epochs reveals its varying time course, along with variations in heart rate with the opposite direction. Carrying out this analysis over the entirety of the non-REM bouts and normalizing to mean power values unravels the regular variations in sigma power around the mean (Figure 2C). Fourier analysis over this power time course shows a major peak around 0.02 Hz, reflecting the periodic increase of sigma power in 50-s intervals (Figure 2D).
To probe the function of the 0.02-Hz oscillation in arousability, mice were exposed to 20-s pulses of 90 dB when sleeping, per the conditions described. Figure 3 displays some of the experimental outcomes of such noise exposures. When mice did not wake up during the noise, and EEG and EMG-ECG waveforms remained unaltered, the outcome was classified as a &#34;Sleep-through&#34; (Figure 3A). When the EEG amplitude decreased and EMG activity was observed, the outcome was scored as a &#34;Wake-up&#34; (Figure 3B). Occasionally, mice switched to REM sleep during a trial (Figure 3C) or woke up in the 40-s interval before noise onset (Figure 3D). These events were excluded from the analysis, because our interest was specifically to identify the hallmarks of consolidated non-REM sleep that precede the outcome of noise exposure (&#34;Sleep-through&#34; or &#34;Wake-up&#34;). Calculating the sigma power in the 40-s period prior to noise stimulation showed that the 0.02-Hz oscillation was at its trough when a &#34;Sleep-through&#34; occurred (Figure 3E, left panel), whereas it peaked for a &#34;Wake-up&#34; event (Figure 3E, right panel). Therefore, scoring the non-REM sleep of a mouse retrospectively, based on a variable behavioral outcome to acoustic stimulation, identifies the phase of the 0.02-Hz oscillation in sigma power as a hallmark for sleep states with variable resilience to noise.

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

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 ...

quantifying-infra-slow-dynamics-spectral-power-heart-rate-sleeping

Universidad San Sebastian

Research

JoVE Journal

Neuroscience

9.9K Views.  University of Lausanne. 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.

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

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy

In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can potentially increase risk of sudden unexpected death in epilepsy (SUDEP). Electroencephalography (EEG) and electrocardiography (ECG) are widely used clinical diagnostic tools to monitor for abnormal brain and cardiac rhythms in patients. Here, a technique to simultaneously record video, EEG, and ECG in mice to measure behavior, brain, and cardiac activities, respectively, is described. The technique described herein utilizes a tethered (i.e., wired) recording configuration in which the implanted electrode on the head of the mouse is hard-wired to the recording equipment. Compared to wireless telemetry recording systems, the tethered arrangement possesses several technical advantages such as a greater possible number of channels for recording EEG or other biopotentials; lower electrode costs; and greater frequency bandwidth (i.e., sampling rate) of recordings. The basics of this technique can also be easily modified to accommodate recording other biosignals, such as electromyography (EMG) or plethysmography for assessment of muscle and respiratory activity, respectively. In addition to describing how to perform the EEG-ECG recordings, we also detail methods to quantify the resulting data for seizures, EEG spectral power, cardiac function, and heart rate variability, which we demonstrate in an example experiment using a mouse with epilepsy due to Kcna1 gene deletion. Video-EEG-ECG monitoring in mouse models of epilepsy or other neurological disease provides a powerful tool to identify dysfunction at the level of the brain, heart, or brain-heart interactions.

Here, we present a protocol to record brain and heart bio signals in mice using simultaneous video, electroencephalography (EEG), and electrocardiography (ECG). We also describe methods to analyze the resulting EEG-ECG recordings for seizures, EEG spectral power, cardiac function, and heart rate variability.

In epilepsy, seizures can evoke cardiac rhythm disturbances such as heart rate changes, conduction blocks, asystoles, and arrhythmias, which can ...

Genetics

Implantation of Radiotelemetry Transmitters Yielding Data on ECG, Heart Rate, Core Body Temperature and Activity in Free-moving Laboratory Mice

The laboratory mouse is the animal species of choice for most biomedical research, in both the academic sphere and the pharmaceutical industry. Mice are a manageable size and relatively easy to house. These factors, together with the availability of a wealth of spontaneous and experimentally induced mutants, make laboratory mice ideally suited to a wide variety of research areas.
In cardiovascular, pharmacological and toxicological research, accurate measurement of parameters relating to the circulatory system of laboratory animals is often required. Determination of heart rate, heart rate variability, and duration of PQ and QT intervals are based on electrocardiogram (ECG) recordings. However, obtaining reliable ECG curves as well as physiological data such as core body temperature in mice can be difficult using conventional measurement techniques, which require connecting sensors and lead wires to a restrained, tethered, or even anaesthetized animal. Data obtained in this fashion must be interpreted with caution, as it is well known that restraining and anesthesia can have a major artifactual influence on physiological parameters1, 2.
Radiotelemetry enables data to be collected from conscious and untethered animals. Measurements can be conducted even in freely moving animals, and without requiring the investigator to be in the proximity of the animal. Thus, known sources of artifacts are avoided, and accurate and reliable measurements are assured. This methodology also reduces interanimal variability, thus reducing the number of animals used, rendering this technology the most humane method of monitoring physiological parameters in laboratory animals3, 4. Constant advancements in data acquisition technology and implant miniaturization mean that it is now possible to record physiological parameters and locomotor activity continuously and in realtime over longer periods such as hours, days or even weeks3, 5.
Here, we describe a surgical technique for implantation of a commercially available telemetry transmitter used for continuous measurements of core body temperature, locomotor activity and biopotential (i.e. onelead ECG), from which heart rate, heart rate variability, and PQ and QT intervals can be established in freeroaming, untethered mice. We also present pre-operative procedures and protocols for post-operative intensive care and pain treatment that improve recovery, well-being and survival rates in implanted mice5, 6.

A surgical technique for implantation of commercially available telemetry transmitters used for continuous measurement of biopotential (one-lead ECG), heart rate, core body temperature and locomotor activity in freely moving mice is shown. Recommendations and protocols for post-operative care and pain relief, improving recovery, well being and survival rate are also presented.

The laboratory mouse is the animal species of choice for most biomedical research, in both the academic sphere and the pharmaceutical industry. Mice are a ...

Medicine

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 ...

Behavior

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

The fields that develop methods for sensory substitution and sensory augmentation have aimed to control external goals using signals from the central nervous systems (CNS). Less frequent however, are protocols that update external signals self-generated by interactive bodies in motion. There is a paucity of methods that combine the body-heart-brain biorhythms of one moving agent to steer those of another moving agent during dyadic exchange. Part of the challenge to accomplish such a feat has been the complexity of the setup using multimodal bio-signals with different physical units, disparate time scales and variable sampling frequencies.
In recent years, the advent of wearable bio-sensors that can non-invasively harness multiple signals in tandem, has opened the possibility to re-parameterize and update the peripheral signals of interacting dyads, in addition to improving brain- and/or body-machine interfaces. Here we present a co-adaptive interface that updates efferent somatic-motor output (including kinematics and heart rate) using biosensors; parameterizes the stochastic bio-signals, sonifies this output, and feeds it back in re-parameterized form as visuo/audio-kinesthetic reafferent input. We illustrate the methods using two types of interactions, one involving two humans and another involving a human and its avatar interacting in near real time. We discuss the new methods in the context of possible new ways to measure the influences of external input on internal somatic-sensory-motor control.

We present protocols and methods of analyses to build co-adaptive interfaces that stream, parameterize, analyze, and modify human body and heart signals in close-loop. This setup interfaces signals derived from the peripheral and central nervous systems of the person with external sensory inputs to help track biophysical change.

The fields that develop methods for sensory substitution and sensory augmentation have aimed to control external goals using signals from the central ...

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 ...

Novel Approach for Simultaneous Recording of Renal Sympathetic Nerve Activity and Blood Pressure with Intravenous Infusion in Conscious, Unrestrained Mice.

Renal sympathetic nerves contribute significantly to both physiological and pathophysiological phenomena. Evaluating renal sympathetic nerve activity (RSNA) is of great interest in many areas of research such as chronic kidney disease, hypertension, heart failure, diabetes and obesity. Unequivocal assessment of the role of the sympathetic nervous system is thus imperative for proper interpretation of experimental results and understanding of disease processes. RSNA has been traditionally measured in anesthetized rodents, including mice. However, mice usually exhibit very low systemic blood pressure and hemodynamic instability for several hours during anesthesia and surgery. Meaningful interpretation of RSNA is confounded by this non-physiological state, given the intimate relationship between sympathetic nervous tone and cardiovascular status. To address this limitation of traditional approaches, we developed a new method for measuring RSNA in conscious, freely-moving mice. Mice were chronically instrumented with radio-telemeters for continuous monitoring of blood pressure as well as a jugular venous infusion catheter and custom-designed bipolar electrode for direct recording of RSNA. Following a 48-72 hour recovery period, survival rate was 100% and all mice behaved normally. At this time-point, RSNA was successfully recorded in 80% of mice, with viable signals acquired up to 4 and 5 days post-surgery in 70% and 50% of mice, respectively. Physiological blood pressures were recorded in all mice (116&plusmn;2 mmHg; n=10). Recorded RSNA increased with eating and grooming, as well-established in the literature. Furthermore, RSNA was validated by ganglionic blockade and modulation of blood pressure with pharmacological agents. Herein, an effective and manageable method for clear recording of RSNA in conscious, freely-moving mice is described.

Anesthetized mice exhibit non-physiological systemic blood pressure, which precludes meaningful assessment of autonomic tone given the intimate relationship between blood pressure and the autonomic nervous system. Thus, a novel method to simultaneously record renal sympathetic nerve activity and blood pressure with intravenous infusion in conscious mice is outlined.

Renal sympathetic nerves contribute significantly to both physiological and pathophysiological phenomena. Evaluating renal sympathetic nerve activity ...

Echocardiographic and Histological Examination of Cardiac Morphology in the Mouse

An increasing number of genetically modified mouse models has become available in recent years. Moreover, the number of pharmacological studies performed in mice is high. Phenotypic characterization of these mouse models also requires the examination of cardiac function and morphology. Echocardiography and magnetic resonance imaging (MRI) are commonly used approaches to characterize cardiac function and morphology in mice. Echocardiographic and MRI equipment specialized for use in small rodents is&#160;expensive and requires a dedicated space. This protocol describes cardiac measurements in mice using a clinical echocardiographic system with a 15 MHz human vascular probe. Measurements are performed on anesthetized adult mice. At least three image sequences are recorded and analyzed for each animal in M-mode in the parasternal short-axis view. Afterwards, cardiac histological examination is performed, and cardiomyocyte diameters are determined on hematoxylin-eosin- or wheat germ agglutinin (WGA)-stained paraffin sections. Vessel density is determined morphometrically after Pecam-1 immunostaining. The protocol has been applied successfully to pharmacological studies and different genetic animal models under baseline conditions, as well as after experimental myocardial infarction by the permanent ligation of the left anterior descending coronary artery (LAD). In our experience, echocardiographic investigation is limited to anesthetized animals and is feasible in adult mice weighing at least 25 g.

Echocardiographic examination is frequently used in mice. Expensive high-resolution ultrasound devices have been developed for this purpose. This protocol describes an affordable echocardiographic procedure combined with histological morphometric analyses to determine cardiac morphology.

An increasing number of genetically modified mouse models has become available in recent years. Moreover, the number of pharmacological studies performed ...

Echocardiographic Measurement of Right Ventricular Diastolic Parameters in Mouse

Diastolic dysfunction is a prominent feature of right ventricular (RV) remodeling associated with conditions of pressure overload. However, the RV diastolic function is rarely quantified in experimental studies. This might be due to technical difficulties in the visualization of the RV in the apical four-chamber view in rodents. Here we describe two positions facilitating the visualization of the apical four-chamber view in mice to assess the RV diastolic function.
The apical four-chamber view is enabled by tilting the mouse fixation platform to the left and caudally (LeCa) or to the right and cranially (RiCr). Both positions provide images of comparable quality. The results of the RV diastolic function obtained from two positions are not significantly different. Both positions are comparably easy to perform. This protocol can be incorporated into published protocols and enables detailed investigations of the RV function.

Here we describe and compare two positions for obtaining the apical four-chamber view in mice. These positions enable the quantification of the right ventricular function, provide comparable results, and can be used interchangeably.

Diastolic dysfunction is a prominent feature of right ventricular (RV) remodeling associated with conditions of pressure overload. However, the RV ...

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. ...

Implantation of Combined Telemetric ECG and Blood Pressure Transmitters to Determine Spontaneous Baroreflex Sensitivity in Conscious Mice

Blood pressure (BP) and heart rate (HR) are both controlled by the autonomic nervous system (ANS) and are closely intertwined due to reflex mechanisms. The baroreflex is a key homeostatic mechanism to counteract acute, short-term changes in arterial BP and to maintain BP in a relatively narrow physiological range. BP is sensed by baroreceptors located in the aortic arch and carotid sinus. When BP changes, signals are transmitted to the central nervous system and are then communicated to the parasympathetic and sympathetic branches of the autonomic nervous system to adjust HR. A rise in BP causes a reflex decrease in HR, a drop in BP causes a reflex increase in HR.
Baroreflex sensitivity (BRS) is the quantitative relationship between changes in arterial BP and corresponding changes in HR. Cardiovascular diseases are often associated with impaired baroreflex function. In various studies reduced BRS has been reported in e.g., heart failure, myocardial infarction, or coronary artery disease. 
Determination of BRS requires information from both BP and HR, which can be recorded simultaneously using telemetric devices. The surgical procedure is described beginning with the insertion of the pressure sensor into the left carotid artery and positioning of its tip in the aortic arch to monitor arterial pressure followed by the subcutaneous placement of the transmitter and ECG electrodes. We also describe postoperative intensive care and analgesic management. After a two-week period of post-surgery recovery long-term ECG and BP recordings are performed in conscious and unrestrained mice. Finally, we include examples of high-quality recordings and the analysis of spontaneous baroreceptor sensitivity using the sequence method.

The baroreflex is a heart-rate regulation mechanism by the autonomic nervous system in response to blood-pressure changes. We describe a surgical technique to implant telemetry transmitters for continuous and simultaneous measurement of electrocardiogram and blood pressure in mice. This can determine spontaneous baroreflex sensitivity, an important prognostic marker for cardiovascular disease.

Blood pressure (BP) and heart rate (HR) are both controlled by the autonomic nervous system (ANS) and are closely intertwined due to reflex mechanisms. ...