Individual Motoneurons Research Articles

Ultrasound pulse repetition frequency preferentially activates different neuron populations independent of cell type

Objective. Transcranial ultrasound (US) stimulation serves as an external input to a neuron, and thus the evoked response relies on neurons' intrinsic properties. Neural activity is limited to a couple hundred hertz and often exhibits preference to input frequencies. Accordingly, US pulsed at specific physiologic pulse repetition frequencies (PRFs) may selectively engage neurons with the corresponding input frequency preference. However, most US parametric studies examine the effects of supraphysiologic PRFs. It remains unclear whether pulsing US at different physiologic PRFs could activate distinct neurons in the awake mammalian brain.Approach. We recorded cellular calcium responses of individual motor cortex neurons to US pulsed at PRFs of 10, 40, and 140 Hz in awake mice. We compared the evoked responses across these PRFs in the same neurons. To further understand the cell-type dependent effects, we categorized the recorded neurons as parvalbumin positive fast spiking interneurons or putative excitatory neurons and analyzed single-cell mechanosensitive channel expression in mice and humans using the Allen Brain Institute's RNA-sequencing databases.Main results. We discovered that many neurons were preferentially activated by only one PRF and different PRFs selectively engaged distinct neuronal populations. US-evoked cellular calcium responses exhibited the same characteristics as those naturally occurring during spiking, suggesting that US increases intrinsic neuronal activity. Furthermore, evoked responses were similar between fast-spiking inhibitory neurons and putative excitatory neurons. Thus, variation in individual neuron's cellular properties dominates US-evoked response heterogeneity, consistent with our observed cell-type independent expression patterns of mechanosensitive channels across individual neurons in mice and humans. Finally, US transiently increased network synchrony without producing prolonged over-synchronization that could be detrimental to neural circuit functions.Significance. These results highlight the feasibility of activating distinct neuronal subgroups by varying PRF and the potential to improve neuromodulation effects by combining physiologic PRFs.

Functional analysis of conserved C. elegans bHLH family members uncovers lifespan control by a peptidergic hub neuron.

Throughout the animal kingdom, several members of the basic helix-loop-helix (bHLH) family act as proneural genes during early steps of nervous system development. Roles of bHLH genes in specifying terminal differentiation of postmitotic neurons have been less extensively studied. We analyze here the function of five C. elegans bHLH genes, falling into three phylogenetically conserved subfamilies, which are continuously expressed in a very small number of postmitotic neurons in the central nervous system. We show (a) that two orthologs of the vertebrate bHLHb4/b5 genes, called hlh-17 and hlh-32, function redundantly to specify the identity of a single head interneuron (AUA), as well as an individual motor neuron (VB2), (b) that the PTF1a ortholog hlh-13 acts as a terminal selector to control terminal differentiation and function of the sole octopaminergic neuron class in C. elegans, RIC, and (c) that the NHLH1/2 ortholog hlh-15 controls terminal differentiation and function of the peptidergic AVK head interneuron class, a known neuropeptidergic signaling hub in the animal. Strikingly, through null mutant analysis and cell-specific rescue experiments, we find that loss of hlh-15/NHLH in the peptidergic AVK neurons and the resulting abrogation of neuropeptide secretion causes a substantially expanded lifespan of the animal, revealing an unanticipated impact of a central, peptidergic hub neuron in regulating lifespan, which we propose to be akin to hypothalamic control of lifespan in vertebrates. Taken together, our functional analysis reveals themes of bHLH gene function during terminal differentiation that are complementary to the earlier lineage specification roles of other bHLH family members. However, such late functions are much more sparsely employed by members of the bHLH transcription factor family, compared to the function of the much more broadly employed homeodomain transcription factor family.

Kinetic features dictate sensorimotor alignment in the superior colliculus

The execution of goal-oriented behaviours requires a spatially coherent alignment between sensory and motor maps. The current model for sensorimotor transformation in the superior colliculus relies on the topographic mapping of static spatial receptive fields onto movement endpoints1–6. Here, to experimentally assess the validity of this canonical static model of alignment, we dissected the visuo-motor network in the superior colliculus and performed in vivo intracellular and extracellular recordings across layers, in restrained and unrestrained conditions, to assess both the motor and the visual tuning of individual motor and premotor neurons. We found that collicular motor units have poorly defined visual static spatial receptive fields and respond instead to kinetic visual features, revealing the existence of a direct alignment in vectorial space between sensory and movement vectors, rather than between spatial receptive fields and movement endpoints as canonically hypothesized. We show that a neural network built according to these kinetic alignment principles is ideally placed to sustain ethological behaviours such as the rapid interception of moving and static targets. These findings reveal a novel dimension of the sensorimotor alignment process. By extending the alignment from the static to the kinetic domain this work provides a novel conceptual framework for understanding the nature of sensorimotor convergence and its relevance in guiding goal-directed behaviours.

Caloric state modulates locomotion, heart rate and motor neuron responses to acute administration of d-amphetamine in zebrafish larvae

Psychostimulant drugs increase behavioral, cardiac and brain responses in humans and other animals. Acute food deprivation or chronic food restriction potentiates the stimulatory effects of abused drugs and increases the propensity for relapse to drug seeking in drug-experienced animals. The mechanisms by which hunger affects cardiac and behavioral activities are only beginning to be elucidated. Moreover, changes in motor neuron activities at the single neuron level induced by psychostimulants, and their modulation by food restriction, remain unknown. Here we investigated how food deprivation affects responses to d-amphetamine by measuring locomotor activity, cardiac output, and individual motor neuron activity in zebrafish larvae. We used wild-type larval zebrafish to record behavioral and cardiac responses and the larvae of Tg(mnx1:GCaMP5) transgenic zebrafish to record motor neuron responses. Physiological state gated responses to d-amphetamine. That is, d-amphetamine evoked significant increases in motor behavior (swimming distances), heart rate and motor neuron firing frequency in food-deprived but not fed zebrafish larvae. The results extend the finding that signals arising from food deprivation are a key potentiator of the drug responses induced by d-amphetamine to the zebrafish model. The larval zebrafish is an ideal model to further elucidate this interaction and identify key neuronal substrates that may increase vulnerability to drug reinforcement, drug-seeking and relapse.

A brainstem preparation allowing simultaneous access to respiratory motor output and cellular properties of motoneurons in American bullfrogs.

Breathing is generated by a complex neural circuit, and the ability to monitor the activity of multiple network components simultaneously is required to uncover the cellular basis of breathing. In neonatal rodents, a single brainstem slice can be obtained to record respiratory-related motor nerve discharge along with individual rhythm-generating cells or motoneurons because of the close proximity of these neurons in the brainstem. However, most ex vivo preparations in other vertebrates can only capture respiratory motor outflow or electrophysiological properties of putative respiratory neurons in slices without relevant synaptic inputs. Here, we detail a method to horizontally slice away the dorsal portion of the brainstem to expose fluorescently labeled motoneurons for patch-clamp recordings in American bullfrogs. This 'semi-intact' preparation allows tandem recordings of motor output and single motoneurons during respiratory-related synaptic inputs. The rhythmic motor patterns are comparable to those from intact preparations and operate at physiological temperature and [K+]. Thus, this preparation provides the ability to record network and cellular outputs simultaneously and may lead to new mechanistic insights into breathing control across vertebrates.

The control and training of single motor units in isometric tasks are constrained by a common input signal.

Recent developments in neural interfaces enable the real-time and non-invasive tracking of motor neuron spiking activity. Such novel interfaces could provide a promising basis for human motor augmentation by extracting potentially high-dimensional control signals directly from the human nervous system. However, it is unclear how flexibly humans can control the activity of individual motor neurons to effectively increase the number of degrees of freedom available to coordinate multiple effectors simultaneously. Here, we provided human subjects (N = 7) with real-time feedback on the discharge patterns of pairs of motor units (MUs) innervating a single muscle (tibialis anterior) and encouraged them to independently control the MUs by tracking targets in a 2D space. Subjects learned control strategies to achieve the target-tracking task for various combinations of MUs. These strategies rarely corresponded to a volitional control of independent input signals to individual MUs during the onset of neural activity. Conversely, MU activation was consistent with a common input to the MU pair, while individual activation of the MUs in the pair was predominantly achieved by alterations in de-recruitment order that could be explained by history-dependent changes in motor neuron excitability. These results suggest that flexible MU recruitment based on independent synaptic inputs to single MUs is unlikely, although de-recruitment might reflect varying inputs or modulations in the neuron's intrinsic excitability.

Sectioning and Counting of Motor Neurons in the L3 to L6 Region of the Adult Mouse Spinal Cord.

Histology is the study of the microscopic structure of tissues. This protocol permits the generation of frozen transverse sections of lumbar spinal cord regions L3 to L6. It enables counting of murine ventral horn lumbar motor neurons in a reproducible manner. Methods include spinal column dissection, hydraulic extrusion, and histological processing. The preparation for cryo-sectioning includes embedding lumbar spinal cord in optimal cutting temperature (OCT) medium. The correct orientation of the tissue is critical as calculating the amount of tissue to discard saved time overall. Specific details regarding section thickness and mounting are described. These requirements not only allow optimum coverage of specific regions but also ensure that no individual motor neuron was counted twice. The Nissl bodies of the motor neurons were stained using gallocyanin. The sections obtained are all of a comparable area and quality assurance is consistent. The specificity of the staining enables the scientist to identify and reliably quantify lumbar motor neurons. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Euthanasia of mouse and isolation of spinal cord Basic Protocol 2: Hydraulic extrusion of the spinal cord Basic Protocol 3: Identification of the lumbar region Basic Protocol 4: Embedding cord in OCT Basic Protocol 5: Collection of frozen sections onto slides Basic Protocol 6: Gallocyanin staining Basic Protocol 7: Motor neuron counting.

Monosynaptic facilitation mediated by group Ia afferents from deltoid to biceps brachii motoneurons in humans.

Effects of low-threshold afferents from the anterior (DA), middle (DM) and posterior parts of the deltoid (DP) on the excitability of biceps brachii (BB) motoneurons in humans were studied. We evaluated the effects on individual motor units and motoneuron pool using a post-stimulus time-histogram (PSTH) and an electromyogram-averaging (EMG-A) methods, respectively, in 11 healthy human subjects. Electrical conditioning stimulation was delivered to the axillary nerve branch innervating DA (DA nerve), DM (DM nerve) and DP (DP nerve) with the intensity below the motor threshold. In the PSTH study, stimulation to the DA, DM and DP nerves produced a significant peak (facilitation) in 26/40 (65%), 28/47 (59%) and 0/32 (0%) of BB motor units, respectively. Since the central latency of the facilitation from the DA and DM nerves was 0.1 ± 0.3 and 0.1 ± 0.2ms (mean ± S.D.) longer than that of the homonymous monosynaptic Ia facilitation of BB, respectively, the facilitation thus being compatible with monosynaptic path. In the EMG-A study, stimulation to the DA and DM nerves produced a significant peak (facilitation) for the BB motoneuron pool in all the subjects, whereas stimulation to the DP nerve produced no effect on BB. The facilitation diminished by vibration stimulation, and the suppression lasted for 30-40min after removal of the vibration. Therefore, group Ia afferents should be responsible for the facilitation. These findings suggest that monosynaptic facilitation mediated by group Ia afferents from the DA and DM nerves to BB motoneurons exists in humans.

Highly Accurate Real-Time Decomposition of Single Channel Intramuscular EMG.

Real-time intramuscular electromyography (iEMG) decomposition, as an identification procedure of individual motor neuron (MN) discharge timings from a streaming iEMG recording, has the potential to be used in human-machine interfacing. However, for these applications, the decomposition accuracy and speed of current approaches need to be improved. In our previous work, a real-time decomposition algorithm based on a Hidden Markov Model of EMG, using GPU-implemented Bayesian filter to estimate the spike trains of motor units (MU) and their action potentials (MUAPs), was proposed. In this paper, a substantially extended version of this algorithm that boosts the accuracy while maintaining real-time implementation, is introduced. Specifically, multiple heuristics that aim at resolving the problems leading to performance degradation, are applied to the original model. In addition, the recursive maximum likelihood (RML) estimator previously used to estimate the statistical parameters of the spike trains, is replaced by a linear regression (LR) estimator, which is computationally more efficient, in order to ensure real-time decomposition with the new heuristics. The algorithm was validated using twenty-one experimental iEMG signals acquired from the tibialis anterior muscle of five subjects by fine wire electrodes. All signals were decomposed in real time. The decomposition accuracy depended on the level of muscle activation and was when less than 10 MUs were identified, substantially exceeding previous real-time results. Single channel iEMG signals can be very accurately decomposed in real time with the proposed algorithm. The proposed highly accurate algorithm for single-channel iEMG decomposition has the potential of providing neural information on motor tasks for human interfacing.

Normal Development and Pathology of Motoneurons: Anatomy, Electrophysiological Properties, Firing Patterns and Circuit Connectivity.

This chapter will provide an introduction into motoneuron anatomy, electrophysiological properties, firing patterns focusing on development and also describing several pathological conditions that affect mononeurons. It starts with a historical retrospective describing the early landmark work into motoneurons. The next section lays out the various types of motoneurons (alpha, beta, and gamma) and their subclasses (fast-twitch fatigable, fast-twitch fatigue-resistant, and slow-twitch fatigue resistant), highlighting the functional relevance of this classification scheme. The third section describes the development of motoneurons' passive and active electrophysiological properties. This section also defines the major terms one uses in describing how a neuron functions electrophysiologically. The electrophysiological aspects of a neuron is critical to understanding how it behaves within a circuit and contributes to behavior since the firing of an action potential is how neurons communicate with each other and with muscles. The electrophysiological changes of motoneurons over development underlies how their function changes over the lifetime of an organism. After describing the properties of individual motoneurons, the chapter then turns to revealing how motoneurons interact within complex neural circuits, with other motoneurons as well as sensory neurons, and how these circuits change over development. Finally, this chapter ends with highlighting some recent advances made in motoneuron pathology, focusing on spinal muscular atrophy, amyotrophic lateral sclerosis, and axotomy.

Lactate ions induce synaptic plasticity to enhance output from the central respiratory network.

Lactate ion sensing has emerged as a process that regulates ventilation during metabolic challenges. Most work has focused on peripheral sensing of lactate for the control of breathing. However, lactate also rises in the central nervous system (CNS) during disturbances to blood gas homeostasis and exercise. Using an amphibian model, we recently showed that lactate ions, independently of pH and pyruvate metabolism, act directly in the brainstem to increase respiratory-related motor outflow. This response had a long washout time and corresponded with potentiated excitatory synaptic strength of respiratory motoneurons. Thus, we tested the hypothesis that lactate ions enhance respiratory output using cellular mechanisms associated with long-term synaptic plasticity within motoneurons. In this study, we confirm that 2mM sodium lactate, but not sodium pyruvate, increases respiratory motor output in brainstem-spinal cord preparations, persisting for 2h upon the removal of lactate. Lactate also led to prolonged increases in the amplitude of AMPA-glutamate receptor (AMPAR) currents in individual motoneurons from brainstem slices. Both motor facilitation and AMPAR potentiation by lactate required classic effectors of synaptic plasticity, L-type Ca2+ channels and NMDA receptors, as part of the transduction process but did not correspond with increased expression of immediate-early genes often associated with activity-dependent neuronal plasticity. Altogether these results show that lactate ions enhance respiratory motor output by inducing conserved mechanisms of synaptic plasticity and suggest a new mechanism that may contribute to coupling ventilation to metabolic demands in vertebrates. KEY POINTS: Lactate ions, independently of pH and metabolism, induce long-term increases in respiratory-related motor outflow in American bullfrogs. Lactate triggers a persistent increase in strength of AMPA-glutamatergic synapses onto respiratory motor neurons. Long-term plasticity of motor output and synaptic strength by lactate involves L-type Ca2+ channels and NMDA-receptors as part of the transduction process. Enhanced AMPA receptor function in response to lactate in the intact network is causal for motor plasticity. In sum, well-conserved synaptic plasticity mechanisms couple the brainstem lactate ion concentration to respiratory motor drive in vertebrates.

Axon initial segment geometry in relation to motoneuron excitability

The axon initial segment (AIS) responsible for action potential initiation is a dynamic structure that varies and changes together with neuronal excitability. Like other neuron types, alpha motoneurons in the mammalian spinal cord express heterogeneity and plasticity in AIS geometry, including length (AISl) and distance from soma (AISd). The present study aimed to establish the relationship of AIS geometry with a measure of intrinsic excitability, rheobase current, that varies by 20-fold or more among normal motoneurons. We began by determining whether AIS length or distance differed for motoneurons in motor pools that exhibit different activity profiles. Motoneurons sampled from the medial gastrocnemius (MG) motor pool exhibited values for average AISd that were significantly greater than that for motoneurons from the soleus (SOL) motor pool, which is more readily recruited in low-level activities. Next, we tested whether AISd covaried with intrinsic excitability of individual motoneurons. In anesthetized rats, we measured rheobase current intracellularly from MG motoneurons in vivo before labeling them for immunohistochemical study of AIS structure. For 16 motoneurons sampled from the MG motor pool, this combinatory approach revealed that AISd, but not AISl, was significantly related to rheobase, as AIS tended to be located further from the soma on motoneurons that were less excitable. Although a causal relation with excitability seems unlikely, AISd falls among a constellation of properties related to the recruitability of motor units and their parent motoneurons.

In-silico development and assessment of a Kalman filter motor decoder for prosthetic hand control

Up to 50% of amputees abandon their prostheses, partly due to rapid degradation of the control systems, which require frequent recalibration. The goal of this study was to develop a Kalman filter-based approach to decoding motoneuron activity to identify movement kinematics and thereby provide stable, long-term, accurate, real-time decoding. The Kalman filter-based decoder was examined via biologically varied datasets generated from a high-fidelity computational model of the spinal motoneuron pool. The estimated movement kinematics controlled a simulated MuJoCo prosthetic hand. This clear-box approach showed successful estimation of hand movements under eight varied physiological conditions with no retraining. The mean correlation coefficient of 0.98 and mean normalized root mean square error of 0.06 over these eight datasets provide proof of concept that this decoder would improve long-term integrity of performance while performing new, untrained movements. Additionally, the decoder operated in real-time (~0.3 ms). Further results include robust performance of the Kalman filter when re-trained to more severe post-amputation limitations in the type and number of motoneurons remaining. An additional analysis shows that the decoder achieves better accuracy when using the firing of individual motoneurons as input, compared to using aggregate pool firing. Moreover, the decoder demonstrated robustness to noise affecting both the trained decoder parameters and the decoded motoneuron activity. These results demonstrate the utility of a proof of concept Kalman filter decoder that can support prosthetics’ control systems to maintain accurate and stable real-time movement performance.

Meta-analysis of biological variables’ impact on spinal motoneuron electrophysiology data

Experimental, methodological, and biological variables must be accounted for statistically to maximize accuracy and comparability of published neuroscience data. However, accounting for all variables is nigh impossible. Thus we aimed to identify particularly influential variables within published neurological data, from cat, rat, and mouse studies, via a robust statistical process. Our goal was to develop tools to improve rigor in the collection and analysis of data. We strictly constrained experimental and methodological variables and then assessed four key biological variables within motoneuron research: species, age, sex, and cell type. We quantified intraexperimental and interexperimental variances in 11 commonly reported electrophysiological properties of spinal motoneurons. We first assessed variances without accounting for biological variables and then reassessed them while accounting for all four variables. We next assessed variances with all possible combinations of these four variables. We concluded that some motoneuron properties have low intraexperimental, but high interexperimental, variance; that individual motoneuron properties are impacted differently by biological variables; and that some unexplained variances still remain. We report here the optimal combinations of biological variables to reduce interexperimental variance for all 11 parameters. We also rank each parameter by intra- and interexperimental consistency. We expect these results to assist with design of experimental and analytical methods, and to support accuracy in simulations. Furthermore, although demonstrated on spinal motoneuron electrophysiology literature, our approach is applicable to biological data from all fields of neuroscience. This approach represents an important aid to experimental design, comparison of reported data, and reduction of unexplained variance in neuroscience data.NEW & NOTEWORTHY Our meta-analysis shows the impact of species, age, sex, and cell type on lumbosacral motoneuron electrophysiological properties by thoroughly quantifying variances across literature for the first time. We quantify the variances of 11 motoneuron properties with consideration of biological variables, thus providing specific insights for motoneuron modelers and experimenters, and providing a general methodological template for the quantification of variance in neurological data with the consideration of any experimental, methodological, or biological variables of interest.

Retrograde Tracing of Drosophila Embryonic Motor Neurons Using Lipophilic Fluorescent Dyes.

We describe a technique for retrograde labeling of motor neurons in Drosophila. We use an oil-dissolved lipophilic dye and deliver a small droplet to an embryonic fillet preparation by a microinjector. Each motor neuron whose membrane is contacted by the droplet can then be rapidly labeled. Individual motor neurons are continuously labeled, enabling fine structural details to be clearly visualized. Given that lipophilic dyes come in various colors, the technique also provides a means to get adjacent neurons labeled in multicolor. This tracing technique is therefore useful for studying neuronal morphogenesis and synaptic connectivity in the motor neuron system of Drosophila.

Strength Training Increases Conduction Velocity of High-Threshold Motor Units.

Motor unit conduction velocity (MUCV) represents the propagation velocity of action potentials along the muscle fibers innervated by individual motor neurons and indirectly reflects the electrophysiological properties of the sarcolemma. In this study, we investigated the effect of a 4-wk strength training intervention on the peripheral properties (MUCV and motor unit action potential amplitude, RMSMU) of populations of longitudinally tracked motor units (MU). The adjustments exhibited by 12 individuals who participated in the training (INT) were compared with 12 controls (CON). Strength training involved ballistic (4 × 10) and sustained (3 × 10) isometric ankle dorsiflexions. Measurement sessions involved the recordings of maximal voluntary isometric force and submaximal isometric ramp contractions, whereas high-density surface EMG was recorded from the tibialis anterior. High-density surface EMG signals were decomposed into individual MU discharge timings, and MU was tracked across the intervention. Maximal voluntary isometric force (+14.1%, P = 0.003) and average MUCV (+3.0%, P = 0.028) increased in the INT group, whereas normalized MU recruitment threshold (RT) decreased (-14.9%, P = 0.001). The slope (rate of change) of the regression between MUCV and MU RT increased only in the INT group (+32.6%, P = 0.028), indicating a progressive greater increase in MUCV for higher-threshold MU. The intercept (initial value) of MUCV did not change after the intervention (P = 0.568). The association between RMSMU and MU RT was not altered by the training. The increase in the rate of change in MUCV as a function of MU RT, but not the initial value of MUCV, suggests that short-term strength training elicits specific adaptations in the electrophysiological properties of the muscle fiber membrane in high-threshold MU.

Target-wide Induction and Synapse Type-Specific Robustness of Presynaptic Homeostasis.

Presynaptic homeostatic plasticity (PHP) is an evolutionarily conserved form of adaptive neuromodulation and is observed at both central and peripheral synapses. In this work, we make several fundamental advances by interrogating the synapse specificity of PHP. We define how PHP remains robust to acute versus long-term neurotransmitter receptor perturbation. We describe a general PHP property that includes global induction and synapse-specific expression mechanisms. Finally, we detail a novel synapse-specific PHP expression mechanism that enables the conversion from short- to long-term PHP expression. If our data can be extended to other systems, including the mammalian central nervous system, they suggest that PHP can be broadly induced and expressed to sustain the function of complex neural circuitry.

Discrimination of EMG Signals Using a Neuromorphic Implementation of a Spiking Neural Network.

An accurate description of muscular activity plays an important role in the clinical diagnosis and rehabilitation research. The electromyography (EMG) is the most used technique to make accurate descriptions of muscular activity. The EMG is associated with the electrical changes generated by the activity of the motor neurons. Typically, to decode the muscular activation during different movements, a large number of individual motor neurons are monitored simultaneously, producing large amounts of data to be transferred and processed by the computing devices. In this paper, we follow an alternative approach that can be deployed locally on the sensor side. We propose a neuromorphic implementation of a spiking neural network (SNN) to extract spatio-temporal information of EMG signals locally and classify hand gestures with very low power consumption. We present experimental results on the input data stream using a mixed-signal analog/digital neuromorphic processor. We performed a thorough investigation on the performance of the SNN implemented on the chip, by: first, calculating PCA on the activity of the silicon neurons at the input and the hidden layers to show how the network helps in separating the samples of different classes; second, performing classification of the data using state-of-the-art SVM and logistic regression methods and a hardware-friendly spike-based read-out. The traditional algorithm achieved a classification rate of [Formula: see text] and [Formula: see text], respectively, and the spiking learning method achieved [Formula: see text]. The power consumption of the SNN is [Formula: see text], showing the potential of this approach for ultra-low power processing.

Silencing of Hypoglossal Motoneurons Leads to Sleep Disordered Breathing in Lean Mice.

Obstructive Sleep Apnea (OSA) is a prevalent condition and a major cause of morbidity and mortality in Western Society. The loss of motor input to the tongue and specifically to the genioglossus muscle during sleep is associated with pharyngeal collapsibility and the development of OSA. We applied a novel chemogenetic method to develop a mouse model of sleep disordered breathing Our goal was to reversibly silence neuromotor input to the genioglossal muscle using an adeno-associated viral vector carrying inhibitory designer receptors exclusively activated by designer drugs AAV5-hM4Di-mCherry (DREADD), which was delivered bilaterally to the hypoglossal nucleus in fifteen C57BL/6J mice. In the in vivo experiment, 4 weeks after the viral administration mice were injected with a DREADD ligand clozapine-N-oxide (CNO, i.p., 1mg/kg) or saline followed by a sleep study; a week later treatments were alternated and a second sleep study was performed. Inspiratory flow limitation was recognized by the presence of a plateau in mid-respiratory flow; oxyhemoglobin desaturations were defined as desaturations >4% from baseline. In the in vitro electrophysiology experiment, four males and three females of 5 days of age were used. Sixteen–nineteen days after DREADD injection brain slices of medulla were prepared and individual hypoglossal motoneurons were recorded before and after CNO application. Positive mCherry staining was detected in the hypoglossal nucleus in all mice confirming successful targeting. In sleep studies, CNO markedly increased the frequency of flow limitation n NREM sleep (from 1.9 ± 1.3% after vehicle injection to 14.2 ± 3.4% after CNO, p < 0.05) and REM sleep (from 22.3% ± 4.1% to 30.9 ± 4.6%, respectively, p < 0.05) compared to saline treatment, but there was no significant oxyhemoglobin desaturation or sleep fragmentation. Electrophysiology recording in brain slices showed that CNO inhibited firing frequency of DREADD-containing hypoglossal motoneurons. We conclude that chemogenetic approach allows to silence hypoglossal motoneurons in mice, which leads to sleep disordered breathing manifested by inspiratory flow limitation during NREM and REM sleep without oxyhemoglobin desaturation or sleep fragmentation. Other co-morbid factors, such as compromised upper airway anatomy, may be needed to achieve recurrent pharyngeal obstruction observed in OSA.

Visualize &lt;em&gt;Drosophila&lt;/em&gt; Leg Motor Neuron Axons Through the Adult Cuticle

The majority of work on the neuronal specification has been carried out in genetically and physiologically tractable models such as C. elegans, Drosophila larvae, and fish, which all engage in undulatory movements (like crawling or swimming) as their primary mode of locomotion. However, a more sophisticated understanding of the individual motor neuron (MN) specification-at least in terms of informing disease therapies-demands an equally tractable system that better models the complex appendage-based locomotion schemes of vertebrates. The adult Drosophila locomotor system in charge of walking meets all of these criteria with ease, since in this model it is possible to study the specification of a small number of easily distinguished leg MNs (approximately 50 MNs per leg) both using a vast array of powerful genetic tools, and in the physiological context of an appendage-based locomotion scheme. Here we describe a protocol to visualize the leg muscle innervation in an adult fly.