Edited by: Birendra N. Mallick, Jawaharlal Nehru University, India
Reviewed by: Giancarlo Vanini, University of Michigan, United States; Mathias Dutschmann, Florey Institute of Neuroscience and Mental Health, Australia
This article was submitted to Sleep and Chronobiology, a section of the journal Frontiers in Neurology
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The sleep-related depression of excitability of upper airway motoneurons is a major neurological cause of obstructive sleep apnea whereas a disruption in the inhibition of spinal motoneurons during rapid eye movement (REM) sleep causes the REM sleep behavioral disorder. The large amount of experimental data has been obtained that deal with neurochemical mechanisms that are responsible for sleep-related depression of various motoneuron groups. However, there is a disagreement regarding the outcome of these studies primarily due to the use of different animal models and approaches, as well as due to differences in quantification and interpretation of obtained results. In this study, we sought to apply the same calculation methodology in order to uniformly quantify and compare the relative contribution of excitatory or inhibitory inputs to the decrease of excitability of different motoneuronal pools during REM and/or non-REM sleep. We analyzed only published quantitative data that were obtained by using receptor antagonists or chemogenetic approach to block receptors or silence neuronal populations. The outcomes of this analysis highlight the differences in the neurotransmitter mechanisms of sleep-related motoneuron depression between different motoneuronal pools and demonstrate the consistency of these mechanisms for hypoglossal motoneurons among various animal models.
The decrease of upper airway motoneuron excitability during rapid eye movement (REM) sleep and non-REM (NREM) sleep is a major neurological cause of obstructive sleep apnea (OSA), which is recognized as a severe and growing sleep disorder (
Recently, a chemogenetic tool was introduced that allows specifically activating or silencing selected groups of neurons by systemic application of clozapine-
In this study, we developed an approach that allows quantifying the contribution of excitatory or inhibitory inputs, which were blocked (or removed) by application of receptor antagonists or chemogenetics, to the decrease of motoneuron excitability during NREM and REM sleep. We applied this approach to uniformly assess the contribution of state-dependent inputs to the three groups of motoneurons—spinal, trigeminal, and hypoglossal—for which published quantitative data are available.
An example of a relatively simple case when a receptor antagonist application disfacilitated a motoneuronal activity by blocking only excitatory state-dependent input(s) to motoneurons is shown in Figure
The effect of antagonist (Eant) that removes the excitatory input during wakefulness is
The relative contribution (RC) of the removed excitatory (e) input to the motoneuron excitability compared to the total sleep effect is the following:
When Equations (1) and (2) are combined, the final equation for the RCe is
This example of antagonist action (Figure
Example of a relatively simple disfacilitatory
An example of the disinhibitory effect of a receptor antagonist is illustrated in Figure
However, in most experiments, antagonists often block both state-dependent and non-state-dependent inputs to motoneurons, which make it challenging to calculate the magnitude of removed state-dependent input. An example of such dual disfacilitatory effect of an antagonist is shown in Figure
Example of a dual disfacilitatory
We developed an approach that allows quantifying the relative contribution of a state-dependent input to the total decrease of motoneuron excitability during sleep when receptor antagonist(s) produce the dual effects as discussed above. The approach consists of upgrading the Formulas (3, 4) to include the elimination of the non-state-dependent effects, as following. For the disfacilitatory mixed effect of an antagonist (Figure
The relative contribution of an inhibitory state-dependent input to the sleep-related depression of motoneuron activity for the disinhibitory antagonist mixed effects (Figure
Both Formulas (5, 6) work well for either the simple (Figure
In the pioneering work conducted by Michael Chase group (
The relative contributions of excitatory (e) and inhibitory (i) inputs to the decrease of motoneuron excitability during REM sleep and NREM sleep that were calculated in this study. Data were used from experiments that were conducted with two approaches: intracellular (intracell.) and extracellular recording; on three motoneuron pools: spinal, trigeminal, and hypoglossal; using different animal models: head-restrained cats, behaving rats, decerebrated cats, anesthetized rats, and behaving mice. The length of black bars shows the relative contribution of tested receptors to the total depression of motoneuron excitability (gray bars) during REM sleep
The role of glutamatergic, GABAergic, and glycinergic receptors in the decrease of excitability of trigeminal motoneurons during both NREM sleep and REM sleep has been studied in behaving rats (
The GABAergic and glycinergic antagonists were also more effective in disinhibition of trigeminal motoneurons during NREM sleep than REM sleep. For the effect of combined antagonism of GABAA and glycine receptors on trigeminal motoneurons, we estimated average numbers of masseter EMG from Figure 6B in (
The decrease of excitability of HM during NREM and REM sleep was investigated in several studies using various animal models. The increased interest to HM was mainly due to their innervation of upper airway muscles including the genioglossus, which play a critical role in maintaining the upper airway patency in OSA patients (
In early studies, the REM sleep-related decrease of excitability of HM was studied in a quantitative manner using decerebrated cats and anesthetized rats (
In the REM sleep model using anesthetized rats, pontine carbachol could repeatedly elicit REM sleep-like state in the same animals, which helped to study neurochemical mechanisms of the depressant effect of REM sleep on HM excitability. In one study, a mix containing four antagonists—bicuculline, strychnine, methysergide, and prazosin—to antagonize GABAA, glycine, 5HT and α1-adrenergic receptors, respectively, was microinjected into hypoglossal nucleus (
The abolition of the carbachol-induced depression of HM that occurred ~30 min after microinjections of the four antagonists into hypoglossal nucleus prompted us for additional studies to determine the role of each antagonist in this effect (
Important data has been obtained during natural sleep and wakefulness in behaving rats that has greatly advanced our understanding of the mechanisms of sleep-related depression of HM (
The effect of 5HT receptor antagonism on the GG muscle EMG have been studied using mianserin, a broad-spectrum 5HT antagonist (
Terazosin was used to study the role of α1-adrenoceptors in sleep-related decrease of GG activity in behaving rats (
The involvement of muscarinic receptor in the decrease of the GG muscle activity during NREM and REM sleep has been studied with scopolamine, a broad-spectrum muscarinic receptor antagonist (
The role of A1C1 catecholaminergic neurons in control of HM has been studied using chemogenetics in behaving transgenic mice. Inhibitory DREADD (designer receptors activated by designer drug) has been used to study the effect of inhibition of A1C1 neurons on EMG of the GG muscle during NREM sleep and wakefulness (
The major advantage of our analysis is that the single approach was used to uniformly quantify the contribution of excitatory and inhibitory inputs to the sleep-induced decrease of motoneuron excitability in different motoneuron pools. The relative contribution of state-dependent excitatory inputs to the total depressing effect of sleep was calculated using the Formula (5) whereas the contribution of state-dependent inhibitory inputs was calculated using Formula (6). These formulas can produce reliable results only when both state-dependent and non-state-dependent inputs that are removed by antagonists are of the same type, either excitatory or inhibitory; otherwise, the formulas produce false results. For example, methysergide had both disfacilitatory and disinhibitory effects on HM activity at the same time [see Figure 7A in (
The performed analysis of the state-dependent inputs, which contribute to the decrease of excitability of motoneurons during NREM and REM sleep, reveals that the neurochemical mechanisms of sleep-induced motoneuron depression is considerably different between the three motoneuronal pools (Figure
Our calculations confirmed that during natural REM sleep the decrease of excitability of spinal motoneurons is mediated only by glycinergic receptors (100%). The depression of trigeminal motoneurons during NREM sleep could be fully explained by excitatory glutamatergic input (~70%) and inhibitory GABAergic and/or glycinergic inputs (30%) whereas the contribution of these inputs during REM sleep was not detected by using either Formulas (5, 6). The depression of HM during natural REM sleep is approximately equally mediated by α1-adrenoceptors and muscarinic receptors (50/50%). In anesthetized animal model of REM sleep, α1-adrenoceptors mainly contributed to depression of HM during the “late” carbachol-induced REM sleep-like episodes (with some 5HT receptor contribution), which together fully (100%) accounted for the depressant effect of REM sleep-like state on HM. During the “early” carbachol-induced REM sleep-like episodes, the combined GABAA, glycinergic, 5HT, and α1-adrenergic inputs minimally contributed to the depression of HM. Other inputs must be responsible for HM depression during “early” REM sleep-like episodes, e.g., muscarinic, but this possibility was not tested. The neurotransmitters GABA, glycine and 5HT had minimal or no contribution to REM sleep-induced depression of HM activity regardless of used animal model. The contribution of A1C1 catecholaminergic neurons to NREM sleep-related depression of HM was not detected using the Formula (5).
VF developed the calculation approach, quantitatively analyzed available published data and wrote the manuscript.
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.