Dual oscillator model of the respiratory neuronal network generating quantal slowing of respiratory rhythm

Temporal variations in the pattern of breathing: techniques, sources, and applications to translational sciences

The breathing process possesses a complex variability caused in part by the respiratory central pattern generator in the brainstem; however, it also arises from chemical and mechanical feedback control loops, network reorganization and network sharing with nonrespiratory motor acts, as well as inputs from cortical and subcortical systems. The notion that respiratory fluctuations contain hidden information has prompted scientists to decipher respiratory signals to better understand the fundamental mechanisms of respiratory pattern generation, interactions with emotion, influences on the cortical neuronal networks associated with cognition, and changes in variability in healthy and disease-carrying individuals. Respiration can be used to express and control emotion. Furthermore, respiration appears to organize brain-wide network oscillations via cross-frequency coupling, optimizing cognitive performance. With the aid of information theory-based techniques and machine learning, the hidden information can be translated into a form usable in clinical practice for diagnosis, emotion recognition, and mental conditioning.

Differential impact of two critical respiratory centres in opioid-induced respiratory depression in awake mice

KEY POINTS

The main cause of death from opioid overdose is respiratory depression due to the activation of µ-opioid receptors (MORs). We conditionally deleted MORs from neurons in two key areas of the brainstem respiratory circuitry (the Kölliker-Fuse nucleus (KF) and pre-Bötzinger complex (preBötC)) to determine their role in opioid-induced respiratory disturbances in adult, awake mice. Deletion of MORs from KF neurons attenuated respiratory rate depression at all doses of morphine. Deletion of MORs from preBötC neurons attenuated rate depression at the low dose, but had no effect on rate following high doses of morphine. Instead, high doses of morphine increased the occurrence of apnoeas. The results indicate that opioids affect distributed key areas of the respiratory network in a dose-dependent manner and countering the respiratory effects of high dose opioids via the KF may be an effective approach to combat overdose.

ABSTRACT

The primary cause of death from opioid overdose is respiratory failure. High doses of opioids cause severe rate depression and increased risk of fatal apnoea, which correlate with increasing irregularities in breathing pattern. µ-Opioid receptors (MORs) are widely distributed throughout the brainstem respiratory network, but the mechanisms underlying respiratory depression are poorly understood. The medullary pre-Bötzinger complex (preBötC) and the pontine Kölliker-Fuse nucleus (KF) are considered critical for inducing opioid-related respiratory disturbances. We used a conditional knockout approach to investigate the roles and relative contribution of MORs in KF and preBötC neurons in opioid-induced respiratory depression in awake adult mice. The results revealed dose-dependent and region-specific opioid effects on the control of both respiratory rate and pattern. Respiratory depression induced by an anti-nociceptive dose of morphine was significantly attenuated following deletion of MORs from either the KF or the preBötC, suggesting cumulative network effects on respiratory rate control at low opioid doses. Deletion of MORs from KF neurons also relieved rate depression at near-maximal respiratory depressant doses of morphine. Meanwhile, deletion of MORs from the preBötC had no effect on rate following administration of high doses of morphine. Instead, a severe ataxic breathing pattern emerged with many apnoeas. We conclude that opioids affect distributed areas of the respiratory network and opioid-induced respiratory depression cannot be attributed to only one area in isolation. However, countering the effects of near maximal respiratory depressant doses of opioids in the KF may be a powerful approach to combat opioid overdose.

Different roles for inhibition in the rhythm-generating respiratory network

Unraveling the interplay of excitation and inhibition within rhythm-generating networks remains a fundamental issue in neuroscience. We use a biophysical model to investigate the different roles of local and long-range inhibition in the respiratory network, a key component of which is the pre-Bötzinger complex inspiratory microcircuit. Increasing inhibition within the microcircuit results in a limited number of out-of-phase neurons before rhythmicity and synchrony degenerate. Thus unstructured local inhibition is destabilizing and cannot support the generation of more than one rhythm. A two-phase rhythm requires restructuring the network into two microcircuits coupled by long-range inhibition in the manner of a half-center. In this context, inhibition leads to greater stability of the two out-of-phase rhythms. We support our computational results with in vitro recordings from mouse pre-Bötzinger complex. Partial excitation block leads to increased rhythmic variability, but this recovers after blockade of inhibition. Our results support the idea that local inhibition in the pre-Bötzinger complex is present to allow for descending control of synchrony or robustness to adverse conditions like hypoxia. We conclude that the balance of inhibition and excitation determines the stability of rhythmogenesis, but with opposite roles within and between areas. These different inhibitory roles may apply to a variety of rhythmic behaviors that emerge in widespread pattern-generating circuits of the nervous system.NEW & NOTEWORTHY The roles of inhibition within the pre-Bötzinger complex (preBötC) are a matter of debate. Using a combination of modeling and experiment, we demonstrate that inhibition affects synchrony, period variability, and overall frequency of the preBötC and coupled rhythmogenic networks. This work expands our understanding of ubiquitous motor and cognitive oscillatory networks.

Computational models of the neural control of breathing

The ongoing process of breathing underlies the gas exchange essential for mammalian life. Each respiratory cycle ensues from the activity of rhythmic neural circuits in the brainstem, shaped by various modulatory signals, including mechanoreceptor feedback sensitive to lung inflation and chemoreceptor feedback dependent on gas composition in blood and tissues. This paper reviews a variety of computational models designed to reproduce experimental findings related to the neural control of breathing and generate predictions for future experimental testing. The review starts from the description of the core respiratory network in the brainstem, representing the central pattern generator (CPG) responsible for producing rhythmic respiratory activity, and progresses to encompass additional complexities needed to simulate different metabolic challenges, closed-loop feedback control including the lungs, and interactions between the respiratory and autonomic nervous systems. The integrated models considered in this review share a common framework including a distributed CPG core network responsible for generating the baseline three-phase pattern of rhythmic neural activity underlying normal breathing. WIREs Syst Biol Med 2017, 9:e1371. doi: 10.1002/wsbm.1371 For further resources related to this article, please visit the WIREs website.

Effects of ion channel noise on neural circuits: an application to the respiratory pattern generator to investigate breathing variability

Neural activity generally displays irregular firing patterns even in circuits with apparently regular outputs, such as motor pattern generators, in which the output frequency fluctuates randomly around a mean value. This "circuit noise" is inherited from the random firing of single neurons, which emerges from stochastic ion channel gating (channel noise), spontaneous neurotransmitter release, and its diffusion and binding to synaptic receptors. Here we demonstrate how to expand conductance-based network models that are originally deterministic to include realistic, physiological noise, focusing on stochastic ion channel gating. We illustrate this procedure with a well-established conductance-based model of the respiratory pattern generator, which allows us to investigate how channel noise affects neural dynamics at the circuit level and, in particular, to understand the relationship between the respiratory pattern and its breath-to-breath variability. We show that as the channel number increases, the duration of inspiration and expiration varies, and so does the coefficient of variation of the breath-to-breath interval, which attains a minimum when the mean duration of expiration slightly exceeds that of inspiration. For small channel numbers, the variability of the expiratory phase dominates over that of the inspiratory phase, and vice versa for large channel numbers. Among the four different cell types in the respiratory pattern generator, pacemaker cells exhibit the highest sensitivity to channel noise. The model shows that suppressing input from the pons leads to longer inspiratory phases, a reduction in breathing frequency, and larger breath-to-breath variability, whereas enhanced input from the raphe nucleus increases breathing frequency without changing its pattern.

NEW & NOTEWORTHY

A major source of noise in neuronal circuits is the "flickering" of ion currents passing through the neurons' membranes (channel noise), which cannot be suppressed experimentally. Computational simulations are therefore the best way to investigate the effects of this physiological noise by manipulating its level at will. We investigate the role of noise in the respiratory pattern generator and show that endogenous, breath-to-breath variability is tightly linked to the respiratory pattern.

Emergent Network Topology within the Respiratory Rhythm-Generating Kernel Evolved In Silico

We hypothesize that the network topology within the pre-Bötzinger Complex (preBötC), the mammalian respiratory rhythm generating kernel, is not random, but is optimized in the course of ontogeny/phylogeny so that the network produces respiratory rhythm efficiently and robustly. In the present study, we attempted to identify topology of synaptic connections among constituent neurons of the preBötC based on this hypothesis. To do this, we first developed an effective evolutionary algorithm for optimizing network topology of a neuronal network to exhibit a ‘desired characteristic’. Using this evolutionary algorithm, we iteratively evolved an in silico preBötC ‘model’ network with initial random connectivity to a network exhibiting optimized synchronous population bursts. The evolved ‘idealized’ network was then analyzed to gain insight into: (1) optimal network connectivity among different kinds of neurons—excitatory as well as inhibitory pacemakers, non-pacemakers and tonic neurons—within the preBötC, and (2) possible functional roles of inhibitory neurons within the preBötC in rhythm generation. Obtained results indicate that (1) synaptic distribution within excitatory subnetwork of the evolved model network illustrates skewed/heavy-tailed degree distribution, and (2) inhibitory subnetwork influences excitatory subnetwork primarily through non-tonic pacemaker inhibitory neurons. Further, since small-world (SW) network is generally associated with network synchronization phenomena and is suggested as a possible network structure within the preBötC, we compared the performance of SW network with that of the evolved model network. Results show that evolved network is better than SW network at exhibiting synchronous bursts.

Oxygen in demand: How oxygen has shaped vertebrate physiology

In response to varying environmental and physiological challenges, vertebrates have evolved complex and often overlapping systems. These systems detect changes in environmental oxygen availability and respond by increasing oxygen supply to the tissues and/or by decreasing oxygen demand at the cellular level. This suite of responses is termed the oxygen transport cascade and is comprised of several components. These components include 1) chemosensory detectors that sense changes in oxygen, carbon dioxide, and pH in the blood, and initiate changes in 2) ventilation and 3) cardiac work, thereby altering the rate of oxygen delivery to, and carbon dioxide clearance from, the tissues. In addition, changes in 4) cellular and systemic metabolism alters tissue-level metabolic demand. Thus the need for oxygen can be managed locally when increasing oxygen supply is not sufficient or possible. Together, these mechanisms provide a spectrum of responses that facilitate the maintenance of systemic oxygen homeostasis in the face of environmental hypoxia or physiological oxygen depletion (i.e. due to exercise or disease). Bill Milsom has dedicated his career to the study of these responses across phylogenies, repeatedly demonstrating the power of applying the comparative approach to physiological questions. The focus of this review is to discuss the anatomy, signalling pathways, and mechanics of each step of the oxygen transport cascade from the perspective of a Milsomite. That is, by taking into account the developmental, physiological, and evolutionary components of questions related to oxygen transport. We also highlight examples of some of the remarkable species that have captured Bill's attention through their unique adaptations in multiple components of the oxygen transport cascade, which allow them to achieve astounding physiological feats. Bill's research examining the oxygen transport cascade has provided important insight and leadership to the study of the diverse suite of adaptations that maintain cellular oxygen content across vertebrate taxa, which underscores the value of the comparative approach to the study of physiological systems.

Pixel timing correction in time-lapsed calcium imaging using point scanning microscopy

In point scanning imaging, data are acquired by sequentially scanning each pixel of a predetermined area. This way of scanning leads to time delays between pixels, especially for lower scanning speed or large scanned areas. Therefore, experiments are often performed at lower framerates in order to ensure a sufficient signal-to-noise ratio, even though framerates above 30 frames per second are technically feasible. For these framerates, we suggest that it becomes crucial to correct the time delay between image pixels prior to analyses. In this paper, we apply temporal interpolation (or pixel timing correction) for calcium imaging in two-photon microscopy as an example of fluorescence imaging. We present and compare three interpolation methods (linear, Lanczos and cubic B-spline). We test these methods on a simulated network of coupled bursting neurons at different framerates. In this network, we introduce a time delay to simulate a scanning by point scanning microscopy. We also assess these methods on actual microscopic calcium imaging movies recorded at usual framerates. Our numerical results suggest that point scanning microscopy imaging introduces statistically significant time delays between image pixels at low frequency. However, we demonstrate that pixel timing correction compensates for these time delays, regardless of the used interpolation method.

Genetic ablation of VIAAT in glycinergic neurons causes a severe respiratory phenotype and perinatal death

Both glycinergic and GABAergic neurons require the vesicular inhibitory amino acid transporter (VIAAT) for synaptic vesicle filling. Presynaptic GABA concentrations are determined by the GABA-synthesizing enzymes glutamate decarboxylase (GAD)65 and GAD67, whereas the presynaptic glycine content depends on the plasma membrane glycine transporter 2 (GlyT2). Although severely impaired, glycinergic transmission is not completely absent in GlyT2-knockout mice, suggesting that other routes of glycine uptake or de novo synthesis of glycine exist in presynaptic terminals. To investigate the consequences of a complete loss of glycinergic transmission, we generated a mouse line with a conditional ablation of VIAAT in glycinergic neurons by crossing mice with loxP-flanked VIAAT alleles with a GlyT2-Cre transgenic mouse line. Interestingly, conditional VIAAT knockout (VIAAT cKO) mice were not viable at birth. In addition to the dominant respiratory failure, VIAAT cKO showed an umbilical hernia and a cleft palate. Immunohistochemistry revealed an almost complete depletion of VIAAT in the brainstem. Electrophysiology revealed the absence of both spontaneous glycinergic and GABAergic inhibitory postsynaptic currents from hypoglossal motoneurons. Our results demonstrate that the deletion of VIAAT in GlyT2-Cre expressing neurons also strongly affects GABAergic transmission and suggest a large overlap of the glycinergic and the GABAergic neuron population during early development in the caudal parts of the brain.

Control of breathing in invertebrate model systems

The invertebrates have adopted a myriad of breathing strategies to facilitate the extraction of adequate quantities of oxygen from their surrounding environments. Their respiratory structures can take a wide variety of forms, including integumentary surfaces, lungs, gills, tracheal systems, and even parallel combinations of these same gas exchange structures. Like their vertebrate counterparts, the invertebrates have evolved elaborate control strategies to regulate their breathing activity. Our goal in this article is to present the reader with a description of what is known regarding the control of breathing in some of the specific invertebrate species that have been used as model systems to study different mechanistic aspects of the control of breathing. We will examine how several species have been used to study fundamental principles of respiratory rhythm generation, central and peripheral chemosensory modulation of breathing, and plasticity in the control of breathing. We will also present the reader with an overview of some of the behavioral and neuronal adaptability that has been extensively documented in these animals. By presenting explicit invertebrate species as model organisms, we will illustrate mechanistic principles that form the neuronal foundation of respiratory control, and moreover appear likely to be conserved across not only invertebrates, but vertebrate species as well.

Integrative approaches for modeling regulation and function of the respiratory system

Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained.

Analysis of a scenario for chaotic quantal slowing down of inspiration

On exposure to opiates, preparations from rat brain stems have been observed to continue to produce regular expiratory signals, but to fail to produce some inspiratory signals. The numbers of expirations between two successive inspirations form an apparently random sequence. Here, we propose an explanation based on the qualitative theory of dynamical systems. A relatively simple scenario for the dynamics of interaction between the generators of expiratory and inspiratory signals produces pseudo-random behaviour of the type observed.

Interacting oscillations in neural control of breathing: modeling and qualitative analysis

In mammalian respiration, late-expiratory (late-E, or pre-inspiratory) oscillations emerge in abdominal motor output with increasing metabolic demands (e.g., during hypercapnia, hypoxia, etc.). These oscillations originate in the retrotrapezoid nucleus/parafacial respiratory group (RTN/pFRG) and couple with the respiratory oscillations generated by the interacting neural populations of the Bötzinger (BötC) and pre-Bötzinger (pre-BötC) complexes, representing the kernel of the respiratory central pattern generator. Recently, we analyzed experimental data on the generation of late-E oscillations and proposed a large-scale computational model that simulates the possible interactions between the BötC/pre-BötC and RTN/pFRG oscillations under different conditions. Here we describe a reduced model that maintains the essential features and architecture of the large-scale model, but relies on simplified activity-based descriptions of neural populations. This simplification allowed us to use methods of dynamical systems theory, such as fast-slow decomposition, bifurcation analysis, and phase plane analysis, to elucidate the mechanisms and dynamics of synchronization between the RTN/pFRG and BötC/pre-BötC oscillations. Three physiologically relevant behaviors have been analyzed: emergence and quantal acceleration of late-E oscillations during hypercapnia, transformation of the late-E activity into a biphasic-E activity during hypercapnic hypoxia, and quantal slowing of BötC/pre-BötC oscillations with the reduction of pre-BötC excitability. Each behavior is elicited by gradual changes in excitatory drives or other model parameters, reflecting specific changes in metabolic and/or physiological conditions. Our results provide important theoretical insights into interactions between RTN/pFRG and BötC/pre-BötC oscillations and the role of these interactions in the control of breathing under different metabolic conditions.