Vagal-dependent nonlinear variability in the respiratory pattern of anesthetized, spontaneously breathing rats

Physiological rhythms, including respiration, exhibit endogenous variability associated with health, and deviations from this are associated with disease. Specific changes in the linear and nonlinear sources of breathing variability have not been investigated. In this study, we used information theory-based techniques, combined with surrogate data testing, to quantify and characterize the vagal-dependent nonlinear pattern variability in urethane-anesthetized, spontaneously breathing adult rats. Surrogate data sets preserved the amplitude distribution and linear correlations of the original data set, but nonlinear correlation structure in the data was removed. Differences in mutual information and sample entropy between original and surrogate data sets indicated the presence of deterministic nonlinear or stochastic non-Gaussian variability. With vagi intact (n = 11), the respiratory cycle exhibited significant nonlinear behavior in templates of points separated by time delays ranging from one sample to one cycle length. After vagotomy (n = 6), even though nonlinear variability was reduced significantly, nonlinear properties were still evident at various time delays. Nonlinear deterministic variability did not change further after subsequent bilateral microinjection of MK-801, an N-methyl-D-aspartate receptor antagonist, in the Kölliker-Fuse nuclei. Reversing the sequence (n = 5), blocking N-methyl-D-aspartate receptors bilaterally in the dorsolateral pons significantly decreased nonlinear variability in the respiratory pattern, even with the vagi intact, and subsequent vagotomy did not change nonlinear variability. Thus both vagal and dorsolateral pontine influences contribute to nonlinear respiratory pattern variability. Furthermore, breathing dynamics of the intact system are mutually dependent on vagal and pontine sources of nonlinear complexity. Understanding the structure and modulation of variability provides insight into disease effects on respiratory patterning.

Multiple pontomedullary mechanisms of respiratory rhythmogenesis

Mammalian central pattern generators producing rhythmic movements exhibit robust but flexible behavior. However, brainstem network architectures that enable these features are not well understood. Using precise sequential transections through the pons to medulla, it was observed that there was compartmentalization of distinct rhythmogenic mechanisms in the ponto-medullary respiratory network, which has rostro-caudal organization. The eupneic 3-phase respiratory pattern was transformed to a 2-phase and then to a 1-phase pattern as the network was physically reduced. The pons, the retrotrapezoid nucleus and glycine mediated inhibition are all essential for expression of the 3-phase rhythm. The 2-phase rhythm depends on inhibitory interactions (reciprocal) between Bötzinger and pre-Bötzinger complexes, whereas the 1-phase-pattern is generated within the pre-Bötzinger complex and is reliant on the persistent sodium current. In conditions of forced expiration, the RTN region was found to be essential for the expression of abdominal late expiratory activity. However, it is unknown whether the RTN generates or simply relays this activity. Entrained with the central respiratory network is the sympathetic nervous system, which exhibits patterns of discharge coupled with the respiratory cycle (in terms of both gain and phase of coupling) and dysfunctions in this coupling appear to underpin pathological conditions. In conclusion, the respiratory network has rhythmogenic capabilities at multiple levels of network organization, allowing expression of motor patterns specific for various physiological and pathophysiological respiratory behaviors.

Abdominal expiratory activity in the rat brainstem-spinal cord in situ: patterns, origins and implications for respiratory rhythm generation

We studied respiratory neural activity generated during expiration. Motoneuronal activity was recorded simultaneously from abdominal (AbN), phrenic (PN), hypoglossal (HN) and central vagus nerves from neonatal and juvenile rats in situ. During eupnoeic activity, low-amplitude post-inspiratory (post-I) discharge was only present in AbN motor outflow. Expression of AbN late-expiratory (late-E) activity, preceding PN bursts, occurred during hypercapnia. Biphasic expiratory (biphasic-E) activity with pre-inspiratory (pre-I) and post-I discharges occurred only during eucapnic anoxia or hypercapnic anoxia. Late-E activity generated during hypercapnia (7-10% CO(2)) was abolished with pontine transections or chemical suppression of retrotrapezoid nucleus/ventrolateral parafacial (RTN/vlPF). AbN late-E activity during hypercapnia is coupled with augmented pre-I discharge in HN, truncated PN burst, and was quiescent during inspiration. Our data suggest that the pons provides a necessary excitatory drive to an additional neural oscillatory mechanism that is only activated under conditions of high respiratory drive to generate late-E activity destined for AbN motoneurones. This mechanism may arise from neurons located in the RTN/vlPF or the latter may relay late-E activity generated elsewhere. We hypothesize that this oscillatory mechanism is not a necessary component of the respiratory central pattern generator but constitutes a defensive mechanism activated under critical metabolic conditions to provide forced expiration and reduced upper airway resistance simultaneously. Possible interactions of this oscillator with components of the brainstem respiratory network are discussed.

Reconfiguration of the pontomedullary respiratory network: a computational modeling study with coordinated in vivo experiments

A large body of data suggests that the pontine respiratory group (PRG) is involved in respiratory phase-switching and the reconfiguration of the brain stem respiratory network. However, connectivity between the PRG and ventral respiratory column (VRC) in computational models has been largely ad hoc. We developed a network model with PRG-VRC connectivity inferred from coordinated in vivo experiments. Neurons were modeled in the "integrate-and-fire" style; some neurons had pacemaker properties derived from the model of Breen et al. We recapitulated earlier modeling results, including reproduction of activity profiles of different respiratory neurons and motor outputs, and their changes under different conditions (vagotomy, pontine lesions, etc.). The model also reproduced characteristic changes in neuronal and motor patterns observed in vivo during fictive cough and during hypoxia in non-rapid eye movement sleep. Our simulations suggested possible mechanisms for respiratory pattern reorganization during these behaviors. The model predicted that network- and pacemaker-generated rhythms could be co-expressed during the transition from gasping to eupnea, producing a combined "burst-ramp" pattern of phrenic discharges. To test this prediction, phrenic activity and multiple single neuron spike trains were monitored in vagotomized, decerebrate, immobilized, thoracotomized, and artificially ventilated cats during hypoxia and recovery. In most experiments, phrenic discharge patterns during recovery from hypoxia were similar to those predicted by the model. We conclude that under certain conditions, e.g., during recovery from severe brain hypoxia, components of a distributed network activity present during eupnea can be co-expressed with gasp patterns generated by a distinct, functionally "simplified" mechanism.

Spatial and functional architecture of the mammalian brain stem respiratory network: a hierarchy of three oscillatory mechanisms

Mammalian central pattern generators (CPGs) producing rhythmic movements exhibit extremely robust and flexible behavior. Network architectures that enable these features are not well understood. Here we studied organization of the brain stem respiratory CPG. By sequential rostral to caudal transections through the pontine-medullary respiratory network within an in situ perfused rat brain stem-spinal cord preparation, we showed that network dynamics reorganized and new rhythmogenic mechanisms emerged. The normal three-phase respiratory rhythm transformed to a two-phase and then to a one-phase rhythm as the network was reduced. Expression of the three-phase rhythm required the presence of the pons, generation of the two-phase rhythm depended on the integrity of Bötzinger and pre-Bötzinger complexes and interactions between them, and the one-phase rhythm was generated within the pre-Bötzinger complex. Transformation from the three-phase to a two-phase pattern also occurred in intact preparations when chloride-mediated synaptic inhibition was reduced. In contrast to the three-phase and two-phase rhythms, the one-phase rhythm was abolished by blockade of persistent sodium current (I(NaP)). A model of the respiratory network was developed to reproduce and explain these observations. The model incorporated interacting populations of respiratory neurons within spatially organized brain stem compartments. Our simulations reproduced the respiratory patterns recorded from intact and sequentially reduced preparations. Our results suggest that the three-phase and two-phase rhythms involve inhibitory network interactions, whereas the one-phase rhythm depends on I(NaP). We conclude that the respiratory network has rhythmogenic capabilities at multiple levels of network organization, allowing expression of motor patterns specific for various physiological and pathophysiological respiratory behaviors.

Modeling the ponto-medullary respiratory network

The generation and shaping of the respiratory motor pattern are performed in the lower brainstem and involve neuronal interactions within the medulla and between the medulla and pons. A computational model of the ponto-medullary respiratory network has been developed by incorporating existing experimental data on the medullary neural circuits and possible interactions between the medulla and pons. The model reproduces a number of experimental findings concerning alterations of the respiratory pattern following various perturbations/stimulations applied to the pons and pulmonary afferents. The results of modeling support the concept that eupneic respiratory rhythm generation requires contribution of the pons whereas a gasping-like rhythm (and the rhythm observed in vitro) may be generated within the medulla and involve pacemaker-driven mechanisms localized within the medullary pre-Botzinger Complex. The model and experimental data described support the concept that during eupnea the respiration-related pontine structures control the medullary network mechanisms for respiratory phase transitions, suppress the intrinsic pacemaker-driven oscillations in the pre-BotC and provide inspiration-inhibitory and expiration-facilitatory reflexes which are independent of the pulmonary Hering-Breuer reflex but operate through the same medullary phase switching circuits.

Computational modeling of the baroreflex arc: nucleus tractus solitarius

In this study, we examine the utility of computational modeling in understanding nervous system function. We start by examining the reasons for, and major approaches to, computational modeling. We then chose a modeling approach and applied different variations to understanding nucleus tractus solitarius (NTS) neuronal responses to various baroreceptive stimuli. We examine the results in light of our objectives and with regard to the known parameters of the system under investigation. Our results demonstrate that modeling can be a useful tool in analysis of (and examination of underlying mechanisms for) NTS behavior on many levels.

A model of attention-guided visual perception and recognition

A model of visual perception and recognition is described. The model contains: (i) a low-level subsystem which performs both a fovea-like transformation and detection of primary features (edges), and (ii) a high-level subsystem which includes separated 'what' (sensory memory) and 'where' (motor memory) structures. Image recognition occurs during the execution of a 'behavioral recognition program' formed during the primary viewing of the image. The recognition program contains both programmed attention window movements (stored in the motor memory) and predicted image fragments (stored in the sensory memory) for each consecutive fixation. The model shows the ability to recognize complex images (e.g. faces) invariantly with respect to shift, rotation and scale.

Modeling neural mechanisms for genesis of respiratory rhythm and pattern. I. Models of respiratory neurons

The general objectives of our research, presented in this series of papers, were to develop a computational model of the brain stem respiratory neural network and to explore possible neural mechanisms that provide the genesis of respiratory oscillations and the specific firing patterns of respiratory neurons. The present paper describes models of single respiratory neurons that have been used as the elements in our network models of the central respiratory pattern generator presented in subsequent papers. The models of respiratory neurons were developed in the Hodgkin-Huxley style employing both physiological and biophysical data obtained from brain stem neurons in mammals. Two single respiratory neuron models were developed to match the two distinct firing behaviors of respiratory neurons described in vivo: neuron type I shows an adapting firing pattern in response to synaptic excitation, and neuron type II shows a ramp firing pattern during membrane depolarization after a period of synaptic inhibition. We found that a frequency ramp firing pattern can result from intrinsic membrane properties, specifically from the combined influence of calcium-dependent K(AHP)(Ca), low-threshold Ca(T) and K(A) channels. The neuron models with these ionic channels (type II) demonstrated ramp firing patterns similar to those recorded from respiratory neurons in vivo. Our simulations show that K(AHP)(Ca) channels in combination with high-threshold Ca(L) channels produce spike frequency adaptation during synaptic excitation. However, in combination with low-threshold Ca(T) channels, they cause a frequency ramp firing response after release from inhibition. This promotes a testable hypothesis that the main difference between the respiratory neurons that adapt (for example, early inspiratory, postinspiratory, and decrementing expiratory) and those that show ramp firing patterns (for example, ramp inspiratory and augmenting expiratory) consists of a ratio between the two types of calcium channels: Ca(L) channels predominate in the former and Ca(T) channels in the latter respiratory neuron types. We have analyzed the dependence of adapting and ramp firing patterns on maximal conductances of different ionic channels and values of synaptic drive. The effect of adjusting specific membrane conductances and synaptic interactions revealed plausible neuronal mechanisms that may underlie modulatory effects on respiratory neuron firing patterns and network performances. The results of computer simulation provide useful insight into functional significance of specific intrinsic membrane properties and their interactions with phasic synaptic inputs for a better understanding of respiratory neuron firing behavior.

Modeling neural mechanisms for genesis of respiratory rhythm and pattern. III. Comparison of model performances during afferent nerve stimulation

The goal of the present study was to evaluate the relative plausibility of the models of the central respiratory pattern generator (CRPG) proposed in our previous paper. To test the models, we compared changes in generated patterns with the experimentally observed alterations of the respiratory pattern induced by various stimuli applied to superior laryngeal (SLN), vagus and carotid sinus (CS) nerves. In all models, short-duration SLN simulation caused phase-resetting behavior consistent with experimental data. Relatively weak sustained SLN stimulation elicited a two-phase rhythm comprising inspiration and postinspiration whereas a stronger stimulation stopped oscillations in the postinspiratory phase ("postinspiratory apnea"). In all models, sustained vagus nerve stimulation produced postinspiratory apnea. A short vagal stimulus delivered during inspiration terminated this phase. The threshold for inspiratory termination decreased during the course of the inspiratory phase. The effects of short-duration vagal stimulation applied during expiration were different in different models. In model 1, stimuli delivered in the postinspiratory phase prolonged expiration whereas the late expiratory phase was insensitive to vagal stimulation. No insensitive period was found in model 2 because vagal stimuli delivered at any time during expiration prolonged this phase. Model 3 demonstrated a short period insensitive to vagal stimulation at the very end of expiration. When phasic CS nerve stimulation was applied during inspiration or the first half of expiration, the performances of all models were similar and consistent with experimental data: stimuli delivered at the beginning inspiration shortened this phase whereas stimuli applied in the middle or at the end of inspiration prolonged it and stimuli delivered in the first half of expiration prolonged the expiratory interval. Behavior of the models were different when CS stimuli were delivered during the late expiratory phase. In model 1, these stimuli were ineffective or shortened expiration initiating the next inspiration. Alternatively, in models 2 and 3, they caused a prolongation of expiration. Although all CRPG models demonstrated a number of plausible alterations in the respiratory pattern elicited by afferent nerve stimulation, the behavior of model 1 was most consistent with experimental data. Taking into account differences in the model architectures and employed neural mechanisms, we suggest that the concept of respiratory rhythmogenesis based on the essential role of postinspiratory neurons is more plausible than the concept employing specific functional properties of decrementing expiratory (dec-E) neurons and that the ramp firing pattern of the late expiratory neuron is more likely to reflect intrinsic properties than disinhibition from the dec-E neurons.

A neuro-mimetic dynamic scheduling algorithm for control: analysis and applications

A simple neuronal network model of the baroreceptor reflex is analyzed. From a control perspective, the analysis suggests a dynamic scheduled control mechanisms by which the baroreflex may perform regulation of the blood pressure. The main objectives of this work are to investigate the static and dynamic response characteristics of the single neurons and the network, to analyze the neuromimetic dynamic scheduled control function of the model, and to apply the algorithm to nonlinear process control problems. The dynamic scheduling activity of the network is exploited in two control architectures. Control structure I is drawn directly from the present model of the baroreceptor reflex. An application of this structure for level control in a conical tank is described. Control structure II employs an explicit set point to determine the feedback error. The performance of this control structure is illustrated on a nonlinear continuous stirred tank reactor with van de Vusse kinetics. The two case studies validate the dynamic scheduled control approach for nonlinear process control applications.

Modeling neural mechanisms for genesis of respiratory rhythm and pattern. II. Network models of the central respiratory pattern generator

The present paper describes several models of the central respiratory pattern generator (CRPG) developed employing experimental data and current hypotheses for respiratory rhythmogenesis. Each CRPG model includes a network of respiratory neuron types (e.g., early inspiratory; ramp inspiratory; late inspiratory; decrementing expiratory; postinspiratory; stage II expiratory; stage II constant firing expiratory; preinspiratory) and simplified models of lung and pulmonary stretch receptors (PSR), which provide feedback to the respiratory network. The used models of single respiratory neurons were developed in the Hodgkin-Huxley style as described in the previous paper. The mechanism for termination of inspiration (the inspiratory off-switch) in all models operates via late-I neuron, which is considered to be the inspiratory off-switching neuron. Several two- and three-phase CRPG models have been developed using different accepted hypotheses of the mechanism for termination of expiration. The key elements in the two-phase models are the early-I and dec-E neurons. The expiratory off-switch mechanism in these models is based on the mutual inhibitory connections between early-I and dec-E and adaptive properties of the dec-E neuron. The difference between the two-phase models concerns the mechanism for ramp firing patterns of E2 neurons resulting either from the intrinsic neuronal properties of the E2 neuron or from disinhibition from the adapting dec-E neuron. The key element of the three-phase models is the pre-I neuron, which acts as the expiratory off-switching neuron. The three-phase models differ by the mechanisms used for termination of expiration and for the ramp firing patterns of E2 neurons. Additional CRPG models were developed employing a dual switching neuron that generates two bursts per respiratory cycle to terminate both inspiration and expiration. Although distinctly different each model generates a stable respiratory rhythm and shows physiologically plausible firing patterns of respiratory neurons with and without PSR feedback. Using our models, we analyze the roles of different respiratory neuron types and their interconnections for the respiratory rhythm and pattern generation. We also investigate the possible roles of intrinsic biophysical properties of different respiratory neurons in controlling the duration of respiratory phases and timing of switching between them. We show that intrinsic membrane properties of respiratory neurons are integrated with network properties of the CRPG at three hierarchical levels: at the cellular level to provide the specific firing patterns of respiratory neurons (e.g., ramp firing patterns); at the network level to provide switching between the respiratory phases; and at the systems level to control the duration of inspiration and expiration under different conditions (e.g., lack of PSR feedback).

[reflection of stimulus orientation in reactions of visual cortex neurons]

A mathematical model of neuronal target structure with spatial anisotropy of lateral inhibition is discussed. The positions of the neuronal target to oriented sensory stimuli are investigated by computer simulation. It is suggested that visual stimuli orientation is coded in the late phase of dynamic responses of cortical neurons. This idea is in agreement with the data obtained in experiments on guinea pig visual cortex neurons.