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1Cellular and Systems Neurobiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland; 2Department of Physiology, Bristol Heart Institute, School of Medical Sciences, University of Bristol, Bristol, United Kingdom; 3Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, Pennsylvania
Submitted 1 September 2007; accepted in final form 28 September 2007
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSREFERENCES |
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; Marder and Calabrese 1996; Selverston and Ayers 2006), the spatial and functional architectures of CPG circuits in the mammalian CNS, such as those generating breathing movements, have not been well defined. Breathing in mammals is a dynamically mutable motor behavior that not only performs a vital homeostatic function but is also integrated with many other physiological functions including suckling, swallowing, sniffing, chewing, and vocalization. With such functional diversity, respiratory CPG circuits must have a robust, yet highly flexible organization, permitting multiple state-dependent modes of operation. Here, we have attempted to uncover structural and functional properties of respiratory circuits that enable multiple modes of rhythmic motor pattern generation.
Breathing movements are produced by a pontine-medullary respiratory network that generates rhythmic patterns of alternating inspiratory and expiratory activities to coordinate activity of spinal and cranial motoneurons (Bianchi et al. 1995; Cohen 1979; Feldman and Smith 1995; Richter 1996). The motor pattern during normal breathing was considered to consist of three phases: inspiration, postinspiration, and late expiration (Richter 1996; Richter and Spyer 2001), which can be recognized in the integrated activities of the phrenic and cranial (e.g., laryngeal) nerves. This pattern originates within a bilateral column of medullary neurons—the ventral respiratory column (VRC)—and is controlled by the pons. The VRC includes three rostro-caudally arranged compartments (Figs. 1 and 2): Bötzinger complex (BötC), pre-Bötzinger complex (pre-BötC), and rostral ventral respiratory group (rVRG). Respiratory neurons in these compartments are usually classified based on their firing pattern (e.g., decrementing, augmenting) and the phase of activity relative to the breathing cycle, such as early-inspiratory (early-I) with a decrementing inspiratory pattern; ramp-inspiratory (ramp-I) with a augmenting inspiratory pattern; postinspiratory (post-I) or decrementing expiratory (dec-E); augmenting or stage II expiratory (aug-E or E-2); and preinspiratory (pre-I) (see Richter 1996 for review).
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; Cohen 1979; Cohen and Shaw 2004; Ezure 2004; Ezure and Tanaka 2006; Okazaki et al. 2002; Song and Poon 2004; St.-John 1998), its functional role in the generation and control of respiratory rhythm and pattern has not been fully established. In addition, several medullary structures, specifically the retrotrapezoid nucleus (RTN; located below the facial nucleus rostral to BötC) and the medullary raphé nucleus, both involved in central chemoreception, modulate medullary respiratory network performance via various drives that adapt the CPG activity to the metabolic state of the system such as the level of carbon dioxide in blood (Guyenet et al. 2005; Richerson 2004).
The BötC, with predominately expiratory neurons (post-I and aug-E), is considered a major source of expiratory activity (Ezure 1990; Ezure et al. 2003; Jiang and Lipski 1990; Tian et al. 1999). The adjacent, more caudal pre-BötC contains circuitry essential for generating inspiratory activity (Feldman and Del Negro 2006; Smith et al. 1991, 2000). The activity of bulbospinal inspiratory (ramp-I) neurons of the rVRG, projecting to phrenic motoneurons and shaping the phrenic output motor pattern, is driven by the pre-BötC and inhibited (during expiration) by the BötC. Although the function of the BötC and its interactions with other VRC compartments were well studied (Ezure 1990; Ezure and Manabe 1988; Ezure et al. 2003; Fedorko and Merrill 1984; Jiang and Lipski 1990; Long and Duffin 1986; Shen et al. 2003; Tian et al. 1999), an exclusive role of BötC neurons in the expression of expiration and coordination of inspiratory and expiratory activities has been recently debated. Specifically, it has been proposed that a separate expiratory oscillator, located outside of the BötC in the parafacial respiratory group (pFRG), interacts with the pre-BötC to generate coordinated patterns of inspiratory and expiratory activity (Feldman and Del Negro 2006; Janczewski and Feldman 2006).
The medullary pre-BötC has been of intense interest because it is thought to function as a kernel structure that can be experimentally isolated in vitro and expresses autorhythmic or pacemaker-like activity (Johnson et al. 2001; Koshiya and Smith 1999). This activity is proposed to be based on intrinsic persistent sodium current (INaP)-dependent mechanisms (Butera et al. 1999a,b; Rybak et al. 2003b, 2004b; Smith et al. 2000). The isolated pre-BötC generates a rudimentary pattern of inspiratory activity (Smith et al. 1991, 2000). However, the mechanisms underlying inspiratory pattern generation in the pre-BötC under more physiological conditions when the pre-BötC is embedded in the intact brain stem have not been established.
Here, we tested our hypotheses that there is a spatial and functional compartmentalization of the respiratory network and that the pre-BötC, as one of the key compartments, is functionally embedded in the spatially distributed brain stem network and, depending on interactions with other compartments, can operate in multiple modes of rhythm generation, such as intrinsic bursting, which does not require phasic inhibition, or a tonic activity mode that needs phasic inhibition for rhythmic bursting activity (Butera et al. 1999a,b; Rybak et al. 2003b, 2004b; Smith et al. 2000). We proposed that inputs from the BötC (providing phasic inhibition) and from more rostral structures including the pons (controlling the state of the pre-BötC) define the mode of pre-BötC operation and hence the rhythmogenic mechanism expressed in the entire brain stem respiratory network.
To uncover this potential hierarchy of network interactions, we used an in situ arterially perfused rat brain stem–spinal cord preparation and performed sequential rostral to caudal transections through the pontine-medullary respiratory column. We analyzed resulting transformations of respiratory motor patterns and studied the dependence of these patterns on chloride-mediated inhibition and intrinsic INaP-dependent mechanisms. A computational model of the brain stem respiratory network with a hierarchy of pontine-medullary circuit components was used to suggest how the inhibitory and excitatory network interactions and the intrinsic INaP-dependent mechanisms contribute to rhythm generation in the different network states. We conclude that there are at least three rhythmogenic mechanisms embedded within hierarchically interacting pontine-medullary circuits that define the expression of different motor patterns underpinning distinct physiological and pathophysiological respiratory behaviors.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSREFERENCES |
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The experimental studies were performed using the in situ perfused brain stem–spinal cord preparation of the juvenile rat (Paton 1996). This preparation allows precise control of arterial perfusion of the in situ brain stem–spinal cord with independent control of perfusate O2/CO2 concentrations, as well as administration of pharmacological agents through the perfusate that would be incompatible with viability of in vivo preparations.
All procedures conformed to the UK Animals (Home Office Scientific Procedures) Act 1986 and were approved by the University of Bristol ethical review committee. In brief, preheparinzed (1,000 units, given intraperitoneally) male Wistar rats (60–110 g) were anesthetized deeply with halothane until loss of paw withdrawal reflex. Rats were bisected subdiaphragmatically, the head and thorax was immersed in ice-chilled carbogenated Ringer solution, and the brain was decerebrated precollicularly. The cerebellum was removed to gain direct visual access to the dorsal brain stem surface. Thoracic phrenic (PN), cervical vagus (cVN), and hypoglossal (HN) nerves (all left) were cut distally. Preparations were transferred to a recording chamber and positioned prone, and the head was fixed using ear bars and a snout clamp that ensured the brain stem was orientated similarly in all preparations. A double lumen cannula (DLR-4, Braintree Scientific) was inserted into the descending aorta for retrograde perfusion. Perfusion was supplied through a peristaltic roller pump (Watson Marlow 505D) and consisted of carbogenated Ringer solution at 32°C. The second lumen of the cannula was used to monitor aortic perfusion pressure. The baseline perfusate flow was preset between 20 and 24 ml/min and adjusted until the inspiratory motor pattern consisted of an augmenting burst discharge. In addition, vasopressin (200–400 pM as required) was added to the perfusate to raise perfusion pressure to between 80 and 90 mmHg (Pickering and Paton 2006).
Solutions and pharmacological agents
The composition of the Ringer solution was (in mM) 125 NaCl, 24 NaHCO3, 3 KCl, 2.5 CaCl2, 1.25 MgSO4, 1.25 KH2PO4, and 10 dextrose, pH 7.35–7.4 after carbogenation. Osmolality was 290 ± 5 mosm·kg H2O–1. Ficoll 70 (1.25%) was added as an oncotic agent. For experiments in which the chloride concentration was reduced, KCl was replaced by KGluconate, NaCl was replaced by NaGluconate, and CaCl2 was replaced by CaSO4 in appropriate concentrations so that the final concentration of Cl– used was 60, 40, or 20% of normal. In all cases, the osmolarity of these low chloride perfusates were matched with the normal solution. Unless stated, all chemicals were from Sigma. Vecuronium bromide (4 µg/ml; Organon Teknica, Cambridge, UK) was added to the perfusion solution to block neuromuscular transmission. Riluzole hydrochloride (Tocris), a persistent sodium current blocker, was prepared fresh daily by dissolving in distilled water (1 mM) and added to the perfusate to give final concentrations of 1–20 µM.
Precision transverse sectioning of the brain stem in situ
A custom-made microvibratome consisting of a piezoelectric bending element (Piezo Systems, Waltham, MA) mounted on a X-Y translational stage and motor driven z-axis (SD Instruments, Grants Pass, OR) was designed to make sequential transverse cuts through the brain stem of the in situ preparation while recording motor activity. Razor blades were cut to size (5.2–5.4 mm) and secured in a miniature clamp at the end of the bending element, which was driven by custom electronics controlling frequency and amplitude of the vibration. This allowed cuts to extend the entire width of the brain stem. We adjusted the flow rate of the perfusion pump or applied vasopressin to the perfusate to correct for any changes in perfusion pressure.
Stimulation of respiratory network activity
To provide a powerful excitatory drive into the respiratory network, the following were performed: 1) stimulation of the peripheral chemoreceptors by injection of low doses of sodium cyanide (NaCN; 0.03% solution; 50- to 100-µl bolus) into the aorta; and 2) brain stem ischemia produced by a transient arrest of brain stem perfusion (40–60 s). These procedures were applied before and after application of riluzole, or under conditions where transections transiently eliminated network activity, allowing us to test whether the respiratory network could be reactivated.
Histological reconstruction
For all experiments, the level of each transverse cut made with the vibratome was documented post hoc by histological reconstruction and related to the changes in motor pattern and response to riluzole. The head of the preparation with the transected brain stem in situ was fixed in 10% buffered formaldehyde–30% sucrose solution for 
2 days, and subsequently, the brain stem was removed and embedded in 10% gelatin (300 bloom, Sigma). The gelatin blocks were postfixed in 10% formaldehyde–30% sucrose solution for 3 h. Sagittal sections were cut (50 µm thick), mounted onto subbed slides, and stained with neutral red (1%; Fig. 1). This allowed reconstruction of the precise boundaries separating the different respiratory patterns and mechanisms underpinning the distinct rhythms generated.
Electrophysiological recording and data analysis
Simultaneous recordings of PN, cVN, and HN activity were obtained with three bipolar suction electrodes mounted on separate three-dimensional (3D) micromanipulators. Population recordings were made from the BötC, pre-BötC, and rVRG with tungsten microelectrodes (1–2 M
), or in some experiments, single units were recorded with glass microelectrodes filled with 4 N NaCl (10–15 M), positioned with a 3D micromanipulator and nanostepper (custom made). We determined recording sites in these compartments by extensively mapping population activity profiles along the rVRG–pre-BötC–BötC column by electrolytic lesions performed at recording sites with subsequent histological reconstruction in some experiments and by histological reconstruction of electrode penetration tracts in fixed counterstained tissue. In reduced preparations, we also positioned electrode penetrations in stereotaxic relationship to vibratome-cut surfaces that were subsequently shown from histological reconstruction to delineate compartment boundaries. All recordings were AC amplified and band-pass filtered (80 Hz to 3 kHz). Nerve and population activity signals were rectified and integrated (50-ms time constant) on-line (Spike 2 software, Cambridge Electronic Design). All electrophysiological data were digitized (5–10 kHz, Cambridge Electronic Design A-D converter) with Spike 2 software and analyzed off-line. Parameters of nerve or population activity (cycle period/frequency, inspiratory duration, expiratory duration, activity amplitude) were measured, and cycle-triggered averages for waveform analysis were made using a custom script for Igor Pro (5.0, Wavemetrics). Significance of data were assessed with either a two-tailed Student's t-test or ANOVA followed by either Dunnett's or Student-Newman-Keul's posttest or Wilcoxon signed-rank test as appropriate (Prism 4, Graphpad Software). All values indicated are the mean ± SD, and n is the number of preparations unless otherwise specified. Differences were considered significant at the 95% confidence limit.
Modeling methods
The model has been developed based on previous models (Rybak et al. 2004a; Smith et al. 2000). All neurons were modeled in the Hodgkin-Huxley style (single-compartment models) and incorporated known biophysical properties and channel kinetics characterized in respiratory neurons in vitro. Specifically, the kinetics of the fast sodium (INa) and the persistent (slowly inactivating, INaP) sodium channels was described using the experimental data obtained in studies of neurons from the rat rostral ventrolateral medulla (Rybak et al. 2003a); the kinetics of high-voltage activated calcium current (ICaL) was described based on the study of calcium currents in rat VRG neurons (Elsen and Ramirez 1998); the intracellular calcium dynamics was described using data by Frermann et al. (1999); the descriptions of other ion channels, e.g., the potassium rectifier (IK) and calcium-dependent potassium (IK,Ca), synaptic conductances, and all other cellular parameters, were as described in previous models (Rybak et al. 1997a,b, 2003b, 2004a,b). Each neuronal type was represented by a population of 50 neurons. The heterogeneity of neurons within each population was set by a random distribution of some parameters and the initial conditions for values of membrane potential, calcium concentrations, and channel conductances. The full description of the model and model parameters can be found in the APPENDIX.
Modeling was performed using a simulation package NSM 2.0, developed at Drexel University by S. N. Markin, I. A. Rybak, and N. A. Shevtsova. Differential equations were solved using the exponential Euler integration method (MacGregor 1987) with a step of 0.1 ms (for details see Rybak et al. 2003b).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSREFERENCES |
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The stereotypical patterns of PN, HN, and cVN activities generated by the intact preparation are shown in Fig. 3A. PN burst frequency in these preparations was in the range 0.24–0.47 bursts/s with a relatively constant PN burst duration (1.00 ± 0.14 s, n = 20 preparations). The activity profiles of different VRC neuron populations and integrated nerve activities are shown in Fig. 4A. These patterns resembled those recorded in vivo during generation of a normal three-phase respiratory rhythm (St.-John and Paton 2003) and exhibited the following characteristics (Fig. 3A): 1) an augmenting shape of PN bursts; 2) preinspiratory onset of HN bursts (50–100 ms before the onset of PN bursts); and 3) a prominent epoch of decrementing postinspiratory (post-I) discharge in cVN.
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Transformations of respiratory pattern with sequential brain stem transections in situ
The spatial organization of pontine-medullary respiratory networks was studied by sequentially reducing the network with a series of rostral to caudal brain stem microtransections starting at the level of the pons or near the pontine-medullary junction. Figure 1 shows an example of the histological appearance of the postfixed brain stem in sagittal view after a series of such transections. These transections allowed us to remove specific circuit components along the brain stem "respiratory column" bilaterally, which included severance of connections across the midline, and to analyze corresponding transformations of neuronal activity and motor output patterns. Vertical dashed lines in Fig. 2 indicate several experimental transections and levels, which delineate the rostral extent of the reduced preparations used in this study. The medullary preparations were obtained after transections through the facial nucleus from the pontine-medullary junction at the rostral end to the rostral boundary of BötC at the caudal end. The pre-BötC preparation was obtained after transection at the rostral boundary of pre-BötC, whereas the rVRG preparation was made after transection at the rostral boundary of rVRG (Fig. 2).
On production of a medullary preparation, by transecting at the rostral end of facial nucleus (i.e., pontine-medullary junction; Fig. 2), the three-phase rhythm was converted into a two-phase inspiratory-expiratory pattern (Figs. 3B and 4B), which was characterized by a nonramping "square-wave" inspiratory motor profile with the onset of activity synchronized in all nerves and by a lack of post-I discharge in cVN. Burst frequency in medullary preparations was in the range 0.14–0.32 burst/s (n = 20); the inspiratory phase duration was 1.73 ± 0.45 s. The amplitude of inspiratory bursts was reduced by >50% relative to bursts generated by the intact brain stem. Neuronal activities within the BötC, pre-BötC, and rVRG during the two-phase rhythm included decrementing expiratory (in BötC) and inspiratory (in pre-BötC and rVRG) discharges (Fig. 4B).
The cycle-to-cycle variability of inspiratory burst frequency in the two-phase rhythm generated by medullary preparations was greater compared with the three-phase rhythm. This variability increased with more caudal transections (reducing the remaining part of FN/RTN; Fig. 2) because of the emergence of shorter duration "ectopic" bursts interposed between longer duration square-wave bursts (Fig. 5). Interestingly, administration of riluzole (
10 µM) eliminated the ectopic bursting and stabilized the two-phase rhythm (Fig. 5).
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10%) and/or extracellular K+ (9 mM). In preparations where activity was eliminated by transection, the rhythm could be reactivated by either peripheral chemoreceptor stimulation or stopping the perfusion for 1 min. The rhythmic motor pattern was stabilized and maintained by a combination of elevating CO2 and extracellular K+. The resultant rhythmic activity pattern consisted of decrementing inspiratory bursts synchronized in all motor outputs as shown in Fig. 3C. Integrated population activity of pre-BötC and rVRG exhibited similar decrementing inspiratory discharge patterns (Fig. 4C). This inspiratory rhythm and its activation/reactivation properties (e.g., with elevation of extracellular K+) were analogous to those described previously for in vitro slices from the neonatal rat medulla containing the pre-BötC (Del Negro et al. 2001; Koshiya and Smith 1999). We called this activity a one-phase inspiratory rhythm because it occurred in the absence of expiratory activity and involved an endogenous bursting mechanism presumably operating within the pre-BötC.
Transection at the rostral boundary of rVRG, which removed the pre-BötC (rVRG preparation in Fig. 2), eliminated all rhythmic motor activity from the PN, HN, and cVN. After this transection, we failed to find rhythmically active neurons in the rVRG (n = 8 preparations). Activity could not be restored by chemosensory stimulation with NaCN injections and/or elevated CO2, and/or elevated extracellular K+ concentrations. This confirmed that pre-BötC circuits are required for the one-phase inspiratory rhythm, as originally shown for the neonatal systems under in vitro conditions (Smith et al. 1991).
Probing for persistent sodium (INaP)-dependent rhythmogenic mechanisms
To study a possible contribution of INaP-dependent mechanisms to the generation of the three-, two-, and one-phase rhythms, we used riluzole (1–20 µM), a pharmacological blocker of INaP (Urbani and Belluzzi 2000). Riluzole was added to the perfusate in the intact and reduced preparations at concentrations (1–20 µM) that were previously shown to attenuate and finally block INaP at the cellular level and abolish intrinsic bursting activity of the pre-BötC in vitro and in situ (Koizumi and Smith 2002; Paton et al. 2006; Rybak et al. 2003b). Figure 6, A and A1, shows effects of riluzole on the frequency and amplitude of PN bursts in the intact pontine-medullary network (n = 8). The INaP blocker reduced the PN burst amplitude but did not significantly affect burst frequency (Fig. 6A).
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7.5 µM) eliminated ectopic bursting (Fig. 5) and stabilized the rhythm at a reduced (
60% of control) burst frequency (n = 7; Fig. 6B); discharge amplitude and frequency were reduced further to 50% of control with progressive elevation of riluzole concentrations to the maximum tested (20 µM; Fig. 6, B and B1).
In contrast, in pre-BötC preparations (n = 7) generating a one-phase rhythm, there was a dose-dependent reduction in discharge frequency, and finally rhythmic activity was terminated at relatively low riluzole concentrations (10 µM; Fig. 6C). The discharge amplitude was less sensitive to riluzole but also was attenuated (50%) before loss of the rhythm (Fig. 6, C and C1). Recordings of pre-BötC population activity mirrored alterations of motor rhythm and amplitude with INaP blockade and verified complete loss of rhythmic activity in the pre-BötC coincident with the loss of motor output (Fig. 6C1). Without exception, rhythmic activity in the PN or pre-BötC could not be restored with hypoxic stimulation, elevations of CO2 and/or extracellular K+, or any combination of these stimuli.
Computational modeling of the brain stem respiratory network: model description
A computational model of the spatially distributed brain stem respiratory network was developed to reproduce the above experimental findings and suggest explanations for transformations of the rhythm-generating mechanism with sequential reduction of the network. The schematic of the model is shown in Fig. 7. The model includes the pons and three major medullary compartments: BötC, pre-BötC, and rVRG. Although some respiratory neuron types (e.g., post-I, aug-E) are not localized in particular compartments but rather distributed throughout the VRC, in our model, we assumed for simplicity that each medullary compartment contains only populations of respiratory neuron types that are known to be dominantly present in this compartment. The BötC compartment contains two populations of inhibitory expiratory neurons, the augmenting expiratory (aug-E) and the postinspiratory (post-I), which are both known to provide widely distributed inhibition within the medullary respiratory network during expiration (Ezure 1990; Ezure and Manabe 1988; Ezure et al. 2003; Fedorko and Merrill 1984; Jiang and Lipski 1990; Shen et al. 2003; Tian et al. 1999). In the model, these populations inhibit neural populations within the pre-BötC and rVRG and each other (Fig. 7). In addition, the BötC compartment contains an excitatory population [conditionally called post-I(e)] that contributes to the post-I component of cVN motor output. We assumed that all BötC neurons [comprising the post-I, post-I(e), and aug-E populations] have intrinsic adapting properties defined by the high-voltage activated calcium (ICaL) and calcium-dependent potassium (IK,Ca) currents in these neurons (see APPENDIX).
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,b; Rybak et al. 2003b, 2004b; Smith et al. 2000) that closely reproduces the population rhythmic bursting activity recorded from the pre-BötC in vitro (Johnson et al. 2001; Koshiya and Smith 1999). Previous modeling studies have shown that an increase in the average neuronal excitability or in external excitatory drive produces an increase in the burst frequency and, finally, switches population activity to the mode of tonic (asynchronous) spiking in the population. This was confirmed experimentally by an increase of extracellular potassium concentration in medullary slices containing the pre-BötC (Del Negro et al. 2001; Koshiya and Smith 1999; Rybak et al. 2003b). In this model under normal conditions, most neurons of this population operate in a tonic-spiking mode because of high tonic excitatory input and are inhibited by expiratory neurons (post-I, aug-E) during expiration.
The early-I(1) population of pre-BötC is a population of inhibitory interneurons with adapting properties (defined by ICaL and IK,Ca, see APPENDIX). This population receives excitation from the pre-I population and serves as a major source of inspiratory inhibition (Bianchi et al. 1995; Ezure 1990; Segers et al. 1987). In this model, this population inhibits all expiratory neurons during inspiration (Fig. 7).
The rVRG compartment contains the ramp-I, and early-I(2) populations (Fig. 7). Ramp-I is a population of excitatory premotor inspiratory neurons that project to phrenic motoneurons. Activity of this population defines phrenic motor output (PN) and the inspiratory component of cVN discharge. The major role of the inhibitory early-I(2) population (with adapting neurons containing ICaL and IK,Ca, see APPENDIX) in the model is in shaping the augmenting patterns of ramp-I neurons (Bianchi et al. 1995; Richter 1996; Segers et al. 1987).
The pons also contains specific compartments with multiple populations of neurons exhibiting various types of tonic and phasic respiratory modulated activities (Bianchi et al. 1995; Cohen 1979; Ezure and Tanaka 2006; Song and Poon 2004; St.-John 1998). These populations seem to have multiple specific uni- and bidirectional connections with particular VRC compartments (Bianchi et al. 1995; Ezure 2004; Ezure and Tanaka 2006; Song and Poon 2004), which allow the pons to control the timing of respiratory phase transitions and phase durations and contribute to respiratory reflexes (Alheid et al. 2004; Cohen and Shaw 2004; Okazaki et al. 2002; Song and Poon 2004; St.-John and Paton 2003). Our previous model (see Rybak et al. 2004a) included different populations of respiratory neurons in the rostral and caudal pons and considered uni- and bidirectional interactions between pontine and VRC compartments and their role in control of respiratory phase durations, phase switching, and respiratory reflexes. However, for simplicity, and also to fit the current experimental studies described here (that did not include recording of pontine neurons and investigations of the effects of transections within the pons), only tonic excitatory drives from the pons to the VRC have been considered.
The behavior of the respiratory CPG depends on a variety of afferent inputs to different respiratory neurons that allow breathing to maintain the appropriate homeostatic levels of O2 and CO2 and adaptively respond to various metabolic demands. These inputs are modeled as "excitatory drives" that carry state-characterizing information provided by multiple sources distributed within the brain stem (pons, RTN, raphé, NTS), including those considered to be major chemoreceptor sites (sensing CO2/pH), and/or receiving input from peripheral chemoreceptors (sensing CO2/pH and low O2) (i.e., RTN, raphé, see Guyenet et al. 2005; Nattie 1999; Richerson 2004). Although currently undefined, these drives seem to have a certain spatial organization that maps specifically on the spatial organization of the brain stem respiratory network. These drives are conditionally represented in the model by three separate sources located in pons, RTN/BötC, and pre-BötC compartments (Fig. 7).
Modeling reorganization of rhythm generating mechanisms after brain stem transections
Figure 8, A, A1, and A2, shows the performance of the intact model. The activity of each population in Fig. 8A1 is represented by an average spike-frequency histogram of population activity. The post-I population of BötC shows decrementing activity during expiration. This population inhibits all other neuron populations in the model [except post-I(e)] during the first half of expiration (postinspiratory phase). With the progressive reduction of post-I inhibition from the adapting post-I neurons, the aug-E population starts firing later in expiration and forms a late expiratory (E2) phase. At the end of expiration, the pre-I population of pre-BötC is released from inhibition and activates the early-I(1) population that in turn inhibits all expiratory populations within the BötC. As a result, the ramp-I [and early-I(2); Fig. 7] population of rVRG is released from inhibition (with some delay relative to pre-I) and initiates the next inspiratory phase. During the inspiratory phase, the activity of the early-I(1) population of pre-BötC decreases providing a slow disinhibition of the post-I population of BötC. Once the post-I population starts firing, it inhibits all inspiratory activity completing the inspiratory off-switch. Then the process repeats. In summary, the three-phase respiratory rhythm in the intact model emerges from the mutual inhibitory interactions between early-I(1), post-I, and aug-E populations comprising a three-population ring structure (marked by gray shading in Fig. 8A), with the pre-I excitatory population participating in the onset of inspiration (Fig. 8A).
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To model perturbations caused by transections removing the pons, we removed the pontine excitatory drive (Fig. 7, transection 1), reducing the intact model to a medullary model. The performance of the medullary model is shown in Fig. 8, B, B1, and B2. Based on experimental evidence that stimulation of the dorsolateral pons (PB/KF region) provides strong activation of post-I neurons (Dutschmann and Herbert 2006; Rybak et al. 2004a), we suggested that a major portion of excitatory tonic drive to post-I neurons of BötC comes from the pons. In contrast, the aug-E population in the model is less dependent on pontine drive but receives a major excitatory drive from the RTN and other medullary sources. Thus in our model, removal of the pons reduces the excitability of post-I neurons relative to aug-E neurons so that the post-I population becomes fully inhibited by the aug-E population, which now exhibits a decrementing pattern (defined by ICaL and IK,Ca). Therefore the two-phase rhythm generated in the medullary model is based on an inhibitory half-center circuit of reciprocally interacting populations of adapting aug-E and early-I(1) neurons (see gray shading in Fig. 8B and neuronal activities in Fig. 8B1). In addition, elimination of pontine drive reduces the excitability and firing frequency of the pre-I and ramp-I populations, reducing the amplitude of all motor outputs (Fig. 8B2). The medullary model reproduces all major characteristics of the respiratory pattern recorded in the corresponding reduced preparations (Figs. 3B and 4B): 1) the loss of post-I activity in the network and cVN; 2) a reduced amplitude, square-wave-like/slightly decrementing profile of all inspiratory populations and motor bursts; and 3) synchronized onset of bursts in all motor outputs (Fig. 8B2).
The pre-BötC model (Fig. 7, transection 2) is characterized by a further reduction in tonic excitatory drive to the pre-I population of pre-BötC and loss of expiratory-related phasic inhibition (Fig. 7). These alterations switch the operating state of the pre-I population, which now generates endogenous bursting activity based on the expression of INaP and mutual excitatory interactions within the population (Butera et al. 1999b; Rybak et al. 2003b, 2004b; Smith et al. 2000) (Fig. 8C, C1). This pre-BötC activity with a decrementing burst shape now drives the activity of the rVRG and all motor outputs exhibit one-phase (inspiratory) oscillations with a decrementing burst shape (Fig. 8, C1 and C2), similar to that recorded from the pre-BötC preparation (Figs. 3C and 4C).
Testing the dependency of model performance on INaP
To study the role of INaP and compare model behaviors to experimental data obtained with the INaP blocker riluzole (Fig. 6, A–C), the mean maximal conductance of NaP channels (
NaP) was progressively reduced (to zero) in all pre-BötC (pre-I) neurons. As shown in Fig. 9A, a progressive reduction of NaP in the intact network model causes only a small reduction in the amplitude and frequency of PN bursts. In the medullary model generating the two-phase rhythm, the oscillatory frequency and PN amplitude become more sensitive to INaP block because after removing pontine excitatory drive the mean level of INaP inactivation is reduced, enabling some participation of the pre-I population in the expiratory-inspiratory cycle dynamics. The two-phase rhythm, however, persists even at NaP = 0 (Fig. 9B). In the pre-BötC model, the one-phase rhythm is generated solely by endogenous INaP-dependent bursting activity within the pre-I population of the pre-BötC (Fig. 8C). Therefore reducing NaP progressively decreases PN burst frequency and finally abolishes the rhythm when NaP becomes less than a critical value (Fig. 9C, 2.5 nS). These modeling results are fully consistent with our experimental data (Fig. 6, A–C).
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NaP) in the pre-I population, eliminates ectopic bursts and stabilizes the two-phase rhythm. These simulation results are fully consistent with our experimental findings (Fig. 5).
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Our model predicted that the generation of the three- and two-phase rhythmic patterns is based on inhibitory synaptic interactions. Both glycine and GABA, known to be the major inhibitory neurotransmitters in the brain stem respiratory network (Büsselberg et al. 2001; Ezure et al. 2003; Haji et al. 2000; Paton and Richter 1995; Schreihofer et al. 1999), involve Cl–-mediated inhibition. Therefore to test the role of Cl–-mediated inhibition, we switched the normal perfusate in intact preparations to a solution containing reduced Cl– concentration (60, 40, or 20% of control concentrations in separate experiments: n = 6, n = 7, and n = 10, respectively; see METHODS). In all cases, after switching to the reduced Cl– perfusate, the three-phase motor output pattern transformed to a two-phase pattern. This transformation developed progressively with time reflecting a slow process of equilibration of the brain extracellular fluid to the reduced Cl– conditions. This transformation was accompanied by a loss of the post-I component in the cVN activity, a reduction of amplitudes of all motor outputs, and an alteration of the shapes of motor bursts similar to those occurring after brain stem transections (synchronous, square-wave-like inspiratory bursts of PN and cVN; Figs. 12, A and B, 2nd columns, and 13B). Further in time, rhythmic motor output terminated under the low Cl– conditions (Figs. 12, A and B, 3rd columns, and 13C).
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Figure 12, A and B, shows the results of separate experiments in which rhythm and pattern transformations were obtained with a perfusate solution containing 20% of control Cl– concentration. With this perfusate, the transition to a two-phase rhythm occurred on average within 4 min, and the termination of rhythmic activities was observed within 30–40 min. In experiments with perfusate solutions containing 60 or 40% of control Cl– concentrations, the sequential pattern transformation described above was consistently observed as well, but the times to the three- to two-phase rhythm transition and to the subsequent termination of rhythmic activity were progressively longer (1.5 and 2 times longer at 60 and 40% Cl– solutions, respectively). In all cases, rhythmic activity was restored when the perfusate was replaced with the control solution, although, after the 20% Cl– perfusate, we could typically achieve only partial recovery of the normal pattern and discharge amplitudes (Fig. 12, A and B, right columns).
To simulate the effect of reduction of chloride-based inhibition by lowering extracellular Cl– concentration ([Cl–]out), the chloride reversal potential in the model (ECl = ESynI) was changed from –75 to –60 mV (to be equal to the average neuronal resting potential), which, according to the Nernst equation and with the temperature T = 305 K (used in the experimental preparation), approximately corresponds to a 50% decrease of [Cl–]out. The results of simulation are shown in Fig. 13D. Similar to our experimental results (Figs. 12, A and B, 3rd columns, and 13C), changing ECl to –60 mV abolished rhythmic activity in PN and cVN motor outputs and produced sustained activity in the aug-E population of BötC and the pre-I population of pre-BötC (Fig. 13D, right). However, the model did not reproduce the transition from the three-phase to a two-phase rhythm after a smaller reduction of inhibition if the latter was applied uniformly to all neuronal populations in the model. The direct simulation of this transition, as observed in our experiments, is difficult because the reduced inhibition during perfusion of low Cl– solutions may provide different effects on different populations of respiratory neurons and/or has different time courses, which are currently unknown.
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONAPPENDIXGRANTSRE |
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