| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
REPORT
1Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania; and 2Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware
Submitted 28 June 2005; accepted in final form 2 December 2005
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
; Lumsden 1923; see Bianchi et al. 1995; Cohen 1981; von Euler 1986 for reviews). The neurons required for rhythmogenesis are localized primarily in a limited region of the ventrolateral medulla (Onimaru and Homma 2003; Smith et al. 1991), but their exact location and the mechanism of primary rhythm generation remains a subject of active inquiry.
Among these ventromedullary regions, the site known as the pre-Bötzinger complex (pBC) (Smith et al. 1991) is an important region for rhythmogenesis. This region contains many different respiratory neuron types (Schwarzacher et al. 1991; Sun et al. 1998) and has been established in vivo as essential for rhythmic breathing (Gray et al. 2001; Pierrefiche et al. 1998; Ramirez et al. 1998). While the exact nature of the mammalian breathing rhythm generator is not known, it is suspected that both intrinsic cellular and network properties contribute to rhythmogenesis with state-dependent (Rybak et al. 2002), and age-varying (Hilaire and Duron 1999; McCrimmon et al. 2000a,b; Paton et al. 1994) degrees of importance. Pharmacological studies in arterially perfused rats have revealed that synaptic inhibition is vital for respiratory rhythm generation in adults but not for neonates, suggesting an overall developmental shift in rhythmogenesis mechanism to a network mechanism (Hayashi and Lipski 1992; Paton et al. 1994). Many of these studies, however, are difficult to reconcile because each in vitro preparation defines a different operational condition compared with in vivo preparations (Richter and Spyer 2001). Clearly, there are differences in the generation of respiratory rhythm between neonates and adult rats, as well as between in vivo and in vitro models.
The pBC has been described in vitro as a major respiratory rhythm-generating region containing (early) inspiratory activity (Johnson et al. 2001; Koshiya and Smith 1999; Smith et al. 1991). On the other hand, in vivo electrophysiological study of the adult cat (Schwarzacher et al. 1995) and rat (Sun et al. 1998) has revealed that the pBC is a neuronally mixed area containing phase-spanning propriobulbar neurons that fire through the respiratory phase transition. These studies hypothesize that such phase-spanning neurons in the pBC promote the expiratory–inspiratory phase transition and are thus critical to rhythmogenesis in vivo. Thus results obtained in vivo versus in vitro suggest very different functional roles for the pBC.
To achieve a more global picture of neuronal distribution, some groups have used optical imaging techniques to visualize large-scale activity. Such studies, however, have concentrated on in vitro preparations of the neonatal rat, either of brain stem slices (Koshiya and Smith 1999; Tokumasu et al. 2001) or en bloc preparations of the brain stem and spinal cord (Onimaru and Homma 2003; Tokumasu et al. 2001). Unfortunately, interpretation of results from these neonatal or reduced preparations, with respect to adult in vivo mechanisms, incurs the same disadvantages described above.
We hypothesize that, in a more mature and intact rat preparation, the area of the pBC would be functionally mixed and exhibit significant activity throughout all phases of respiration, as in in vivo preparations. In addition, we expect that inhibitory mechanisms will be evident. To test this hypothesis, we used voltage-sensitive dye imaging to study the large-scale electrical spatiotemporal activity in the pBC area of a largely intact juvenile rat preparation. We performed high-speed wide-field fluorescence video microscopy of the surface of the medulla immediately ventral to the ventrolateral respiratory group (VRG) in an arterially perfused preparation of the juvenile rat (Paton 1996; St.-John and Paton 2000) using the voltage-sensitive dye di-8-ANEPPS. Using correlation coefficient analysis (Bandettini et al. 1993; Durduran et al. 2005), we identified nonoverlapping spatial regions within the pBC exhibiting fractional fluorescence signals at different phases of respiration.
A preliminary report of this work has been published in abstract form (Marchenko et al. 2004).
|
METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
All procedures were performed with the approval of the University of Delaware Institutional Animal Care and Use Committee. Following the "working heart-brain stem preparation" (Paton 1996), juvenile rats (72–100 g; n = 5) were bisected just below the diaphragm, decerebrated at the precollicular level, and skinned under deep isoflurane anesthesia in 4°C artificial cerebrospinal solution. Deep anesthesia was assured by the absence of limb withdrawal and reflexive changes in breathing after limb pinch. They were bilaterally vagotomized, with the diaphragm, heart, lungs, and portions of the rib cage removed, and appropriate vasculature was ligated to prevent excessive leakage of the perfusate. The descending aorta was cannulated, and rats were perfused with a 95% O2-5% CO2-saturated solution consisting of 125 mM NaCl, 1.25 mM NaHCO3, 4 mM KCl, 2.5 mM CaCl2, 1.25 mM MgSO4, 1.25 mM KH2PO4, 20 mM dextrose, 0.05 mg/ml vecuronium bromide, and 2.5% dextran (230 kDa) at 95–105 mmHg and gradually warmed to 31–33°C. This experimental preparation has been shown to produce eupneic breathing patterns in mice (Paton 1996) as well as rats (St.-John and Paton 2000).
Phrenic nerve (300–3,000 Hz) and single unit (500–3,000 Hz) recordings (10,000 samples/s) were made with silver wire hook electrodes and glass electrodes (2 M NaCl), respectively. Signals were amplified and filtered using conventional electronics (Neurolog, Digitimer). Raw phrenic nerve recordings were used to monitor the respiratory state of the preparation (e.g., eupnea, gasping) and to adjust perfusate flow accordingly.
Imaging system
Simultaneous image and electrophysiological data acquisition was performed with custom-built hardware (including camera) and custom-written software (Rector and George 2001; Rector et al. 1999, 2001) capable of continuous image and data recording at high speeds (up to 1-kHz frame rate for video data, 20 kHz/channel for electrophysiology data) for long periods of time (>1 h). The detector was a CCD camera (TC255, Texas Instruments, Dallas, TX; 10 x 10 µm pixels, 336 x 243 pixel array). To achieve appreciable signal levels, the frame rate was set to 100 Hz. The imaging optics consisted of a custom 1:1 focal length ratio lens couplet (Fig. 1 A). Two identical achromatic lenses (Edmund Optics, Barrington, NJ) served as objective and focusing lenses. Light from a 200-W halogen white light source (Thermo Oriel, Newport Corp., Irvine, CA) was filtered with a 480 ± 20-nm excitation filter (Chroma Technology Corp., Rockingham, VT). The filtered light was coupled into the imaging device through a multimode fiber bundle that was recollimated with a collimating lens triplet (Melles Griot, Barloworld Scientific, Carlsbad, CA) and reflected off of a dichroic mirror (<500 nm R, Chroma Technology Corp.) to provide epi-illumination through the achromatic objective lens (Edmund Optics). The fluorescence signal was filtered with a >590-nm long-pass filter (Chroma Technology).
|
Dye staining
Stock solutions of voltage-sensitive dye di-8-ANEPPS dissolved in F-127 Pluronic (20% in DMSO; both from Molecular Probes/Invitrogen, Carlsbad, CA) were diluted to final concentrations of 500 µg/ml in Ringer solution. The diluted dye solution was loaded into the tissue systemically through a side port of the aortic perfusion line. After perfusion with di-8-ANEPPS, reduced rat preparations continued to exhibit eupneic breathing. In addition, it was possible to elicit the Hering-Breuer reflex—whereby inspiration is terminated and expiration extended—through electrical stimulation of the vagus nerve (Fig. 1B). We used the time latency and efficacy of the Hering-Breuer reflex and the overall phrenic activity (amplitude, duration, pattern, and rhythmicity) as indicators of possible toxic effects of systemic dye introduction. In all preparations, these parameters were not changed more than ±5% after 15–90 min of dye injection. In addition, the presence of stereotypical respiratory-related single-neuron activity (Fig. 1, C and D) provided further confidence that the effects of the dye-staining were inconsequential. Because the perfusate is optically transparent at the excitation and emission wavelengths (480 ± 20 and >590 nm, respectively) used in the experiment, erythrocyte-dependent, oxygenation-related optical artifacts, large sources of noise in in vivo conditions, were eliminated.
Measurement protocol
The imaged region included areas just rostral and lateral to the rostralmost XII rootlets, and the region indicated in Fig. 1A (rectangle) was used in all experiments. The focal plane of the camera was set to 
200 µm below the ventral surface. After the dye was loaded, raw images and electrophysiological data were collected for long durations (40 min), during which several hundred eupneic breaths typically occurred. Triggered averaging of video and electrophysiology was performed off-line using custom written functions in Matlab software (MathWorks, Natick. MA). Integrated phrenic recordings (
= 50 ms) were used to create trigger markings for averaging, and the final processed data were averaged over 20–50 breaths. Off-line averaging enabled arbitrarily long pretrigger times. Because of the variability in phrenic burst duration, off-line triggered averaging was performed using both early- and late-phase triggering points. The onset of the integrated phrenic burst (defined by a threshold set just above the noise level) served as the "early" trigger point; the peak (i.e., turning point) of the integrated phrenic burst defined the "late" trigger point. For characterizing onset times and peak response values, early-phase triggered averaging was used for optical responses occurring just before the onset of the phrenic burst (preinspiratory period), and late-phase triggered averaging was used for responses during and after inspiration. Fractional fluorescence (
F/F) images were produced by subtracting a reference image, F, from averaged video images to generate F. This quantity was divided by F to yield normalized changes and correct for irregularity in staining. Using our emission filter (>590 nm), di-8-ANEPPS exhibits a decrease in amplitude of fluorescence emission during membrane depolarization. Thus depolarizations are accompanied by negative changes in fractional fluorescence (F/F), and vice versa for membrane hyperpolarization. Fractional fluorescence CCD recordings were smoothed spatially with a 5 x 5 Gaussian filter and temporally with a five-frame sliding box car average. Other than this simple spatiotemporal smoothing, all data traces are presented unfiltered. After the imaging experiment, dye was preferentially applied to the two rostralmost XII rootlets by placing a small di-8-ANEPPS–saturated piece of gauze directly onto the rootlets with a pair of forceps for the purpose of generating a high-contrast background image including identifiable anatomical landmarks in the imaging field of view. After 5 min, the gauze was removed, and unbound dye was washed away by the constant outflow of perfusate in the brain stem area. Several seconds' worth of frames of this background were averaged to resolve anatomical details in the low-contrast tissue. Thresholded montage images (Fig. 2 C) are displayed superimposed over this background image.
|
Voltage-sensitive dyes yield fluorescence changes linearly proportional to membrane potential changes and can therefore be used as a molecular voltmeters (Bullen and Saggau 1999; Cohen and Salzberg 1978; Salzberg 1983). However, because the polarity reported by F/F depends on the choice of reference image, F, we compared F/F using two different reference images. One reference image was generated by averaging the first 10 frames of the triggered average CCD recording. To achieve a reference fluorescence image more likely close to steady-state potentials, the preparation was cooled to a temperature of 16°C, during which no rhythmic or tonic phrenic activity was observed and fluorescence images were recorded and averaged to generate F.
Correlation coefficient images (Bandettini et al. 1993; Durduran et al. 2005) were computed by calculating the correlation coefficient for each pixel with a given correlation function. The correlation coefficient, cci, is defined as
 | (1) |
F/F for a given pixel, ri (i = 1... N) is the function representing the desired correlation function during respiration, µf and µr are the mean values of f and r, and N is the number of frames.
Two types of functions were used in our correlation analysis: functions that approximate firing frequency rates for five basic types of respiratory neurons (preinspiratory, late-inspiratory, postinspiratory, ramp-inspiratory, and expiratory-augmenting) and functions that approximate the membrane potential trajectories for those same neuron types. Approximations were based on descriptions by Bianchi et al. (1995). Following the description of the respiratory phases in Richter et al. (1986), three points on the integrated phrenic burst recording were used to define the inspiratory and expiratory phases (Fig. 2B) and to define correlation functions (Fig. 3 A): the onset of the inspiratory phrenic burst, the peak/turning point of the inspiratory phrenic trace, and the return to baseline of the phrenic trace. The period of "inspiration" spanned the duration between the phrenic burst onset point and the peak/turning point. "Postinspiration" (i.e., E1) was defined as the period between the integrated phrenic peak/turning point and the return to baseline of the phrenic trace. "Expiration" (i.e., E2), spanned the duration between the return to baseline of the integrated phrenic trace and the onset of the next breath's phrenic burst.
|
F/F is identical to the correlation function multiplied by an arbitrary constant; a |cc| value of 0 indicates no similarity between the F/F time-course and the correlation function. Maximum values of |cc| for our data ranged from 0.4 to 0.7, because of mismatch between model functions and real activity and the presence of physiological and CCD noise in optical recordings. |
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
F/F averaged over the entire field of view.
Averaging over all animals, the integrated phrenic burst duration, defined here as the time between the onset and the return to baseline of the phrenic burst, was 935 ± 68 (SD) ms. The range of breath durations was between 870 and 1,000 ms and the SD of the phrenic burst duration was <9% within individual experiments. Because of the variability in phrenic burst duration, onset times (in ms) of optical responses will be described both in terms of mean ± SD (averaging over all animals) and in terms of percentages of the inspiratory burst duration (i.e., onset values are divided by individual experiment phrenic burst duration before group averaging) to give more qualitatively general descriptions. As described in METHODS, the variability in phrenic burst durations necessitated the use of early- and late-phase triggered averaging. Averaging using either trigger points did not erase any of the responses but did lead to smaller SD when the trigger closest to the optical response was used. The "preinspiratory" response onset preceded the phrenic burst onset by 178 ± 85 ms or 19 ± 9% of the phrenic burst duration. This initial gross fluorescence response had an average peak value of –0.029 ± 0.014% and always ended before the middle of inspiration. The F/F response (triggered off of the onset of inspiration) that peaked during inspiration began 296 ± 107 ms (27 ± 9%) after the phrenic burst onset and reached peak values of –0.037 ± 0.015%. The F/F response (triggered off of the phrenic peak) that reached maximum during the postinspiratory period (e.g., Fig. 2B, last peak in red trace) began 329 ± 174 ms before the phrenic burst peak (29 ± 12% of the burst width), and reached F/F values of –0.038 ± 0.024%. We found a small but significant overall increase in fluorescence of +0.023 ± 0.020% during the expiratory period, indicating hyperpolarization (Fig. 2C; note the graph scales and color bars have been inverted so a decrease in fluorescence indicates membrane depolarization).
Using either the average of the first 10 triggered-average frames or the average of 10 random frames in a continuous fluorescence recording of the cooled brain stem (of the same preparation), the pre- and late-inspiratory F/F changes were negative, indicating widespread depolarization (e.g., Fig. 2C, middle row, last 2 frames). In addition, using the cooled-brain stem fluorescence signal (no phrenic activity) as a baseline, F, revealed gross depolarization during the presence of tonic activity (data not shown).
On the scale of our field of view (1 x 1.2 mm), we were able to distinguish both global and spatially localized phasic F/F responses without the aid of image processing. Figure 2B shows F/F responses at two different locations within the field of view. The top trace (blue) shows the F/F time trace from the blue marker on the field of view in Fig. 2A. While this trace is representative of the gross postinspiratory F/F changes seen in the frame montage in Fig. 2C, the red trace in Fig. 2B, corresponding to the area near the rostral-most XII rootlet (Fig. 2A, red dot), shows an additional pre- and postinspiratory signal not present in other regions. Figure 2C shows the typical degree of spatiotemporally restricted fluorescence changes from the region over the course of a breath.
While some spatiotemporal variations were apparent without any image processing, other features could be identified through correlation coefficient imaging. Figure 3 shows the results of correlation coefficient analysis using functions approximating both firing frequency and membrane potential patterns for five basic respiratory neuron types. The histograms in Fig. 3, A and B, represent correlation coefficients of all pixels in all experiments, using both early- and late-phase triggered averaging. Some of the histograms have one main peak, whereas others are clearly multimodal, indicating high or low consistency among experiments, respectively. Early- and late-phase triggered averaging revealed differences in this spread of correlation values; triggered averaging led to a decrease in the cc value spread when the selected trigger event was near the main feature (if any) of the correlation function (e.g., pre-I pattern using phrenic onset triggering). Because of this triggering-dependent effect, we additionally analyzed correlation statistics for the initial portion (beginning immediately after the return of the integrated phrenic trace to baseline) of the expiratory-augmenting firing frequency function, which has main features coincident with both early and late trigger events. For both firing frequency and membrane potential functions, the least experimental variability was observed in the correlation analysis using preinspiratory (pre-I), late-inspiratory (late-I), and initial expiratory-augmenting [exp-aug (initial)] functions (functions shown in left columns of Fig. 3, A and B). Of those, pre-I and exp-aug (initial) firing-frequency functions revealed nonzero mean |cc| values, indicating some degree of similarity to those functions among pixels in all experiments. A negative mean cc value was observed among experiments to the pre-I firing-frequency correlation function, and a positive mean cc value was observed using the exp-aug firing frequency function, interpreted as depolarization and hyperpolarization in those temporal patterns, respectively. Compared with the truncated exp-aug (initial) function, the full exp-aug correlation function revealed considerable experimental variability and no significant nonzero mean cc value.
Examination of an individual experiment (Fig. 3, C–E) reveals a spatial mixture of regions correlated with significantly different functions. The top two images in Fig. 3C show a thresholded map of cc values for pre-I and exp-aug (initial) correlation functions and reveal that both regions of high correlation cover a similar portion of the field of view. The bottom image in Fig. 3C displays the combined regions of the top two images (minimum threshold set to 1 SD of the mean |cc| value), showing that the highly correlated (|cc| > 2 SD) subregions are largely nonoverlapping. For all experiments, there was <5% overlap for regions with |cc| values >2 SD for pre-I and exp-aug firing-frequency functions, indicating spatial separation between the regions with the strongest temporal correlations.
Region-averaged plots of F/F (Fig. 3D) revealed that |cc| values larger than 2 SD showed significantly different time traces for the two correlation functions. While the region-averaged plot of pre-I-correlated activity did not exhibit the exp-aug (initial) characteristic increase in fluorescence (note again the reversed y-axis), some degree of pre-I–like F/F response (peak at 300 ms; Fig. 3D) was seen in pixels highly correlated with the exp-aug function. Additionally, similar to the traces in Fig. 2B (in a different experiment), the pre-I–correlated region contained smaller optical responses in the postinspiratory and expiratory periods.
During simultaneous optical recordings, we recorded extracellularly from 13 neurons that exhibited respiratory phase-related activity, all in the CCD field of view and within 340 µm from the ventral surface. Among these, were neurons with pre-I activity (onset of activity 65.2 ± 8.4 ms before phrenic onset with maximum firing frequency at the phrenic onset), early-I, and late-I activity (frequency peaks; see Fig. 1C for examples). In regions exhibiting post-I activity, several expiratory-decrementing units were also found (onset of activity mid-inspiration; max firing at phrenic post-I onset). Figure 1D shows an example of one of these units. Thus neurons with or without "prototypical" firing patterns for a given region may be observed within that region, indicating a fair amount of spatial mixture, particularly on scales >200 µm.
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
). Ramping, eupneic integrated phrenic recordings combined with the ability to elicit the Hering-Breuer reflex in this artificially perfused preparation (even after the injection of voltage-sensitive dye di-8-ANEPPS into the circulatory system) suggests superior degrees of functional relevance compared with brain stem/spinal cord en bloc or in vitro medullary slice preparations. The results clearly show the feasibility and use of optical imaging of the working heart–brain stem preparation via voltage-sensitive dyes. We also showed that the components of an important portion of the rhythm generator may be spatiotemporally characterized using these methods. This represents the first step in dissecting this system as it functions in its intact form, with the ultimate goal of creating a realistic quantitative model.
This is the first study, to our knowledge, to show correlation in subregions of the optical image to specific known firing patterns of respiratory neurons in a relatively intact preparation. The results shown in Figs. 2 and 3 suggest that the F/F response in the area of the pBC can be divided into at least four periods of response: preinspiratory, inspiratory, postinspiratory, and expiratory. The presence of F/F signals during all four of these periods is fully consistent with recent voltage-sensitive dye imaging results in the brain stem–spinal cord preparation (Onimaru and Homma 2003) and with known membrane-potential dynamics for respiratory neuron types (Bellingham 1998; Ezure et al. 1988; Hayashi et al. 1996; Richter 1996; Rybak et al. 1997a).
Several reports have found that among neighboring regions in the VRG, the pBC is a region containing a relatively high variety of respiratory neuron types including pre-I, post-I, phase-spanning, and exp-2 neuron types (Ezure et al. 2003b; Howard and Tabatabai 1975; Sun et al. 1998). While it was apparent that distinctly preinspiratory and postinspiratory F/F responses could be spatially distinguished within our imaging field of view (Fig. 2), the largest homogeneous subregions observed in one experiment were 400 µm in diameter. Additionally, correlation coefficient images showed that regions exhibiting strong preinspiratory F/F signals also exhibited significant postinspiratory activity (Fig. 3D, blue trace with small peak at post-I onset), akin to recent optical imaging studies of the ventral surface of the para-facial respiratory group (pFRG) (Onimaru and Homma 2003). Our findings are therefore in agreement with the model of the rat pBC as a region consisting of predominantly mixed neuron types and involved in phase-transition (Sun et al. 1998).
The results of correlation coefficient image analysis revealed widespread correlation of the optical signal with pre-I and exp-aug (initial) firing-frequency functions. The least speculative interpretation of this finding is that the optical signal tended to take on the same general form as those particular functions. The extent to which this finding depends on integration time remains unclear and is beyond the scope of this study.
Our findings of significant increase in fluorescence, corresponding to hyperpolarization, directly after the termination of inspiration in a region containing the pBC represent the first optical imaging evidence in support of the prevalence of inhibitory activity during rhythmogenesis. Glycinergic inhibition of distinct subsets of respiratory neurons in the VRG has been increasingly identified as crucial for respiratory rhythmogenesis (Busselberg et al. 2001a,b; Dutschmann and Paton 2002; Ezure et al. 2003a; Markstahler et al. 2001). The region of the pBC, specifically, has been shown pharmacologically to be rich in glycine receptors (Chitravanshi and Sapru 2002). That similar increases in fluorescence were not seen in previous imaging studies of the brain stem–spinal cord preparation (Onimaru and Homma 2003; Tokumasu et al. 2001) suggests further functional differences between neonatal in vitro and our juvenile in situ preparations.
The measurements in this report used linear (one-photon) fluorescence. Thus the contribution of out-of-focus light and scattering of the returning fluorescence must be considered. Voltage-sensitive dyes exhibit linear changes in fluorescence and absorption spectra as a function of membrane potential, but the definite spatial and temporal localization of the signal depend on the collection optics and integration time, respectively. Our system specifications (integration time = 8 ms; NA = 0.38) enabled us to discern fast optical signals with a wide field-of-view and long working distance. These specifications lead to uncertainty in both temporal and spatial localization of the signal origins. The observed signal at each pixel represents a spatial and temporal summation of the fluorescence activity in all of the stained membrane surface area contained within the volume defined by the lateral width (10 x 10 µm) and by the fluorescence depth-of-field (10 µm). Calibration tests with fluorescent polystyrene beads placed at varying degrees of defocus show that the optical signal at each pixel reflects fluorescence from up to approximately ±50 µm surrounding the focal plane (Fisher et al. 2004).
Because the optical signal at each pixel represents a summation over a potentially unknown distribution of membrane area, the electrophysiological interpretation of the voltage-sensitive dye signal warrants further discussion. High-speed microscopy using voltage-sensitive dyes can provide optical recordings identical to all excitable membranes in the cellular architecture (including pre- and postsynaptic elements, somata, glia, etc; Konnerth and Orkand 1986; Konnerth et al. 1987). However, studies in which single detector pixels correspond to a mixture of neuronal architecture have found that voltage-sensitive dye measurements largely reflect a superposition of subthreshold membrane potential dynamics rather than spiking (Grinvald et al. 1982; Kleinfeld and Delaney 1996; Kleinfeld et al. 1994; Tokumasu et al. 2001). Other voltage-sensitive dye studies using spike-triggered imaging found that the optical signal was most similar to local field potential (LFP) measurements (Arieli et al. 1995; Grinvald et al. 1994), further concluding that the optical signal likely reflects primarily dendritic synaptic potentials rather than spiking. Unfortunately, the basic respiratory neurons are not nearly as well characterized in terms of their dendritic electrical properties as they are in terms of spiking behavior. Likewise, there is less certainty about the consistency of subthreshold membrane potential dynamics of respiratory neurons than of firing frequency. The best interpretation of our imaging results therefore is as indicative of summed membrane potential dynamics.
Because the imaged plane was 200 µm below the ventral surface of the brain stem, scattering of the returning fluorescence signal can be expected to account for some further loss of spatial resolution. In the rat brain stem, the scattering properties increase significantly after 3 weeks of life because of increased myelination (Kasparov et al. 2002). To avoid this potential limitation, our study used rats just less than 3 weeks old. Taking into account the absence of blood in the artificially perfused preparation, as well as the fact that in vitro scattering coefficient values are almost always higher than in vivo values in brain tissue (Bevilacqua et al. 1999), it is reasonable to assume that there are relatively few scattering events in the first few hundred micrometers of tissue.
In light of these interpretive issues associated with the optical response, the thresholded regions in Fig. 2 and the significantly correlated regions in Fig. 3 should not necessarily be interpreted as the locations of cell bodies. Respiratory neurons in the VRG send their axonal projections and branching collaterals over large distances, frequently exceeding a diameter of several millimeters (Ezure 1990). A large fraction of the resulting F/F signal likely contains contributions from portions of neurons other than the somata, particularly from the dendrites, which contain a large fraction of the surface area of these neurons (Ezure 1990). Overall, our results show that the area of the pBC contains spatially mixed subregions that exhibit optical responses during all phases of respiration, and that those subregions' optical responses exhibit further similarities to the electrical properties of specific respiratory neuron types. These results suggest that even at the juvenile developmental stage, the pBC region already shows stereotypical network-driven phenomena (i.e., widespread inhibition), and may participate in the generation of respiratory phase transitions.
In conclusion, our findings support the model of the pBC in the juvenile rat as a network of neurons that is spatially mixed in its organization, but with identifiable substructural organization that receives near-global excitatory and inhibitory influences during inspiration and expiration, respectively. In addition, the subregions that show the strongest pre-I and E-aug correlations are not spatially overlapping. We expect the methods used herein will lead to higher-resolution qualitative and quantitative models of the respiratory rhythm generator.
|
GRANTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
|
ACKNOWLEDGMENTS |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
|
FOOTNOTES |
|---|
Address for reprint requests and other correspondence: J.A.N. Fisher, Dept. of Physics and Astronomy, Univ. of Pennsylvania, 209 S. 33rd St., Philadelphia, PA 19104 (E-mail: aafisher{at}physics.upenn.edu)
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
|---|
Bandettini PA, Jesmanowicz A, Wong EC, and Hyde JS. Processing strategies for time-course data sets in functional MRI of the human brain. Mag Res Med 30: 161–173, 1993.[CrossRef]
Bellingham MC. Driving respiration: the respiratory central pattern generator. Clin Exp Pharmacol Physiol 25: 847–856, 1998.[Web of Science][Medline]
Bevilacqua F, Piguet D, Marquet P, Gross JD, Tromberg BJ, and Depeursinge C. In vivo local determination of tissue optical properties: applications to human brain. Appl Optics 38: 4939–4950, 1999.
Bianchi AL, Denavit-Saubié M, and Champagnat J. Central control of breathing in mammals: neuronal circuitry, membrane properties, and neurotransmitters. Phys Rev 75: 1–45, 1995.
Bullen A and Saggau P. High-speed, random-access fluorescence microscopy: II. Fast quantitative measurements with voltage-sensitive dyes. Biophys J 76: 2272–2287, 1999.[Web of Science][Medline]
Busselberg D, Bischoff AM, Becker K, Becker CM, and Richter DW. The respiratory rhythm in mutant oscillator mice. Neurosci Lett 316: 99–102, 2001a.[CrossRef][Web of Science][Medline]
Busselberg D, Bischoff AM, Paton JF, and Richter DW. Reorganisation of respiratory network activity after loss of glycinergic inhibition. Pflugers Arch 441: 444–9, 2001b.[CrossRef][Web of Science][Medline]
Chitravanshi VC and Sapru HN. Microinjections of glycine into the pre-Bötzinger complex inhibit phrenic nerve activity in the rat. Brain Res 947: 25–33, 2002.[CrossRef][Web of Science][Medline]
Cohen MI. Central determinants of respiratory rhythm. Ann Rev Physiol 43: 91–104, 1981.[CrossRef][Web of Science][Medline]
Cohen LB and Salzberg BM. Optical measurement of membrane potential. Rev Physiol Biochem Pharmacol 83: 35–88, 1978.[Medline]
Del Negro CA, Morgado-Valle C, and Feldman JL. Respiratory rhythm: an emergent network property? Neuron 34: 832–830, 2002.
Durduran T, Burnett MG, Yu G, Zhou C, Furuya D, Yodh AG, Detre JA, and Greenberg JH. Spatiotemporal quantification of cerebral blood flow during functional activation in rat somatosensory cortex using laser-speckle flowmetry. J Cereb Blood Flow Metab 24: 518–525, 2005.[CrossRef][Web of Science]
Dutschmann M and Paton JFR. Glycinergic inhibition is essential for co-coordinating cranial and spinal respiratory motor outputs in the neonatal rat. J Physiol 532. 2: 643–653, 2002.
Ezure K. Synaptic connections between medullary respiratory neurons and considerations on the genesis of respiratory rhythm. Prog Neurobiol 35: 429–450, 1990.[CrossRef][Web of Science][Medline]
Ezure K, Manabe M, and Yamada H. Distribution of medullary respiratory neurons in the rat. Brain Res 455: 262–270, 1988.[CrossRef][Web of Science][Medline]
Ezure K, Tanaka I, and Kondo M. Glycine is used as a transmitter by decrementing expiratory neurons of the ventrolateral medulla in the rat. J Neurosci 23: 8941–8948, 2003a.
Ezure K, Tanaka I, and Saito Y. Activity of brainstem respiratory neurons just before the expiration-inspiration transition in the rat. J Physiol 547: 629–640, 2003b.
Feldman JL. Neurophysiology of breathing in mammals. In: Handbook of Physiology. The Nervous System. Intrinsic Regulatory System in the Brain, edited by Bloom FE. Washington, DC: American Physiological Society, 1986, p. 463–524.
Fisher JAN, Civillico EF, Contreras D, and Yodh AG. In vivo fluorescence microscopy of neuronal activity in three-dimensions by use of voltage-sensitive dyes. Optics Lett 29: 71–73, 2004.[CrossRef][Web of Science][Medline]
Flourens MJP. Note sur le point vital de la moelle allongée. C R Seances Soc Biol 33: 437–439, 1851.
Gray PA, Janczewski WA, Mellen N, McCrimmon DR, and Feldman JL. Normal breathing requires preBotzinger complex neurokinin-1 receptor-expressing neurons. Nat Neurosci 4: 927–930, 2001.[CrossRef][Web of Science][Medline]
Grinvald A, Lieke EE, Frostig RD, and Hildesheim R. Cortical point-spread function and long-range lateral interactions revealed by real-time optical imaging of Macaque monkey primary visual cortex. J Neurosci 14: 2545–2568, 1994.[Abstract]
Grinvald A, Manaker A, and Segal M. Visualization of the spread of electrical activity in rat hippocampal slices by voltage sensitive optical probes. J Physiol 333: 269–291, 1982.
Hayashi F, Coles SK, and McCrimmon DR. Respiratory neurons mediating the Breuer-Hering reflex prolongation of expiration in rat. J Neurosci 16: 6526–6536, 1996.
Hayashi F and Lipski J. The role of inhibitory amino acids in control of respiratory motor output in an arterially perfused rat. Respir Physiol 89: 47–63, 1992.[CrossRef][Web of Science][Medline]
Hilaire G and Duron B. Maturation of the mammalian respiratory system. Physiol Rev 79: 325–360, 1999.
Howard BR and Tabatabai M. Localization of the medullary respiratory neurons in rats by microelectrode recording. J Appl Physiol 39: 812–817, 1975.
Johnson SM, Koshiya N, and Smith JC. Isolation of the kernel for respiratory rhythm generation in a novel preparation: The pre-Bötzinger complex "island" J Neuorphysiol 1772–1776, 2001.
Kashiwagi M, Onimaru H, and Homma I. Correlation analysis of respiratory neuron activity in ventrolateral medulla of brainstem-spinal cord preparation isolated from newborn rat. Exp Brain Res 95: 277–290, 1993.[Web of Science][Medline]
Kasparov S, Teschemacher AG, and Paton JFR. Dynamic confocal imaging in acute brain slices and organotypic slice cultures using a spectral confocal microscope with single photon excitation. Exp Physiol 87: 715–724, 2002.[Abstract]
Kleinfeld D and Delaney KR. Distributed representation of vibrissa movement in the upper layers of somatosensory cortex revealed with voltage-sensitive dyes. J Comp Neurol 375: 89–108, 1996.[CrossRef][Web of Science][Medline]
Kleinfeld D, Delaney KR, Fee MS, Flores JA, Tank DW, and Gelperin A. Dynamics of propagating waves in the olfactory network of a terrestrial mollusc: an electrical and optical study. J Neurophysiol 72: 1402–1419, 1994.
Konnerth A, Obaid AL, and Salzberg BM. Optical recording of electrical activity from parallel fibres and other cell types in skate cerebellar slices in vitro. J Physiol 393: 681–702, 1987.
Konnerth A and Orkand RK. Voltage-sensitive dyes measure potential changes in axons and glia of the frog optic nerve. Neurosci Lett 66: 49–54, 1986.[CrossRef][Web of Science][Medline]
Koshiya N and Smith JC. Neuronal pacemaker for breathing visualized in vitro. Nature 400: 360–363, 1999.[CrossRef][Medline]
Lumsden T. Observations on the respiratory centers in the cat. J Physiol 57: 153–160, 1923.
Marchenko VA, Fisher JAN, Rector DM, Yodh AG, and Rogers RF. Optical recording of respiratory-related activity from the ventrolateral medulla of artificially perfused juvenile rats. Soc Neurosci Abstr 187.1, 2004.
Markstahler U, Kremer E, Kimmina S, Becker K, and Richter DW. Effects of functional knock-out of 
1 glycine-receptors on breathing movements in oscillator mice. Respir Physiol Neurobiol 130: 33–42, 2001.[CrossRef][Web of Science]
McCrimmon DR, Monnier A, Hayashi F, and Zuperku EJ. Pattern formation and rhythm generation in the ventral respiratory group. Clin Exp Pharmacol Physiol 27: 126–131, 2000a.[CrossRef][Web of Science][Medline]
McCrimmon DR, Ramirez J-M, Alford S, and Zuperku EJ. Unraveling the mechanism for respiratory rhythm generation. BioEssays 22: 6–9, 2000b.[CrossRef][Web of Science][Medline]
Onimaru H and Homma I. A novel functional neuron group for respiratory rhythm generation in the ventral medulla. J Neurosci 23: 1478–1486, 2003.
Onimaru H, Kanamaru A, and Homma I. Optical imaging of respiratory burst activity in newborn rat medullary block preparations. Neurosci Res 25: 183–90, 1996.[Web of Science][Medline]
Paton JF, Ramirez JM, and Richter DW. Mechanisms of respiratory rhythm generation change profoundly during early life in mice and rats. Neurosci Lett 170: 167–70, 1994.[CrossRef][Web of Science][Medline]
Paton JFR. A working heart-brainstem preparation of the mouse. J Neurosci Methods 65: 63–68, 1996.[CrossRef][Web of Science][Medline]
Pierrefiche O, Schwarzacher SW, Bischoff AM, and Richter DW. Blockade of synaptic inhibition within the pre-Botzinger complex in the cat suppresses respiratory rhythm generation in vivo. J Physiol 1: 245–254, 1998.
Ramirez JM, Schwarzacher SW, Pierrefiche O, Olivera BM, and Richter DW. Selective lesioning of the cat pre-Botzinger complex in vivo eliminates breathing but not gasping. J Physiol 507. 3: 895–907, 1998.
Rector DM and George JS. Continuous image and electrophysiological recording with real-time processing and control. Methods 25: 151–163, 2001.[CrossRef][Web of Science][Medline]
Rector DM, Rogers RF, and George JS. A focusing image probe for detecting neural activity in vivo. J Neurosci Methods 91: 135–145, 1999.[CrossRef][Web of Science][Medline]
Rector DM, Rogers RF, Schwaber JS, Harper RM, and George JS. Scattered light imaging in vivo tracks fast and slow processes of neurophysiological activation. NeuroImage 14: 977–994, 2001.[CrossRef][Web of Science][Medline]
Rekling JC and Feldman JL. Prebotzinger complex and pacemaker neurons: hypothesized site and kernel for respiratory rhythm generation. Annu Rev Physiol 60: 385–405, 1998.[CrossRef][Web of Science][Medline]
Richter DW. Neural regulation of respiration: rhythmogenesis and afferent control. In: Comprehensive Human Physiology, vol. II, edited by Greger R and Windhorst U. Berlin: Springer-Verlag, 1996, p. 2079–2095.
Richter DW, Ballantyne D, and Remmers JE. How is the respiratory rhythm generated? A model. News Physiol Sci 1: 109–112, 1986.
Richter DW and Spyer KM. Studying rhythmogenesis of breathing: comparison of in vivo and in vitro models. Trends Neurosci 24: 262–472, 2001.
Rybak IA, Paton JFR, Rogers RF, and St.-John WM. Generation of the respiratory rhythm: state-dependency and switching. Neurocomputing 44-46: 605–614, 2002.[CrossRef]
Rybak IA, Paton JFR, and Schwaber JS. Modeling neural mechanisms for genesis of respiratory rhythm and pattern. I. Models of respiratory neurons. J Neurophysiol 77: 1994–2006, 1997a.
Rybak IA, Paton JFR, and Schwaber JS. Modeling neural mechanisms for genesis of respiratory rhythm and pattern. II. Network models of the central respiratory pattern generator. J Neurophysiol 77: 2007–2026, 1997b.
Salzberg BM. Optical recording of electrical activity in neurons using molecular probes. In: Current Methods in Cellular Neurobiology, edited by Barker J and McKelry J. New York: John Wiley, 1983, p. 139–187.
Schwarzacher SW, Smith JC, and Richter DW. Pre-Botzinger complex in the cat. J Neurophysiol 73: 1452–1461, 1995.
Schwarzacher SW, Wilhelm Z, Anders K, and Richter DW. The medullary respiratory network in the rat. J Physiol 435: 631–644, 1991.
Smith JC, Ellenberger HH, Ballanyi K, Richter DW, and Feldman JL. Pre-Botzinger complex: a brainstem region that may generate respiratory rhythm in mammals. Science 254: 726–729, 1991.
St.-John WM, and Paton JFR. Characterizations of eupnea, apneusis and gasping in a perfused rat preparation. Respir Physiol 123: 201–213, 2000.[CrossRef][Web of Science][Medline]
Sun Q-J, Goodchild AK, Chalmers JP, and Pilowsky PM. The pre-Bötzinger complex and phase-spanning neurons in the adult rat. Brain Res 809: 204–213, 1998.[CrossRef][Web of Science][Medline]
Tokumasu M, Nakazono Y, Ide H, Akagawa K, and Onimaru H. Optical recording of spontaneous respiratory neuron activity in the rat brain stem. Jap J Physiol 51: 613–9, 2001.[CrossRef][Web of Science][Medline]
von Euler C. Brain stem mechanism for generation and control of breathing pattern. In: Handbook of Physiology. The Respiratory System II: Control of Breathing, edited by Chernack NS and Widdicombe JG. Washington, DC: American Physiological Society, 1986, p. 1–67.
This article has been cited by other articles:
|
|
 |
|
  V. Marchenko and R. F. Rogers Temperature and state dependence of dynamic phrenic oscillations in the decerebrate juvenile rat Am J Physiol Regulatory Integrative Comp Physiol, December 1, 2007; 293(6): R2323 - R2335. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Oku, H. Masumiya, and Y. Okada Postnatal developmental changes in activation profiles of the respiratory neuronal network in the rat ventral medulla J. Physiol., November 15, 2007; 585(1): 175 - 186. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. M. Wilson, D. A. Dombeck, M. Diaz-Rios, R. M. Harris-Warrick, and R. M. Brownstone Two-Photon Calcium Imaging of Network Activity in XFP-Expressing Neurons in the Mouse J Neurophysiol, April 1, 2007; 97(4): 3118 - 3125. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 F. Funke, M. Dutschmann, and M. Muller Imaging of respiratory-related population activity with single-cell resolution Am J Physiol Cell Physiol, January 1, 2007; 292(1): C508 - C516. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Visit Other APS Journals Online |
Phr) trace (red) shown along with each different correlation function based on the firing-frequency traces of respiratory neurons (blue). Middle: histograms of calculated pixel correlation coefficients (for all experiments) based on the correlation function (blue) on the left using phrenic onset-triggered averaging (early-phase triggering). Right: histograms of calculated pixel correlation coefficients (based on the same correlation functions as middle) using phrenic peak-triggered averaging (late-phase triggering). B: correlation analysis (over all experiments) using subthreshold membrane potential-based correlation functions. B: left: averaged integrated phrenic (