USF Libraries
USF Digital Collections

Functional connectivity and responses to chemoreceptor stimulation of medullary ventrolateral respiratory column neurons

MISSING IMAGE

Material Information

Title:
Functional connectivity and responses to chemoreceptor stimulation of medullary ventrolateral respiratory column neurons
Physical Description:
Book
Language:
English
Creator:
Ott, Mackenzie
Publisher:
University of South Florida
Place of Publication:
Tampa, Fla
Publication Date:

Subjects

Subjects / Keywords:
Respiration
Control of Breathing
Chemoreception
Neural Networks
Rostral Ventrolateral Respiratory Column
Cross-correlation
Dissertations, Academic -- School of Biomedical Sciences -- Doctoral -- USF   ( lcsh )
Genre:
non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: Ventrolateral medullary neurons have important roles in cardiorespiratory coordination. A rostral extension of the ventral respiratory column (RVRC), including the retrotrapezoid nucleus (RTN), has neurons responsive to local perturbations of CO2 / pH. Respiratory-modulated firing patterns of RVRC neurons are attributed to influences of more caudal (CVRC) neurons. These circuits remain poorly understood. This study addressed the hypothesis that both local interactions and influences from the CVRC shape rostral neuron discharge patterns and responses. Spike trains from 294 rostral and 490 caudal neurons were recorded with multi-electrode arrays along with phrenic nerve activity in 14 decerebrate, vagotomized cats. Overall, 214 rostral and 398 caudal neurons were respiratory-modulated; 124 and 95, respectively, were cardiac-modulated. Subsets of these neurons were evaluated for responses to sequential, selective, transient stimulation of central and peripheral chemoreceptors and arterial baroreceptors. In 5 experiments, Mayer wave-related oscillations (MWROs) in neuronal firing rates were evoked, enhanced, or reduced following central chemoreceptor stimulation. Overall, 174 of the rostral neurons (59.5%) had short- time scale correlations with other RVRC neurons. Of these, 49 triggered cross-correlograms with RVRC targets yielding 330 offset features indicative of paucisynaptic actions from a total of 2,884 rostral pairs evaluated. Forty-nine of the CVRC neurons (10.0%) were triggers in 142 CVRC-RVRC correlograms - from a total of 8,490 - with offset features indicative of actions on RVRC neurons. Correlation linkage maps support the hypothesis that local circuit mechanisms contribute to the respiratory and cardiac modulation of RVRC neurons and their responses to chemoreceptor and baroreceptor challenges.
Thesis:
Dissertation (Ph.D.)--University of South Florida, 2010.
Bibliography:
Includes bibliographical references.
System Details:
Mode of access: World Wide Web.
System Details:
System requirements: World Wide Web browser and PDF reader.
Statement of Responsibility:
by Mackenzie Ott.
General Note:
Title from PDF of title page.
General Note:
Document formatted into pages; contains X pages.
General Note:
Includes vita.

Record Information

Source Institution:
University of South Florida Library
Holding Location:
University of South Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
usfldc doi - E14-SFE0003472
usfldc handle - e14.3472
System ID:
SFS0027787:00001


This item is only available as the following downloads:


Full Text
xml version 1.0 encoding UTF-8 standalone no
record xmlns http:www.loc.govMARC21slim xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.loc.govstandardsmarcxmlschemaMARC21slim.xsd
leader nam 22 Ka 4500
controlfield tag 007 cr-bnu---uuuuu
008 s2010 flu s 000 0 eng d
datafield ind1 8 ind2 024
subfield code a E14-SFE0003472
035
(OCoLC)
040
FHM
c FHM
049
FHMM
090
XX9999 (Online)
1 100
Ott, Mackenzie.
0 245
Functional connectivity and responses to chemoreceptor stimulation of medullary ventrolateral respiratory column neurons
h [electronic resource] /
by Mackenzie Ott.
260
[Tampa, Fla] :
b University of South Florida,
2010.
500
Title from PDF of title page.
Document formatted into pages; contains X pages.
Includes vita.
502
Dissertation (Ph.D.)--University of South Florida, 2010.
504
Includes bibliographical references.
516
Text (Electronic dissertation) in PDF format.
538
Mode of access: World Wide Web.
System requirements: World Wide Web browser and PDF reader.
3 520
ABSTRACT: Ventrolateral medullary neurons have important roles in cardiorespiratory coordination. A rostral extension of the ventral respiratory column (RVRC), including the retrotrapezoid nucleus (RTN), has neurons responsive to local perturbations of CO2 / pH. Respiratory-modulated firing patterns of RVRC neurons are attributed to influences of more caudal (CVRC) neurons. These circuits remain poorly understood. This study addressed the hypothesis that both local interactions and influences from the CVRC shape rostral neuron discharge patterns and responses. Spike trains from 294 rostral and 490 caudal neurons were recorded with multi-electrode arrays along with phrenic nerve activity in 14 decerebrate, vagotomized cats. Overall, 214 rostral and 398 caudal neurons were respiratory-modulated; 124 and 95, respectively, were cardiac-modulated. Subsets of these neurons were evaluated for responses to sequential, selective, transient stimulation of central and peripheral chemoreceptors and arterial baroreceptors. In 5 experiments, Mayer wave-related oscillations (MWROs) in neuronal firing rates were evoked, enhanced, or reduced following central chemoreceptor stimulation. Overall, 174 of the rostral neurons (59.5%) had short- time scale correlations with other RVRC neurons. Of these, 49 triggered cross-correlograms with RVRC targets yielding 330 offset features indicative of paucisynaptic actions from a total of 2,884 rostral pairs evaluated. Forty-nine of the CVRC neurons (10.0%) were triggers in 142 CVRC-RVRC correlograms from a total of 8,490 with offset features indicative of actions on RVRC neurons. Correlation linkage maps support the hypothesis that local circuit mechanisms contribute to the respiratory and cardiac modulation of RVRC neurons and their responses to chemoreceptor and baroreceptor challenges.
590
Advisor: Bruce G. Lindsey, Ph.D.
653
Respiration
Control of Breathing
Chemoreception
Neural Networks
Rostral Ventrolateral Respiratory Column
Cross-correlation
690
Dissertations, Academic
z USF
x School of Biomedical Sciences
Doctoral.
773
t USF Electronic Theses and Dissertations.
4 856
u http://digital.lib.usf.edu/?e14.3472



PAGE 1

Functional Connectivity and Responses to Chemoreceptor Stimulation of Medullary Ventrolateral Respiratory Column Neurons by Mackenzie M. Ott A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Molecular P harmacology and Physiology College of Medicine University of South Florida Co-Major Professor: Bruce G. Lindsey, Ph.D. Co-Major Professor: Kendall F. Morris, Ph.D. John R. Dietz, Ph.D. Eric S. Bennett, Ph.D. Samuel Saporta, Ph.D. Date of Approval: April 9, 2010 Keywords: Control of breathing, brains tem respiratory network, respiratory modulation, cross-correlat ion, rostral ventral lateral medulla, Mayer waves Copyright 2010, Mackenzie M. Ott

PAGE 2

DEDICATION In honor of my beloved par ents, Margaret Faye and John Herbert Ott, whose love and encouragement have successfully guided me along life’s path.

PAGE 3

ACKNOWLEDGEMENTS I would like to express my deepest gratitude to my mentors, Dr. Bruce G. Lindsey and Dr. Kendall F. Morris, for thei r guidance, support, and encouragement throughout my graduate student career. I would also like to thank the members of my committee, Dr. John R. Dietz, Dr. Er ic S. Bennett, and Dr. Samuel Saporta for their patience and support in the completion of this research. I am extremely grateful to all the staff and faculty of the Department of Pharmacology and Physiology and the Grad uate and Postdoctoral Affairs office for being part of my support structure. I am indebted to all the members of the Lindsey Lab: Dr. Sarah C. Nuding for assistance during experiments and data analysis training, Peter Barnhill, Russe ll O’Connor and Dr. Lauren S. Segers for their programming expertise, and Kimberly Ruff for her su rgical skills. Thanks to Kathryn Zahn, Bridget Shields and Barbar a Nicholson for their tireless efforts. This work would not have been possibl e without the unrelenting support and encouragement of my parent s, family and friends. This research was supported by grant R 37 NS19814 from the National Institute of Health.

PAGE 4

NOTE TO READER The original of this document contains color that is necessary for understanding the data. The original dissertation is on file with the USF library in Tampa, Florida.

PAGE 5

i TABLE OF CONTENTS LIST OF TABLES iii LIST OF FIGURES iv LIST OF ABBREVIATIONS v ABSTRACT vii INTRODUCTION 1 MULTISITE RECORDINGS REVEAL LOCAL CIRCUIT MODULATION OF CHEMORESPONSIVE ROSTRAL VENTROLATERAL MEDULLARY RESPIRATORY NEURONS WITH CARDIOVASCULAR-RELATED RHYTHMS 7 Introduction 8 Methods 11 General Methods and Surgical Preparation 11 Neuronal Recordings and Post-E xperimental Processing 14 Histological Confirmation of Electrode Location 15 Neuron Characterization: Respiratory and Cardiac Modulation of Firing Rates 16 Protocol for the Stimul ation of Chemoreceptors and Baroreceptors 17 Measurement of Responses to Chemoreceptor and Baroreceptor Stimulation 18 Evaluation of Mayer Wave-Related Oscillations 18 Cross-correlation Analysis 20

PAGE 6

ii Results 22 Discharge Patterns of Neurons 24 Responses to Central Chem oreceptor Stimulation 28 Responses to Arterial Baroreceptor Stimulation 35 Responses to Peripheral Chemoreceptor Stimulation 39 Neuron Response Profiles Mapped to Recording Site Coordinates 45 Cross-correlation Analysis 45 Evidence for Inputs Shared by RVRC Neurons 48 Evidence for RVRC RVRC Functional Connectivity 51 Evidence for CVRC RVRC Functional Connectivity 54 Extended Correlational Linkages 56 Correlational Linkages among Cardiacand Cardiac/RespiratoryModulated Neurons 63 Discussion 66 Relationship to Prior Work and Functional Implications 70 Advantages and Limitations of th e Experimental Approach 72 Future Directions 74 CONCLUSIONS 78 REFERENCES 80 ABOUT THE AUTHOR End Page

PAGE 7

iii LIST OF TABLES Table 1 Primary responses of single neurons to sequential central chemoreceptor stimulation 31 Table 2 Primary responses of single neurons to sequential arterial baroreceptor stimulation 38 Table 3 Primary responses of single neurons to sequential peripheral chemoreceptor stimulation 42 Table 4 Characterization of single neurons responsive to select stimulation protocols 47 Table 5 RVRC-to-RVRC significant offset feature correlations detected in the analysi s of 2,884 RVRC–RVRC neuron pairs 52 Table 6 CVRC-to-RVRC significant offset feature correlations detected in the analysi s of 8,490 CVRC–RVRC neuron pairs 55 Table 7 Responses and offset correlation features for tested neuron pairs 58

PAGE 8

iv LIST OF FIGURES Figure 1 Recording sites 23 Figure 2 Respiratory and cardiac modulation 26 Figure 3 Central chemoreceptor stimulation 29 Figure 4 Mayer wave-related oscillations 33 Figure 5 Baroreceptor stimulation 36 Figure 6 Peripheral chemoreceptor stimulation 40 Figure 7 Response profiles of neurons 43 Figure 8 Intra-RVRC functional connectivity 49 Figure 9 CVRC-to-RVRC functional connectivity 59 Figure 10 Extensive f unctional linkages 61 Figure 11 Correlations among cardio/respiratory neurons 64 Figure 12 Inferred intra-RVRC and CVRC-to-RVRC interactions proposed to contribute to t he respiratory modulated discharge patterns of RVRC neurons 68

PAGE 9

v LIST OF ABBREVIATIONS ACH Autocorrelation histogram A / P Anterior / Posterior AUG Augmenting BP Blood pressure DEC Decrementing CM Cardiac-modulated CCH Cross correlation histogram cCTH Cardiac cycle triggered histogram cCVLM Caudal ventrolateral medulla CPA Caudal pressor area C / R Cardiac/respiratory-modulated CUSUM Cumulative sum histogram CVRC Caudal ventral respiratory column DI Detectability index E Expiratory EI Expiratory inspiratory phase spanning FTG Gigantocellular tegmental field FTM Magnocellular tegmental field Hz Hertz I Inspiratory IE Inspiratory expiratory phase spanning i.m. Intramuscular IML Intermediolateral cell column iv Intravenous kHz Kilohertz Max. Maximum MWRO Mayer wave-related oscillation NRM Non respiratory modulated NT Not tested P Pyramidal tract P Peak pCO2 Partial pressure of carbon dioxide PGCL Lateral paragigantoc ellular reticular nucleus PH Nucleus praepositus hypoglossi Phr Phrenic nerve PPR postpyramidal nucleus of the raph PSTH Peri-stimulus time histogram R Respiratory-modulated

PAGE 10

vi rCTH Respiratory cycle triggered histogram Resp. Respiratory RTN Retrotrapezoid nucleus RVLM Rostral ventrolateral medulla RVRC Rostral ventral respiratory column s Seconds spikes s-1 Spikes per second T Trough VIN Inferior vestibular nucleus VMN Medial vestibular nucleus VRC Ventral respiratory column 5ST Spinal trigeminal tract 7M Medial division of facial nucleus 7L Lateral division of facial nucleus 2 Delta squared Increase Increase-decrease Decrease Decrease-increase No change

PAGE 11

vii Functional Connectivity and Responses to Chemoreceptor Stimulation of Medullary Ventrolateral Respiratory Column Neurons Mackenzie M. Ott ABSTRACT Ventrolateral medullary neurons have im portant roles in cardiorespiratory coordination. A rostral extension of t he ventral respiratory column (RVRC), including the retrotrapezoid nucleus (R TN), has neurons responsive to local perturbations of CO2 / pH. Respiratory-modulat ed firing patterns of RVRC neurons are attributed to influences of more caudal (CVRC) neurons. These circuits remain poorly understood. This st udy addressed the hypothesis that both local interactions and influences from the CVRC shape rostral neuron discharge patterns and responses. Spike trains from 294 rostral and 490 caudal neurons were recorded with multi-electrode arrays along with phrenic nerve activity in 14 decerebrate, vagotomized cats. Overa ll, 214 rostral and 398 caudal neurons were respiratory-modulated; 124 and 95, respectively, were cardiac-modulated. Subsets of these neurons were evaluated fo r responses to sequential, selective, transient stimulation of central and per ipheral chemoreceptors and arterial baroreceptors. In 5 experim ents, Mayer wave-related oscillations (MWROs) in neuronal firing rates were evoked, enhanc ed, or reduced following central chemoreceptor stimulation. Overall, 174 of the rostral neurons (59.5%) had short-

PAGE 12

viii time scale correlations with other RVRC neurons. Of these, 49 triggered crosscorrelograms with RVRC targets yielding 33 0 offset features indicative of paucisynaptic actions from a total of 2,884 rostral pairs evaluated. Forty-nine of the CVRC neurons (10.0%) were trigger s in 142 CVRC—RVRC correlograms from a total of 8,490 with o ffset features indicative of actions on RVRC neurons. Correlation linkage maps support the hypot hesis that local circuit mechanisms contribute to the respiratory and card iac modulation of RVRC neurons and their responses to chemoreceptor and baroreceptor challenges.

PAGE 13

1 INTRODUCTION The primary role of the respiratory and cardiovascular systems in vertebrates is to maintain cardiore spiratory homeostasis by exchanging respiratory gases between the environment and the tissues (Feldman at al. 1988). Cardiorespiratory coupling (the coordination of cardiovascular and respiratory function) is the result of interacting neuronal networks in the brainstem which integrate the control of alveolar ventilation, cardiac output, and peripheral blood flow ( Richter and Spyer 1990). Respiratory output from the brainstem is responsible for the motor control which makes ventilation possible (Bi anchi et al. 1995). The phrenic nerve innervates the diaphragm which is the primary inspirator y muscle. During Inspiration, the diaphragm contracts and moves downward, while the external intercostals contract and move the ri bcage up and out, lowering the air pressure in the lungs and air is inhaled. Expiration during resting breathing normally results as a passive relaxation of the exte rnal intercostals in combination with the elastic recoil of the lung tissue. Bipolar electrodes commonly record e fferent phrenic nerve activity during experiments. The durations of the inspiratory and expiratory phases.are

PAGE 14

2 measured from these signals. The activi ty of the phrenic nerve also serves as the predominate indicator of whether or not the cell’s firing pattern is respiratory modulated and eval uating the response of respiratory drive to system perturbations. The brainstem also receives sensory information from multiple sources including chemoreceptors, which are s ensors that monito r the effects of ventilation in order to maintain the hom eostasis of oxygen, carbon dioxide, and pH (Loeschcke 1982). Chemor eceptors detect chemical changes in the blood and cerebral spinal fluid and they provi de stimulatory input to the brainstem necessary for respiratory drive. There ar e two classes of chem oreceptors: central and peripheral. Multiple brainstem regi ons are proposed to be sites of central chemoreception, including the retrotrapez oid nucleus near the ventromedullary surface, the region of the nucleus of the solitary tract, and the midline raph (Nuding et al. 2009a). Peripheral chemorec eptors are located near the carotid and aortic bodies. Arterial baroreceptors prov ide additional sensory i nput to the respiratory brainstem. Baroreceptors ar e stimulated by pressure changes in the arteries and are located near the carotid sinus as well as above and below the aortic arch. Sensory afferent information from the ca rotid body and sinus areas travels to the nucleus of the solitary tract via th e glossopharyngeal nerve, while sensory information from the aortic body and arch receptors travels to the brainstem via

PAGE 15

3 the vagus nerve. Other sources of input to the respiratory c ontrol system include: pain nociceptors, stretch receptors in the lungs and irritant receptors. Pulmonary stretch receptors assist in the modulati on of the rate and depth of breathing. Sensory afferent information from the pul monary stretch receptors is carried to the medulla via the vagus nerve. Populations of medullary neurons in volved in the control of breathing include the dorsal respirat ory group and the ventral respiratory group which contain neurons that project down to the phrenic moto r neurons in the spinal cord which drive the diaphragm. The ventral respiratory group makes up part of a column of cells located in the ventrola teral medulla including the Btzinger and the pre-Btzinger Complexes (Alheid et al. 2002; Feldman and Del Negro 2006; Onimaru and Homma 2006; Rybak et al. 20 07; Smith et al. 1991, 2007). The preBtzinger complex is the proposed site of the respiratory central pattern generator responsible for the generation of the respirator y rhythm (Smith et al. 1991). However, the exact mechanism underlying central pattern generation remains controversial. This column of ce lls is also referred to as the ventral respiratory column (VRC). The pontine re spiratory group is also required to maintain a normal respiratory rhythm. Rostral ventral respiratory colu mn (RVRC) neurons, including those located in the regions of t he lateral tegmental field, re trotrapezoid nucleus (RTN), and parafacial nuclei have impor tant roles in respirat ory rhythm generation and

PAGE 16

4 modulation (Connelly et al. 1990; On imaru and Homma 2003), but their interactions with caudal ventral respirator y column (CVRC) populations including the Btzinger and pre-Btzinger complexes remain poorly understood. More specifically, pathways contributing to t he network mechanisms for respiratory modulation and chemoresponsiveness among RVRC neurons remain unknown. Early goals of the neurophysiologist were to locate and classify the firing patterns of neurons comprising the cardio respiratory brainstem network. While the anatomical location and cell classifi cation are phenotypically important, less is known about the functional and/or m odulatory role of the neurons comprising the network. Abnormalities in the m odulation and configuration of this cardiorespiratory network contribute to disorders such as congenital central hypoventilation syndrome (Dubreuil et al. 2008), Sudden Infant Death Syndrome (Kinney 2009), sleep-disor dered breathing, sleep apnea, and various forms of neurogenic hypertension (Duffin 2004; Guy enet 2006). Contemporary goals have transitioned from identifying anatomical projections of brainstem nuclei to a more specific focus involving the investigat ion of functional connectivity among the neurons comprising this network, in order to infer their corresponding roles in the maintenance of cardiorespiratory homeostasis. Several lines of evidence support the hy pothesis that the RTN is a site of central chemoreception for CO2 and pH (Guyenet 2008; Loeschcke 1982): (i) the region contains chemoresponsive neurons (Nattie et al. 1993); (ii) RTN neurons

PAGE 17

5 have properties indicative of intrinsic chemosensitivity (Guyenet et al. 2005b; Mulkey et al. 2004; Nattie and Li 1995; Ta kakura et al. 2006); iii) some RTN neurons have respiratory modulated firi ng patterns and iv) neurons that respond to peripheral chemoreceptor inputs have been identified in the RTN (Takakura et al. 2006). However, connectivity and pat hways mediating the respiratory modulation and functional convergence of c hemoreceptor influences are not well understood. The RTN and the adjacent subretrofacial region and lateral paragigantocellular nucleus also in clude sympathetic-related baroresponsve cardiac-modulated neurons (Barm an and Gebber 1985; Brown and Guyenet 1984; Connelly et al. 1990; Guyenet et al. 2005b). Neurons with both cardiovascularand respiratory-related ac tivity near the ventral surface of the medulla have been identified (McAllen 1986b). Neural networks in this rostral VRC (RVRC) region thus play an important integrative ro le in the control of the respiratory and cardiovascula r systems, but the network architecture responsible for their coordinated activities remain s poorly understood (Bianchi et al. 1995; Calaresu 1988; Millhorn and Eldr idge 1986; Taylor et al. 1999). Experiments in the present study used innovative multi-electrode array technology to record neuronal activity in two regions of the cat brainstem: the RVRC and the CVRC, sites associated with the integration of cardiovascular and respiratory function. Spike train corre lation methods were used to evaluate

PAGE 18

6 neurons for modulations of average firing ra te time-locked to the respiratory and cardiac cycles and for evidence of loca l circuit influences upon RVRC neurons. A subset of neurons was tested for responses to selective stimulation of central chemoreceptors and evaluated for evoked changes in slow-rhythm Mayer wave related oscillations (MWROs; Montano et al 1996, Morris et al. 2007). We also investigated whether neurons were re sponsive to peripheral chemoreceptor stimulation and to changes in arterial blo od pressure. This project helped to fill fundamental gaps in knowledge of how br ainstem nuclei contribute to complex regulation of the card iorespiratory system. The results of this study support t he hypothesis that the respiratorymodulated discharge patterns of RVRC neur ons are shaped i) by the distributed functional connectivity among the RVCR neurons and ii) by those respiratoryand non-respiratory-modulated neurons of the CVRC that exhibit correlations with RVRC neurons. The results also sugge st that three different sensory modalities – central and peripheral chem oreceptors as well as arterial baroreceptors – influence the respiratory network through shared multifunctional neurons.

PAGE 19

7 Multisite Recordings Reveal Local Cir cuit Modulation of Chemoresponsive Rostral Ventrolateral Medullary Respirat ory Neurons with Cardiovascular-Related Rhythms Mackenzie M. Ott, Sarah C. Nuding, Lauren S. Segers, Bruce G. Lindsey, and Kendall F. Morris Department of Molecular Pha rmacology and Physiology and Neuroscience Program, School of Biom edical Sciences, University of South Florida College of Medi cine, Tampa, Florida 33612

PAGE 20

8 INTRODUCTION The rostral ventrolateral medulla including the retrotrapezoid nucleus/parafacial respiratory group (R TN) (Connelly et al. 1990; Onimaru and Homma 2003), the adjacent subretrofaci al region (McAllen 1986a), and other parts of the lateral tegmental field (Orer et al. 2006), has an important role in the control of breathing and cardioresp iratory system regulation (Feldman and McCrimmon 1999; Feldman et al. 2003). Contemporary views consider the region of the RTN to be the rostral medulla ry extent of the ventral respiratory column (VRC), which also includes the Btzinger and pre-Btzinger complexes and the rostral and caudal ventral respirat ory groups (Alheid et al. 2002; Feldman and Del Negro 2006; Onimaru and Homma 2006; Rybak et al. 2007; Smith et al. 1991, 2007). Several lines of evidence support the hy pothesis that the RTN is a site of central chemoreception (Guyenet 2008; Loe schcke 1982): i) t he region contains chemoresponsive neurons (Nattie et al. 1993) ; ii) lesions of neurons in the region reduce or eliminate phrenic activity, alter cycle frequency (St. John et al. 1989), and decrease CO2 sensitivity (Nattie et al. 1991); and iii) RTN neurons have properties indicative of intrinsic chemos ensitivity (Guyenet et al. 2005b; Mulkey et al. 2004; Nattie and Li 1995; Takakura et al. 2006). Some RTN neurons have respiratory-modulated firing patterns (Connelly et al. 1990; Pearce et al. 1989),

PAGE 21

9 and neurons that respond to peripheral chemoreceptor inputs have been identified (Takakura et al 2006). The RTN and the adjac ent subretrofacial region and lateral paragigantocellular nucl eus also include sympathetic-related baroresponsive cardiac-modulated neur ons (Barman and Gebber 1985; Brown and Guyenet 1984; Connelly et al. 1990; Guyenet et al. 2005b). Neurons with both cardiovascularand respiratory-m odulated activity are found near the ventral surface of the medulla (McAllen 1986b). Neural networks in this rostral VRC (R VRC) region thus play an important integrative role in the control of the respiratory and cardiovascular systems, but the network architecture responsible fo r their coordinated activities remains poorly understood (Bianchi et al. 1995; Calaresu 1988; Millhorn and Eldridge 1986; Taylor et al. 1999). While anatomical location and cell classification are phenotypically important, little is known ab out the functional connectivity among RVRC neurons in the region of the RTN. Although anatomical projections from this region to other medullary neurons in volved in respiratory control have been demonstrated (Smith et al. 1989), the roles of these RVRC neurons in the control of breathing are not well und erstood. More specifically pathways contributing to the network mechanisms for respirator y modulation and chemoresponsiveness within the RVRC remain unknown. The functional connectivity between populations in the caudal ventral respirat ory column (CVRC) and the RVRC also remain poorly understood (Takakura et al. 2006). Three questions addressing specific gaps in knowledge motivated this work. First, do CVRC neurons shape the respiratory modul ation of RVRC

PAGE 22

10 neurons? Lesions within the CVRC r educe or eliminate the respiratory modulation of a subset of RVRC neurons in the RTN, an effect that has been attributed to loss of inhibitory influences from the respiratory central pattern generator (Guyenet et al. 2005b). However, t here are several potential routes for these influences (Nuding et al. 2009a), and t here is a need to identify interactions between specific categories of RVRC neur ons and more caudal domains of the VRC. Second, do RVRC chemoresponsive neurons have both respiratoryand cardiac-modulated discharge patterns in vivo and are they responsive to blood pressure changes? Third, do connections among RVRC neuron populations contribute to both their re spiratory modulation and mult i-modal response profiles? Multi-electrode arrays were used to simultaneously monitor RVRC and CVRC neurons. Spike train correlation methods were used to evaluate neurons for modulations of average firing rate time -locked to the respiratory and cardiac cycles and for evidence of local circuit influences upon RVRC neurons. A subset of neurons was tested for responses to selective stimulation of central chemoreceptors and evaluated for evoked changes in slow-rhythm Mayer wave related oscillations (MWROs). We also investigated whether neurons were responsive to peripheral chemoreceptor st imulation and to changes in arterial blood pressure; changes in blood pr essure are commonly evoked by chemosensory perturbations (Dampney 1994; Feldman and E llenberger 1988; Guyenet 2006; Koshiya and Guyenet 1996; Nuding et al. 2009b). Preliminary accounts of some of t he results have been reported (Ott et al. 2007, 2008).

PAGE 23

11 METHODS General methods and surgical preparation All experiments were performed accord ing to protocols approved by the University of South Florida’s Institut ional Animal Care and Use Committee with strict adherence to all American Associ ation for Accreditation of Laboratory Animal Care International (AAALAC), Nati onal Institutes of Health and National Research Council guidelines. Data were obtained from 14 adult cats (2.9 – 5.2 kg) of either sex. Animals were initially anesthetized with 5% isoflurane mixed with air and maintained with 0.5 – 3.0% isoflur ane until decerebration using a te chnique adapted from Kirsten and St. John (1978). The level of anest hesia was evaluated periodically by testing the corneal reflex and toe pinch; in the event of limb withdrawal, eye blink, twitch reflexes, or fluctuations in arteri al pressure, heart rate or respiratory rate, the percentage of isoflurane in the in spired gas was incr eased until these responses were eliminated. Following the initial anesthesia, atropine (0.4 mg kg-1 i.m.) was administered to reduce tracheal airway secretions. A urinary catheter was inserted to monitor renal function; rectal temperature was measured and maintained at 38.0 0.5 C. The trachea was cannulated and the animal was artificially ventilated.

PAGE 24

12 The right femoral artery was catheter ized. Arterial blood pressure, endtidal CO2, and tracheal pressure were monitored continuously; arterial PO2, PCO2, and pH were measured periodically. These parameters were maintained within normal limits by supplement al administration of O2, adjusting the flow rate of ventilation gases, changing the resp iratory rate, and the intravenous administration of sodium bicarbonate (8%) in the event of metabolic acidosis. Solutions of 6% Dextran 70 in 0.9% sodium chloride, dopamine (0.08%) or phenylephrine (0.075 mg mL-1) in lactated Ringer’s were administered as needed to maintain arterial pressure. The ri ght femoral vein was catheterized for intravenous administration of drugs and fl uids. Dexamethasone (initial bolus of 2.0 mg kg-1 followed by 4.5 mg kg-1 hr-1 constant infusion in an isotonic K+ and Na+ solution) was administered to help pr event hypotension, reduce swelling in the brainstem, and keep the vein pat ent. A bolus of the antihistamine diphenhydramine (1.8 mg kg-1) minimized airway secretions. An embolectomy catheter was placed into the left femoral artery and advanced into the descending aorta until it was rostral to t he renal arteries. Placement was verified by inflating the catheter to increase blood pressure by 20 – 25 mmHg above the mean systemic value. A concentric catheter was inserted in to the external carotid artery and advanced to a level caudal to the carotid si nus (Arita et al. 1988; Li et al. 1999). Another catheter was inserted into the left axillary artery and advanced to the bifurcation of the vertebral artery (N uding et al. 2009b); preceding branches of the axillary artery were ligated (Kuwana and Natsui 1987). The outer barrel of

PAGE 25

13 each catheter was continuously infus ed at a minimum rate, with heparinized saline (pH 7.4), to maintain a patent vessel. The left and right C5 phrenic nerve rootlets were isolated, desheathed, cut peripherally, and placed on bipolar silver elec trodes in a pool of warm mineral oil. The left and right vago-sympathetic nerve (CN X) trunks were isolated in the neck caudal to the carotid sinus area and sectioned to remove vagal sensory feedback from pulmonary stretch receptors. Both external carotid arteries were ligated rostral to the lingual arteries to minimize bleeding during and after the decerebration procedure. Be fore decerebration, an anes thetic assessment was performed. Animals were then neuromuscularly blocked by pancuronium bromide (initial bolus of 0.1 mg kg 1 followed by 0.2 mg kg 1 hr 1, iv), and the brainstem was immediately transected at the midcol licular level (Kirsten and St. John 1978). Brain tissue rostral to the transection was aspirated. Following the decerebration, isoflurane was discontinued and the air flow was increased to ai d elimination as quickly as possible (Sasano et al. 2001). Sufficient CO2 was added to maintain the CO2 level at 30 mmHg to prevent hyper ventilation and decreased brainstem microcirculation during this period (Vesely et al. 2003). To minimize brainste m movement, animals were placed in a prone position in a stereotaxic frame, a t horacotomy was performed, and the T4 vertebral process was isolated and clamped to elevate the abdomen. The fraction of inspired O2 was increased as necessary to prevent hypoxemia that may occur due to ventilation-perfusion mismatching resulting from the open chest. The trachea was periodically suct ioned and the lungs hyperinflated to

PAGE 26

14 counteract atelectasis. An occipita l craniotomy was performed and the caudal portion of the cerebellum was removed by aspiration to expose the dorsal surface of the brainstem. The pia mater was removed over the region of interest to minimize tissue compression and a llow for unforced microelectrode array penetration. Neuronal recordings and post-experimental processing Neuronal activity was extracellularl y recorded using two multi-electrode arrays, each with 24 or 32 individua lly-adjustable high impedance tungsten microelectrodes (10-12 M ). Anatomical landmarks (e.g., obex, brainstem midline) and stereotaxic coordinates we re used to determine array placement. Tips of a 24-electrode array were coat ed with a fluorescent dye (di-I) before recording (DiCarlo et al. 1996) and placed in the rostral region of the medulla to monitor RVRC neurons. A 32-electrode arra y was placed in the region of the CVRC. Neuronal signals were amplified, filtered (0.3 – 10 kHz bandpass) and recorded on a DataMAX instrumentation recorder (25 kHz sampling frequency with 16-bit accuracy per channel) together wi th systemic arterial blood pressure, end-tidal CO2, stimulus event markers, effe rent nerve activity, and tracheal pressure. Filtered phrenic nerve activity (10 Hz – 10 kHz bandpass) was used as an indication of respiratory drive, to asse ss stimulus effectiveness, and to identify the phases of respiration. Control neuronal activity was recorded for 30 minutes before any stimulus protocol.

PAGE 27

15 Signals from single neurons were isol ated using interactive spike sorting software (O'Connor et al. 2005). Autocorrelation histograms were calculated as an indicator that each spike train represented the activi ty of a single neuron; spike event times derived from multiple neurons would include short intervals not constrained by a refractory period. X-scope, a utility program designed in our laboratory (Lin dsey et al. 1992), provided a graphical representation of the times of action potentials in simultaneously monitored neurons, othe r event timing pulse codes, and analog signals. This program includes a bandpass filter fo r spike train data and was used to identify oscillations in neuronal fi ring rate around the 0.1 Hz frequency of Mayer waves. Stereotaxic coordinates of recording sites we re mapped into the three-dimensional space of a compute r-based brain stem atlas derived from The Brain Stem of the Cat: A Cytoarchitectonic Atlas with Stereotaxic Coordinates (Berman 1968) with permission of the Univ ersity of Wisconsin Press, as described in Segers et al. (2008). Histological confirmation of electrode location At the end of each expe riment, animals were overdosed with Beuthanasia (0.97 mg kg-1; Schering-Plough Anim al Health) and perfused using a 10% neutralbuffered formalin solution. Al ternate frozen sections (40 m) were stained with cresyl violet and examined using bright field optics. Unstained sections were examined for fluorescent electrode tra cks using a Typhoon 94 10 multiple mode

PAGE 28

16 imager. Images were aligned and stac ked using the image processing program Image J. Histological data we re used to corroborate ster eotaxic recording sites by comparing anatomical landm arks delineated by coordi nates from Berman (1968). Neuron characterization: respiratory and cardiac modulation of firing rates All neurons were characterized as either respiratory-modulated or nonrespiratory modulated using tw o complementary statistica l tests: an analysis of variance (ANOVA) using a subjects-bytreatments experimental design (Netick and Orem 1981; Orem and Ne tick 1982) and a nonparametric sign test (Morris et al. 1996). Neurons were classified as respir atory-modulated if ei ther test rejected the null hypothesis ( p < 0.05); neurons with no preferred phase of maximum activity as assessed by both statistica l tests were considered non-respiratory modulated (NRM). Standard and normalized respiratory cycle-triggered histograms (rCTH) were constructed for each recorded neuron by comparing the cell’s activity with phrenic nerve activity to provide an estima te of the average firing rate of each cell throughout the respiratory cycle. The no rmalized rCTH was computed using a spike train in which the durations of t he inspiratory and expiratory phases were normalized to the average phase lengths; individual spike times within each phase were proportionately shifted to fit the normalized phase. The rCTHs were used to classify respiratory-modulated neuron s as inspiratory (I), expiratory (E), or phase-spanning (IE or EI) according to the part of the cycle during which the

PAGE 29

17 cell was most active (Cohen 1968). I and E cells were further classified as decrementing (Dec) or augmenting (Aug) if the peak firing rate occurred during the first or second half of the phase, respectively. The abrupt rise in pulse pressure associated with systole was used as a reference point to calculate cardiac cycl e-triggered histograms (cCTH) for each neuron. Spike trains were evaluated for significant arterial pulse pressure modulation using an ANOVA as de scribed in Dick and Morris (2004). Protocol for the stimulation of chemoreceptors and baroreceptors Central and peripheral c hemoreceptors were select ively stimulated by 30s injections of 1.0 mL of a CO2 -saturated 0.9% saline solution into the vertebral and external carotid arteries respectively (Nuding et al. 2009b). Each stimulus challenge was presented at least 5 times; trials were separated by 4.5 minute intervals to allow phrenic nerve activity to return to pre-stimulus levels. Injections of 1.0 mL sterile 0.9% sa line separated by 1.5 minute intervals were used as a negative control in some experiments to verify that changes in blood pressure and/or efferent phrenic output during centra l chemoreceptor stimulation were not due to volume effects. Arterial baroreceptors were stimul ated by 30-s inflations of the embolectomy catheter to transiently elevate blood pressure 20 – 25 mmHg (Lindsey et al. 1998). Baroreceptor stim ulus challenges were repeated at least

PAGE 30

18 four times and separated by 1.5 minute intervals to allow the mean systemic arterial pressure to return to pre-stimulus levels. Measurement of responses to chemor eceptor and baroreceptor stimulation Stimulus effectiveness was confirmed by measures of the peak amplitude of the integrated phrenic nerve signal and mean systemic arterial pressure. Effective reflexes were i dentified by a change ( 2 s.d.) in the peak integrated phrenic nerve amplitude from the mean of pre-stimulus values (Nuding et al. 2009b). Spike trains were evaluated fo r rate changes during each effective stimulus challenge. A peri-stimulus time histogram (PSTH) was constructed for each neuron to aid assessment of changes in firing rate following stimulus onset relative to the immediately preceding c ontrol period. Cumulative sum (CUSUM) histograms (Ellaway 1978) were calculated from the PSTHs; changes in activity that exceeded 3 s.d. (Davey et al. 1986) were confirmed using a bootstrap statistical method (as described in Nuding et al. 2009b). Response classification consisted of five categories: increase ( ), decrease ( ), biphasic response (increase-decrease [ ] or decrease-increase [ ]), or no change ( ). Evaluation of Mayer wave-related oscillations The X-scope program was used to det ect the presence of Mayer waverelated oscillations (MWROs) in the fi ring rates of the neurons by applying a

PAGE 31

19 bandpass filter (5 – 7 cycles per minute) to spike train data around the 0.1 Hz frequency of Mayer waves. To evaluate t he significance of components in the frequency band of interest, the instantaneous fi ring rate of the original spike train was bandstop filtered (5 – 7 cycles per mi nute) and 20 random spike trains were generated from the result. T hese surrogate spike trains were bandpass filtered in the same way as the original. Random ness in the surrogate spike trains generated power in the band of interest despite the band-stop filtering of the firing rate. The surrogates were us ed to define a threshold at the 99th percentile of the distribution of the cycle-by-cycle peak amplitude of the filtered surrogates. The logarithm of the ratio of the cycle-by-cycle peak am plitudes of the original filtered spike train to the threshold was mapped to a color display with black designating periods in which the spike train had power that was less than the 99th percentile of the surrogates (i.e., less than threshold). The resulting “heat maps” indicated intervals with significant spike train MWROs. Changes in MWRO activity in response to central chemoreceptor stimulation were evaluated by compari ng spike train data segments from 90-s periods preceding and immediately follo wing the onset of the first central chemoreceptor stimulus trial. MWROs were considered to be i) evoked if the control period did not exhibi t the oscillations and they were present (above the surrogate-derived threshold) duri ng the stimulus period, ii) enhanced if there was an increased duration of oscillatory acti vity during the stimulus period as compared to control, or iii) reduced if the total duration of oscillations was decreased or absent wit hin the stimulus period relative to their presence in the

PAGE 32

20 control interval. A two-tailed binomial test of statistical significance was performed using equal time segments of sp ike train data before and after the first central chemoreceptor trial as pairs of samples. Neuronal MWROs were considered to be significantly enh anced or evoked following stimulus presentation if the sign test rejected the null hypothesis that t he stimulus did not enhance or evoke the presence of the slow wa ve oscillations (RVRC: p < 0.0005, CVRC: p < 0.0001). Cross-correlation analysis Cross-correlation histograms (CCHs) were calculated for all pairs of simultaneously monitored neurons and evalua ted for evidence of features that departed significantly from background firi ng rates in shift-predictor control correlograms calculated for each pair (Nuding et al. 2009a). Primary peaks and troughs 3 standard deviations from the mean control histograms were considered significant. Corresponding detect ability indices (equal to the ratio of the maximum amplitude of departure from background divided by the standard deviation of the correlogram noise) were calculated (Aertsen and Gerstein 1985; Melssen and Epping 1987). Correlogram f eatures permit model-based inferences about several simple classes of functi onal connectivity between the neurons (Aertsen and Gerstein 1985; Kirkwood 1979; Moore et al. 1970). Central peaks and troughs are indicative of a common s hared influence of lik e or opposite sign, respectively. A peak offset in time relati ve to the trigger event origin suggests

PAGE 33

21 excitation of the target neuron or a common (unobser ved) shared input that influences both cells with different time delays, while an offset trough suggests an inhibitory process. Autocorrelation histograms calculated for each neuron aided in the interpretation of the CCHs (Moor e et al. 1970; Perkel et al. 1967a,b).

PAGE 34

22 RESULTS The results presented herein on RVRC neuron interactions and evidence for CVRC-to-RVRC neuron connect ivity are part of a lar ger study of functional connectivity among RVRC and CVRC neurons. Data were acquired from 18 recording sessions in 14 decerebrate, vagotomized, neuromuscularly blocked, and ventilated cats. The spike trains of 784 neurons were monitored extracellularly using multi-electrode arra ys. Figure 1A illustrates the location of rostral fluorescent dye-labeled el ectrode tracks relative to surrounding anatomical structures; a si ngle section detailing segmen ts of three electrode tracks is shown as an inset outlined in r ed. Stereotaxic coordi nates of recording sites were mapped into a brain stem atlas; the resulting graphical summary of the rostral and caudal regions surveyed is s hown in Fig. 1B. Color-coded spheres indicate sites monitored with the rostral (green) or caudal (pink) arrays. Neurons recorded at identical coordi nates are depicted as vertic ally displaced spheres.

PAGE 35

23 FIG. 1. Recording sites. A : Caudal view (4.88 mm rostra l to the obex) of rostral fluorescent dye-labeled electrode tracks co nstructed from a stack of six alternate 40 m sections; inset outlined in red shows detail of fluorescent electrode tracks from a single section. B : Sagittal view of recording sites, plotted in coordinate space, for all recorded neurons (n = 294 rostral/green; n = 490 caudal/pink) made from two mult i-electrode arrays. C : Recorded neurons color-coordinated according to significant modulation of fi ring rate discharge pattern. Abbreviations: 5ST, spinal trigeminal trac t; 7M, medial division of facial nucleus; 7L, lateral division of facial nucleus; FTG, gigant ocellular tegmental field; FTM, magnocellular tegmental field; P, pyramidal tract; PGCL, lateral paragigantocellular reticular nucleus; PH, nucleus praepositus hypoglossi; PPR, postpyramidal nucleus of t he raph; RTN, retrotrapezoid nucleus; VIN, inferior vestibular nucleus; VMN, m edial vestibular nucleus.

PAGE 36

24 We sampled extensive portions of the rostral medulla including regions of the retrotrapezoid nucleus, the par afacial respiratory group, the paragigantocellular nucleus, and the su rrounding lateral tegmental field. Recording sites for RVRC neurons (n = 294) ranged from 5.0 mm to 8.1 mm rostral to the obex, 1.4 to 5. 9 mm lateral to the midli ne, and 3.3 to 7.8 mm below the dorsal surface of t he medulla. CVRC neurons (n = 490) were monitored within a region extending from 1.5 mm caudal to 5.1 mm rostral to the obex, 3.3 mm to 4.6 mm lateral to t he midline, and 2.5 mm to 6.2 mm below the dorsal surface of the medulla. The spike trains of 75 single neurons were simultaneously recorded in a single anima l. Twelve neurons were recorded in regions of array overlap; these cells were classified as CVRC. Discharge patterns of neurons Overall, 214 (73%) of the RVRC and 398 (81%) of the CVRC neurons were respiratory modulated, whil e 124 (42%) RVRC and 95 (19%) CVRC neurons were cardiac (pulse-pressure) mo dulated. Neurons were evaluated for significant respiratory and cardiac modul ation of their discharge patterns and classified as follows: i) respiratory only (123 RVRC, 322 CVRC neurons; Fig. 1C red spheres), ii) cardiac only (33 RVRC, 19 CVRC neurons; blue), iii) respiratory and cardiac (91 RVRC, 76 CVRC neurons; gr een), or iv) neither (47 RVRC, 73 CVRC neurons; yellow). Figure 2 shows ex amples of RVRC neuron respiratory cycle-triggered histograms (A) and t he numbers and proportions of both RVRC

PAGE 37

25 and CVRC neurons in each category of re spiratory modulation (B). Cardiac cycle-triggered histograms from three RVRC neurons are shown together with corresponding first-order autocorrelograms (Fig. 2C), which illustrate preferred interspike intervals. We note that approximately 20% of cardiac modulated neurons from each region fired with an interval of around 100 ms.

PAGE 38

26

PAGE 39

27FIG. 2. Respiratory and cardiac modulation. A : normalized RVRC neuron respiratory cycle-triggered histograms (rCTHs) grouped by the half of the respiratory phase or transition in which the neuron fires with peak average activity. Respiratory phases were defined by efferent phrenic nerve activity (blue trace).The number of respirator y cycles averaged, bin widths, and maximum firing rates, for each CTH are as follows ( top to bottom ). I-Dec neurons : 905 cycles, 35.0 ms, 65.2 spikes s1; 759 cycles, 35.0 ms, 39.5 spikes s-1; 759 cycles, 35.0 ms, 25.0 spikes s-1; 1299 cycles, 25.0 ms, 20.7 spikes s-1. I-Aug neurons : 759 cycles, 35.0 ms, 68.2 spikes s-1; 591 cycles, 30.7 ms, 28.0 spikes s-1; 295 cycles, 75.0 ms, 9.0 spikes s-1; 295 cycles, 75.0 ms, 10.9 spikes s-1. IE neurons : 202 cycles, 30.0 ms, 12.2 spikes s-1; 403 cycles, 80.0 ms, 20.8 spikes s1; 1060 cycles, 15.0 ms, 12.8 spikes s-1; 418 cycles, 70.0 ms, 3.4 spikes s-1. E-Dec neurons : 1060 cycles, 15.0 ms, 23.3 spikes s-1; 759 cycles, 35.0 ms, 11.4 spikes s-1; 418 cycles, 70.0 ms, 2.6 spikes s-1; 418 cycles, 70.0 ms, 0.9 spikes s-1. EAug neurons : 759 cycles, 35.0 ms, 57.4 spikes s-1; 177 cycles, 105.0 ms, 48.5 spikes s-1; 418 cycles, 70.0 ms, 4.4 spikes s-1; 591 cycles, 30.7 ms, 15.7 spikes s-1. EI neurons : 1060 cycles, 15.0 ms, 29.4 spikes s-1; 401 cycles, 60.0 ms, 20.7 spikes s-1; 401 cycles, 60.0 ms, 45.5 spikes s-1; 591 cycles, 30.7 ms, 5.6 spikes s-1. B : respiratory discharge patterns of all recorded RVRC ( left ) and CVRC ( right ) neurons. C : cardiac cycle-triggered histograms (cCTHs; left ) and first-order autocorrelation histograms ( right ) of representative cardiac -modulated RVRC neurons. The 2 value (measure of cardiac modulation) and bin widths for each cCTH are as follows ( top to bottom ): 0.11, 10.0 ms; 0.41, 10.0 ms, 0.19, 10.0 ms.

PAGE 40

28 Responses to central chemoreceptor stimulation Significant changes in phrenic nerve activity in response to selective stimulation of central chemoreceptors were identified in 8 recordings (7 animals). Neuronal firing rate data acquired during one set of trials together with integrated efferent phrenic activity and arterial bloo d pressure are shown in Fig. 3A. The respiratory pattern, identification num ber, response to central chemoreceptor perturbation, and maximum firing rate are shown for each neuron; color-coded spheres (Fig. 3B: green=RVRC, pink=CV RC) mark stereotaxic coordinates of recording sites. Vertical grey panels in 3A delineate 90-s response evaluation periods, including the 30-s stimulus injection. Methods used to identify and classify neuronal responses are illustrated in Fig. 3C. The peri-stimulus time (PSTH – top ; averaged from all 5 trials) and corresponding cumulative sum (CUSUM – middle ) histograms display significant firing rate increases (e.g., neuron 481) and decreases (e.g., neuron 429) in response to stimulation. The bottom graph displays mean firing rates per cycle for paired control (white panels) and stim ulus (grey panels) periods. The activity during responses (red) and preceding contro l periods (black) were assessed by a bootstrap statistical method to determi ne changes that reached significance. Table 1 is a summary of RVRC and CVRC neuron responses to central chemoreceptor stimulation.

PAGE 41

29

PAGE 42

30 FIG. 3. Central chemoreceptor stimulation. A : firing rate histograms for 56 of 75 simultaneously monitored RVRC and CVRC neuron spike trains during sequential stimulation of central chemoreceptors For each trace, the respiratory modulated pattern, cell identification num ber, primary response to central chemor eceptor stimulus, and maximum firing rate are shown. Vertical grey panels del ineate central chemoreceptor stimulus eval uation periods: 30-s stimulus injection plus a 60-s post-stimulus period. Response profiles of neurons outlined with red boxes are detailed in C The indicates the administration of Dextran to combat the declining arterial blood pressure. B : Color-coded spheres (green=RVRC, pink=CVRC) mark coordinates of recording site locations fo r single neurons illustrated in A C : peri-stimulus time histograms (PSTH) and corresponding cumulative sum histograms (CUSUM) depicting the increase ( left ) and decrease ( right ) responses of neurons 481 and 429, respectively. The PSTH pl ots the average firing rate of the cell 90s before and after stimulus onset (applied at time 0) over the five challenges shown in A The CUSUM reflects the data trends depicted in the PSTH. The bottom graph is a display of the firing rate per respiratory cycle fo r five paired control (white panels) and stimulus periods (grey panels) us ed to calculate statistics. See METHODS.

PAGE 43

31 Table 1. Primary responses of single neurons to sequential central chemoreceptor stimulation Location and numbers of neurons Response to Central Chemoreceptor Stimulation RVRC CVRC 25 101 10 5 52 42 3 6 54 78 Totals 144 232 376 neurons tested for response in 7 animals

PAGE 44

32 In 5 experiments, we identified the evocation (23 RVRC, 55 CVRC), enhancement (50 RVRC, 72 CVRC) or redu ction (36 RVRC, 45 CVRC) of Mayer wave-related oscillations (MWROs) in t he firing rates of neurons following central chemoreceptor stimulation. Heat maps in Fig. 4A (trial 1) and B (detailed from Fig. 3A, trial 2) illustrate intervals with significant spike train MWROs. Figure 4A shows the 90-s periods preceding and i mmediately following the onset of the stimulus trial used to evaluate changes in MWRO activity; examples are shown of evoked (e.g., neuron 446), enhanced (424 ), and reduced (401) MWROs. The heat map in Fig. 4B illustrates MWRO ac tivity in the same cells and over the same time period as the firing rate histograms shown in Fig. 4C. The process used to detect and depict MW ROs in spike trains is illustrated for RVRC neuron 426. The bandpass-filtered pl ot below this cell’s firing rate histogram clearly shows the presence of cyclic activity prior to and following the stimulus trial; these MW ROs are reflected in the corresponding heat map (top trace). The MWROs occurred at a visibl y slower frequency than the respiratory rhythm in this record and had distinct phase relationships with each other and with concurrent oscillations of systemic mean arterial blood pressure. Neuronal MWROs and blood pressure Mayer waves briefly dissipated following the trial shown in this figure but returned withi n the control period preceding the next stimulus challenge. We note that slow wave oscillati ons in the neuronal firing rates preceded the return of Mayer waves in the blood pressure.

PAGE 45

33

PAGE 46

34FIG. 4. Mayer wave-r elated oscillations. A : Evaluation of significant enhanced, evoked, or reduced Mayer-wave relat ed oscillations (MWROs) present in neuronal firing rates. Heat maps from example RVRC neurons illustrate 90s preceding and 90s immediately following the onset of firs t central chemoreceptor stimulus trial. B : Heat maps illustrating the delayed MWROs present in the neuronal firing rates from neurons in C following central chemoreceptor stimulation. C : Expanded section (from FIG. 3 A ) of firing rate histograms from 7 representative RVRC and 3 CVRC neurons wh ich exhibit MWROs in their firing rates following central chemoreceptor stimul ation (trial 2 grey panel); injection duration is denoted by the horizontal bar labeled 30 s. Respiratory-modulated discharge pattern, cell identification number, primary response to central chemoreceptor stimulation, and maximum firing rates are shown for each neuron. The 3 traces shown for neuron 426 illustrate the process of detecting MWROs. See METHODS and text for details.

PAGE 47

35 Responses to arterial baroreceptor stimulation Arterial baroreceptors were stimulat ed in a total of 9 recordings (7 animals). Firing rate histograms from neurons recorded during sequential stimulation of arterial baroreceptors ar e shown together with integrated efferent phrenic nerve activity and arterial blood pr essure in Fig. 5A (same recording session as Fig. 3). Vertical grey panels delineate periods of embolectomy catheter inflation (3 of 5 trials shown for greater detail). For all baroreceptor stimulus trials, a transient decline in the amplitude of the phrenic nerve signal was elicited; for this recording, the el evation in blood pressure evoked an abrupt decline of the phrenic nerve si gnal to apnea following each stimulus presentation. Upon deflation of the cathet er, the phrenic nerve signal returned to prestimulus levels. CUSUMs (Fig. 5B) calculated from representative RVRC and CVRC neurons depict the responses to barorec eptor activation. A summary of neuronal responses to arterial baroreceptor stimulation is organi zed in Table 2. We evaluated whether blood pressure changes evoked by chemoreceptor activation could have contributed to the co mplex temporal firing rate modulation observed with chemoreceptor perturbat ion by sequentially applying central chemoreceptor and arterial bar oreceptor stimulation protocols (5 recordings from 4 animals). For example, the response profile of RVRC neuron 401 consisted of a decrease to central chemoreceptor stim ulation (see Fig. 3A) and an increase to baroreceptor activation (see Fig. 5A). Th is result suggests that the primary response of cell 401 to central chemorec eptor activation was not a consequence of blood pressure changes resulting fr om the chemorecept or stimulus.

PAGE 48

36

PAGE 49

37FIG. 5. Baroreceptor stimulation. A : firing rate histograms for 34 of 75 simultaneously monitored RVRC and CVRC neuron spike trains during sequentia l stimulation of arterial baror eceptors (3 of 5 trials shown for greater detail). For each trace, the respiratory-m odulated pattern, cell identificati on number, primary response to arte rial baroreceptor stimulus, and peak firing rate are shown. Vertical grey panels delineate baroreceptor stimulus trials: 30-s embolectomy catheter inflation period. B : Cumulative sum histograms (CUS UM) from representative neurons ( outlined with grey boxes in 5A ) detail the varying responses of RVRC and CVRC neur ons to baroreceptor activation. See METHODS.

PAGE 50

38 Table 2. Primary responses of single neurons to sequential arterial baroreceptor stimulation Location and numbers of neurons Response to Baroreceptor Stimulation RVRC CVRC 19 26 1 3 44 83 0 2 86 147 Totals 150 261 411 neurons tested for response in 7 animals

PAGE 51

39 Overall, of 230 dually-test ed neurons (detailed below in Fig. 7), concurrent changes in blood pressure could have contributed to the observed chemoreceptor-evoked firing ra te changes in 28 primary and 3 secondary central responses, assuming "excitatory" or "inhi bitory" influences comparable to those observed with the separate tests. Responses to peripheral chemoreceptor stimulation Significant changes in phrenic nerve activity in response to selective stimulation of peripheral chemoreceptors were identified in 6 recordings (4 animals). Neuronal firing rate data from one set of trials t ogether with integrated efferent phrenic activity and arterial bloo d pressure are shown in Fig. 6A; colorcoded spheres (Fig. 6B) mark stereotaxic co ordinates of recording sites. Vertical grey panels in 6A delineate 60-s response evaluation periods, including the 30-s stimulus injection. The graphs in Fig. 6C display mean firing rates per cycle for paired control and stimulus periods; acti vity during responses and preceding control were assessed to determine change s that reached significance. Table 3 is a summary of neuronal responses to peripheral chemorecept or stimulation.

PAGE 52

40

PAGE 53

41FIG. 6. Peripheral chemoreceptor stimulation. A : firing rate histograms for 57 of 71 simultaneously monitored RVRC and CVRC neuron spike trains during sequential stimulation of peripheral chemoreceptors. For each trace, the respiratory modulated pattern, cell identific ation number, primary response to peripheral chemoreceptor st imulus, and maximum firing rate are shown. Vertical grey panels delineate the 60-s peripheral chemoreceptor stimulus ev aluation periods (30-s stimulus injection plus a 30-s post-stimulus period). B : Color-coded spheres (green=RVRC, pink=CVRC) mark coordinates of recording site locations for single neurons illustrated in A C : display of the firing rate per respiratory cycle for five paired control (white panels) and st imulus periods (grey panels) used to ca lculate statistics for responses of RVRC neurons 418 and 406 (increase and decre ase; outlined with red boxes in A ). See METHODS.

PAGE 54

42 Table 3. Primary responses of single neurons to sequential peripheral chemoreceptor stimulation Location and numbers of neurons Response to Peripheral Chemoreceptor Stimulation RVRC CVRC 7 63 2 14 14 35 2 5 38 67 Totals 63 184 247 neurons tested for response in 4 animals

PAGE 55

43

PAGE 56

44FIG. 7. Response profiles of neurons. A : RVRC ( top ) and CVRC ( bottom ) neuron response profile diagrams from recordings (arranged in columns) where co mbinations of central chemoreceptor (C ), arterial barorec eptor (B), and/or peripheral chemoreceptor (P ) stimulation were applied. Each set of boxes represents a single neuron and the boxes are arranged by respiratory discharge pattern. B : Isometric views of color-coded spheres indicating the initial responses (blue = increase, red = decrease, grey = no c hange) and stereotaxic coordinates of subs ets of neurons tested with stimulation of central chemoreceptor (167 RVRC, 261 CVRC), baroreceptor (106 RVRC, 174 CVRC ), and peripheral chemoreceptors (49 RVRC, 154 CVRC).

PAGE 57

45 Neuron response profiles mapped to recording site coordinates The response profile diagrams in Fig. 7A summarize the initial responses of 376 neurons to central chemoreceptor st imulation. Responses to perturbations of peripheral chemorecept ors and baroreceptors are also shown along with the cell’s respiratory-modula ted discharge pattern. Because of signal loss, some neurons could not be tested with all stimuli. The use of a rrays of microelectrodes, each with individual depth adj ustment, permitted the testing of many neurons at the same time under identical envir onmental conditions. The stereotaxic coordinates of the neuronal recording si tes were mapped (Fig. 7B); each cell is represented as a sphere with its initial response to the particular stimulus correspondingly colored. Table 4 summa rizes the primary responses of all neurons tested with a specific stimulus protocol; cells are arranged by their respective firing rate discharge patterns. Cross-correlation analysis Cross-correlogram features described herein were from 472 (4.1%) of the 11,374 pairs of neurons evaluated for short-timescale correlations. These features included either a significant pr imary peak or trough f eature or multiple periodic peaks and troughs that deviated sign ificantly from the shift-control mean. Overall, 174 of the rostra l neurons (59.5%) had short-time scale correlations with other RVRC neurons. Of these, 49 tr iggered cross-correlograms with RVRC

PAGE 58

46 target neurons, yielding 330 offset featur es indicative of paucisynaptic actions from a total of 2,884 rostral pairs ev aluated. Forty-nine of the CVRC neurons (10.0%) were triggers in 142 CVRC—RVRC correlograms from a total of 8,490 with offset features indicative of actions on the RVRC neurons.

PAGE 59

47 Table 4. Characterization of single neurons re corded during effective stimulus protocols. Stimuli: Central Chemoreceptor Baroreceptor Peripheral Chemoreceptor Modulation Region NT NT NT Respiratory Only Inspiratory RVRC 9 9 5 0 0 14 18 1 3 5 7 0 CVRC 641723 0 1050 53 2 50 17 22 1 Expiratory RVRC 12129 0 7 11 24 2 2 1 9 2 CVRC 201219 2 1120 31 2 12 15 22 1 Not Modulated RVRC 4 1116 0 2 3 14 1 3 4 7 1 CVRC 116 24 3 3 5 31 3 7 3 16 0 Cardiac Only RVRC 4 4 8 1 3 8 4 0 0 1 6 0 CVRC 3 3 2 0 0 1 7 0 0 1 0 0 Cardiac & Respiratory RVRC 6 1916 1 8 8 26 1 1 5 9 0 CVRC 8 1010 0 5 9 25 2 8 4 7 1

PAGE 60

48 Evidence for inputs shared by RVRC neurons A total of 137 (46.6% ) of the RVRC neurons we re elements of RVRC neuron pairs with correlation features indica tive of a shared input. These central features, including 161 peaks and 43 troughs, we re detected in 7.1% of the 2,884 pairs evaluated. The cross-correlation feature summary diagram in Fig. 8A details the respiratorymodulated discharge patterns and brainstem regions of the pairs with the indicated central f eatures. In this and subsequent summary diagrams, trigger neuron ca tegories are arranged along the left side of the diagram while target neurons are shown across the top. The connecting lines delineate the observed correlational link age for that neuronal pair type with small circles attached to the target cell represent ing the feature detected in at least one CCH. Circled numbers correspond to the representative CCHs shown in the figures. Central peaks and troughs were detect ed for pairs that shared the same respiratory-modulated pattern (e.g., Fig. 8A, CCH 1) and those that did not (e.g., Fig. 8A, CCH 2). Central features from 241 pairs of inspiratory (I) neurons included 13 peaks and 6 troughs. Among 583 expiratory (E) neuron pairs, 37 peaks and 10 troughs were identified. Cent ral features from 210 pairs of NRM cells included 15 central peaks and 2 central troughs, while RVRC pairs containing at least one NRM cell provi ded evidence for shared inputs with every category of RVRC neuron.

PAGE 61

49

PAGE 62

50FIG. 8. Intra-RVRC f unctional connectivity. A : cross-correlation feature summary diagram (CFSD) representing the cent ral peaks (unfilled circles) and troughs (half-filled circles) detected in cro ss-correlation histograms calculated among RVRC neurons. Cross-correlograms labeled with circled numbers have features corresponding to similarly labeled corre lational linkages represented in the CFSD. 1: peak, detectability index (DI) = 24.05, 39,692 trigger and 21,095 target spikes; 2: trough, DI = 9.09, 134, 779 trigger and 48,510 target spikes. B : CFSD illustrating the offset peaks (+) and tr oughs (-) detected in cross-correlation histograms calculated for RVRC trigger neur on-to-RVRC target neurons. 3: peak, DI = 15.26, 162,941 trigger and 36,042 target spikes; 4: peak, DI = 6.15, 91,386 trigger and 397,751 target spikes; 5: tr ough, DI = 7.63, 91, 386 trigger and 97,841 target spikes; 6: trough, DI = 4.49, 91,786 trigger and 12,201 target spikes; 7: trough, DI = 13.97, 162,941 tri gger and 28,460 target spikes.

PAGE 63

51 Central features detected in 635 pairs co mposed of neurons active in different respiratory phases (I vs. E) included 28 peaks and 10 troughs. Evidence for RVRC RVRC functional connectivity Offset features were identifi ed in RVRC neuron pair correlograms triggered by 49 (16.7%) of the RVRC neurons sa mpled (Fig. 8B). Primary features with positive time lags were obs erved in correlograms from 99 of these 2,884 pairs (3.4%; 49 peaks, 50 troughs ; Table 5). Correlograms of RVRC inspiratory neuron pairs included 7 pea ks and 4 troughs, while 10 peaks and 13 troughs were indicative of expiratory neuron pair interactions. NRM neuron pair correlograms included 5 offset peaks and 1 offset trough. For pairs composed of neurons most active in opposite respir atory phases, 6 peaks and 3 troughs with positive lags were identified in 366 CCHs calculated using I neurons trigger spikes and E neuron target events, while offset features from 269 pairs of E trigger-I target neuron pairs included 3 peaks and 3 troughs. Thirty-one (10.5%) RVRC neurons were involved in correlations characterized by multiple peaks and troughs.

PAGE 64

52 Table 5. RVRC-to-RVRC significant offset feature correlations detected in the analysis of 2,884 RVRC–RVRC neuron pairs. RVRC I-Dec I-Aug I IE E-Dec E-Aug E EI NRM P T P T P T P T P T P T P T P T P T R V R C I-Dec 5 3 1 12 1 94 96 14 25 188 124 28 16 225 I-Aug 1 131 4 22 160 79 18 10 137 I 1 1 2 3 11 16 11 2 37 IE 1 1 1 13 1 1 2 1 49 28 7 4 49 E-Dec 4 4 1 2 1 43 35 1 1 1 1 2 293 179 38 18 279 E-Aug 1 3 21 1 46 20 12 214 E 11 2 7 5 56 EI 1 15 NRM 1 2 1 1 1 66 1 1 5 1 210 Detected peaks and troughs simply interpre ted as evidence for a functional connection from one RVRC neuron to another. Correlated neuron pairs are organized so that offset correlogram features have positive time-lags. Shaded numbers indicate the total number of pairs composed of neurons with the discharge patterns indicated by the row and column labels. These numbers were used to calculate the percentages of neur ons correlated (e.g., of the 279 pairs composed of an E-Dec and an NRM neuron, an E-Dec NRM connection may be inferred for 3 pairs (1.1%; 1 peak and 2 troughs) and an NRM E-Dec

PAGE 65

53 connection for 1 pair (0.4%; 1 trough)). The shaded numbers were summed to calculate the total number of RVRC–RV RC pairs analyzed. Mean DI, half-width, and time-lag from origin (mean SD) for offset peaks: 7.6 7.3, 33.4 23.1 ms, 27.6 37.1 ms; offset troughs: 6.2 3.4, 50.2 35.6 ms, 36.5 40.0 ms.

PAGE 66

54 Evidence for CVRC RVRC functional connectivity Offset short-timescale features we re identified in CVRC—RVRC neuron pair correlograms triggered by 49 (10%) of the CVRC neurons sa mpled. Primary offset features simply interpreted as CVRC neurons exerting paucisynaptic actions on RVRC neurons were detected in 74 (0.9%) of CVRC—RVRC pairs (Fig. 9); features with positive time l ags included 29 peaks and 45 troughs (Table 6). Primary peaks (n = 4) and troughs (n = 4) were detected in CCHs of 1,232 CVRC—RVRC neuron pairs composed of inspiratory neurons; 3 peaks and 6 troughs were detected in CCHs of 973 expiratory neuron pairs. Correlogram features identified from 532 pairs com posed of two NRM cells included 3 peaks and 4 troughs. We detected 5 peaks and 5 troughs from 838 CCHs calculated from CVRC inspiratory trigger cells to ex piratory RVRC target neurons; 2 offset peaks and 8 offset troughs among 1,382 pai rs composed of a CVRC expiratory trigger and an RVRC inspiratory target neuron. Forty-six (9.4%) of the CVRC neurons were involved in correlations with 13.6% (n = 40) of RVRC neurons characterized by multiple peaks and troughs.

PAGE 67

55 Table 6. CVRC-to-RVRC significant offset feature correlations detected in the analysis of 8,490 CVRC–RVRC neuron pairs. Detected peaks and troughs simply interpre ted as evidence for a functional connection from CVRC-to-RVRC neurons. Correlated neuron pairs are organized so that offset correlogram features have positive time-lags. Shaded numbers indicate the total number of pairs composed of neurons with the discharge patterns indicated by the row and column labels. These numbers were used to calculate the percentages of neurons correla ted (e.g., of the 348 pairs composed of an E-Dec CRVRC and an E-Dec RVRC neuron, an offset connection may be inferred for 2 pairs (0.6%; 1 peak and 1 trough). The shaded numbers were summed to calculate the total number of CVRC-to-RVRC pairs analyzed. Mean DI, half-width, and time-lag fr om origin (mean SD) for offset peaks: 5.9 2.4, 52.1 58.0 ms, 57.8 63.7 ms; offset troughs: 5.9 5.4, 62.5 57.1 ms, 37.1 33.3 ms. RVRC I-Dec I-Aug I IE E-Dec E-Aug E EI NRM P T P T P T P T P T P T P T P T P T C V R C I-Dec 2 2 1 11 1 1 396 223 58 19 296 137 60 10 357 I-Aug 1 1 258 191 15 13 172 82 27 10 180 I 1 2 11 4 1 36 33 22 4 31 14 19 24 IE 2 1 2 1 61 45 4 3 50 25 7 2 49 E-Dec 1 2 1 1 11 14 1 2 5 368 300 42 41 348 98 43 6 405 E-Aug 2 2 1 2 5 285 193 33 17 213 101 33 10 256 E 1 1 94 42 25 12 73 34 30 4 36 EI 1 27 25 2 4 30 13 4 1 14 NRM 3 113 4 612 367 52 33 410 209 65 15 532

PAGE 68

56 Extended correlational linkages Our arrays permitted both the mappi ng of extended pair-wise correlational linkages among neurons monitored simu ltaneously at multiple sites and assessment of their responses to stimulat ion of multiple sensory modalities under the same state and history-dependent condit ions. In the illustrated correlation linkage maps (Fig. 10), each neuron is represented by a rectangle labeled with the cell’s respiratory modulat ion, identification number (white) and responses to various stimuli (blue = increase, red = dec rease, gray = no change, white = not tested). Line color indicates the primary correlogram feature for the pair (blue = peak, red = trough) and line width reflects the value of the detectability index. The map of linkages within the RVRC (Fig. 10A) depicts the offset correlogram features fr om a single recording session in which central chemoreceptors and arterial barorecept ors were stimulated. Correlograms provided evidence for 27 RVRC-RVRC neuron interactions (6 peaks and 21 troughs), including "nodes" with multip le divergent (cells 418 and 402) and convergent (427) functional connections. Some cross-correlograms with offset peaks and troughs represented on the map (y ellow numbered circles) are shown in Fig. 8B. For example, connection 7 repr esents an offset trough indicative of an inhibitory influence of neuron 402 on neur on 427. The former neuron exhibited a decreased firing rate with central chemor eceptor stimulation while the latter showed an initial increase, c onsistent with a disinhibitor y process. Table 7 shows

PAGE 69

57 both offset correlogram features and responses identified for all neuron pairs tested with central chemoreceptor and/or baroreceptor challenges. The second map (Fig. 10B) shows linkage evidence for actions of CVRC neurons upon RVRC cells together with re sponses to sequential stimulation of central chemoreceptors, arterial baror eceptors, and peripheral chemoreceptors; correspondingly numbered CCHs are shown in Fig. 9. The depicted offset correlogram features provided evi dence for several CVRC-to-RVRC neuron interactions (2 peaks and 9 troughs). The of fset peak in CCH 8 (illustrated in Fig. 9) provides evidence of an excitato ry connection from CVRC trigger neuron 805 to target RVRC neuron 406; both cells have similar respiratory profiles.

PAGE 70

58 Table 7. Responses and offset corre lation features for tested neuron pairs. Stimulation of: Central Chemoreceptors Baroreceptors Response Offset correlogram feature Offset correlogram feature RVRC Trigger RV RC Target peaks troughs peaks troughs 2 4 1 1 2 1 1 1 2 0 3 2 4 14 1 0 5 4 3 0 3 3 3 2 2 7 5 2 0 0 1 7 1 1 17 9 CVRC Trigger RVRC Target peaks troughs peaks troughs 0 1 0 0 2 1 0 3 2 0 3 2 0 2 0 1 7 6 2 3 2 6 2 2 1 4 0 1 0 0 4 7 4 1 5 13

PAGE 71

59

PAGE 72

60FIG. 9. CVRC-to-RVRC functional connectivity CFSD representing the offset peaks (+ ) and troughs (-) detected in crosscorrelation histograms calculated for pairs of CVRC trigger neuron-to-RVRC tar get neurons. Cross-co rrelograms labeled with circled numbers have features corresponding to similarly labeled correlational linkages represented in the CFSD. 8: peak, DI = 9.21, 72,867 trigger and 118,307 target spikes; 9: trough, DI = 8.24, 16,508 trigger and 36,032 target spikes; 10: peak, DI = 9.56, 40,638 trigger and 33 ,461 target spikes; 11: tro ugh, DI = 5.98, 114,866 trigger and 12,201 target spikes; 12: peak, DI = 6.82, 4,263 tri gger and 33,461 target spikes; 13: trough, DI = 6.39, 35,709 trigger and 375,817 target spikes; 14: trough, DI = 4.02, 16,508 trigger and 30,857 target spikes.

PAGE 73

61

PAGE 74

62FIG. 10. Extensive functional linkages. A : correlation linkage map shows primary offs et features and stre ngth of extended correlation linkages among simultaneously recorded RVRC neuron s (see Key). Numbers circled in yellow represent correspondingly numbered cross-correla tion histograms shown in Figure 8 B B : correlation linkage ma p from a multi-array recording illustrates the ext ended correlation linkages from CVRC-to-RVRC neur ons. Numbers circled in yellow represent correspondingly numbered cross-correla tion histograms shown in Figure 9.

PAGE 75

63 The offset troughs in CCHs 9 and 14 (Fig. 9) infer divergent functional inhibitory connections from an augm enting expiratory CVRC neuron 816 to both an augmenting inspiratory RVRC neuron 423 and the non -respiratory modulated RVRC neuron 424. Evidence for convergent i nhibitory influences was also found: the firing rate of RVRC neuron 402 decreas ed following spikes in CVRC cells 832 (circle/CCH 13) and 881. Correlational linkages among cardiacand cardiac/respiratory-modulated neurons We also identified correlational linkages between neurons with average firing rate modulations time-locked to the respiratory or cardiac cycle and cells dually modulated with both rhyt hms. Features indicative of functional shorttimescale interactions were detect ed between RVRC cardiac modulated and RVRC dually modulated neurons (Fig. 11A): 22 peaks (4 offset, 18 central) and 11 troughs (8 offset, 3 central). In addi tion, we noted functional connections between RVRC respiratory modula ted and RVRC dually modulated cardiac/respiratory neurons (Fig. 11B): 29 peaks (5 offset, 24 central) and 22 troughs (14 offset, 8 central).

PAGE 76

64

PAGE 77

65FIG. 11. Correlations among cardio/respiratory neurons. A : cardiac cycle-triggered histograms (cCTHs shown in 10 ms binwidth; top ) and normalized respiratory cycle -triggered histograms (rCTHs; middle ) for trigger neuron 408 ( left ) and target neuron 427 ( right ). Neuron 408: cardiac-modulated only, 2 = 0.05; neuron 427: cardia c/respiratory-modulated, 2 = 0.08, 80.0 ms rCTH binwidth, 403 respiratory cycles averaged. bottom: Cross correlation histogram (CCH) calculated from a cardiac-modulated RVRC neuron and a cardiac/respiratory-mo dulated RVRC neuron exhibiting an offset trough with positive timelag: DI = 11.71, 10.5 ms binwidth 71,132 trigger spikes, and 28,460 target spikes. B : neuron 462: respiratorymodulated only, 70.0 ms rCTH binwidth, 341 cycl es; neuron 493: cardiac/respiratory-modulated, 2 = 0.47, 70.0 ms rCTH binwidth, 418 respiratory cycles aver aged; neuron 409: respiratory-modulated onl y, 70.0 ms rCTH binwidth, 418 respiratory cycles averaged. bottom: CCH calculated from a respir atory-modulated RVRC neuron and a cardiac/respiratory-modulated RVRC neuron exhibiting an offset peak with positive timelag ( left ): DI = 6.93, 10.5 ms binwidth, 6,182 trigger spikes, and 3,182 target spikes; CCH calculated from a cardiac/ respiratory-modulated RVRC neuron and a respiratory-modulated RVRC neuron exhibiting an offset peak with positive timelag ( right ): DI = 6.57, 15.5 ms binwidth, 3,182 trigger spikes, and 21,095 target spikes.

PAGE 78

66 DISCUSSION This study characterized the rostral ventral medullary region of the cat brainstem by monitoring RVRC neurons and evaluating their respiratorymodulated discharge patterns and res ponses during chemoreceptor and baroreceptor stimulation. We used extrac ellular recording me thods to monitor RVRC neurons together with CVRC neurons in the decerebrate, vagotomized cat. Cross-correlation methods were used to infer functional connectivity among neurons. This study provides the first evidence that the re spiratory-modulated discharge patterns of RVRC neurons are shaped by both respiratoryand nonrespiratory-modulated neurons of t he CVRC and by diverse functional connections within the RVRC neuron populat ion. The results also support the hypotheses that local circuit interactions i) contribute to the cardiac modulation of RVRC neurons and ii) mediate modulatory influences of central and peripheral chemoreceptors and arterial baroreceptor s. In addition, we demonstrated that MWROs in the firing rates of RVRC and CVRC neurons can be modulated by central chemoreceptor stimulation. Within and between the RVRC and CVRC regions, we observed neuron pairs that exhibited central features in their cross-correlograms which implied the influence of an unobserved shared input, as well as offset peaks and troughs suggestive of paucisynaptic influences of one neuron upon another. Simple

PAGE 79

67 interpretations of the features detec ted in the correlograms suggest both excitatory and inhibitory interacti ons among RVRC neurons and from CVRC-toRVRC neurons appropriate for modulation of respiratory pattern and drive. The data suggest multiple pathways for func tional network interactions among RVRC and from CVRC-to-RVRC neurons includi ng the promotion of excitation and inhibition as well as connections suggestive of “limiting” the extent of responses. These interactions portray a variety of distinct functional relationships among neurons responsive to chemosensory per turbation and support the hypothesis that these rostral area neurons are part of a widely-dist ributed medullary network of neurons capable of modulating respir atory motor output. Ball-and-stick models were gener ated from inferences based on correlational data. Models in Fig. 12A support multiple interactions among RVRC neurons with a variety of respiratory-m odulated discharge patterns. For example, respiratory-modulated I-Dec activity coul d be at least partially derived from functional influences coming from other RVRC decrementing I neurons. Models shown in Fig. 12B depict interacti ons detected from CVRC neurons with functional connections indicative of paucisynaptic influences on RVRC neuron populations. These show that an additional source of RVRC I-Dec activity could be established functional inputs from CVRC I-Dec neurons.

PAGE 80

68

PAGE 81

69 FIG. 12. Inferred intra-RVRC ( A ) and CVRC-to-RVRC interactions ( B ) proposed to contribute to the respiratory modul ated discharge patterns of RVRC neurons. Ball-and-stick models illustrate network in teractions inferred from correlogram features. RVRC and CVRC neuron populations are represented by large spheres labeled with a respiratory discharge patte rn. Inferred excitato ry and inhibitory influences are indicated by blue and red arrows, respectively. The number and percentage of each type of neuronal pai r that exhibited evidence for the suggested connection is shown aside the large spheres. RVRC triggers represented as green spheres in A Purple spheres in B represent the RVRC target neurons.

PAGE 82

70 The relative percentages of respir atory-modulated RVRC neurons and their respective respiratory discharge pr ofiles were similar to those found for CVRC neurons. This observation supports the hypothesis that RVRC neurons, as a rostral extension of the CVRC, ar e elements of distributed circuit-level mechanisms for modulating the respiratory motor pattern. Other functional roles include the possibility that subsets of these rostral-region neurons may regulate both inspiratory and expiratory outputs, which may explain the variety of respiratory-modulated discharge patte rns exhibited by RVRC neurons. Relationship to prior work and functional implications The present results extend the work of Nattie et al. (1993), who found both respiratory (37%) and non-respiratory (63%) modulated neurons in the RTN. They reported that 47% of respiratory and 38% of non-respiratory modulated RTN neurons responded to an increased pCO2 with a significant increase in firing rate. We observed that 73% of the RV RC neurons in a region encompassing but extending beyond the RTN were respirat ory modulated. We also found that a larger percentage of the respirator y-modulated RVRC neurons tested (23%) had significantly increased firing rates with c entral chemoreceptor st imulation relative to 16% of the non-respiratory modulat ed neurons sampled. In addition, we identified cardiacand dually-modul ated RVRC neurons which responded to stimulation of peripheral as well as cent ral chemoreceptors. Overall, 42% of the RVRC neurons recorded were cardiac modul ated. Of the 35 RVRC neurons that

PAGE 83

71 increased firing rates in response to c entral chemoreceptor stimulation, 29% were cardiac modulated. The present results also support and extend a model of interactions between RTN and VRC neurons developed by Guyenet and colleagues, which proposed that VRC neurons shape the resp iratory-modulated discharge pattern of RTN neurons. Briefly, this mode l suggests that various VRC neuron populations contribute similarly to shaping the firing patterns of neurons located in more rostral regions of the respir atory column through inhibitory inputs (Guyenet et al. 2005a; Mulkey et al. 2004; Takakura et al. 2006). Our model incorporates cross-correlation evidenc e including excitatory and inhibitory interactions which contribute to the s haping of the respiratory modulated patterns of RVRC neurons. Our observations on Mayer wave related oscillations in RVRC neuron firing rates and its enhancement by centra l chemoreceptor stimulation extends the seminal observations of the Chernia ck laboratory who found that hypercapnia and central chemoreceptor stimulation enhances or evokes Mayer waves in systemic arterial blood pressure (Cherni ack et al. 1969). Recently, Morris et al. (2007) reported that both pontine and raph neurons exhibit MWROs phaselocked with integrated phrenic activity in a 1:1 or N:1 ratio, with the 1:1 ratio appearing following "on-line" vagotomy. In the present study, neurons were not recorded until several hours post vagotomy. The absence of a 1:1 ratio phaselocking of respiratory and MWRO dischar ge patterns in different simultaneously recorded neurons suggests the possibility that the faster respiratory rate

PAGE 84

72 reemerges with time after v agotomy. While this spec ulation remains an area for further research, the present results ar e consistent with t he hypothesis that RVRC neurons are elements of a distribut ed network responsible for generation of MWROs and coordination of respiratory and vasomo tor rhythms (Montano et al. 1996). Advantages and limitations of the experimental approach The use of multi-electrode arrays a llowed the simultaneous extracellular sampling of many spike trains per reco rding session and enabled the detection of multiple correlational linkages am ong the neurons. Moreover, concurrent recording of phrenic, RVRC and CVRC neural activity, and blood pressure assured that all parameters were m easured under identical history-dependent conditions and therefore were not c onfounded by possible state-dependent changes in the animal. Cross-correlational analysis was us ed to infer functional connections between monitored neurons. Cross-corre lation has been established as a powerful analytical tool for detecting functional connectivity; however, this method does not reveal the precise in terconnections of the underlying circuit. The purpose of this approach is to offer a set of plausible connections to produce “the simplest neuronal model that rep licates the experimentally observed features of measurements m ade” (Aertsen et al. 1989). Pr evious studies from our laboratory have shown that the cross-correlation technique is sufficiently

PAGE 85

73 sensitive to detect evidence of excita tory and inhibitory connections among a variety of respiratory and non-respirator y neurons (e.g., Dick et al. 2008; Nuding et al. 2009b). Confirmation of electrode placement into the rostral/RTN region of the VRC poses a problem due to the small si ze, dense nature, and location of this region near the ventral surfac e of the medulla, all of wh ich make it difficult to record well-isolated cells (Cream et al 2002). We marked electrode tracks with a fluorescent dye (di-I) and used standar d histological methods to confirm placement of the electrodes (DiCarlo et al. 1996). Each animal was ventilated with room air during stimulus protocols to avoid the possibility of paradox ical stimulation of chemor eceptors by exposure to 100% O2 (Dean et al. 2004). Following t he decerebration, isoflurane was removed from the inhaled gas system and the compressed air flow rate was increased to aid elimination as quickly as po ssible, thereby avoidi ng the effects of anesthetics during the stim ulation protocol (Sasano et al. 2001). Sufficient CO2 was added to maintain the CO2 level at 30 mmHg to prevent hyperventilation during this period (Vesely et al. 2003). Central chemoreceptor activation may elicit a reflex increase in blood pressure in addition to changes in the respiratory motor pattern. In some experiments we assessed the potential in fluence of the chemoreceptor-evoked baroreceptor stimulation by sequential stimulation of t he baroreceptors, although this approach may not replicate all the e ffects of concurrent activation of both systems. Opposite responses of the sa me neuron to central chemoreceptor and

PAGE 86

74 baroreceptor activation suggest that the responses evoked during central chemoreceptor stimulation were not ex clusively due to baroreflex activation (Bishop 1974; Heymans and Bouckaert 1930). Future directions Abnormalities in the configurati on and modulation of the brainstem respiratory network have been implicated in numerous disorders of breathing that are a cause or consequence of hypovent ilation, includi ng sleep-disordered breathing, sleep apnea, various forms of neurogenic hypertension, stroke, heart failure, autonomic dysfunction, Sudden Infant Death Syndrome, and the mechanisms of auto resuscitation following severe hypoxia (Dubreuil et al. 2008; Duffin 2004; Guyenet 2006; Kinney 2009). The respiratory modulation of sympathetic outflow pl ays an important role in cardiovascular control. Cardiorespirator y coupling is vital to the coordination of components of cardiorespiratory function in cluding heart rate, ventricular stroke volume, contractility, vascular tone, t he effect of mechanical input from respiratory-related thoracic movem ents on venous blood return, and overall cardiorespiratory performance (Baint on et al. 1985; Barman and Gebber 1976; Feldman and Ellenberger 1988). The juxtaposition of RVRC respiratory, cardiac, and cardiac/respiratory modulated neurons suggests an additional functional role of these neurons in cardiorespiratory in tegration and modulatio n of both rhythms.

PAGE 87

75 It has been established that neurons in the caudal-most end of the caudal ventrolateral medulla (cCVLM; corres ponding to the caudal pressor area (CPA)) and neurons in the rostral ventrola teral medulla (RVLM) project to intermediolateral cell column (IML) neurons of the spinal cord (Iigaya et al. 2007). These IML neurons play an essential role in the regulation of sym pathetic activity and the maintenance of vasomotor tone (I igaya et al. 2007, Sun and Panneton 2002). Subsets of CVRC neurons recorded in the present study most likely correspond to CPA neurons since these neurons exhibit cardiac modulation and decrease their firing rate in response to an increase in arterial blood pressure and baroreceptor activation. Confirmati on of this possibility was beyond the scope of this study and remains an important goal for the future. Although previous investigations have placed the kernel of the respiratory rhythm generator within the region of the pre-Btzinger complex (Smith et al. 1991), available data suggest that neurons ro stral to the pre-Btzinger complex may also be involved in generat ing the respiratory rhythm in vitro (Ballanyi et al. 1999). There is evidence for endogenously rh ythmic, pre-inspiratory neurons with pacemaker properties that may contribute to rhythm generation located more rostral to the pre-Btzinger complex wi thin the medulla (Ballantyne and Scheid 2000; Del Negro et al. 2005; Mellen et al. 2003; Onimaru and Homma 2003). Existing models for rhythmogenesis, whether they involve pacemaker neurons or emergent network interactions, require a tonic excitato ry drive for the maintenance and regulation of oscillator y activity which may be provided by neural inputs from neighboring rostral areas including the reticular formation and

PAGE 88

76 lateral tegmental field (Funk et al. 1993) Anatomical connectivity and synaptic interactions among these neurons have been inferred (Ballanyi et al. 1999; Mellen and Feldman 2001), but the functi onal significance of their underlying actions remains unknown (Mellen et al. 2003). This study is part of a larger effort to elucidate the architecture of the RVRC -CVRC network and circuit mec hanisms through which this region influences breathing and cardiorespirat ory coordination. Pontine-ventral respiratory column connectivity is im portant for the regul ation and maintenance of the normal respiratory rhythm (Di ck et al. 2008). Recent studies have used transections through the pontomedullary junc tion and rostral-to-caudal sectioning of the neuraxis to investi gate the origin of respirat ory rhythmogenesis (Abdala et al. 2009a,b; Baekey et al. 2008; Smith et al. 2007). A major insight gained from these studies is the hypothesis that ther e exists a rostral-to-caudal stacking of respiratory network “buildi ng blocks” which allow the network to be re-organized upon sequential sectioning (Smith et al. 2009). Sectioning studies that disrupt signaling between the pons and medulla to i dentify functions of the pons in the control of breathing (e.g., Baekey et al. 2008) may also disrupt connections between and among RVRC and the CVRC neur ons. Thus, future goals include extending the present analyses to ident ify functional connections from RVRC neurons to the CVRC, both directly and i ndirectly through recently identified routes in parallel raph-dor solateral pontine circuits (Nuding et al. 2009a). Circuit maps such as those generated in the pres ent study provide a framework for the design and interpretation of perturbative studies on the generation, modulation,

PAGE 89

77 and reconfiguration of the re spiratory network, improving our ability to distinguish local circuit disruptions from loss of signals from more remote network nodes.

PAGE 90

78 CONCLUSIONS RVRC neurons compose a heterogeneous population of cells, some of which respond with a change in firing rate, to the stimulation of the central and peripheral chemoreceptors and arterial baroreceptors. This study characterized the less-explored rostral ventral medulla ry region of the cat brainstem by monitoring RVRC neurons and evaluatin g their respiratoryand cardiacmodulated discharge patterns com pared to CVRC neurons. We used extracellular recording methods to monitor RVRC neurons together with CVRC neurons in the decerebrate, vagotomized cat. Cross-correlation methods were used to infer functional connectivity among monitored neurons. The relative numbers of respirator y-modulated RVRC neurons and their respective respiratory di scharge profiles were simila r to those neurons of the CVRC. This observation supports the hypothesis that RVRC neurons, as a rostral extension of the CVRC, are elements of distributed circuit-level mechanisms for modulating the respirator y motor pattern. Other functional roles include the possibility that subsets of these rostral-region neurons regulate both inspiratory and expiratory outputs, which may explain the variety of respiratorymodulated discharge patterns ex hibited by RVRC neurons.

PAGE 91

79 Over the course of this study, subsets of RVRC and CVRC neurons were identified as exhibiting slow-rhythm MWRO s in their firing rate histograms which were evoked, enhanced or reduced by cent ral chemoreceptor st imulation. This observation extends the MWRO and resp iratory rhythm data involving pontine and raph neurons previously reported in Mo rris et al. (2007) to include neurons in the rostral and caudal parts of the VRC. Pairs of neurons within the RVRC and t hose composed of cells from both the CVRC and RVRC exhibited central f eatures in their cross-correlograms indicative of shared inputs, as well as offset peaks and troughs suggestive of paucisynaptic influences of one neuron upon another within the RVRC and from caudal to rostral circuit elements. The in teractions inferred from the correlogram features represent a variety of distin ct functional relationships among neurons responsive to chemosensory perturbation an d also support the hypothesis that these rostral area neurons are part of a widely-distributed medullary network of neurons capable of modulating respiratory motor output.

PAGE 92

80 REFERENCES 1. Abdala APL, Rybak IA, Smith JC, Paton JFR Abdominal expiratory activity in the rat brainstem-spinal cord in situ: patterns, origins and implications for respir atory rhythm generation. The Journal of Physiology 587: 3539-3559, 2009a. 2. Abdala APL, Rybak IA, Smith JC Zoccal DB, Machado BH, St-John WM, Paton JFR Multiple pontomedullary mechanisms of respiratory rhythmogenesis. Respiratory Physiology & Neurobiology In Press, Corrected Proof: 2009b. 3. Aertsen AM, Gerstein GL Evaluation of neuronal connectivity: Sensitivity of cross-correlation. Brain Research 340: 341-354, 1985. 4. Aertsen AM, Gerstein GL, Habib MK, Palm G Dynamics of neuronal firing correlation: Modulation of "effective connectivity". Journal of Neurophysiology 61: 900-917, 1989. 5. Alheid GF, Gray PA, Jiang MC, Feldman JL, McCrimmon DR Parvalbumin in respiratory neurons of the ventrolateral medulla of the adult rat. Journal of Neurocytology 31: 693-717, 2002. 6. Arita H, Kogo N, Ichikawa K Locations of medullary neurons with nonphasic discharges excited by stimul ation of central and/or peripheral chemoreceptors and by activation of nociceptors in cat. Brain Research 442 (1): 1-10, 1988. 7. Baekey DM, Dick TE, Paton JFR Pontomedullary transection attenuates central respiratory modul ation of sympathetic disc harge, heart rate and the baroreceptor reflex in the in situ rat preparation. Experimental Physiology 93: 803-816, 2008.

PAGE 93

81 8. Bainton CR, Richter DW, Selle r H, Ballantyne D, Klein JP Respiratory modulation of sympathetic activity. Journal of the Autonomic Nervous System 12: 77-90, 1985. 9. Ballantyne D, Scheid P Mammalian brainstem chemosensitive neurons: linking them to respiration in vitro. Journal of Physiology 525.3: 567-577, 2000. 10. Ballanyi K, Onimaru H, Homma I Respiratory network function in the isolated brainstem-spinal cord of newborn rats. Progress in Neurobiology 59: 583-634, 1999. 11. Barman SM, Gebber GL Axonal projection patterns of ventrolateral medullospinal sympat hoexcitatory neurons. Journal of Neurophysiology 53: 1551-1566, 1985. 12. Barman SM, Gebber GL Basis for synchronization of sympathetic and phrenic nerve discharges. American Journal of Physiology: Regulatory, Integrative and Comp arative Physiology 231: 1601-1607, 1976. 13. Berman AL The brain stem of the cat: A cytoarchitectonic atlas with stereotaxic coordinates Madison, WI: University of Wisconsin Press, 1968. 14. Bianchi AL, Denavit-Saubie M, Champagnat J Central control of breathing in mammals: Neuronal ci rcuitry, membrane properties, and neurotransmitters. Physiological Reviews 75: 1-45, 1995. 15. Bishop B Carotid baroreceptor modulat ion of diaphragm and abdominal muscle activity in the cat. Journal of Applied Physiology 36: 12-19, 1974. 16. Brown DL, Guyenet PG Cardiovascular neurons of brain stem with projections to spinal cord. American Journal of Physiology: Regulatory, Integrative and Comp arative Physiology 247: R1009-R1016, 1984. 17. Calaresu FR Medullary basal sympathetic tone. Annual Review of Physiology 50: 511-524, 1988.

PAGE 94

82 18. Cherniack NS, Edelman NH, Fishman AP Pattern of discharge of respiratory neurons during syst emic vasomotor waves. American Journal of Physiology 217: 1375-1383, 1969. 19. Cohen MI Discharge patterns of brain-st em respiratory neurons in relation to carbon dioxide tension. Journal of Neurophysiology 31: 142165, 1968. 20. Connelly CA, Ellenberger HH, Feldman JL Respiratory activity in retrotrapezoid nucleus in cat. American Journal of Physiology Lung Cellular & Molecular Physiology 258: L33-L44, 1990. 21. Cream C, Li A, Nattie E The retrotrapezoid nucleus (RTN): local cytoarchitecture and afferent connections. Respiratory Physiology & Neurobiology 130: 121-137, 2002. 22. Dampney RA Functional organization of c entral pathways regulating the cardiovascular system. Physiological Reviews 74: 323-364, 1994. 23. Davey NJ, Ellaway PH, Stein RB Statistical limits for detecting change in the cumulative sum derivative of the peristimulus time histogram. Journal of Neuroscience Methods 17: 153-166, 1986. 24. Dean JB, Mulkey DK, Henderson RA, Potter SJ, Putnam RW Hyperoxia, reactive oxygen specie s, and hyperventilation: oxygen sensitivity of br ain stem neurons. Journal of Applied Physiology 96: 784791, 2004. 25. Del Negro CA, Morgado-Valle C, Hayes JA, Mackay DD, Pace RW, Crowder EA, Feldman JL Sodium and Calcium Current-Mediated Pacemaker Neurons and Respir atory Rhythm Generation. Journal of Neuroscience 25: 446-453, 2005. 26. DiCarlo JJ, Lane JW, Hsiao SS, Johnson KO Marking microelectrode penetrations with fluorescent dyes. Journal of Neuroscience Methods 64: 75-81, 1996.

PAGE 95

83 27. Dick TE, Morris KF Quantitative analysis of ca rdiovascular modulation in respiratory neural activity. Journal of Physiology 556.3: 959-970, 2004. 28. Dick TE, Shannon R, Lindsey BG, N uding SC, Segers LS, Baekey DM, Morris KF Pontine respiratory-modulated activity before and after vagotomy in decerebrate cats. Journal of Physiology 586: 4265–4282, 2008. 29. Dubreuil V, Ramanantsoa N, Troche t D, Vaubourg V, Amiel J, Gallego J, Brunet J-F, Goridis C A human mutation in Phox2b causes lack of CO2 chemosensitivity, fatal central apnea, and specific loss of parafacial neurons. Proceedings of the National Academy of Sciences 105: 10671072, 2008. 30. Duffin J Functional organization of respir atory neurons: a brief review of current questions and speculations. Experimental Physiology 89.5: 517529, 2004. 31. Ellaway PH Cumulative sum technique and its application to the analysis of peristimulus time histograms. Electroencephalography and Clinical Neurophysiology 45: 302-304, 1978. 32. Feldman JL, Del Negro CA Looking for inspiration: new perspectives on respiratory rhythm. Nat Rev Neurosci 7: 232-241, 2006. 33. Feldman JL, Ellenberger HH Central coordination of respiratory and cardiovascular control in mammals. Annual Review of Physiology 50: 593606, 1988. 34. Feldman JL, McCrimmon DR Neural control of breathing. In: Fundamental Neuroscience edited by Squire LRElsevier Science, 1999, p. 1063-1090. 35. Feldman JL, Mitchell GS, Nattie EE Breathing: rhythmicity, plasticity, chemosensitivity. Annual Review of Neuroscience 26: 239-266, 2003.

PAGE 96

84 36. Funk GD, Smith JC, Feldman JL Generation and transmission of respiratory oscillations in medullary s lices: role of excitatory amino acids. Journal of Neurophysiology 70: 1497-1515, 1993. 37. Guyenet PG The 2008 Carl Ludwig Lecture: retrotrapezoid nucleus, CO2 homeostasis, and breat hing automaticity. J Appl Physiol 105: 404-416, 2008. 38. Guyenet PG The sympathetic control of blood pressure. Nature Review Neuroscience 7: 335-346, 2006. 39. Guyenet PG, Mulkey DK, Stornetta RL, Bayliss DA Regulation of ventral surface chemoreceptors by the central respiratory pattern generator. Journal of Neuroscience 25: 8938-8947, 2005a. 40. Guyenet PG, Stornetta RL, Bayliss DA, Mulkey DK Retrotrapezoid nucleus: a litmus test for the identif ication of central chemoreceptors. Experimental Physiology 90.3: 247-253, 2005b. 41. Heymans C, Bouckaert JJ Sinus caroticus and re spiratory reflexes. I. Cerebral blood flow and re spiration. Adrenaline apnoea. Journal of Physiology (London) 69: 255–266, 1930. 42. Iigaya K, Kumagai H, Onimaru H, Kawai A, Oshima N, Onami T, Takimoto C, Kamayachi T, Ha yashi K, Saruta T, Itoh H Novel axonal projection from the caudal end of t he ventrolateral medulla to the intermediolateral cell column. American Journal of Physiology: Regulatory, Integrative and Comp arative Physiology 292(2): R927-36, 2007. 43. Kinney HC Brainstem mechanisms underly ing the sudden infant death syndrome: Evidence from human pathologic studies. Developmental Psychobiology 51: 223-233, 2009. 44. Kirkwood PA On the use and interpretation of cross-correlation measurements in the mammali an central nervous system. Journal of Neuroscience Methods 1: 107-132, 1979.

PAGE 97

85 45. Kirsten EB, St. John WM A feline decerebrati on technique with low mortality and long-term homeostasis. Journal of Pharmacological Methods 1: 263-268, 1978. 46. Koshiya N, Guyenet PG Tonic sympathetic chemoreflex after blockade of respiratory rhythmogenesis in the rat. Journal of Physiology 491: 859869, 1996. 47. Kuwana S, Natsui T Effect of hypercapnic blood injection into the vertebral artery on the phreni c nerve activity in cats. Japanese Journal of Physiology 37: 155-159, 1987. 48. Li Z, Morris KF, Baekey DM, Shannon R, Lindsey BG Responses of simultaneously recorded respirator y-related medullary neurons to stimulation of multiple sensory modalities. Journal of Neurophysiology 82: 176-187, 1999. 49. Lindsey BG, Arata A, Morris KF, Hernandez YM, Shannon R Medullary raphe neurones and barorecept or modulation of the respiratory motor pattern in the cat. Journal of Physiology 512: 863-882, 1998. 50. Lindsey BG, Hernandez YM, Morri s KF, Shannon R, Gerstein GL Dynamic reconfiguration of brain st em neural assemblies: respiratory phase-dependent synchrony versus modulation of firing rates. Journal of Neurophysiology 67: 923-930, 1992. 51. Loeschcke HH Central chemosensitivity and the reaction theory. Journal of Physiology 332: 1-24, 1982. 52. McAllen RM Identification and properties of sub-retrofacial bulbospinal neurones: a descending cardiovascular pathway in the cat. Journal of the Autonomic Nervous System 17: 151-164, 1986a. 53. McAllen RM Location of neurones with card iovascular and respiratory function, at the ventral su rface of the cat's medulla. Neuroscience 18: 4349, 1986b.

PAGE 98

86 54. Mellen NM, Feldman JL Phasic vagal sensory feedback transforms respiratory neuron activity in vivo. Journal of Neuroscience 21: 7363-7371, 2001. 55. Mellen NM, Janczewski WA, Bocchiaro CM, Feldman JL Opioidinduced quantal slowing reveals dual networks for respiratory rhythm generation. Neuron 37: 821-826, 2003. 56. Melssen WJ, Epping WJ Detection and estimation of neural connectivity based on crosscorrelation analysis. Biological Cybernetics 57: 403-414, 1987. 57. Millhorn DE, Eldridge FL Role of the ventrolateral medulla in regulation of respiratory and cardiovascular systems. Journal of Applied Physiology 61: 1249-1263, 1986. 58. Montano N, Gnecchi-Ruscone T, Port a A, Lombardi F, Malliani A, Barman SM Presence of vasomotor and re spiratory rhythms in the discharge of single medullary neurons involved in the regulation of cardiovascular system. Journal of the Autonomic Nervous System 57(12):116-22, 1996. 59. Moore GP, Segundo JP, Perkel DH, Levitan H Statistical signs of synaptic interaction in neurons. Biophysical Journal 10: 876-899, 1970. 60. Morris KF, Arata A, Shannon R, Lindsey BG Inspiratory drive and phase duration during carotid chemorec eptor stimulation in the cat: Medullary neurone correlations. Journal of Physiology 491: 241-259, 1996. 61. Morris KF, Lindsey BG, Baekey DM Nuding SC, Segers LS, Shannon R, O'Connor RE, Dick TE Cardiorespiratory rhythms in spike trains of caudal raphe and pontine neurons in cats : Insights from computational models of acute vagotomy. 2007 Neuroscience Meeting Planner Program No. 230.11: Online, 2007.

PAGE 99

87 62. Mulkey D, Stornetta R, Weston M, Simmons J, Parker A, Bayliss D, Guyenet P Respiratory control by ventra l surface chemoreceptor neurons in rats. Nature Neuroscience 7: 1360-1369, 2004. 63. Nattie EE, Fung ML, Li A, St. John WM Responses of respiratory modulated and tonic units in the retrotrapezoid nucleus to CO2. Respiration Physiology 94: 35-50, 1993. 64. Nattie EE, Li A Retrotrapezoid nucleus (RTN) metabotropic glutamate receptors and long-term stimulation of ventilatory output. RTN glutamate receptors and breathi ng. 1995, p. 39-45. 65. Nattie EE, Li A, St. John WM Lesions in retrotrapezoid nucleus decrease ventilatory output in anesthetized or decerebrate cats. Journal of Applied Physiology 71: 1364-1375, 1991. 66. Netick A, Orem J Erroneous classification of neuronal activity by the respiratory modulation index. Neuroscience Letters 21: 301-306, 1981. 67. Nuding SC, Segers LS, Baekey DM, Dick TE, Solomon IC, Shannon R, Morris KF, Lindsey BG Pontine-Ventral Respirat ory Column Interactions Through Raphe Circuits Detected Us ing Multi-Array Spike Train Recordings. Journal of Neurophysiology 101: 2943-2960, 2009a. 68. Nuding SC, Segers LS, Shannon R, O'Connor R, Morris KF, Lindsey BG Central and peripheral chemoreceptor s evoke distinct responses in simultaneously recorded neurons of the raph-pontomedullary respiratory network. Philosophical Transactions of the Royal Society B: Biological Sciences 364: 2501-2516, 2009b. 69. O'Connor RE, Barnhill PR, Nuding SC, Morris KF, Lindsey BG Open source spike sorting software fo r large multi-el ectrode systems. Society for Neuroscience (Abstract) 31: Program No. 689.683, 2005. 70. Onimaru H, Homma I A novel functional neuron group for respiratory rhythm generation in the ventral medulla. Journal of Neuroscience 23: 1478-1486, 2003.

PAGE 100

88 71. Onimaru H, Homma I The parafacial respir atory group/prebotzinger complex is the primary site of respiratory rh ythm generation in the mammal. Journal of Applied Physiology 100: 20094-20098, 2006. 72. Orem J, Netick A Characteristics of midbr ain respiratory neurons in sleep and wakefulness in the cat. Brain Research 244: 231-241, 1982. 73. Orer HS, Gebber GL, Barman SM Medullary lateral tegmental field neurons influence the timing and pattern of phrenic nerve activity in cats. J Appl Physiol 101: 521-530, 2006. 74. Ott MM, Nuding SC, Morris KF, B.G. L Correlational linkage maps of rostral medullary neurons and the vent ral respiratory column suggest multiple network sites for motor pattern modulation. Neuroscience Meeting Planner Program No. 476.4: Online, 2008. 75. Ott MM, Nuding SC, Morris KF, B.G. L Functional interactions and responses of retrotrapezoid nucle us and ventral respiratory column neurons to central chemoreceptor and baroreceptor stimulation. Neuroscience Meeting Planner Program No. 297.9: Online, 2007. 76. Pearce RA, Stornetta RL, Guyenet PG Retrotrapezoid nucleus in the rat. Neuroscience Letters 101: 138-142, 1989. 77. Perkel DH, Gerstein GL, Moore GP Neuronal spike trains and stochastic point processes I: The single spike train. Biophysical Journal 7: 391-418, 1967a. 78. Perkel DH, Gerstein GL, Moore GP Neuronal spike trains and stochastic point processes II: Simultaneous spike trains. Biophysical Journal 7: 419440, 1967b. 79. Richter DW, and Spyer KM Cardiorespiratory control. In: Central Regulation of Aut onomic Functions edited by Lowey AD, and Spyer KM. New York: Oxford Universitry Press, 1990, p. 189-207.

PAGE 101

89 80. Rybak IA, Abdala APL, Markin SN, Paton JFR, Smith JC, Paul Cisek TD, John FK Spatial organization and st ate-dependent mechanisms for respiratory rhythm and pattern generation. In: Progress in Brain Research. Elsevier, 2007, p. 201-220. 81. Sasano H, Vesely A, Iscoe S, Tesler J, Fisher J A simple apparatus for accelerating recovery from inhaled volitile anesthetics. Anesthesia & Analgesia 93: 1188-1191, 2001. 82. Segers LS, Nuding SC, Dick TE, Sh annon R, Baekey DM, Solomon IC, Morris KF, Lindsey BG Functional connectivity in the pontomedullary respiratory network. J Neurophysiol 100: 1749-1769, 2008. 83. Smith JC, Abdala APL, Koizumi H, Rybak IA, Paton JFR Spatial and functional architecture of the mamma lian brain stem resp iratory network: a hierarchy of three oscillatory mechanisms. Journal of Neurophysiol 98: 3370-3387, 2007. 84. Smith JC, Abdala APL, Rybak IA, Paton JFR Structural and functional architecture of respiratory netwo rks in the mammalian brainstem. Philosophical Transactions of the Roya l Society B: Biological Sciences 364: 2577-2587, 2009. 85. Smith JC, Ellenberger HH, Balla nyi K, Richter DW, Feldman JL PreBotzinger complex: A brainstem r egion that may generate respiratory rhythm in mammals. Science 254: 726-729, 1991. 86. Smith JC, Morrison DE, Ellenberg er HH, Otto MR, Feldman JL Brainstem projections to the major respiratory neuron populations in the medulla of the cat. Journal of Comparative Neurology 281: 69-96, 1989. 87. St. John WM, Hwang Q, Nattie EE, Zhou D Functions of the retrofacial nucleus in chemosensitivity and ventilatory neurogenesis. Respiration Physiology 76(2): 159-171, 1989.

PAGE 102

90 88. Sun W, Panneton WM The caudal pressor area of the rat: its precise location and projections to the ventrolateral medulla. American Journal of Physiology: Regulatory, Integrat ive and Comparative Physiology 283(3): R768-78, 2002. 89. Takakura AC, Moreira TS, Colombar i E, West GH, Stornetta R, Guyenet PG Peripheral chemoreceptor inputs to retrotrapezoid nucleus (RTN) CO2-sensitive neurons in rats. Journal of Physiology 572.2: 503523, 2006. 90. Taylor EW, Jordan D, Coote JH Central control of the cardiovascular and respiratory systems and their in teractions in vertebrates. Physiological Reviews 79: 855-916, 1999. 91. Vesely A, Fisher JA, Sasano N, Prei ss D, Somogyi R, El-Beheiry H, Prabhu A, Sasano H Isocapnic hyperpnoea accelerates recovery from isoflurane anaesthesia. British Journal of Anaesthesia 91: 787-792, 2003.

PAGE 103

ABOUT THE AUTHOR Mackenzie M. Ott received a Bachelor of Arts in Interdisciplinary Natural Sciences Chemistry from the Honors College of the University of South Florida in 2000. She worked as a gas chromatogr aph / mass spectrometer operator and semi-volatile Organic Chemist until she ent ered the Ph.D. program in the College of Medicine at t he University of South Florida in 2004. During her time at the Coll ege of Medicine, Ms. Ott has actively participated in many projects and organizations includi ng consecutive terms as president and vice president of the US F Association of Medical Sciences Graduate Students. She has presented her research at mult iple conferences and has a first author manuscript submitted for publication in the Journal of Neurophysiology.