The long range goal of this research is to delineate the brainstem mechanisms by which cough is produced and regulated. The central hypothesis of this research is that the core respiratory network is controlled to produce cough by neuronal assemblies dynamically organized into regulatory elements required for the expression of airway defensive behaviors. These behavioral control assemblies (BCA) are composed of neurons that operate cooperatively in circuits and are transiently configured to process and store information related to the regulation of a given behavior. We propose that BCAs for cough are composed of neurons (raphe neurons and a novel medullary population) that are not currently considered to be part of the central respiratory pattern generator (CPG). BCAs exert a critical controlling function of the respiratory CPG, allowing it to a) reconfigure to generate widely variant motor patterns associated with different respiratory behaviors such as cough, and b) impart novel regulatory characteristics to the system such that each behavior can be controlled by afferent systems in a manner that is functionally appropriate. Our overall approach will be to expand and test the current model to account for the known regulatory features of the cough reflex. The rationale for the proposed research is that once the organization and regulation of the brainstem cough pattern generator are established, the mechanisms responsible for the production of pathological cough can be identified.
The Specific Aims of the project are: 1) Identify the functional relevance of raphe and caudal medial column neurons in the neurogenesis of cough, 2) Develop a predictive model that accounts for known regulatory features of cough as well as the proposed roles of raphe and caudal medial column neurons in the neurogenesis of this behavior, and 3) Identify the role of raphe and caudal medial column neurons in cough hyperresponsiveness induced by laryngeal inflammation. In the first aim, multiple raphe, caudal medial medullary, and ventral respiratory column (VRC) neurons will be recorded simultaneously during cough. Advanced spike train analysis and metrics of synchrony will be used to determine cooperative discharge patterns among these neurons specific to cough. Our preliminary data support an important role of these populations of neurons in assemblies that control coughing.
In aim 2, we will test a revised model of the cough network using network simulation tools that allow both discrete """"""""integrate and fire"""""""" (IF) populations and """"""""hybrid"""""""" populations that incorporate Hodgkin-Huxley style equations for subthreshold currents. We will also iteratively incorporate inferred functional interactions among specific brainstem neuronal populations identified from analyses of spike trains simultaneously recorded with multiple electrode arrays.
In aim 3, metrics of synchrony and neuronal population dynamics will be applied to data from a model of acute laryngeal inflammation to identify cooperative discharge patterns that contribute to enhanced coughing. The results of these experiments will significantly advance our understanding of neural mechanisms for cough. Cough is responsible for over 25 million visits to physicians annually in this country. Patients often suffer from chronic debilitating cough for years before they are successfully treated, largely because of our lack of understanding of the basic mechanisms that produce this behavior in health and disease.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Exploratory/Developmental Grants Phase II (R33)
Project #
5R33HL089071-03
Application #
7864090
Study Section
Special Emphasis Panel (ZHL1-CSR-K (M1))
Program Officer
Laposky, Aaron D
Project Start
2008-09-15
Project End
2012-05-31
Budget Start
2010-06-01
Budget End
2012-05-31
Support Year
3
Fiscal Year
2010
Total Cost
$239,332
Indirect Cost
Name
University of South Florida
Department
Physiology
Type
Schools of Medicine
DUNS #
069687242
City
Tampa
State
FL
Country
United States
Zip Code
33612
O'Connor, Russell; Segers, Lauren S; Morris, Kendall F et al. (2012) A joint computational respiratory neural network-biomechanical model for breathing and airway defensive behaviors. Front Physiol 3:264
Poliacek, Ivan; Morris, Kendall F; Lindsey, Bruce G et al. (2011) Blood pressure changes alter tracheobronchial cough: computational model of the respiratory-cough network and in vivo experiments in anesthetized cats. J Appl Physiol 111:861-73
Bolser, Donald C; Pitts, Teresa E; Morris, Kendall F (2011) The use of multiscale systems biology approaches to facilitate understanding of complex control systems for airway protection. Curr Opin Pharmacol 11:272-7
Davenport, Paul W; Bolser, Donald C; Morris, Kendall F (2011) Swallow remodeling of respiratory neural networks. Head Neck 33 Suppl 1:S8-13