The brain integrates and coordinates neural processing across multiple levels of organization to produce behavior. This project takes the neural control of breathing as a system for computational modeling of cross-level integration of cellular, network and systems neural mechanisms. The overall objective is to build a united multi-level model of neural control of respiration, within a uniform framework to incorporate existing data and current hypotheses on respiratory control. It remains controversial whether respiratory oscillation is produced primarily by endogenous cellular 'pacemaker' activity, or instead by properties of excitation and inhibition within a network circuit. This project models membrane activity for single respiratory neurons to investigate bursting activity; models the whole circuitry of the central pattern generator (CPG) network to investigate how connectivity can result in a steady respiratory rhythm with realistic firing patterns and changes from external perturbations; and elaborates the CPG model to generate a pacemaker-driven rhythm under simulated conditions. Mechanisms and conditions for the transition between pacemaker-driven and network-based states for generating rhythms are investigated in computational models and directly compared to experimental biological data from other laboratories. Results will clarify fundamental aspects of the important topic of respiratory control, may settle a current controversy, and will have an impact beyond basic neuroscience, eventually to biomedical work including control-systems analysis of physiology. The complex multi-scale approach is novel, and will provide valuable postdoctoral and student training.
