The use of multiscale systems biology approaches to facilitate understanding of complex control systems for airway protection

Airway protection is a critically important function that prevents/limits the intrusion of foreign material into the pulmonary tree. A host of different behaviors participate in this process. The control, coordination, and execution of these behaviors is a complex process that has recently received increased attention. Data from human clinical and animal studies support the concept of a coordinated neural control system that governs the appropriate expression and sequencing of airway protective behaviors. Our current knowledge of the proposed neural control network for breathing, cough, swallow and other airway protective behaviors indicates that it is a highly complex system that can ‘rewire’ (reconfigure) itself to perform several different functions. Computational modeling and simulation have been used as tools to investigate this system. The results of modeling efforts have yielded motor output patterns of upper airway and respiratory muscles that are very similar to those recorded in vivo. Regulation and coordination of multiple different airway protective behaviors have been successfully simulated. Outcomes of simulation efforts support the hypothesis that computational modeling of airway protection can yield important testable hypotheses regarding brainstem neural network functions and organization. Modeling of complex systems can be challenging but the open availability of straight-forward computational tools is likely to result in increased implementation of modeling and simulation as adjuncts to traditional methods of investigation of the control of the upper airway.

► Protection of the airway from aspiration is a complex process involving multiple behaviors. ► These behaviors are subject to coordinated control that is poorly understood. ► The central mechanism for airway protection is better understood when computational modeling and simulation are used as investigative tools. ► There are online modeling and simulation resources that can be utilized by investigators interested in adapting these methods to their research.