Modeling and Parameter Estimation in Respiratory Control
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Experimentalists tend to revel in the complexity and multidimensionality of biological processes. Modelers, on the other hand, generally look towards parsimony as a guiding prin ciple in their approach to understanding physiological systems. It is therefore not surprising that a substantial degree of miscommunication and misunderstanding still exists between the two groups of truth-seekers. However, there have been numerous instances in physiology where the marriage of mathematical modeling and experimentation has led to powerful in sights into the mechanisms being studied. Respiratory control...
Experimentalists tend to revel in the complexity and multidimensionality of biological processes. Modelers, on the other hand, generally look towards parsimony as a guiding prin ciple in their approach to understanding physiological systems. It is therefore not surprising that a substantial degree of miscommunication and misunderstanding still exists between the two groups of truth-seekers. However, there have been numerous instances in physiology where the marriage of mathematical modeling and experimentation has led to powerful in sights into the mechanisms being studied. Respiratory control represents one area in which this kind of cross-pollination has proven particularly fruitful. While earlier modeling ef forts were directed primarily at the chemical control of ventilation, more recent studies have extended the scope of modeling to include the neural and mechanical aspects pertinent to respiratory control. As well, there has been a greater awareness of the need to incorpo rate interactions with other organ systems. Nevertheless, it is necessary from time to time to remind experimentalists of the existence of modelers, and vice versa. The 4th Annual Biomedical Simulations Resource (BMSR) Short Course was held in Marina Del Rey on May 21-22,1989, to acquaint respiratory physiologists and clinical researchers with state-of-the art methodologies in mathematical modeling, experiment design and data analysis, as well as to provide an opportunity for experimentalists to challenge modelers with their more recent findings.
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