Modeling and analysis of nonlinear biological systems

Abstract

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation focuses on the modeling and analysis of a set of biological phenomenon at a cellular (Part I) and systems (Part II) level. In Part I, the development and analysis of a biologically realistic single neuronal model that alone can mimic resonance filtering properties seen in the in behavioral data in a species of katydid is outlined. Additionally, a network level model of the BLA-NAc pathway was developed to investigate how dopamine and glutamate modulate the cue-primed relapse circuitry. In Part II, a systematic approach to determine correction factors on individual characteristics was developed to adjust the tolerance time predictions of an 'average' computational model of heat strain. Additionally, a new computational model of the human thermal system was developed that accounts for asymmetric environments and includes the arteriovenous anastomoses (AVAs) to provide finer prediction of toe and fingertip temperatures.