Stress Reaction System Modeling
Disciplines
Databases and Information Systems | Experimental Analysis of Behavior | Other Psychology
Abstract (300 words maximum)
Stress Reaction System Modeling
Pengcheng Xiao and Vanessa Phan
First-Year Scholar Program, Kennesaw State University
The HPA axis, a stress responsive system, is responsible in regulating the production of cortisol. Cortisol level varies corresponding to different psychiatric disorders resulting in divergent strength of negative feedback. We can interpret these variabilities into diagrams for quantitative analysis using nonlinear ordinary differential equations (ODE). This model was formulated to illustrate the cortisol dynamics in a twenty-four-hour window. The parameters used in this ODE were evaluated by clinical data and global optimization and also went through bifurcation analysis. We collected data from examination of numerous possible inputs, including chronic and acute stress. Starting with the cortisol dynamic model, we explored the changes and impacts with different variations and parameters. The cortisol dynamics model was tested in 3 subjects, Normal, PTSD, and Depression with an expanded stimulating time window (compared to the original 24-hour range from the literature). After the results analysis, the outcomes support the sufficiency of this cortisol dynamic model. We have come to an agreement with the reference literatures. Further investigation may be carried out to validate this model’s proficiency as well as develop its potential in psychiatric disorders treatments.
Academic department under which the project should be listed
CSM - Mathematics
Primary Investigator (PI) Name
Pengcheng Xiao
Stress Reaction System Modeling
Stress Reaction System Modeling
Pengcheng Xiao and Vanessa Phan
First-Year Scholar Program, Kennesaw State University
The HPA axis, a stress responsive system, is responsible in regulating the production of cortisol. Cortisol level varies corresponding to different psychiatric disorders resulting in divergent strength of negative feedback. We can interpret these variabilities into diagrams for quantitative analysis using nonlinear ordinary differential equations (ODE). This model was formulated to illustrate the cortisol dynamics in a twenty-four-hour window. The parameters used in this ODE were evaluated by clinical data and global optimization and also went through bifurcation analysis. We collected data from examination of numerous possible inputs, including chronic and acute stress. Starting with the cortisol dynamic model, we explored the changes and impacts with different variations and parameters. The cortisol dynamics model was tested in 3 subjects, Normal, PTSD, and Depression with an expanded stimulating time window (compared to the original 24-hour range from the literature). After the results analysis, the outcomes support the sufficiency of this cortisol dynamic model. We have come to an agreement with the reference literatures. Further investigation may be carried out to validate this model’s proficiency as well as develop its potential in psychiatric disorders treatments.