Graduation Year
2018
Document Type
Thesis
Degree
M.A.
Degree Name
Master of Arts (M.A.)
Degree Granting Department
Mathematics and Statistics
Major Professor
Gregory McColm, Ph.D.
Committee Member
Eric Storch, Ph.D.
Committee Member
Natasha Jonoska, Ph.D.
Keywords
behavior, brain, compulsive, game theory, Society of Mind
Abstract
The most common method of diagnosing Obsessive-Compulsive Disorder is the Yale-Brown Obsessive Compulsive Scale, which measures the severity of symptoms without regard to compulsions. However, this scale is limited to only considering the quantifiable time and energy lost to compulsions. Conversely, current systems of brain imaging arrest mobility and thus make it virtually impossible to observe compulsions at all, focusing instead on neurological responses to external stimuli. There is little research which merges both approaches, to consider the neuro-physiological effects of obsessions as well as the physical response through compulsions. As such, this research is focused on developing a model of compulsivity based upon neurological chemical pathways. The objective is to develop a model which would predict, given a set of environmental parameters, the probability of an individual with OCD performing compulsive behavior and the prevalence of such behavior. By applying this concept to a neural system known as the worry circuit, a computer program was composed and simulations run by this program suggest that the likelihood of compulsive behavior can be predicted using a function of the number of compulsions performed previously. In this model, each neurological agent in the worry circuit, represented by an automaton, has a certain probability of reacting to a stimulus and moving into one of two distinct excited states. Based on the final state of the automaton, the agent will send excitatory or inhibitory signals to surrounding agents, which also have a certain probability of changing states. If the final agent within the cycle shifts into an excited state, the subject will perform a compulsion. These results may be considered preliminary, given the sample size of the case study and the primitive nature of the model.
Scholar Commons Citation
Fields, Lindsay D., "Developing a Model to Predict Prevalence of Compulsive Behavior in Individuals with OCD" (2018). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/7286
