Applying a Dynamical Systems Model and Network Theory to Major Depressive Disorder.

ABSTRACT: Mental disorders like major depressive disorder can be modeled as complex dynamical systems. In this study we investigate the dynamic behavior of individuals to see whether or not we can expect a transition to another mood state. We introduce a mean field model to a binomial process, where we reduce a dynamic multidimensional system (stochastic cellular automaton) to a one-dimensional system to analyse the dynamics. Using maximum likelihood estimation, we can estimate the parameter of interest which, in combination with a bifurcation diagram, reflects the expectancy that someone has to transition to another mood state. After numerically illustrating the proposed method with simulated data, we apply this method to two empirical examples, where we show its use in a clinical sample consisting

SUBMITTER: Kossakowski JJ 

PROVIDER: S-EPMC6692450 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature