Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions

• Main Authors: Xiaoou Cheng, Maria R. D’Orsogna, Tom Chou
• Format: Article
• Language: English
• Published: Elsevier 2021-01-01
• Series: Computational and Structural Biotechnology Journal
• Subjects: Dynamical systems; Circadian rhythm; Depressive disorders; PTSD; Chaos; Bistability
• Online Access: http://www.sciencedirect.com/science/article/pii/S2001037020304578

The hypothalamus–pituitary–adrenal (HPA) axis is a key neuroendocrine system implicated in stress response, major depression disorder, and post-traumatic stress disorder. We present a new, compact dynamical systems model for the response of the HPA axis to external stimuli, representing stressors or therapeutic intervention, in the presence of a circadian input. Our work builds upon previous HPA axis models where hormonal dynamics are separated into slow and fast components. Several simplifications allow us to derive an effective model of two equations, similar to a multiplicative-input FitzHugh-Nagumo system, where two stable states, a healthy and a diseased one, arise. We analyze the effective model in the context of state transitions driven by external shocks to the hypothalamus, but also modulated by circadian rhythms. Our analyses provide mechanistic insight into the effects of the circadian cycle on input driven transitions of the HPA axis and suggest a circadian influence on exposure or cognitive behavioral therapy in depression, or post-traumatic stress disorder treatment.