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Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Research Network of Computational and Structural Biotechnology
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815682/ https://www.ncbi.nlm.nih.gov/pubmed/33510869 http://dx.doi.org/10.1016/j.csbj.2020.10.035 |
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author | Cheng, Xiaoou D’Orsogna, Maria R. Chou, Tom |
author_facet | Cheng, Xiaoou D’Orsogna, Maria R. Chou, Tom |
author_sort | Cheng, Xiaoou |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7815682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-78156822021-01-27 Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions Cheng, Xiaoou D’Orsogna, Maria R. Chou, Tom Comput Struct Biotechnol J Research Article 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. Research Network of Computational and Structural Biotechnology 2020-11-21 /pmc/articles/PMC7815682/ /pubmed/33510869 http://dx.doi.org/10.1016/j.csbj.2020.10.035 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Cheng, Xiaoou D’Orsogna, Maria R. Chou, Tom Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions |
title | Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions |
title_full | Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions |
title_fullStr | Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions |
title_full_unstemmed | Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions |
title_short | Mathematical modeling of depressive disorders: Circadian driving, bistability and dynamical transitions |
title_sort | mathematical modeling of depressive disorders: circadian driving, bistability and dynamical transitions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815682/ https://www.ncbi.nlm.nih.gov/pubmed/33510869 http://dx.doi.org/10.1016/j.csbj.2020.10.035 |
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