Affective Disorders as Complex Dynamic Diseases – a Perspective from Systems Biology

Abstract

Understanding mental disorders and their neurobiological basis encompasses the conceptual management of "complexity" and "dynamics". For example, affective disorders exhibit several fluctuating state variables on psychological and biological levels and data collected of these systems levels suggest quasi-chaotic periodicity leading to use concepts and tools of the mathematics of nonlinear dynamic systems. Regarding this, we demonstrate that the concept of "Dynamic Diseases" could be a fruitful way for theory and empirical research in neuropsychiatry. In a first step, as an example, we focus on the analysis of dynamic cortisol regulation that is important for understanding depressive disorders. In this case, our message is that extremely complex phenomena of a disease may be explained as resulting from perplexingly simple nonlinear interactions of a very small number of variables. Additionally, we propose that and how widely used complex circuit diagrams representing the macroanatomic structures and connectivities of the brain involved in major depression or other mental disorders may be "animated" by quantification, even by using expert-based estimations (dummy variables). This method of modeling allows to develop exploratory computer-based numerical models that encompass the option to explore the system by computer simulations (in-silico experiments). Also inter- and intracellular molecular networks involved in affective disorders could be modeled by this procedure. We want to stimulate future research in this theoretical context.

Computational psychiatry

“…Biophysical modeling is important for elucidating key relationships in a hugely complex system [8] and thus predicting the possible effects of therapeutic interventions (see [9] for an example using dynamic causal modeling). For example, it is well known that critical mechanisms within neuromodulatory systems, such as dopamine, serotonin, norepinephrine and acetylcholine, are subject to intricate patterns of feedback and interactive control, with autoreceptors regulating the activity of the very neurons that release neuromodulators.…”

Does “crisis-induced intermittency” explain bipolar disorder dynamics?

“…(B) Example of temporal pattern of mood variation in a patient with bipolar disorder (Tretter et al, 2011). …”

Towards a complex system understanding of bipolar disorder: A map based model of a complex winnerless competition

“…In the absence of a coherent neural model of its aetiology, mathematical representation is a critical tool for understanding the complex temporal phenomenology of bipolar disorder (Benes and Berretta, 2001;Berns and Nemeroff, 2003;Davidson et al, 2002;Goldbeter, 2011;López-Muñoz et al, 2006;Tretter et al, 2011). Here, manic and depressive episodes of bipolar disorder are proposed to be mathematically representable as two "strange sub-attractors" of a nonlinear discrete dynamical system through which the mood trajectory moves.…”

“…Studies using a variety of methods suggest that pathological competition between electrical activity generated by excitatory (glutamatergic) and inhibitory (GABAergic) neural circuits, may explain the bistability and erratic time-course of bipolar disorder (Benes and Berretta, 2001;Berns and Nemeroff, 2003;Davidson et al, 2002;Duman, 2002;Montague et al, 2012;Tretter et al, 2011). Our coupled chaotic model is grounded in the dynamics of electrical activity in these coupled neuronal excitatory and inhibitory circuits.…”

“…In addition, our simulations show that there exists a high degree of correlation between the external stimuli and the reaction of the system. In the case of intermittent switching between depression and manic episodes in bipolar disorder, however, mutual inhibition of two competitive networks results in an anti-phase synchrony between the agents (Goldbeter, 2011;Tretter et al, 2011). Therefore, two abnormal sub-attractors are formed nearby both the depressive and manic axes in the manic-depressive plane (Fig.…”