Pharmacopsychiatry 2013; 46(S 01): S44-S52
DOI: 10.1055/s-0033-1341502
Original Paper
© Georg Thieme Verlag KG Stuttgart · New York

Origin of Cyclicity in Bipolar Disorders: A Computational Approach

A. Goldbeter
1  Unité de Chronobiologie théorique, Faculté des Sciences, Université Libre de Bruxelles, Brussels, Belgium
› Author Affiliations
Further Information

Publication History

Publication Date:
18 April 2013 (online)


Bipolar disorders are characterized by the spontaneous, recurrent alternation of episodes of mania and depression. To investigate the type of mechanism capable of accounting for the cyclical nature of the manic depressive illness, we recently proposed a minimal model for bipolar disorders based on the assumption that the propensities to mania and depression are governed by the activities of 2 putative neural circuits that inhibit each other. When mutual inhibition is sufficiently strong, the model predicts bistability: the bipolar system is then in a stable state corresponding either to unipolar depression or mania, and can display abrupt switches between these states. To account for the cyclical nature of bipolar disorders 2 simple, additional regulations allow the model to pass from bistability to oscillations. Self-sustained oscillations provide a mechanism for the spontaneous, recurrent switching between mania and depression. The model can generate oscillations with a variety of waveforms, including periodic oscillations with comparable or unequal durations of the manic and depressive episodes, or small-amplitude oscillations around one of the 2 states preceding large-amplitude periodic changes in the propensities to mania or depression, with phases during which these propensities reach intermediate levels, a situation that could correspond to mixed bipolar states. Oscillations become irregular when fluctuations of parameter values are taken into account. The model provides a theoretical framework that covers the bipolar spectrum, i. e., cycling between the 2 poles of the disease, or evolution to a stable steady state corresponding to various degrees of unipolar depression or mania or to a “normal” state in which the ­propensities to mania or depression remain low, without alternation between the 2 poles of the disease. The computational approach may help the exploration of plausible mechanisms for bipolar disorders and possible dynamic bases for clinical observations on the effect of antidepressants, which can trigger the transition to mania or increase the frequency of bipolar cycling.