Abstract
Severe and enduring psychiatric illnesses, including melancholia and bipolar illness, show prolonged deviations in motivation and mood yet lack a unifying account of their long-term dynamics. Solomon’s opponent-process theory provides a qualitative framework for short-timescale affective responses, composed of a fast stimulus-locked a-process opposed by a slower adaptive b-process. Here we evaluated whether these dynamics can be implemented as a computational homeostatic controller, and whether distinct clinical trajectories emerge as canonical failure modes of the same system. We formulated a tractable control-systems model with feedforward a- and b-processes, and examined its behaviour across minute-scale and month-scale regimes. Under “healthy” parameters, the model reproduced classical opponent-process responses. Altering only opponent-process gain and decay generated a prolonged downward drift, matching the clinical timescale and asymmetry of melancholia. Reducing damping within the same controller produced an endogenous underdamped oscillation with long period and phase asymmetry characteristic of bipolar illness. Together, these proof-of-principle simulations suggest that severe severe affective illnesses may be expressed as distinct dynamical regimes of a single motivational homeostat. This framework generates testable predictions and may facilitate experimental quantification of opponent-process recovery, damping, and gain as mechanistic markers of severe affective illnesses.