Regulatory Instability Theory: Dynamic Regulatory Margins and Nonlinear Self-Regulatory Failure

Self-regulatory failures can appear abrupt: sustained control is followed by impulsive action, disproportionate affective expression, behavioral error, physiological dysregulation, or other forms of maladaptive release. Existing theories of drive, frustration, allostasis, and self-regulation identify relevant processes but do not generally specify how distributed demand and time-varying regulatory capacity jointly determine when failure occurs. Regulatory Instability Theory models self-regulation as a dynamical system composed of functionally distinct regulatory channels. Each channel has activation, capacity, and a regulatory margin defined as the difference between current capacity and activation. Persistent activation may create capacity deficit; recovery and dissipation restore margin; compensatory control can reduce immediate activation while, under some conditions, imposing delayed regulatory cost; and coupling can transmit strain between channels. Instability is defined as a first-passage event in which the smallest local regulatory margin reaches a breach boundary. A quadratic Lyapunov function establishes global recovery of the autonomous capacity-deficit model, while a barrier condition specifies sufficient conditions for preserving a positive-margin safe set under continuing demand. The theory predicts that failure is better explained by the trajectory of the smallest evolving margin and the concentration of normalized strain than by total demand or a unitary self-control resource. The framework provides falsifiable behavioral, physiological, and neural hypotheses and a formal basis for simulation, laboratory, and intensive longitudinal research.