The Constrained Disorder Principle: Beyond Biological Allostasis

Abstract

The constrained disorder principle (CDP) defines complex biological systems based on inherent variability. Allostasis refers to the physiological processes that help maintain stability in response to changing environmental demands. Allostatic load describes the cumulative wear and tear on the body resulting from prolonged exposure to stress, and it has been suggested to mediate the relationship between stress and disease. This study presents the concepts of CDP and allostasis while discussing their similarities and differences. We reviewed the current literature on the potential benefits of introducing controlled doses of biological noise into interventions, which may enhance the effectiveness of therapies. The paper highlights the promising role of variability provided by a CDP-based second-generation artificial intelligence system in improving health outcomes.

Keywords: allostasis; allostatic load; artificial intelligence; constrained disorder; randomness.

Figure 1

A schematic representation of homeostasis, allostasis, and the constrained disorder principle (CDP). All theories involve the response to environmental perturbations. The forces and energy push the system back to its set point in homeostasis. In allostasis, the forces set a new point based on the circumstances, demanding energy expenditure. Per the CDP, each system has an inherent disorder that is mandatory for its proper function. Adapting to changes does not involve predictability and is conducted by alterations in the dynamic borders, which regulate the level of noise in the system. In allostasis, each of the three set points represents a range of different values associated with noise, and these distributions may overlap. The set points can belong to the same or different but related systems. In contrast, the CDP does not have set points; instead, the boundaries for noise are dynamic and change based on the environment. The small arrows illustrate the variability of these noise boundaries, highlighting that the noise level within a system may adjust to adapt to environmental changes.