Jaba Tkemaladze
Contemporary geroscience provides a detailed catalog of aging phenotypes but lacks an integrative, systems-level framework explaining their coordinated progression. This paper proposes a novel, hypothesis-generating perspective: biological aging can be usefully conceptualized as a process of progressive adaptation narrowing linked to dysregulated predictive homeostasis. We conceptualize an organism as a hierarchical predictive system managing a fundamental trade-off between the cost of updating its internal model and the penalty for bearing prediction errors. We introduce a core postulate: that under the constraints of accumulating stochastic damage and finite resources, aging systems exhibit a trend toward elevated thresholds for registering and responding to prediction errors. This reduces short-term updating costs but renders the system progressively less sensitive to novel signals, potentially leading to a drift away from optimal homeostasis. We present a simplified conceptual model to illustrate this trade-off. From this framework, we generate unique, testable predictions distinct from those of existing theories. We then explore how established hallmarks of aging could be reinterpreted through this lens, offering high-level, speculative analogies intended to generate novel research questions. The perspective is rigorously positioned against major evolutionary and computational theories of aging. We discuss hormesis as a potential countermeasure that may work by forcing model updates. Finally, we outline a critical research program for validation. This perspective aims to provide an integrative conceptual scaffold for investigating aging as a process of declining adaptive fidelity and informational openness.