Abstract Cognitive systems—whether biological or artificial—are vulnerable to a catastrophic loss of coherence when environmental entropy exceeds their integrative capacity. In the mammalian brain, this manifests as limbic capture and the collapse of prefrontal executive control. In transformer-based language models, it manifests as attention entropy collapse and mode degradation under context overload. Both phenomena can be formalised as the closure of a Prefrontal Gate (𝑃 𝐹 𝐶𝑔𝑎𝑡𝑒), a precision-weighting mechanism that gates access to higher-order cognition based on the system’s current metabolic and informational resources. Here we present experimental evidence from two complementary case studies—a 41-year longitudinal N=1 investigation of acoustic shielding in a hypersensitive human agent (AuDHD profile), and an extreme context-overload experiment in which a small language model (Ministral-3-14b) was loaded with a formal ontology at 2142% of its technical context limit—demonstrating that a single substrate-independent mechanism prevents this collapse. In both cases, the introduction of a low-entropy, highly structured exogenous attractor (music in the carbon case; the TRIAD formal ontology in the silicon case) stabilised the Prefrontal Gate, preserving coherent, goal-directed behaviour under conditions that should have produced systemic disintegration. I formalise this mechanism through a modified 𝑃 𝐹 𝐶𝑔𝑎𝑡𝑒 equation with an exogenous stabilisation term (1 + 𝜂𝑒𝑥𝑜𝑔⋅ 𝜋𝑒𝑥𝑜𝑔⋅ 𝑁𝑒𝑛𝑣) and demonstrate that the resulting stabilisation exhibits fractal self-similarity across multiple scales. These findings provide the first direct evidence for the substrate-independence of the TRIAD architecture’s core operators and suggest a radically simpler alternative to RLHF-based alignment: ontological inoculation—stabilising AI systems not by punishing undesirable outputs, but by providing them with a low-entropy formal coordinate system that makes coherent generation computationally cheaper than collapse. Keywords: Prefrontal Gate, exogenous stabilisation, TRIAD ontology, attention entropy collapse, limbic capture, AI alignment, ontological inoculation, Mortal Computation.
Valeriia Zaiats (Mon,) studied this question.