Noise Decorrelation as a Hypothetical Mechanism for Phase-Specific Neurometabolic Outcomes in HIV Infection: A Computational Framework

Despite direct neurotoxic assault and cytokine storm during acute HIV infection, over 90% of individuals maintain normal neurocognitive function with preserved N-acetylaspartate (NAA)--a clinical paradox that has resisted mechanistic explanation for 35 years. Here we show that environmental noise correlation length ({xi})--a quantum biophysical parameter inferred across photosynthesis, magnetoreception, and now neuronal metabolism--distinguishes protected from vulnerable neurometabolic states. Using hierarchical Bayesian inference on magnetic resonance spectroscopy data (13 group-level observations aggregating [~]220 patients across 4 independent studies), we find shorter noise correlation during acute infection ({xi}acute = 0.425 {+/-} 0.065 nm) compared to chronic infection ({xi}chronic = 0.790 {+/-} 0.065 nm), with non-overlapping 95% highest density intervals. The inferred protection exponent {beta}{xi} = 2.33 {+/-} 0.51 (95% HDI: 1.49-3.26) indicates superlinear scaling of metabolic protection with decreasing correlation length. Independent validation via enzyme kinetics modeling yields concordant results (protection ratio = 1.28 {+/-} 0.17), and the inferred{xi} values (0.42-0.81 nm) converge with noise correlation scales in photosynthetic energy transfer and avian magnetoreception--systems where{xi} is likewise inferred from functional data rather than directly measured. The phase-specific and regionally structured modulation observed implicates a conserved mechanism for maintaining neuronal metabolic integrity during acute inflammatory stress, with cross-system convergence of noise correlation scales providing independent biophysical validation.