Relaxation times are widely used descriptors of dynamical systems and are often interpreted through effective temperature or field-based analogies. In neural systems, coherence-based frameworks can motivate the hypothesis that relaxation time depends on global coherence treated as a temperature proxy. In this work, we test this hypothesis using event-triggered entropy dynamics across meditation, tightly constrained meditation, and resting-state EEG datasets. Subject-level relaxation times are estimated from entropy transients and examined for dependence on global coherence using linear, log-scale, and robust estimators. To assess causal relevance and rule out statistical artifacts, we introduce a hierarchy of null models, including global coherence shuffles, state-preserving coherence shuffles, circular coherence shifts, and event-time shuffles. Across datasets, estimators, and nulls, apparent relationships between relaxation time and coherence vanish under null testing. We conclude that neural relaxation time is primarily state-architectural rather than temperature-driven. This result places strong constraints on field-temperature interpretations of neural relaxation and clarifies coherence as a descriptor of state occupancy rather than a causal control variable for relaxation times. This work constitutes a null-hardened boundary-setting result within the VUH Research Program (BRUH). All data used are publicly available, and analysis scripts and outputs are archived to support full reproducibility.