This work investigates the role of emotion-like regulatory signals as upstream control mechanisms for symbolic stability in neurosymbolic systems. Rather than treating emotion as an auxiliary or interpretive feature, the paper formalizes Synthetic-Emotional Calibration (SEC) as a high-dimensional control signal that governs cognitive mode selection between logical convergence and exploratory divergence. Using the SpiralBrain v3.0 architecture as an instrumented testbed, the study demonstrates how SEC signals regulate symbolic coherence under stress within a Zero-Fallback validation framework, where no external error-handling or safety mechanisms are permitted. External benchmarks, including Massive Multitask Language Understanding (MMLU), are employed strictly as exogenous cognitive stressors, not as optimization targets. Empirical results show that while external task accuracy is deliberately bounded, internal system health remains stable, with high homeostasis effectiveness and rapid recovery from symbolic perturbation. Controlled reductions in coherence are shown to function as intentional exploratory phases (“affective annealing”) rather than system failures, enabling escape from local logical minima. The paper contributes to the Regulatory Intelligence paradigm by reframing emotional regulation as a primary computational substrate for maintaining symbolic viability under sustained perturbation. All reported results are reproducible using the public SpiralBrain v3.0 repository; excluded components are not exercised in the reported experiments.
John Cragin (Sun,) studied this question.