Proposes a framework for psychical homeostasis, revealing how emotional states interact within a hierarchy.
This paper proposes a five-level hierarchical framework for psychical homeostasis, integrating principles of affective neuroscience, predictive coding, and ego-state architecture. We postulate that the diversity of psychological states can be modeled through a systematic combinatory logic of 20 Phylogenetic Core Functions, organized into ten reciprocal, subcortical processing axes, including a foundational Validation Axis (WRONG ↔ RIGHT). By treating emotional states as a dual-space predictive inference engine, the framework demonstrates how global identity systems (Super-Priors) modulate top-down precision weightings through active inference clamping under the thermodynamic constraints of the Free Energy Principle. The model establishes a mechanistic bridge between computational neuroscience and structural personality theory, offering a systematic, non-metaphorical taxonomy of human experiencing. While the framework provides the formal state-equations of psychical homeostasis, it acknowledges these as the necessary substrate for phenomenological emergence, rather than a replacement for the subjective richness of lived experience. We explicitly challenge current modular theories of prosocial affect, arguing that states like CARE or GRIEF are emergent Tier 2 combinations rather than hardwired circuits. Finally, we define specific falsification points through predicted metabolic costs and subcortical constraints, alongside clinical predictive validity in pathological disturbances, providing a testable challenge to the biological basis of hierarchical top-down dominance.
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Michael Jirsch (2026) studied this question.
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