Structural Organization and Structural-Update Governance in Self-Regulating Cognitive Systems: A Candidate Functional Decomposition

This paper develops the Structural Organization projection of the Architecture of Self-Regulating Cognitive Systems. Its central distinction is between Processing Organization—the current organization through which processing is structured—and Structural-Update Governance—the organization that constrains how structurally consequential change may occur. The paper proposes two candidate functional decompositions. Processing Organization is analyzed through content distinctions, differential processing relevance, relations, relational organization, configuration-comparison criteria, configuration/processing thresholds, and processing allocation. Structural-Update Governance is analyzed through update-relevant difference sensitivity, update-source constraints, relational-change constraints, differential-relevance change constraints, mismatch tolerance, update-tempo constraints, and structural-history dependence in updating. The two decompositions are not claimed to be exhaustive, universally seven-part, graph-based, scalar, or arranged as a one-to-one mapping. The paper further distinguishes transient operational holding, retained content records, and structural-history dependence; states a bounded relative-plasticity hypothesis; and preserves explicit boundaries with GTCS Coherence Evaluation, Significance Fields, Human Psychic Processing, and Governance of Cognitive Continuity. The account is substrate- and implementation-neutral at the architectural level. It does not establish empirical validation, universal necessity, a complete algorithm of cognition, or a universal internal topology.