Filtering the Unitary Information Field: An N-Tier Architectural Model of Informational Access in Conscious Systems

This paper presents a theoretical framework modelling the universe as a self-generatingcomputational system organized in an n-tier distributed architecture. The Informational AccessBoundary (IAB) and Informational Access Capacity (IAC) are introduced as centralconstructs. The foundational tier comprises the Unitary Information Field (UIF), anundifferentiated, informationally complete, atemporal substrate that functions as a self-trainingsystem optimizing toward Dual Symmetry. The intermediate tier comprises Instantiated Nodes,localized, self-similar informational subsystems generated by the UIF. The client tier comprisesconscious observers, biological systems coupled to Nodes through the IAB, which functions as afiltering mechanism calibrated by evolutionary pressures and modulated by individual agency.The IAC is introduced as the unified underlying variable, manifesting as inhibitory control,attentional direction, and meta-cognition, that determines IAB permeability. A formal modelis presented relating these constructs through information-theoretic functions. A two-gate modelof agency is proposed: Gate One (evolutionary permission) determines whether a speciespossesses the architecture for agency, and Gate Two (individual choice) determines whetheran individual develops that capacity through practice. The framework offers a parsimoniousexplanation for four previously disparate phenomena: cross-species differences in consciousaccess, within-species individual variation, altered states of consciousness, and the presence ofsubjective experience itself. Observable correlates of high IAC are identified and predicted to bepositively associated, with the strength of these associations constituting an empirical question.The framework engages with existing research in contemplative neuroscience, default modenetwork studies, flow psychology, and impulse control, proposing unification under a coherentarchitectural explanation. Testable hypotheses are advanced, inviting empirical investigation.