Memory as Persistent Content and Learned Access presents an interdisciplinary field-theoretic framework for understanding how memory can remain recoverable despite continuous changes in its physical carriers, temporary loss of accessibility, and reorganization during learning and consolidation. The article introduces the Primary Organizational Field Φ (x, ω, t) (x, , t) Φ (x, ω, t), defined over physical space, spectral coordinate, and time. Within this framework, memory is not treated as a static object stored in one location. It is described as a coupled organization of: persistent, recoverable content, learned relations between field structures, history-dependent access pathways, informational impedance, and dynamostatic return after perturbation. A central distinction is made between memory content and memory access. Information may remain latent and recoverable even when natural retrieval fails, while an accessible route does not necessarily imply that the original content is still intact. This distinction provides a formal language for phenomena such as activity-silent memory, changing retrieval thresholds, systems consolidation, and history-dependent effective connectivity. The article develops: a functional definition of recoverable content; phase-current and constitutive-memory dynamics; an adaptive transport tensor GijG₈₉Gij; a path-dependent definition of informational impedance; a candidate variational closure for learned transport geometry; explicit boundary and timescale assumptions; a translation table connecting formal concepts with possible neurobiological observables; and a set of falsifiable experimental hypotheses involving perturbation, effective-connectivity modelling, Dynamic Causal Modelling, Parametric Empirical Bayes, retrieval thresholds, and directional modulation. Earlier ring and torus simulations are reinterpreted as constrained demonstrations of persistence within prescribed morphological families. The article does not claim that memories are literal toroids or that the Primary Organizational Field is identical to EEG, fMRI, extracellular electric fields, or synaptic connectivity. Numerical results support the distinction between retained content and learned access, while spontaneous toroidal memory nodes and selective rerouting remain unconfirmed. The framework is intended as a common formal language for three problems that are usually studied separately: persistence, accessibility, and plasticity. It is presented as a testable interdisciplinary proposal rather than a completed theory of the brain. ***Old version description: Active Memory Persistence in Field-Theory proposes a new field-theoretic view of memory: not as static storage, but as a dynamically self-repairing regime of a field. Using two reproducible Symformism/DIFT benchmarks — a 2D amplitude–phase ring and a 3D toroidal field evolved through time — the paper shows how coherent structures can preserve topological identity, recover from perturbations, increase active memory, and reduce informational impedance across repeated stress episodes. The central claim is simple but far-reaching: a memory-like form may persist because topology protects it, dynamostasis repairs it, and repeated recovery makes it cheaper to maintain. This reframes memory as a field-organized process of return rather than a passive trace stored in a substrate. The article connects field theory, topology, self-organization, complex systems, artificial intelligence, neuroscience, and the Symformism/DIFT framework. It may be of interest to readers working on distributed memory, engram theory, attractor dynamics, topological protection, active matter, computational field models, and the philosophy of persistence.
Sławomir Krakowski (Fri,) studied this question.