Structural Crystallization: A Unified Computational Framework for Memory Formation, Persistence, and Modification

Prevailing models of memory treat strength as a unitary quantity that increases with learning and decreases with forgetting or extinction. We argue that this conflation obscures a fundamental distinction: memory has separable dimensions of structural accumulation and representational fidelity, which are differentially modified by retrieval. Structural accumulation captures how much of a memory trace has been consolidated; representational fidelity captures how faithfully that trace preserves its original encoding. The two can change independently — a memory can retain its full structural extent while becoming progressively distorted, or dissolve while remaining perfectly faithful. This distinction, combined with a second distinction between structurally protective retrieval (externally guided, high-constraint) and structurally risky retrieval (internally generated, low-constraint), resolves several phenomena that have resisted unified explanation: why extinction is temporary but retrieval-extinction can produce lasting change, why stress-enhanced fear memories persist for orders of magnitude longer than ordinary memories, and why fear extinction is fragile while appetitive extinction is durable. We formalize these distinctions in a system of four coupled differential equations (the Structural Crystallization framework), calibrate it to two datasets, and show that it correctly predicts — without parameter adjustment — outcomes across five independent benchmarks where competing models (Rescorla–Wagner; latent cause) fail. Extensions to human declarative memory capture the testing effect crossover, while an explicit failure on the spacing effect reveals interpretable boundary conditions. The results demonstrate that separating accumulation from fidelity is not merely a modeling convenience but a theoretical necessity for any account of both the persistence and the modifiability of memory.

• memory consolidation
• retrieval
• extinction
• structural accumulation
• representational fidelity
• Rescorla–Wagner
• latent cause models