Sajeev Aadithya Vishnu

DMN v3.0 - The Dream Loop: Memory Consolidation, Familiarity-Weighted Retrieval, and the Learned Graph Executor in the Lár Default Mode Network

Zenodo (CERN European Organization for Nuclear Research) April 19, 2026 Sajeev Aadithya Vishnu

DMN v3.0 adds three mechanisms to the Lár Default Mode Network architecture: Consolidation Loop, Familiarity-Weighted Retrieval, and Learned Graph Executor. The Consolidation Loop mirrors biological memory consolidation with three tiers—Episodic, Semantic, and Procedural—and requires exclusive, isolated cycles to avoid interference. Familiarity-Weighted Retrieval uses a saturating, temporally-decaying confidence measure for memory retrieval, grounded in dual-process theory. The Learned Graph Executor distinguishes the routing policy from Mixture-of-Experts by using offline imitation learning, analogous to hierarchical reinforcement learning's Options Framework. A prospective hybrid with a JEPA world model enables one-step look-ahead planning. DMN v2.0 is deployed; v3.0 is a formal specification.