ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems
ZenBrain is a seven-layer, neuroscience-derived memory architecture for LLM agents that unifies fifteen mechanisms - from Two-Factor synaptic consolidation to a Simulation-Selection sleep loop - under a single MemoryCoordinator: nine foundational algorithms plus six Predictive Memory Architecture components. No system among those we survey integrates more than two of them. Ablating each mechanism separately exposes an effect we call cooperative masking. Under moderate load, fourteen of the fifteen ablations look costless - the architecture reads as mostly dead weight. Raising decay to 0.25/day over 60 days, with no change to the mechanisms, makes nine of the fifteen individually critical ...
| Authors | Alexander Bering |
|---|---|
| Primary category | cs.AI |
| Published | 26 April 2026 |
| Last updated at source | 9 August 2026 |
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