ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems
Author
Alexander Bering
Date
May 2026
Publication form
Open-access preprint (arXiv) and open-access publication with DOI (Zenodo / CERN)
Summary (short form)
This work presents a seven-layer memory architecture for autonomous AI systems whose design principles are derived from cognitive neuroscience. The architecture integrates Working Memory, Short-Term Memory, Episodic Memory, Long-Term Memory, Procedural Memory, Core Memory, and Predictive Memory into a unified system. Consolidation follows sleep-replay mechanisms with Hebbian-driven strengthening and Ebbinghaus-driven decay. The architecture is available as a modular open-source library under Apache 2.0 and is deployed in production applications.
The full scientific abstract and the formal presentation of methods and results are available in the preprint and DOI versions.
Access