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Published April 9, 2026 | Version v6
Preprint Open

ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems

Authors/Creators

  • 1. ZenSation AI

Description

ZenBrain v6 — Quality Evolution: Cooperative Gradient & Fair Competitive Comparison

A neuroscience-inspired 7-layer memory architecture (Working, Short-Term, Episodic, Semantic, Procedural, Core, Cross-Context) for autonomous AI systems, integrating 15 algorithms grounded in peer-reviewed neuroscience.

v6 Changes:

  • NEW Challenging Ablation Suite (400 facts, decay=0.20, 50 days): 7 of 15 algorithms become individually significant, proving cooperative redundancy is genuine compensation
  • 3-Level Difficulty Gradient: moderate → challenging → stress reveals four-class algorithm taxonomy (progressive, always-critical, stress-only, cooperatively redundant)
  • Table 1 Extended: 9 comparison systems (added LightMem, MemoryOS, Tiwari 2026) + Neuromodulation/Reconsolidation feature rows
  • Abstract & Discussion Reframed: cooperative survival network as central finding
  • 95 experiment tests across 4 suites (was 77 in v5), all passing with seeded PRNG

Key Results (unchanged): 31.1x retention advantage, 84.7% emotional gap at day 60, Sleep as 1.92x multiplier, Fiedler Δ +0.051 after consolidation.

Reproducibility: All experiments use Mulberry32 seeded PRNG (10 seeds). Full source code at github.com/zensation-ai/zenbrain.

11,607 total tests | 322K LOC | Phase 145 | 60 AI tools

Notes

v6 (2026-04-09): Quality Evolution — Cooperative Gradient & Fair Competitive Comparison Major experiment expansion across 4 suites (95 tests, was 77): NEW — Challenging Ablation (400 facts, 50d, decay=0.20): - 7 of 15 algorithms become individually significant (ΔQ -25.5% to -93.1%) - Proves the moderate-condition redundancy reflects genuine cooperative compensation, not algorithm inactivity - Establishes measurable gradient: moderate → challenging → stress Moderate Ablation (300 facts, 45d, decay=0.15): - Sleep impact: -34.4% (p < 0.005) - Cooperative redundancy confirmed: no single non-Sleep algorithm removal degrades quality, yet PMA group removal causes -67.5% (p < 0.005) - Fault-tolerance analogy: individual strands dispensable, rope essential Stress Ablation (500 facts, 60d, decay=0.25): - 9 Tier-1 (survival) algorithms: ΔQ -3.4% to -93.7% - 6 Tier-2 (quality) algorithms: no individual retention impact - Two-tier cooperative structure confirmed under extreme conditions Competitive Comparison — Fair Baseline: - ZenBrain and SimpleMemory share same base decay rate (0.15/day) - SimpleMemory collapses to P@5=0 by day 30; ZenBrain retains 100% Integration Cascade (unchanged from v5): - 31.1x retention advantage, 84.7% emotional gap at day 60 - Sleep as 1.92x multiplier, Fiedler Δ +0.051 after consolidation Paper improvements: - Abstract reframed: leads with cooperative gradient, not retrieval benchmarks - NEW Table 8: Challenging ablation with gradient evidence - NEW Table 10: Gradient summary with four-class taxonomy - Table 1: Extended to 9 systems (LightMem, MemoryOS, Tiwari '26) - Discussion reframed: cooperative network as central finding - MemoryAgentBench underperformance honestly discussed - BM25 dominance explanation strengthened with citation - Experimental roadmap paragraph added to guide reader - British spellings standardized to American English - fleming2014 bib key corrected to fleming2012 - Appendix seed count corrected (3→10) Stats: 95 experiment tests, 11,607 total tests, 322K LOC, Phase 145, 60 tools

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