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155 changes: 155 additions & 0 deletions .claude/research/2026-10-31-staunen-dt64-hdc-snn-convergence.md
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# D-STAUNEN-0 | Convergence scratchpad | 2026-10-31

**Status: INCEPTION / WORKING HYPOTHESIS, NOT ADMITTED ARCHITECTURE.** Preserve the entire research thread before it fragments. Source-derived fact, repository-measured result, user decision and untested hypothesis must remain distinct. CC owns any implementation only after current source re-audit, explicit operator decision and falsifier.

## North star
Make **plasticity an intrinsic DT64 hypercube capability**: an activated pattern can influence which local neural/symbolic connections become eligible for adaptation; competing sparse thoughts test changes; only external evidence licenses consolidation into the next sealed WORLD version. Not a second runtime, storage engine, palette registry, graph or truth oracle. Faster bit primitives are not equivalent to biologically faithful or general learning.

## Convergence mindmap

```mermaid
mindmap
root((DT64 built-in learning))
Biological cognition
ACT-R Anderson goals chunks productions
AtlasIR validated neuron physics
Spike STDP eligibility traces
Staunen novelty salience
Structural and myelin plasticity
Metaplasticity learning to learn
Hyperdimensional representation
HDC VSA bind bundle permute compare
SpikeHD SynapseHD Spiking Phasors
XOR popcount packed u64 tiles
DR64 DR256 global local addressing
Moore eight-slot typed neighborhood
Symbolic structure
XLOG typed RIR PIR EIR
Quack R2IL mask-risc ndarray
NSL graph loss and neighbors
Palette512 epistemic U9
TurboVec9 numeric centroids
Evidence and mind
CE64 activation and epistemic contract
WORLD 0 immutable givens
THOUGHTS 1 through 63 sparse branches
Pearl ablation causal interventions
Qualia operational readings optional
PointCare situated world context
Replay and evidence independence
Outcomes
Competing learning strategies
Useful synapse and rule change
Tested consolidation
Brain SoC long-term target
Falsifiable steps toward adaptive intelligence
```

## Important distinctions
1. Staunen = candidate novelty/salience *event* modulating plasticity; it is neither facial expression nor an automatic claim of synaptic growth.
2. Wisdom = evidentially warranted consolidation/reuse; not a biological synapse, not certification by novelty.
3. Brain mirror neurons specifically concern observation/action coupling, not arbitrary routing to brain regions. Proposed cross-assembly recruitment is a distinct hypothesis.
4. Gray matter synaptic/structural change and white-matter myelination are both plasticity on different mechanisms/timescales; explicit distinct simulator models required.
5. BNN is ambiguous: binary, Bayesian or biological neural network. Always spell out.
6. Atlas supports bounded STDP and separate surrogate-gradient/BPTT/SGD/Adam training; no universal Bayesian learner or brain-complete simulation.
7. A Moore8 palette projection is not a biological adjacency index; any true neighbors must come from the authenticated synaptic topology.
8. 64 CE64 bits are typed word semantics; a hypervector has many 64-bit tiles; 64 thought slots are a different axis.
9. CE64 46..49 activation *decision* conflicts with legacy opcode reader; 50..52 novelty/wisdom vs plasticity owner ruling OPEN; W 53..58 denotes ephemeral thought slot, not durable evidence ID.
10. No copy of WORLD per thought: 0 sealed givens, 1..63 sparse deltas over one frame; per-thought evidence roots prevent self-confirmation.
11. CE64 is an ISA, **not a storage contract** (#1628); physiology, eligibility traces, gradients and synaptic topology belong to typed external state.
12. Do not market subjective experience, mirror-neuron routing, AGI attainment, permanent structural synapse growth, physical Brain SoC power or nanosecond whole-brain simulation as demonstrated.

## Proposed learning loop
Observed spike / event -> HDC pattern -> novelty prediction residual -> authenticated Moore/graph neighborhood -> eligibility + signed 3rd factor -> bounded synaptic/structural candidate -> XLOG/NSL symbolic hypotheses -> 64 sparse thoughts with root-disjoint comparison and held-out external observations -> revision, ablation, consolidation, or abstention. Re-evaluate future plasticity policies = *metaplasticity*.

## Concrete existing anchors
- #1400 Moore/NARS delayed consequence recipe learning: evidence of structure-based selection; later #1440 found delayed credit inconclusive under Holm. No claim of neuronal validity.
- #1405 Morton Moore shifts; #1408 historical tenants 18..20 not a license to ratify production slots; #1336 256×256 palette pair LUT.
- #1839 ClassView per-class U8/U9; #1846 NSL neighbor and graph-loss oracles; #1847 distinguishes DR512 SM9 never-touched vs TurboVec9 centroids, and proposes P64×T64×CE64 (32 KiB ideal dense logical payload).
- #1869 DT64 bind store; #1884 XLOG compiled plan/count bound to native ndarray::simd with Epi5 base `Direct×Open`, composition `IndirectKnown×Open`; joins do not certify causality.
- #1597 bit decisions and conflicts, #1628 64 thought slots / CE64 ISA not storage, D-TGB distinct live slot generations and durable commits.
- AtlasIR Definition/Instance/Run hashes, effect algebra and ordered events (manuscript §§2.2–2.4); Pair/Triplet STDP + bounded native BPTT (§§3.7–3.8). Biological equivalence remains empirical.
- ACT-R bridges goal/chunk/production dynamics at cognitive level, not an assumed neural-lowering compiler. PointCare/WorldModel are candidate situated contexts only.

## Stage map
- D-STAUNEN-0 this conservation map.
- D-STAUNEN-1 typed CE64 / DT64 plasticity and ownership admission.
- D-STAUNEN-2 AtlasIR × SNN × HDC × Moore experimental bridge.
- D-STAUNEN-3 XLOG × NSL × Palette512 / TurboVec9 structure and learning adapters.
- D-STAUNEN-4 64-thought metaplasticity, evidence-root independence, evaluation and integration gates.

## Minimum falsifiers
- Novelty shuffled vs genuine; time-shuffled spikes; neuron ID permutation; topology- and Moore-shuffled; duplicate evidence across 63 thoughts; silent loss of spike timing; synaptic weights changed without Atlas permission; equality of candidate neighbors under quantization; no-learning and no-meta baselines; stale DR frame refusal; thought slot reuse; K3 UNKNOWN; bag multiplicity loss; replay determinism; OOD / held-out behavior; end-to-end runtime with preparation and state movement charged.

## Source and evidence register (do not flatten status)
- Uploaded primary manuscript: Xinjun Li, *A Unified Intermediate Representation and Execution Architecture for Heterogeneous and Distributed Neural Simulation*, 44-page manuscript, §2.2–2.5, §3.7–3.8, §4–6; https://github.com/RockLi/brian2-atlas-preprint/blob/main/paper/MANUSCRIPT.md ; source-pinned Atlas commit `ae649a244e28d7d4b3eb5df4e35215e14c1378c7`, archive `biorxiv-v1` (the tag name does not assert journal review). Atlas source https://github.com/RockLi/brian2-atlas ; frozen AtlasIR https://github.com/RockLi/brian2-atlas/blob/dev/brian2-rust/AtlasIR.md . Atlas original Apache-2.0, inherited Brian2 CeCILL-2.1.
- A. Anderson & Lebiere, *The Atomic Components of Thought* (1998): ACT-R goals, chunks and productions: https://www.routledge.com/The-Atomic-Components-of-Thought-1st-Edition/Anderson-Lebiere/p/book/9780805828160
- B. Lisman & Grace (2005), hippocampus–VTA novelty/LTP loop: https://doi.org/10.1016/j.neuron.2005.05.002
- C. Frey & Morris (1997), synaptic tagging: https://doi.org/10.1038/385533a0
- D. Gerstner et al. (2018), eligibility and neo-Hebbian three-factor rules: https://doi.org/10.3389/fncir.2018.00053
- E. Abraham & Bear (1996), metaplasticity: https://doi.org/10.1016/S0166-2236(96)80018-X
- F. Miconi, Stanley & Clune (2018), differentiable plasticity/meta-learning: https://arxiv.org/abs/1804.02464
- G. Zou et al. (2022), SpikeHD SNN/HDC co-learning: https://doi.org/10.1038/s41598-022-11073-3
- H. Orchard et al. (2024), spiking phasor/FHRR operations: https://pubmed.ncbi.nlm.nih.gov/39106467/
- I. Zhou et al. (2026), SynapseHD SNN/HDC training: https://doi.org/10.1016/j.neucom.2025.131757
- J. Kinavuidi, Peres & Rhodes (2026), hyperdimensional SNN decoding: https://doi.org/10.1088/2634-4386/ae4f1e
- K. Bui, Ravi & Ramavajjala (2017), Neural Graph Machines/structured graph regularization: https://arxiv.org/abs/1703.04818
- L. XLOG typed logic, distinct RIR/PIR/EIR/NN semantic lanes: https://github.com/BrainyBlaze/xlog
- M. Chalmers' hard problem/qualia is philosophical framing only; no computational variable proves phenomenal experience. Do not make consciousness claims.
- Internal: CE64 capstone https://github.com/AdaWorldAPI/lance-graph/blob/main/.claude/knowledge/epistemic-frontier-capstone.md ; CE64 layout https://github.com/AdaWorldAPI/lance-graph/blob/main/docs/architecture/ce64-semantic-upper-half.md ; #1597, #1628, #1400, #1405, #1408, #1440, #1839, #1846, #1847, #1884, #1869.

## Round 2 | CC read-before-code / scientific triangulation
**Do not treat the mindmap as permission to modify source.** Each later PR is independently reviewable and has its own decision list; stage numbers are logical review dependencies, not necessarily Git branches stacked on each other.

### Owner map and source gates
| Owner / source | What it uniquely determines | Existing anchor |
|---|---|---|
| `contract`, `causal-edge` | CE64 byte layout, sign, W, Epi5, legacy ISA conflicts | #1597, #1628 and `crates/causal-edge/src/layout.rs` |
| `lance-graph-dt64` | class/field/method binding, ON/WHEN/DO guard; routes not values | #1869 |
| DR, Alpha, Thought-Git | immutable source identity, focus generation, sparse speculative writes, protected merges | #1628, #1739, #1837 |
| AtlasIR | physiological time, state, synapse ownership, delays, RNG, effect dependencies | Li manuscript, §2/§3 |
| XLOG compiled plan | typed deterministic vs probabilistic vs epistemic derivation | #1884 and upstream XLOG |
| NSL/ndarray | reproducible neighbor order, graph-loss semantics and quantized numeric operations | #1846, #1847 |
| Moore | local projection and 8-slot readings, not graph ontology | #1400, #1405, #1408 |

### Explicit hypotheses (hypothesis, not established science)
H1. Spike-time-aware HDC signatures recognize structural novelty without destroying information needed for credit assignment.
H2. Novelty/salience gated eligibility updates improve held-out adaptation compared with equally budgeted STDP and randomized novelty gates.
H3. Stable identity + true adjacency + Moore-local projection reduces exact active-neighborhood work without turning anatomical connectivity into Morton coordinates.
H4. XLOG symbolic consistency/ablation and NSL graph regularization can improve the *next* physical learning decision, not just downstream classification.
H5. Cross-thought policy comparison improves learning outcome under equal compute and source-root-independent evidence.
H6. Learning the admission/reward/eligibility policy itself (metaplasticity) transfers to unseen tasks without overwriting the sealed WORLD or multiplying evidence by branch count.

### External biology: the missing layers
- Hedrick et al. (2022), activity-related clustered spinogenesis (real spatial structural plasticity; does **not** imply eight Moore directions are synapses): https://doi.org/10.1038/s41593-022-01086-6 .
- McKenzie et al. (2014), motor-skill learning requiring active central myelination: https://doi.org/10.1126/science.1254960 .
- Denève (2008), Bayesian spiking neurons II: local spike-time-dependent learning under a Bayesian model: https://doi.org/10.1162/neco.2008.20.1.118 . This is an example, **not** proof that STDP in general is Bayes.
- Semantic pointer spiking networks/NEF: https://pmc.ncbi.nlm.nih.gov/articles/PMC4762696/ . Prior art for VSA over spikes, not a new contribution by us.

### User-intent preservation: anything omitted is a loss
- Staunen was intended as **biological novelty initiating plasticity**, not facial affect.
- Biological plasticity includes synaptic weights, structural spines, intrinsic excitability, and myelin, with distinct biological scales.
- Einstein's philosophical wonder is motivation, not an experimental neural definition.
- User asks intrinsic DT64 hypercube capability, not a pluggable bolt-on; only semantics and execution binding are intrinsic, physical algorithms are typed strategies.
- Pattern ISA = compact CE64 state and ops, not a 64-bit complete HDC representation.
- The structural mapping involves `Palette512/U9 × Moore`, `TurboVec9`, NSL, AtlasIR, XLOG, R2IL/Quack/ndarray and 64 thoughts without multiplying runtimes.
- Qualia/Chalmers, ACT-R/Anderson, PointCare and Brain SoC are research context with deliberately weaker claims.
- The competition story is *testable, lower-resource learning-to-learn and causal replay*, not human-brain emulation achieved.

### Common cold/hot economics
Do not quote a nanosecond end-to-end learning result from a single `popcount`, `mask_and`, or lookup. Follow repo `CLAUDE.md` folding doctrine: resident terminal primitives measured in ns, bounded query batches in µs; report compilation/oracle preparations separately in µs and not as fold gates. Biological wall-time workloads and scientific fidelity are a distinct paper-level measurement class, and do not establish a nanosecond biological tick.

### How CC should consume these PRs
1. Read this map, `CLAUDE.md`, the CE64 capstone and stage-specific references.
2. Fetch current `main` and the owning upstream repositories before asserting source behavior.
3. Reconfirm whether current branches already supersede #1846, #1847 and #1884; never fork an existing implementation by accident.
4. Enter a source/file/contract ledger with statuses: **EXISTS / TESTED / MEASURED / DECISION / OPEN / PROPOSED**.
5. Propose experiment-only branches under the owning stage, one falsifiable gate at a time; no source edits from this preservation PR.
6. Close each gate with independent oracle, disable-to-red result, precision and provenance report, or named refusal.
7. Preserve **explicitly rejected** results (quantized near-zero distances, duplicate evidence, arbitrary mirror routing) as negative tests.

### Cross-stage links
- Stage 1 https://github.com/AdaWorldAPI/lance-graph/pull/1886
- Stage 2 https://github.com/AdaWorldAPI/lance-graph/pull/1887
- Stage 3 https://github.com/AdaWorldAPI/lance-graph/pull/1888
- Stage 4 https://github.com/AdaWorldAPI/lance-graph/pull/1889