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Research Document ID Date Status Authors Related ADRs
RD-C-11 2026-04-21 Draft RuView Research Team proposed ADR-084 through ADR-088

RD-C-11: Risks, Positioning, and Roadmap

Abstract

This is the governance document for the compendium. It specifies what CC-OS is allowed to claim in public artifacts, what it must never claim, the dual-use and ethics considerations implied by running the same counterfactual-perturbation pipeline on any connectome, comparisons against prior art (Eon, OpenWorm, Blue Brain, Brian2 + NeuroMechFly, BrainScaleS), the decision rubric from the originating proposal, full drafts of five proposed ADRs (ADR-084 through ADR-088), and a five-phase implementation roadmap with phase gates, success KPIs, and out-of-scope items for v1. It closes with a publication plan that prioritises honest scope-limited claims over headline-chasing.

Table of Contents

  1. Scientific positioning — CC-OS
  2. Hype and ethics risk matrix
  3. Scope limits
  4. Security / dual-use considerations
  5. Comparison with prior art
  6. Decision rubric
  7. Proposed ADRs (ADR-084 through ADR-088)
  8. Five-phase implementation roadmap
  9. Success KPIs per phase
  10. Out-of-scope items for v1
  11. Publication and talk plan
  12. Appendix A: 200-word short-form summary
  13. References

1. Scientific Positioning — CC-OS

CC-OS is a coherence-aware connectome operating system. It loads a published connectome, simulates its neural dynamics at millisecond resolution, closes the sensorimotor loop through an embodied simulator, and provides auditable counterfactual analysis of the resulting behavior. It is a platform for circuit science, not a model of mind.

What CC-OS is:

  • a graph-native connectome runtime;
  • a Rust event-driven LIF engine at 10k–139k neuron scale;
  • an embodied sensorimotor loop closed in real time;
  • a structural + behavioral fragility pipeline;
  • an auditable, witness-logged, reproducible platform.

What CC-OS is not:

  • not a mind, not a subject, not a locus of experience;
  • not a whole-brain emulation in the Sandberg–Bostrom sense;
  • not a replacement for NEURON, Brian2, Nengo, or Blue Brain;
  • not a claim about consciousness, identity, or memory continuity.

2. Hype and Ethics Risk Matrix

Claim Risk Mitigation
"Mind upload" / "digital consciousness" VERY HIGH Never use in any RuView artifact. Formal prohibition.
"Simulated fly brain" (unqualified) HIGH Use only with "structural + dynamical model of a subgraph of the adult Drosophila connectome, not a whole organism" qualifier.
"Fly running on a laptop" MEDIUM Acceptable if accompanied by scope caveat and acceptance-test reference.
"Coherence-aware connectome OS" LOW Preferred framing.
"Auditable circuit discovery" LOW Core value proposition; encouraged.
"Counterfactual circuit fragility scoring" LOW Novel, defensible, auditable.
"Digital fly companion / pet" HIGH Avoid anthropomorphic framing; simulator, not companion.
"Road to mammalian minds" VERY HIGH Out of scope; do not gesture at.

Public posts, READMEs, and talk abstracts must pass a checklist that rejects the VERY HIGH and HIGH items above by default.

3. Scope Limits

  • v1 organism: adult Drosophila melanogaster only.
  • v2 candidates: larval Drosophila, larval zebrafish (when proofread connectomes ship).
  • Out of scope: mouse, rat, primate, human connectomes — pending external ethics review and a dedicated ADR.
  • Out of scope: clinical / medical / patient-facing applications.
  • Out of scope: consciousness or phenomenal-experience claims.
  • Out of scope: real-time human-scale simulation.

4. Security / Dual-Use Considerations

The same pipeline that discovers behaviour-responsible circuits can be used to design perturbations that abolish behavior. At fly scale this is a research tool; at any biological-organism scale it is an experimental design, not an action. The dual-use risk is structurally mitigated by the witness-log property: every perturbation has a manifest with an SHA-256 fingerprint, making post-hoc audit feasible regardless of author intent. Guidelines:

  • CC-OS runs shall emit witness bundles for any perturbation sweep.
  • CC-OS shall not accept non-published connectomes (no BYO-connectome in v1 to prevent unaudited organism targeting).
  • Perturbation recipes shall be version-pinned and hashed so that a published paper's experimental design is reproducible.

5. Comparison with Prior Art

System Scale Lang Graph-native Coherence-gated Counterfactual Witness-audit Open-source
OpenWorm 302 (C. elegans) C++ / Python Partial No No No Yes
NEURON Arbitrary C / Python No (biophysics) No Manual No Yes
Brian2 Arbitrary Python Partial No Manual No Yes
Nengo Arbitrary Python No (NEF) No Manual No Yes
NeuroMechFly + Kakaria-LIF ~10k Python Partial No No No Partial
Blue Brain Nexus 10^6+ cortex C++ / Python Partial No No Partial No
BrainScaleS 10^5 (hardware) Hardware No No Yes (hardware) No No
"Eon"-style stack ~100k Python Partial No No No No
CC-OS (this compendium) 10k–139k Rust Yes Yes Yes Yes (ADR-028) Yes

The differentiation is not scale or biophysical fidelity; it is the combination of graph-native storage + coherence gating + counterfactual fragility + witness audit + Rust.

6. Decision Rubric

From the originating proposal (user quote, verbatim structure):

Dimension Verdict
Feasibility today HIGH
Novelty with RuVector HIGH
Scientific validity if carefully positioned MEDIUM–HIGH
Risk of hype if framed as "mind upload" VERY HIGH
Best positioning Embodied connectome simulation + coherence analysis

We accept this rubric and commit to the "best positioning" in all external artifacts.

7. Proposed ADRs

Five ADRs land this compendium in the project's decision record. ADR numbers are reserved starting at ADR-084 (the last existing ADR before this compendium is ADR-081; ADR-082 and ADR-083 are reserved for unrelated in-flight work).

Each ADR follows the existing RuView format: Status, Context, Decision, Consequences, Links.

7.1 ADR-084 — Connectome Graph Substrate (Layer 1)

  • Status: Proposed
  • Context: CC-OS requires a typed, provenance-tagged, performance-adequate graph substrate for 10k–139k neuron connectomes with 1M–60M synapses. Existing wifi-densepose-db is row-store oriented; existing wifi-densepose-ruvector is signal/MAT focused. Neither covers the connectome use case directly.
  • Decision: Introduce wifi-densepose-connectome crate implementing the ConnectomeGraph aggregate (02-connectome-graph-substrate.md §10), Neuron / Synapse / Region value objects, and adapters to ruvector-mincut edge triplets and ruvector-temporal-tensor per-neuron voltage buffers. FlyWire loader first; MICrONS and larval Drosophila loaders behind feature flags.
  • Consequences (positive): graph-native circuit queries; provenance-tagged synapses; witness-log-compatible. (negative): adds a new crate to maintain; widens NodeId to u64 in a new namespace. (neutral): publishing order changes.
  • Links: RD-C-02, RD-C-03.

7.2 ADR-085 — Neural Dynamics Runtime (Layer 2)

  • Status: Proposed
  • Context: CC-OS requires an event-driven LIF runtime at 1 kHz real-time for 50k-neuron subgraphs, with deterministic replay and compressed voltage/spike storage.
  • Decision: Introduce wifi-densepose-neuro crate (04-neural-dynamics-runtime.md §10). Uses ruvector-solver for rate-code and perturbation solves; ruvector-temporal-tensor for voltage and spike storage; ruvector-attention for motif queries. Inner loop single-threaded for determinism; rayon fan-out per time slot for throughput.
  • Consequences: full cross-region LIF runtime available to the workspace; reuses RuVector patterns without duplication; introduces rand_chacha and rayon dependencies to a new crate.
  • Links: RD-C-04, RD-C-05.

7.3 ADR-086 — Embodied Simulator Closed Loop (Layer 3)

  • Status: Proposed
  • Context: Without a body, circuit dynamics do not produce behavior. CC-OS needs a deterministic Rust-native inner-loop body simulator at 1 kHz physics / 100 Hz control, with an optional bridge to NeuroMechFly for biomechanical validation.
  • Decision: Introduce wifi-densepose-embody crate using Rapier for physics and a hand-authored minimal fly body (41 DoF). Optional nmf-bridge feature for NeuroMechFly cross-validation.
  • Consequences: tight in-proc Rust loop; no Python dependency on the critical path; validation story intact via optional bridge; rapier3d becomes a workspace dependency.
  • Links: RD-C-06.

7.4 ADR-087 — CRV Behavioral Episodes + Coherence Gating (Layer 4)

  • Status: Proposed
  • Context: Behaviors are episodic. CC-OS needs a bout-level encoding that is reproducible, queryable, and integrates with the existing ruvector-crv six-stage protocol and CoherenceGate.
  • Decision: Implement BehaviorPipeline inside the existing wifi-densepose-ruvector crate as a sibling of WifiCrvPipeline. Map CRV stages I–VI to behavior-class / neural-sensory-feature / body-pose-sketch / coherence-gate-state / circuit-query / min-cut respectively (07-coherence-crv-behavioral-episodes.md §2).
  • Consequences: six-stage bout encoding for free via CrvSessionManager; Stage VI's MinCut directly yields behavior-responsible circuits; cross-subject convergence via find_convergence retargeted to behavior_class.
  • Links: RD-C-07, RD-C-05.

7.5 ADR-088 — Governance, Positioning, and Counterfactual Protocol

  • Status: Proposed
  • Context: Running connectome dynamics with counterfactual perturbation invites both scientific mis-statement ("mind upload") and dual-use misuse. A governance ADR fixes the framing, the allowed-claim boundaries, and the perturbation-audit protocol.
  • Decision:
    1. CC-OS is positioned as a "coherence-aware connectome operating system". The terms "mind upload", "digital consciousness", and their synonyms are prohibited in RuView public artifacts.
    2. Counterfactual perturbations (08-counterfactual-perturbation.md) must emit witness bundles compatible with the ADR-028 convention.
    3. Only published, peer-reviewed connectomes may be loaded in v1 (FlyWire, MICrONS partial).
    4. Mammalian connectomes are out of scope for v1 without external ethics review.
  • Consequences: clear framing for public communications; dual-use risk structurally mitigated by audit requirements; mammalian exploration is gated behind process, not policy.
  • Links: RD-C-11 (this document), RD-C-08, RD-C-01.

8. Five-Phase Implementation Roadmap

Phase Weeks Deliverables Gates
1 — Connectome import 1–4 wifi-densepose-connectome crate; FlyWire loader; graph storage and query benchmarks Load 139k-neuron FlyWire in < 10 s; k-hop query < 10 ms
2 — LIF runtime 5–10 wifi-densepose-neuro crate; event-driven kernel; voltage + spike storage; deterministic replay 1 kHz real-time for 10k-neuron subgraph; replay SHA-256 reproducible
3 — Closed loop 11–16 wifi-densepose-embody crate; Rapier fly body; sensorimotor loop; 100 Hz control Stable 100 Hz loop for 60 s without divergence
4 — Grooming acceptance 17–20 All four criteria of 10-acceptance-test-grooming.md pass on CI Acceptance test green
5 — Fragility + convergence 21–26 BehaviorPipeline + PerturbationRunner; cross-subject convergence via find_convergence; first public witness bundle Fragility correlates with published Hampel 2015 result; witness bundle self-verifies 7/7

Total: 26 weeks (6 months) from kickoff to first publishable witness bundle.

9. Success KPIs per Phase

Phase Primary KPI Secondary KPIs
1 Load time, query latency Memory footprint, loader coverage
2 Real-time factor Replay reproducibility, compression ratio
3 Closed-loop stability duration Physics step rate, actuator saturation rate
4 All four acceptance criteria green CI wall-clock, flake rate
5 Behavioral fragility \mathcal{F} distribution Jaccard with published circuits, convergence score

Each KPI has a target and a minimum; missing the minimum blocks promotion to the next phase.

10. Out-of-Scope Items for v1 (Explicit)

  • Mammalian connectomes (mouse cortex, larger).
  • Consciousness or phenomenal-experience claims.
  • Real-time human-scale simulation.
  • GPU-accelerated LIF.
  • Distributed multi-node simulation.
  • Live web visualisation.
  • Unsupervised behavior discovery.
  • Plasticity in the inner loop.
  • Wing aerodynamics.
  • Photorealistic rendering or optic-flow vision beyond simple luminance.
  • Companion or anthropomorphic framing.

11. Publication and Talk Plan

Venue Submission Target claim Artifact
NeurIPS workshop on neural connectomics 2026 Coherence-aware runtime + fragility pipeline First witness bundle
eLife methods (or PLOS Comp Biol) 2026 CC-OS architecture + grooming reproduction Peer-reviewed paper
RustConf 2026 Rust systems architecture + determinism Live demo
Strange Loop 2026 Coherence-aware framing + dual-use ethics Talk
bioRxiv preprint Month 6 Full methods Accompanies ADRs

No press-first releases. Every external communication follows the positioning and avoids the VERY HIGH / HIGH risk items of §2.

12. Appendix A: 200-Word Short-Form Summary

We built CC-OS, a coherence-aware connectome operating system, as a substrate for studying circuits that drive behavior in published insect connectomes. CC-OS is Rust-native, graph-first, and deterministic. It loads a peer-reviewed connectome (FlyWire is the v1 target at 139,255 neurons and 54M synapses), runs an event-driven LIF neural runtime at real-time rates for 50k-neuron subgraphs, closes the sensorimotor loop through a Rapier-based fly body, and provides auditable counterfactual perturbation with min-cut-based fragility scoring. Every run emits a witness bundle with SHA-256 provenance that can be independently replayed. The first acceptance test reproduces the published fly antennal-grooming circuit (Hampel 2015) inside simulation, and shows the RuView min-cut identifies the same minimal sufficient circuit that optogenetic dissection did. CC-OS is not a mind, not a consciousness upload, not a replacement for NEURON or Brian2, and not a gesture at human-brain emulation. It is a platform for reproducible, auditable, graph-native connectome circuit science at insect scale.

13. References

  1. Sandberg, A., Bostrom, N. (2008). Whole Brain Emulation: A Roadmap. Future of Humanity Institute, Oxford.
  2. Seth, A. (2021). Being You: A New Science of Consciousness. Faber.
  3. Friston, K. (2013). Life as we know it. J. R. Soc. Interface.
  4. ADR-028 — ESP32 capability audit + witness verification.
  5. ADR-017 — RuVector signal + MAT integration.
  6. ADR-011 — Python proof of reality.
  7. Dorkenwald, S., et al. (2024). Neuronal wiring diagram of an adult brain. Nature.
  8. Hampel, S., et al. (2015). A neural command circuit for grooming movement control. eLife.
  9. Seeds, A. M., et al. (2014). A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila. eLife.
  10. Lappalainen, J. K., et al. (2024). Connectome-constrained networks predict neural activity across the fly visual system. Nature.
  11. Kakaria, K. S., de Bivort, B. L. (2017). Ring attractor dynamics emerge from a spiking model of the entire protocerebral bridge. Front Behav Neurosci.

End of compendium. Return to 00-index.md for the table of contents.