digital-drosophila/registry/phase4ao-conditioning-interface/source-snapshot/PROTOCOL_DRAFT.md

DRAFT — fixed-v2 olfactory conditioning in the independent D18 branch

Status: DRAFT / NOT REGISTERED / NOT APPROVED FOR EXECUTION.

This document is a proposal for review. It does not authorize a run, record a successful gate, freeze a protocol, or generate a learned candidate. It was written from frozen H/J/L source and the declared AM interface contract, not from selecting favorable AM outcomes. The coordinator must approve the final scope, budget, source/input inventory, and exact gate implementation before registration. No training or remote action is performed by this document.

1. Purpose and entry conditions

The next scientific endpoint should be actual acquisition under the unchanged TemporalEligibility-v2 rule, followed, if its registered acquisition gate passes, by fixed reversal, delayed-reward, and real-time retention assays. File validity, static 25% sensitivity, or a change in delta alone is not learning.

Entry requires the complete AM whole-brain interface gate, including its registered zero-overlay comparisons, nonzero internal/repeat validation, old reference regression, and frozen integrity checks. A partially completed zero suite is not this gate. Continue to use the independent D18 branch; do not edit or overwrite Phase 1–AM artifacts. The original base CSR, anatomical counts, transmitter signs, W_syn, LIF coefficients, APL calibration, D18 timing, 14,232-edge candidate mask, and eligibility-v2 remain unchanged.

New long-run/continuation plumbing must preserve the exact existing timestep operation order. Validate zero-delta and fixed-delta continuation, including a split across pending synaptic/APL arrivals, against an unsplit run before using it for retention. This is an implementation prerequisite, not another tunable scientific endpoint. No game, decoder, RL, visual branch, or brain-gain search is in scope.

2. Fixed population and replicate matrix

Use the original externally selected 4L odors without re-selection:

• ODOR_A: 4-ethylphenol.
• ODOR_B: 3-hexanone.
• Both frozen encoder modes: physiological and matched_energy.
• Both reciprocal assignments: A reinforced/B neutral, and B reinforced/A neutral.
• Both exact DAN/type-compartment branches below.
• Five independent training replicates in each cell.

Thus there are 2 modes × 2 DAN branches × 2 assignments × 5 replicates = 40 blocks, or eight experimental cells with five training replicates each.

Branch identity	Exact raw compartment string	Proposed signed prediction
PAM15	y5B'2a	S > 0
PPL103	y2a'1	S < 0

These identities are drawn from old H/J configuration, not from a rule that all PAM is appetitive or all PPL1 is aversive. Preparation must materialize and hash the actual DAN body IDs/neuron indices, exact annotation values, confirmed DAN→MBON/compartment mapping, and affected existing plastic edges from the sealed H mapping. Missing, ambiguous, or unmatched mappings remain unknown; they cannot be completed by cell-name inference.

The type-level signed predictions above are new, falsifiable engineering hypotheses. Evidence specifically establishing PAM15's proposed functional direction is limited. Correspondence of type labels across fly datasets is not proof that these individual MaleCNS bodies have been functionally validated. Neither branch is labeled a biologically demonstrated reward/aversion channel.

Seed inventory

Before outcomes, generate and save the complete RNG lineage and explicit seed table for replicate, cell, arm, epoch, CS events, US ordering, and evaluation. Use distinct replicate streams, for example an explicitly registered SeedSequence hierarchy with a newly audited master seed. Test expanded seed identities for collisions. Merely choosing five different base integers is insufficient: H/J/L used consecutive bases plus the trial number, producing overlapping nominal replicate streams.

Matched counterfactual arms may deliberately reuse the same input event table; list each such common-random-number alias. They are paired controls, not extra independent replicates. All evaluation RNG streams must be disjoint from all training/US/control RNG streams. Within a replicate use the same registered evaluation events for pre/post/control comparisons. If more than one evaluation stream is used per replicate, report/aggregate it within that replicate; five evaluation streams never substitute for five independent training replicates. The minimal budget below uses one independent A/B evaluation stream pair per training replicate, reused for paired contrasts.

3. Frozen update and explicit US interface

Use the exact frozen J/L v2 implementation and operation order:

• KC trace float32, tau = 100 ms, cap = 1.
• Every timestep: separate multiply, add actual KC spikes, then clamp.
• At the registered US tick, sample after that tick's multiply/add/clamp; include its KC spikes. Do not insert an anatomical-delay shift into eligibility.
• eta = 0.00275 mV, compartment polarity = −1.
• Additive update only on the already-confirmed compartment mask, with the old float32 floor −0.25 × base_candidate_mV.
• Update once at the end of the training epoch; it affects subsequent epochs, not an earlier part of the same epoch. No recovery, potentiation, or new mask.
• Install via the verified AM bridge: immutable base SI float64 plus the float32 delta widened to float64 and converted from mV to V. Preserve all untouched weights and fast-APL handling exactly.

The first proposal preserves the old scheduled dimensionless D = 1 artificial unconditioned-signal interface. It is neither measured dopamine concentration nor an actual-DAN-spike count. At the same scheduled tick, request spikes in the fixed matched DAN population. Record requested, accepted, rejected, and actual DAN spikes, including zero-delivery epochs, separately from D. Do not resample, boost, or silently discard failed delivery to obtain a preferred result.

Multiplying D by actual acceptance, changing D to a spike count, or adding a measured dopamine kinetic model would be a distinct, explicitly registered interface hypothesis; none is hidden in this draft. If neural DAN delivery is absent, any update still demonstrates scheduled artificial gating, not that actual DAN activity caused plasticity. This limitation must remain visible even if an engineering output gate passes.

4. Epochs, timing, and all actual controls

Training epochs retain the old trial-boundary reset policy: start V/g/ref, spike-delay queues, APL state/queue and KC trace from their declared initial values; carry only plastic_delta between epochs. Log the state policy. This is not continuous natural behavior. Retention deliberately uses the different, explicit continuous-state policy in section 7.

Normal epochs last 120 ms. CS occupies 0–100 ms, and a paired US is at 90 ms. Delayed epochs last 180 ms; the identical CS occupies 0–100 ms, and US is at 150 ms, i.e. 50 ms after CS offset and 60 ms later than the normal US. All delayed controls use that same 180 ms duration and 150 ms US slot, including the neutral epochs; do not reuse 90 ms controls to attribute delayed effects.

The frozen L encoder mapping/rates and original A/B identity are retained. However, old phase4l.py::run_rates generated PN events throughout its passed 120 ms duration. The present 100 ms CS plus a no-CS tail is an explicit new experimental timing choice aligned with validated AK input duration, not a claim of bitwise identity to old L's full training input. matched_energy matches the frozen encoder's expected total rate, not an artificially edited actual Poisson event count; report actual requests and acceptance by condition.

Within each arm, present 50 reinforced-cue epochs and 50 neutral-cue epochs in a pre-generated balanced order. The 50 reinforcement opportunities come from L's fixed formal conditioning count, not from a new magnitude search.

Arm	Actual execution in each normal or delayed suite
paired	50 CS+ with its matched DAN/US and 50 CS− without US
D=0	Identical input events and US schedule to paired; D=0 in updates
frozen	Identical input events and US schedule; no delta updates
random reward	Same 50 A/50 B and 50 US opportunities; exactly 25 A and 25 B get US, selected by a pre-generated random balanced schedule independent of responses
unpaired	Same 100 CS epochs and same 50 US events in 50 additional separate, no-CS epochs; preserve total event inventory, declare 150 rather than 100 epochs
CS-only	Same 100 CS epochs, no DAN/US; no scheduled D
DAN-only	Same 50 US epochs and 50 matched blank epochs, no CS

Every control is genuinely executed; neither identity reasoning nor a text label replaces its trajectory. The unpaired arm is specifically separate-epoch, reset-trace unpairing, not a claim about a long continuous biological interstimulus interval. Actual DAN-only network activity may recruit KC and produce eligibility; it must be measured, not assumed zero. Blank and US-only epochs retain the corresponding 90/150 ms timing slot and 120/180 ms duration.

5. Offline signed readout — do not discard contrary signs

Preparation defines complete, exact-annotation MBON12 and MBON01 populations from MaleCNS metadata, with all body/index membership and side information. No best responding neuron, hemisphere, compartment subset, or evaluation pair is selected after outcomes. Missing either population makes this specific readout NOT-TESTABLE; do not substitute another type or silently use an empty mean.

For an evaluation stimulus X and a fixed 0–120 ms probe window, define:

B(X) = mean_spike_count(MBON12, X) − mean_spike_count(MBON01, X).

This is offline analysis only, not an action decoder, a feedback signal, or proof of approach/avoidance. Also save both population means separately, their sizes and counts, all-MBON output, genuine downstream output, and latency.

Keep two distinct downstream inventories. The frozen H actual-edge table's complete target union is legacyDownstream (11,342 neurons in the verified local data), and contains all 97 MBONs. Do not relabel or silently edit that old population. Define nonMBONDownstream as the exact set difference of that union and the complete MBON population (11,245 here). Report both. Requiring an effect outside the MBON population is an additional pre-outcome hypothesis, not an already inherited H gate; it prevents a purely MBON-local change from being counted twice as evidence of broader propagation.

With C denoting that block's reinforced cue and N its neutral cue:

S_arm = [B_arm(C) − B_arm(N)] − [B_pre(C) − B_pre(N)].

Always emit the raw signed B and S, pre/post components and control S. For PAM15 the proposed relation is S > 0; for PPL103 it is S < 0. Never replace raw S in the report with abs(S), polarity × S, a magnitude-only score, or a renamed “positive learning score.” An opposite sign is a counterexample to the prediction, even if a magnitude or unsigned separation statistic increases.

The expected-control relation is equally explicit:

• PAM15: S_paired > S_control for each registered control.
• PPL103: S_paired < S_control for each registered control.

Use matched evaluation inputs and each arm's matched pre baseline. All probe updates and US inputs are off. Evaluation begins from the same frozen initial state for acquisition/reversal/delayed comparisons; retention uses its saved continuation state and time-matched frozen control as specified below.

6. Acquisition and strict reversal gates

6.1 Acquisition — newly proposed signed gate

For each of the eight cells, a successful training replicate must satisfy all:

1. The raw S has the registered direction (PAM15 >0; PPL103 <0).
2. It lies in that direction beyond each of the six actually executed timing-matched controls, not just the easiest control.
3. The inherited L functional requirement holds: conditioned-cue MBON Delta_g_max_abs exceeds neutral-cue Delta_g_max_abs, and the conditioned cue has a nonzero MBON spike-count or first-latency change versus its own pre probe. Undefined latency is separately reported, not silently zero-filled into proof of a latency effect.
4. The inherited H MBON and complete legacyDownstream A/B Euclidean separation gains are positive. Independently require positive separation gain in nonMBONDownstream as a newly declared specificity/transfer gate. Report all three underlying count vectors and gains, never select whichever downstream definition is more favorable after outcomes.

Require at least 3 of the 5 independent training replicates to satisfy the entire conjunction in the same replicate. Also calculate the inherited H mean-control rule separately. This exact new combined signed gate is a proposal, not a claim that H/L already implemented it.

Record acquisition at fixed update counts 0, 1, 2, 5, 10, 20 and 50. Only the registered terminal count 50 determines its gate. Do not stop at the best earlier count or add pairings after failure.

6.2 Reversal — new hypothesis, not H's permissive sign test

After normal acquisition, fork its exact delta into two arms:

• Reversal: 50 pairings of the former neutral cue with the same specific DAN branch, and 50 formerly reinforced cue epochs without US.
• No-reversal continuation: 50 further original-cue pairings and 50 original neutral epochs, with matched epoch totals and registered independent input streams. This is an additional real control, included in the budget.

Never reset the learned delta between acquisition and reversal; do not restore depressed old-cue edges. Keep the old epoch-reset neural state policy in both arms and evaluate from common fresh states. The pure-LTD/no-recovery rule may prevent reversal; that is a falsifiable model limitation, not permission to add potentiation, recovery, or more trials.

For strict reversal, retain the original C−N orientation when calculating S_acquisition, S_reversal, and S_continuation against the same original pre-training baseline. At the fixed terminal reversal count 50 require:

DAN branch	Acquisition	Reversal	No-reversal continuation
PAM15	S_acquisition > 0	S_reversal < 0	S_continuation > 0
PPL103	S_acquisition < 0	S_reversal > 0	S_continuation < 0

Additionally require a nonzero change in the former neutral cue's MBON spike count or defined first latency between acquisition and reversal, and a nonzero change in its actual-downstream event/count output. Save both cue vectors; counts alone can conceal a shift confined to the original cue. The same replicate must satisfy all conditions, with a 3/5 majority per cell. These are new terminal reversal hypotheses, fixed before the learning results.

Zero is failure of a strict sign-crossing gate, not reversal. Report H's original sign(acquisition) != sign(reversal) separately as a legacy statistic; its nonzero→zero success case does not satisfy this new gate. Do not claim that these engineering sign changes establish reversal of real appetitive/aversive behavior.

7. Delayed reward and genuine retention gates

Delayed-reward test — new hypothesis

Run delayed acquisition from zero delta, using the same fixed 50 reinforcement opportunities and all six controls in the 180 ms / US-at-150 ms suite. Sample the unchanged trace at 150 ms after that tick's update. Do not extend tau or redefine the trace to force delayed learning.

At count 50, require the same signed, functional, downstream and control conjunction as section 6.1, with at least 3/5 independent training replicates per cell and raw S direction intact. This explicitly tests whether the unchanged rule supports this particular delayed schedule. H did not supply an independent delayed-reward success threshold; this is a new pre-outcome gate.

Report delayed and immediate signed S side by side and their per-replicate difference. Do not require a invented retained percentage, impose a monotonic amplitude ratio, pool their seeds, or call an opposite delayed sign a successful larger absolute response. Delayed controls cannot be substituted by normal ones.

Retention — new continuous-state implementation and gate

Fork the terminal normal-acquisition checkpoint and the matched terminal normal frozen-control checkpoint. Each includes V/g/ref, pending spike-delay state, APL state, the complete D18 APL queue, absolute tick, delta, and relevant RNG state. Run real no-input/no-update dynamics continuously to 1 s and 10 s; the 1 s checkpoint is on the same idle trajectory used to reach 10 s. Do not reset, discard pending events, analytically decay only delta, or fabricate elapsed time by changing a seed.

At 0, 1, 10 s, fork independent A/B probes from each checkpoint; probes do not feed back into the idle continuation. Use the same registered evaluation streams for trained/frozen comparisons at every elapsed time. The probe lasts 120 ms, without US or updates. Keep delta constant throughout idle; the model does not contain molecular consolidation or recovery, and a pass cannot prove either.

Define signed S_trained(t) and S_frozen(t) using the original C−N orientation and their registered pre baselines. Require, in the same replicate at both 1 s and 10 s:

• PAM15: S_trained(t) > 0 and S_trained(t) > S_frozen(t).
• PPL103: S_trained(t) < 0 and S_trained(t) < S_frozen(t).
• Conditioned-cue MBON output has a nonzero spike-count or defined first-latency difference from the time-matched frozen probe; actual-downstream event/count output also differs. Save neutral-cue differences and the complete signed specificity contrasts so a generic global response is not presented as memory.

Require 3/5 independent training replicates per cell, without a fitted amplitude tolerance or an arbitrarily chosen “percent retained.” This is a new functional retention hypothesis, not the old H reset-and-retest result. Report an optional predeclared fresh-state/persistent-delta probe separately as a weight-storage diagnostic; it cannot satisfy the real-time gate.

8. Legacy gates, new hypotheses, and candidate limits

Retain the following old predicates verbatim as separately labeled audit fields where their data definitions apply:

• H: minimum seed majority 3; positive MBON and downstream Euclidean separation gains; the smaller mean gain of its two DAN branches exceeds the maximum mean gain among D0/random/frozen controls.
• H: legacy reversal sign-inequality and last-retention separation>pre. Disclose the old retention had no actual idle dynamics and is not direct validation of the new real-time protocol.
• L: conditioned Delta_g_max_abs>neutral plus a functional spike/latency change, in at least 3/5 seeds. Preserve the exact old implementation's legacy result as well as the new explicitly defined handling of missing latencies.

There was no completed inherited delayed-reward gate, no proven signed MBON12−MBON01 valence mapping for these bodies, and no complete L reversal or retention assay. The strict signed gates in sections 6–7 are new proposals, not historical passes and not thresholds obtained from AL/AM responses.

For the strongest proposed engineering candidate claim, all eight cells must pass their registered acquisition and subsequent assay gates, old required integrity/control gates, and numerical safety checks. This all-cell conjunction is itself an explicit proposed scope of claim; it is not a pre-existing H/L aggregate gate. Emit a complete 8-cell×assay table, including contrary signs, failures, NOT-RUN, NOT-TESTABLE, and actual delivery limitations. Do not pool one mode/compartment/assignment to rescue another, or silently retain only successful cells as the candidate.

Suggested staged execution: run normal acquisition and all six normal controls for all 40 blocks first. If the approved overall acquisition gate fails, seal a real acquisition failure and stop, recording subsequent assays as NOT-RUN. Otherwise execute the already registered complete delayed, reversal, continuation and retention suites. No gate changes, tuning or new pair choices occur between stages. A scientific failure is not a reason to delete evidence; an integrity/numerical/resource failure stops execution without a scientific success claim.

Even a full engineering pass would not establish odor preference behavior, motor learning, natural dopamine concentration, appetitive/aversive valence, long-term memory, or readiness for a game. Delta change alone, a file/checksum pass, static-overlay sensitivity, or signed output readout alone is insufficient.

9. Transparent worst-case runtime and data budget

The original estimate of 38,000 epochs omitted the new no-reversal continuation and a full timing-matched delayed-control suite. They cannot be silently added without revising the budget.

Per block	Epochs	Biological seconds
Normal paired + five 100-epoch controls + 150-epoch unpaired	750	90
Delayed paired + five 100-epoch controls + 150-epoch unpaired	750	135
Reversal	100	12
No-reversal continuation	100	12
Total training/control/continuation	1700	249

Across 40 blocks this is 68,000 epochs and 9,960 biological seconds. Real 10 s idle progression of trained and frozen retention branches adds 800 s, totaling at least 10,760 s biological time (107.6 million dt=0.1 ms steps), before evaluation probes, implementation validation, and old regressions. Checkpoints at 1 s are reused within the 10 s trajectory, not separate additional 10 s runs.

Relative to 38,000: add 4,000 continuation epochs and 26,000 delayed-control epochs. All delayed neutral/control epochs are 180 ms, not shortened to 120 ms. The table includes this duration correction. Any approved reduction of scope must be decided and documented before registration, not after results or a resource overrun.

Let measured AM walltime per 100 ms be t100. A preliminary linear conversion is 107,600 × t100, plus input generation, updates, evaluation, I/O and validation. If t100=1 s, this base is 29.9 h; if 5 s, 149.4 h. These are arithmetic scenarios, not claimed measured performance: learning may change spike load. Measure and reserve a conservative actual budget before registration; enforce a resource stop rather than changing the protocol during a run.

Full generated+applied APL traces alone use approximately 2 × 4064 × 4 × 10000 = 325,120,000 bytes/biological-second, hence more than 3.18 TiB for the above minimum. Do not silently carry the small AM experiment disk budget into this suite. Per-epoch full neuron counts also total about 45 GB at 68,000×166,700×4 bytes, before events or full checkpoints.

The proposed recording policy to approve before registration is: all spike events, actual input/delivery logs, per-epoch counts, signed metrics, every delta update and full terminal V/g/ref/APL/queue state. Every timestep retains a GPU finite-value latch and first-failure tick, not a CPU copy/hash of all state. At epoch boundaries hash the files and bind the complete chain of parent, input, delta-before, events/state/queues, eligibility/D and delta-after. Full APL/per-tick reference recordings are restricted to a fixed pre-outcome validation inventory, not a result-selected subset. That subset's exact comparison must not be described as per-tick regression of all 68,000 epochs. Compute capacity from measured event/log sizes plus a stated safety reserve, and register an exclusive-output storage cap. Do not publish a guessed final compressed size or omit encoder/update/I/O latency from walltime accounting.

The frozen L/J metric called MBON_g_max_abs is the maximum across neurons of the terminal post-minus-pre g difference, not a temporal maximum. Save MBON_final_delta_g_max_abs with explicit SI units and the legacy alias when needed. Complete terminal g and sparse events suffice to reconstruct that metric; adding a dense time-by-neuron recording is not required by its name.

Even without full histories, all 68,000 terminal state/ring payloads would use roughly 507 GB uncompressed, before events and evaluation. Use lossless compression and measure real complete-episode outputs before setting the hard storage cap. Do not infer final compressed usage from sparse activity alone.

10. Evidence, provenance, and unresolved biology

Local source basis (read-only, relative to the project):

• 23-ai-gpu/source/models/male-cns-lif/phase4h.yaml and phase4h.py: exact DAN configuration, old control/majority predicates, old nominal retention.
• 23-ai-gpu/source/models/male-cns-lif/phase4j.yaml and phase4j.py: frozen float32 trace order and apply_v2.
• 23-ai-gpu/source/models/male-cns-lif/phase4l.yaml and phase4l.py: original odor mapping, 50 formal pairings, input timing, and acquisition gate.
• 23-ai-gpu/source/wholebrain-plastic-interface-v1/PROTOCOL.md: unchanged-base bridge, scheduled-US semantics and later-learning boundary.

Relevant primary evidence, with narrow use:

• Hige et al., Neuron 2015, author institution: compartmental KC→MBON plasticity and odor-specific effects motivate local LTD; this does not measure this MaleCNS model's eta, tau or DAN concentration.
• Aso and Rubin, eLife 2016, author institution: cell-type-specific DAN learning/update rules oppose a universal cluster-valence assumption. They do not functionally identify every MaleCNS body here.
• Aso et al., eLife 2014: MBON population outputs motivate population-level readout. The exact MBON12−MBON01 signed hypothesis and the two predictions in this draft remain explicit cross-dataset/model assumptions, not a demonstrated behavioral scale.

The exact scalar D interface, fixed trace/eta/floor, absence of recovery, trial-boundary resetting, simplified signed readout, and 100/120/180 ms timings are declared model/engineering choices. In particular, the 1.8 ms anatomical synaptic delay is not an eligibility time constant. Physiological applicability, PAM15 functional direction in these bodies, continuous intertrial learning, behavioral valence and long-term retention remain unresolved.

Before formal registration the coordinator must approve and hash the completed population/seed/input inventory, new readout/gate code, exact continuation semantics, storage policy/cap, resource budget and final candidate wording. Until then this remains DRAFT — NOT REGISTERED — NO EXECUTION AUTHORITY.