From d193a352039f4c1b2f998529d146003b8a9eb90d Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Wed, 22 Jul 2026 05:39:42 -0500 Subject: experiments: preregister Harnett signature gates --- ORAL_B.md | 172 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ ROADMAP.md | 6 +++ 2 files changed, 178 insertions(+) create mode 100644 ORAL_B.md diff --git a/ORAL_B.md b/ORAL_B.md new file mode 100644 index 0000000..1f18de3 --- /dev/null +++ b/ORAL_B.md @@ -0,0 +1,172 @@ +# Oral-bar B: preregistered Harnett-signature programme + +This programme is grounded in Francioni et al., *Vectorized instructive +signals in cortical dendrites* (Nature, 2026), +. It does not treat +"apical activity carries error" as sufficient novelty. The target is the +paper's specific somato-dendritic innovation signatures and its explicitly +unresolved distinction between an online control signal and a plasticity-only +teaching signal. + +No oral-B result may be generated before this protocol is committed. Native +accept-bar baselines may continue in parallel, but the oral-B confirmation may +not be inspected until C4 is closed. + +## What the biological experiment establishes + +The paper motivates four experimental conditions for a vectorized dendritic +teaching signal: + +1. dendritic activity contains information absent from parent-soma magnitude; +2. a population of SD residuals contains reward and trial-outcome information; +3. residual sign depends on the causal role of each neuron (opposite for P+ + and P- cells) and follows error change rather than error magnitude alone; +4. suppressing apical computation abolishes the vectorized signal and impairs + learning. + +The paper also reports that surrounding-network activity predicts whether a +coincident event is dendritically amplified or attenuated, and that residual +sign relates to subsequent activity changes. It explicitly leaves open whether +the residual first controls neural state online, directly gates plasticity, or +does both. That phase ambiguity is the model's central prospective prediction. + +## Continuous synthetic BCI + +The task is deliberately closer to the experiment than shuffled image +minibatches. An episode contains 28 temporally contiguous steps. Five P+ and +five P- units control a scalar cursor through + +`z(t) = mean(h_P+(t)) - mean(h_P-(t))`. + +The target is fixed within an episode, and reward is delivered when the cursor +crosses the target. Thirty P0 units provide task-correlated surrounding-network +activity but have zero direct cursor coefficient. Somatic dynamics have inertia, +an autoregressive context input, and independent process noise. Task seed and +model seed are separate. + +For every cell, raw apical activity is + +`a_i(t) = d_i h_i(t) + A_i c(t)`, + +where the first term is ordinary soma-predictable traffic and `A_i c(t)` is a +locally calibrated causal instruction. A per-cell affine neutral-period model +predicts normal soma-dendrite coupling and defines + +`r_i(t) = a_i(t) - P_i h_i(t)`. + +`A` is trained only from antithetic forward causal perturbations of neural +state; forward plasticity uses local eligibility times `r`. No gradient, +transpose weight, or reverse graph is available to learning. Exact derivatives +may be used only in post-hoc diagnostics. + +The current image-runner option `feedback=error_deriv` is ineligible: it +subtracts errors from unrelated shuffled minibatches and therefore has no +temporal interpretation. The BCI runner must compute velocity features only +within one contiguous episode and reset them at episode boundaries. + +## Frozen development screen + +Development uses environment seeds 0, 1, and 2 and model seed 0 only. No +confirmation environment seed may be evaluated during selection. The fixed +task has 40 neurons, 16 context variables, 14 training days, 64 episodes per +day, 28 steps per episode, and a separate 256-episode final evaluation with +plasticity disabled. + +Four mechanistic variants are crossed: + +- scalar error, plasticity only; +- scalar error, online control plus plasticity; +- error plus within-episode error velocity, plasticity only; +- error plus within-episode error velocity, online control plus plasticity. + +For control variants, `kappa` is selected from `{0.1, 0.3}`. Forward learning +rate is selected from `{0.01, 0.03}`. All variants use one simultaneous +antithetic perturbation every four steps, predictor neutral updates every step, +and the same trajectories/noise under paired seeds. A candidate is eligible +only when all three development environments satisfy all of: + +- at least a 10-point early-to-late success-rate gain; +- final success at least 20 points above the fixed-random-vectorizer control; +- finite state, loss, weights, predictor, and vectorizer values; +- absolute residual-parent-soma correlation no larger than 0.10; +- positive P+/P- error-change sign-inversion index; +- a both-phase apical lesion removes at least half of the intact learning gain. + +Among eligible candidates, select the largest worst-environment final success +rate. Break a within-one-point tie by larger worst-environment sign-inversion +index, then smaller `kappa`, then smaller learning rate. If none is eligible, +oral B stops as failed; thresholds or seeds are not changed. + +## Frozen confirmation + +The selected configuration is frozen and crossed over environment seeds +10--15 and model seeds 0--4. All metrics are computed by predetermined code; +no run or seed may be removed. A result file must record the source revision, +dirty state, task/model seed, full dynamics, phase masks, scalar reward +observations, forward-equivalent work, and peak memory. + +### B1. Innovation identification and network predictability + +- Mean absolute per-cell `corr(r_i, h_i)` is at most 0.10. +- Raw apical activity has at least 0.20 greater mean absolute soma correlation + than the innovation. +- A cross-validated linear decoder using the preceding surrounding-network + state predicts amplified versus attenuated events at at least 55% accuracy. +- Decoder hyperplane distance correlates positively with residual magnitude; + the mean cell-level correlation is at least 0.10. + +### B2. Reward, outcome, and causal-role vectorization + +- A cross-validated linear decoder of the residual population predicts final + episode success at at least 57%, and exceeds the matched soma-population + decoder by at least 3 points. +- The causal-role sign-inversion index is positive in at least 25/30 paired + runs. Define + + `I = 0.5 * [(r_P+ - r_P-)_(error decreases) + - (r_P+ - r_P-)_(error increases)]`. + +- Role-aligned innovation `s_i r_i` is more strongly associated with signed + error change than with unsigned instantaneous error by at least 0.05 in + absolute cross-validated correlation. +- Mean early-training residual per neuron predicts its late-minus-early mean + somatic activity with correlation at least 0.30. + +### B3. Phase-specific causal lesion + +Four paired conditions reuse identical environment trajectories: + +1. intact online control and plasticity; +2. online-control lesion only (residual excluded from state dynamics but still + available to local plasticity); +3. plasticity lesion only (residual controls state but is excluded from weight + updates); +4. both phases lesioned. + +A sham lesion consumes the same random numbers and arithmetic calls but +multiplies no signal by zero. + +- Plasticity-only lesion reduces early-to-late learning gain by at least 50% + relative to intact. +- After intact training, online-only lesion with weights frozen acutely reduces + final success by at least 5 points. +- Both-phase lesion is no better than either single lesion on its corresponding + endpoint. +- Sham lesion changes success by no more than 1 point. + +This factorial result is stronger than simply reproducing the paper's +throughout-task NDNF manipulation: it predicts that suppressing dendritic +innovation during learning and suppressing it after learning have dissociable +effects. Failure of the acute online-lesion criterion supports a +plasticity-only interpretation and falsifies SDIL's desired-velocity claim, +even if the learning lesion remains positive. + +## Reporting boundary + +Passing B1 alone establishes faithful innovation statistics, not teaching. +Passing B1+B2 without B3 establishes correlational biological signatures, not +causal mechanism. "Oral bar B" requires all three confirmation gates and must +include the failed structural variants and phase lesions. A match to empirical +decoder percentages is not claimed as quantitative neuroscience; the claim is +that one local learning-and-control mechanism jointly produces the qualitative +signatures and a new phase-specific prediction. diff --git a/ROADMAP.md b/ROADMAP.md index 88b5e19..871f946 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -14,6 +14,12 @@ than triggering selective seed removal or post-hoc protocol changes. developed early so long jobs can use otherwise idle, explicitly authorized GPUs without delaying stages 1–2. +The preregistered oral-B task, structural screen, confirmation seeds, signature thresholds, and +phase-specific lesion are specified in `ORAL_B.md`. They were frozen while C4 author baselines +were still running and before any continuous-BCI result was generated. Oral-B confirmation remains +sequenced after C4; implementation and CPU-only mechanics may be prepared while the accept jobs +occupy both authorized GPUs. + ## Frozen accept claims and gates ### C1. Innovation is necessary under naturally mixed apical traffic -- cgit v1.2.3