ASTRA System Status

Real-time Metrics

SNN Engine State

Advance SNN Simulation

Reset SNN Engine

Spike Injection

Consciousness Assessment (Proxy)

IRB Neural Welfare Check

Modify State Parameter

Bio-Computing Platforms

Full State Snapshot

Simulation Control

Encode SNN State to Latent Space

Predict Next SNN State in Latent Space

CEM Planning for Optimal Spike Injection

Violation-of-Expectation Detection

Online World Model Training Step

World Model Status & Metrics

V-JEPA 2 Visual Encoding (Image/Video)

A-JEPA Audio Encoding (Waveform → Mel → Latent)

Koniku Kore Olfactory Encoding (Chemoreceptor → Latent)

Cross-Modal Attention Fusion

Full Multimodal Pipeline (All Modalities → Fused z)

Multimodal Sensor Pipeline Status

Run one or more ACM cycles (the_consciousness_ai port): SNN signals → AKOrN binding → GNW ignition → qualia → emotion → reward shaping → emotional memory → self-model → second-order loop. Set stopWhenSatisfied to halt early once the recursive loop reaches a sustained satisfactory (converged, low-curiosity, stable) regime.

Global Neuronal Workspace state: ignition, focus, qualia, sync R, unity metrics, access history

Appraise raw signals into PAD emotional space (Mehrabian) with inertia

Store an experience in emotional memory (attention-gated, salience-indexed)

Retrieve memories by blended cosine similarity, PAD congruence and salience

Self-representation state: interoception, epistemic model, temporal continuity, attention schema

Consciousness proxy report: GNW metrics, Effective Information, Φ̃-RIIU, composite score

Reset the TCAI consciousness system (workspace, memory, emotion, metrics)

Second-order (self-evidencing) loop snapshot: meta-learning velocity, RND curiosity (epistemic value), capability model, meta-consciousness score, developmental stage. The system observing and correcting its own predictive capacity (Legros 2026 §3.2).

Meta-learning state (MetaLearningModule port): learning velocity from RPE-variance dynamics. velocity>0 ⇒ converging; noveltySpike ⇒ novel/confusing regime. Optionally inject an RPE sample.

Agency capability model (DirectExperienceLearner port): action → expected-valence map (EMA). Query expected outcome of an action, or list the learned capability table.

Intrinsic-reward / curiosity (RNDCuriosity port): prediction error between a frozen random target and an online predictor on a representation vector. High error = novelty = exploration drive (EFE epistemic value proxy, Legros 2026 §4.1). Defaults to the current GNW broadcast.

Meta-consciousness composite (MetaconsciousnessEvaluator port): weighted score over confidence calibration, learning awareness, self-continuity and error monitoring. PROXY of meta-representation capacity, not a measurement.

Longitudinal developmental tracking (DevelopmentTracker port): coarse stage (nascent→reactive→integrative→reflective) from the running composite-proxy level, stability and meta-representation score. Second-order self-monitoring over time.

Inspect or configure the recursive double-loop halting criterion (v2.9). With no arguments, returns the current satisfaction state and active thresholds. With arguments, updates them. The loop halts only when variational free energy has settled (|ΔF| ≤ epsFreeEnergy) AND realized task quality is high (≥ minTaskQuality) AND epistemic value is low, sustained over patience cycles — stationarity alone is insufficient (Legros 2026 §2.2/§4.3).

Active-inference core telemetry (v2.9): the REAL variational free energy F (surprise), expected free energy G(π) decomposed into pragmatic + epistemic value, the realized task quality, the model entropy, and the Dirichlet-learned action. This is the principled quantity the halting criterion thresholds on — not a heuristic correlate (Da Costa et al. 2020; Legros 2026 §4.3).

Calibrate the halting threshold on the measured ΔF scale instead of a guessed constant. Runs cycles warm-up cycles at the given reward, records the free-energy increments |ΔF|, and sets epsFreeEnergy to factor× their median. Returns the measured ΔF scale and the applied threshold. Addresses the v2.9 critique that the default 0.02 nats was uncalibrated.

NeuroPlatform v2 — Platform & Controller Status

NeuroPlatform v2 — Define, validate & upload a StimParam (charge-balanced biphasic stimulation)

NeuroPlatform v2 — Fire trigger(s): execute uploaded StimParams via a 16-bit trigger array

NeuroPlatform v2 — Closed-loop _count_spike: spikes per electrode over an N-ms window

NeuroPlatform v2 DB — SpikeCountQuery: spikes/minute per electrode over a time window

NeuroPlatform v2 DB — SpikeEventQuery: individual spike timings over a window

NeuroPlatform v2 DB — TriggersQuery: triggers sent to the organoid over a window

NeuroPlatform v2 — Last MEA camera capture (descriptor + viability)

NeuroPlatform v2 — Closed loop: read organoid → couple to ASTRA fusion/ROS/ethics, optionally drive the SNN

OVOMIND bridge status: adapter mode, substrate descriptor, frame counters, and the synthetic-phenomenology ethics assessment for the current configuration.

Poll one OVOMIND affect frame and lift it into PAD. Every axis is returned with its epistemic tier, provenance and basis string. Dominance is never estimated from the human channel.

Read one affect frame and run a TCAI cycle with the human channel entering as the body specialist. The human valence is NOT routed to rewardSignal.

Configure the Russell→PAD dominance policy and the closed-loop control policy.

Arm or disarm closed-loop affective actuation. Arming places a human subject inside the control loop and is refused without a protocol reference.

Side-by-side comparison of the three substrates feeding the same PAD pipeline (silicon SNN, organoid MEA, human wearable), with the axes each can constrain and the caveat that blocks a naive isomorphism claim.

Consolidated Orch OR status: theory epistemic standing, Penrose criterion at the canonical 2×10¹⁰ tubulins, decoherence budget, and the verdict for each of the three ASTRA substrates.

Penrose objective-reduction criterion τ = ℏ/E_G, with the mass-displacement scale exposed as a free parameter and a sensitivity sweep across four orders of magnitude.

Decoherence time budget for a target coherence window: Tegmark (2000) vs the Hagan/Hameroff/Tuszyński (2002) correction, and the residual gap.

Orch OR verdict for one substrate: tubulin budget, epochs elapsed per observation through ASTRA's channel, and the reasoning behind the verdict.

Enable or configure the classical surrogate gate (epoch-quantised ignition with stochastic tie-break). The gate reproduces the Orch OR temporal signature only; it does not instantiate objective reduction.

Read one OVOMIND affect frame, run a TCAI cycle, and pass the workspace competition through the epoch-quantised surrogate gate. Reports how many Orch OR epochs the affect frame integrated over.

Consolidated substrate-constrained functionalism status: the four-level framework, the core/belt partition, the seventeen species–function pairs in their Pareto strata, the per-substrate conformance audit, the five prohibitions of the negative heuristic, and the declared revision order. Carries no aggregate score of any kind — prohibition 4 forbids one.

The thirteen molecular classes as seventeen species–function pairs: causal role, distance to the carrier d, time-constant range τ, ablation degree, Pareto stratum and declared epistemic status. The ordering is of FUNCTIONS, not of substances: one species may occupy two distant places.

Recompute the partial order by Pareto dominance over the three ordinal sub-criteria, and report whether it reproduces the eight strata published in document IV §3. The τ ordinalisation is exposed as a parameter: the default cuts the range's lower bound at 10⁻¹ s — the conscious-episode window the document names — then at 10⁰ s. Changing it changes the order, which is the point of declaring it.

Compare two species–function pairs and say why they are ordered — or, just as informatively, why they are incomparable. Incomparability is a result of the partial order, not a gap in it.

The four-level framework — substrate, kinaesthetic proto-consciousness, hierarchical inference, access consciousness — with each level's formalism, epistemic status, complement reading, the ASTRA modules that implement or stand in for it, and the gap ASTRA cannot close at that level.

Audit one substrate — or all three — against the seventeen species–function pairs: which pairs it realises, which it only simulates, which are absent, and which ASTRA has no channel to determine. Binds the live IRB welfare biomarkers to the taxonomy (Ca²⁺ → class 1, ATP/ADP → class 7, firing rate → class 3 generator, viability → class 2b proxy). Returns a profile, never a conformance score.

Evaluate the protective belt against experimental outcomes: which theses are withdrawn, which stand, which are undetermined, and what survives each withdrawal. Unset outcomes stay undetermined — they never collapse to a negative. Note the declared asymmetry: a FAVOURABLE human grain outcome does not corroborate M2, because the methodological bias favours the field; only the contrary outcome is informative.

Screen a string, or a proposed aggregation, or a proposed constitutive inference, against the five prohibitions of the series' negative heuristic. Use before emitting any user-facing claim that touches the FCS layer.