A Pre-Registered Two-Stage Empirical Program for Testing a Three-Surface Decomposition of Recursive Maintenance Cost in Anesthesia State Transitions

This document pre-registers a two-stage empirical program for testing a three-surface decomposition of recursive maintenance cost during anesthesia state transitions. The decomposition proposes that recursive system maintenance imposes a cost multiplier of the form:

R(t) = k₁ρ(t) + k₂γ(t) + k₃μ(t),

where ρ(t) represents effective coupling density, γ(t) represents perturbation amplification, μ(t) represents meta-constraint load, and k₁–k₃ are substrate-dependent structural coefficients.

The program tests whether anesthesia transitions exhibit the structural signatures predicted by this decomposition: transition-linked precursor ordering, hysteresis/path dependence between induction and emergence, and cross-term escalation near behavioral thresholds.

Stage 1 is a sensitivity-first Go/No-Go screen using the publicly available OpenNeuro dataset ds005620 (propofol sedation with repeated awakenings). It evaluates whether the decomposition is instrumentable using real multichannel EEG data before committing to resource-intensive validation. Stage 2 is a full pre-registered clinical validation protocol requiring defined induction and emergence ramps under IRB governance.

The program addresses observability, precursor structure, and boundary nonlinearity predictions. It does not test consciousness directly and does not assume the validity of any broader theoretical framework. The decomposition originates in prior theoretical work (Thomas, 2026a) but is treated here as a standalone falsifiable structural hypothesis.