Computational Efficiency η and Dissipation Norm ||Δ|| as Universal Markers of Phenomenal Transition in EEG: Evidence from Three Independent Datasets

Abstract We introduce two integrated scalar metrics derived from the Effective Power framework (Waterman 2026): computational efficiency η = ||Ψ|| / ||A||, where ||Ψ|| is the norm of the five-band Phenomenal Vector and ||A|| is the norm of total oscillatory power; and dissipation norm ||Δ|| = ||A - Ψ||, the norm of the Dissipative Vector. These metrics aggregate across all five frequency bands to provide scalar summaries of the organised-to-dissipative ratio of neural computation at any moment. We test whether η and ||Δ|| constitute universal markers of phenomenal transition across three independent EEG paradigms: probabilistic reversal learning (ds004295, N=22), anagram insight (Oh et al. 2020, N=30), and meditation mind-wandering (ds001787, N=24). η is significantly reduced in all three paradigms at cognitive transition events (reversal: d=−2. 583, p<0. 001; insight: d=−0. 492, p=0. 011; meditation MW: d=−0. 862, p<0. 001). ||Δ|| is significantly elevated in all three paradigms (reversal: d=+1. 619, p<0. 001; insight: d=+0. 577, p=0. 003; meditation MW: d=+0. 410, p<0. 001). The frequency centroid Ψc = Σ (fᵢ × Effᵢ) / Σ (Effᵢ) is significantly elevated during mind-wandering (d=+0. 415, p=0. 025) but not at reversal or insight events. We interpret these results within RDRT: η operationalises the computational efficiency of the current phenomenal state, and its reduction marks the transition toward the thermodynamic halt boundary at which Pₙoncalc is generated. ||Δ|| directly quantifies the energy expenditure that fails to produce organised output — the operational EEG signature of Pₙoncalc generation. These two metrics, together with band-specific Eff profiles, provide a complete multi-level characterisation of phenomenal transitions in EEG data.