We derive D* = 2. 3107 as the optimal fractal dimension for self-organized conscious systems, emerging from three convergent mathematical derivations (Golden Triad, Murray's asymmetric branching, information-energy cost optimization). From this constant, we predict two characteristic neural frequencies via f = 432/φD: f₁ = 102 Hz for ordinary perception (D=3) and f₂ = 142 Hz for concentrated integration (D=D*). Four independent tests across two datasets validate the framework: 1. COGITATE iEEG (N=4): 80-120 Hz band differentiates conscious from unconscious perception (p = 0. 027), validating f₁. 2. Elite Athletes CCT (N=17): Controls show 6. 1× higher 142 Hz than athletes (p = 0. 0034, Cohen's d = -2. 48). 3. Task specificity (N=26): 142 Hz differentiates concentration from vigilance (p = 0. 0029) ; 102 Hz does not (p = 0. 117). 4. Neural efficiency (N=22): Athletes and controls show OPPOSITE 142 Hz modulation — athletes decrease 60% during concentration, controls increase 30% (p = 0. 0041). KEY DISCOVERY: 142 Hz high-gamma activity indexes the COST of cognitive integration, not integration itself. Experts achieve equivalent concentration with 12× less neural activity — a direct neurophysiological signature of expertise-driven efficiency. This framework offers quantitative, falsifiable predictions bridging fractal geometry, golden ratio mathematics, and consciousness research. It reframes high-gamma interpretation from "more gamma = more consciousness" to "more gamma = more effort, " with immediate implications for meditation research, clinical assessment, neurofeedback, and AI architecture design.
Aurélie Assouline (Wed,) studied this question.