Proposes an intervention framework to enhance executive function in ADHD, suggesting new adaptive strategies for high-reconfiguration individuals.
What we call attention-deficit/hyperactivity disorder is, under the Cortical Informational Field Theory (CIFT), a near-critical cortical regime — RC³ — in which λ_CIFT fluctuates chronically near the critical threshold λ_c. This is not a pathological state but a cortical architecture with ancient evolutionary roots that was functionally optimal in high-novelty environments and became costly only with the Neolithic transition to sedentary, routine-demanding contexts. The mismatch is environmental. The architecture is not disordered. The present paper has two objectives. First, it provides the evolutionary and dynamical foundation for the RC³ designation, drawing on genomic evidence spanning 45,000 years of human history. Second, it derives from the field equation ∂_tΦ = D_eff∇²Φ + λ_CIFTΦ − βΦ³ + η(x,t) a structured three-layer intervention protocol — CIFT-EXEC — for optimizing functional C2[Φ] in RC³ regimes during executive function tasks. The protocol addresses the four modulable parameters of the field equation: λ_CIFT (pharmacological layer), η(x,t) (environmental layer), G(x,t) (behavioral layer), and D_eff (long-term conditioning). Empirical grounding comes from Paper V of this program, which demonstrated increased inter-task cortical reconfiguration in ADHD (Cohen's d = 0.73–0.79), consistent with the near-critical prediction R ∝ 1/ΔU = 4β/λ_eff². The protocol predicts synergistic effects of medication combined with structured environment, multimodal learning advantage in high-reconfiguration individuals, and specific experimental conditions distinguishing RC³ from neurotypical regimes. Six falsifiable predictions are derived. The CIFT-EXEC protocol is the first intervention framework for ADHD grounded in a formal field equation rather than a symptom checklist. Its goal is not to correct the RC³ architecture but to build the environmental and behavioral scaffolding within which it can function adaptively.
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Danko Stjepovic Gonzalez (2026) studied this question.
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