Neural Coherence as a Scale-Invariant Network Constraint

This paper introduces a computational framework in which consciousness emerges as a navigational property of oscillatory networks operating under constraint. Optimal cognitive function is shown to arise from high local coherence combined with enforced global incoherence in sparse, small-world topologies. The framework provides falsifiable predictions testable using EEG, MEG, and fMRI data, reframing consciousness as an emergent survival geometry rather than a localized substrate.