Soliton Dynamics of Consciousness
Zenodo (CERN European Organization for Nuclear Research) August 20, 2026 DOI: 10.5281/zenodo.22030777 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Proposes that consciousness can be modeled as a topological soliton whose dynamic coherence depends on topological protection, dissipation, and resonance, with a collapse threshold at a coherence value of 1/2 marking a bifurcation between pre-conscious and reflexive states. Argues this yields seven discrete soliton velocities matching seven states of consciousness and that positive dynamic coherence is necessary for Darwinian continuity in a topological network. |
Abstract
We present a dynamical extension of the Ontological Fundamental Network(OFN) framework in which consciousness is modeled as a topological soliton propa-gating on the discrete vacuum manifold Ω21. The static phase coherence parameterσϕ is upgraded to a Dynamic Coherence Parameter Σdyn = Ctop · Cdiss · Cread, whereCtop is the static topological protection (spectral gap λ(1)1 = 4), Cdiss is the dissipa-tive coupling to the environment (AQCRCD coherent/decoherent bands), and Creadis the resonance between the reading velocity of the network and its eigenfrequencies.We model Cread using the Korteweg–de Vries (KdV) soliton relation vsol = v0 +χA, where vsol is the soliton velocity, v0 is the linear wave speed set by the spectralgap, χ is an effective nonlinearity coefficient, and A is the soliton amplitude. Theresonance condition Cread → 1 corresponds to vsol = vres, where vres is the networkeigenfrequency. Detuning from resonance reduces the amplitude; when it falls belowa critical value Acrit, the soliton collapses. This critical condition corresponds toCread = Ccrit = 1/2, the bifurcation point between pre-conscious and reflexive states.The model predicts a discrete spectrum of soliton velocities corresponding tothe seven states of consciousness (n = 0, . . . , 6) in the OFN phenomenology. Weconnect this framework to Butzbach’s Retained-State Necessity Theorem, showingthat Σdyn > 0 is the necessary condition for Darwinian continuity in a topologicalnetwork. Falsifiable predictions for EEG/fMRI correlates are stated.