Predictive Bioharmonics: A Pre-Pilot Observation of Shared Dynamical Regimes in Mind–Body Signals

The relationship between mental and bodily states is often discussed in psychological, physiological, or philosophical terms, but rarely examined through a shared dynamical framework. In this pre-pilot study, Predictive Bioharmonics (PB), a domain-agnostic dynamical stability analysis method, is applied to real-world polysomnography data containing simultaneous EEG and cardiovascular signals. Using a single publicly available record from the Sleep Heart Health Study (SHHS), PB drift analysis was performed independently on neural (EEG) and bodily (cardiovascular) time-series. The analysis examined whether transitions between stable and unstable dynamical regimes occurred independently or in coordinated fashion across signal types. The observed result is that major dynamical transitions—such as arousals and sleep-stage changes—were accompanied by concurrent shifts in PB-derived stability metrics in both EEG and cardiovascular signals. No extended periods were observed in which one signal exhibited sustained instability while the other remained dynamically stable. These findings do not establish causality, mechanism, or universality. Rather, they provide an initial real-world observation that mental and bodily signals may occupy a shared dynamical stability regime, detectable without semantic, clinical, or psychological labeling. The result motivates further controlled studies across individuals, states, and contexts.