Time-Scalar Field Theory (TSFT) models time as a physical scalar field whose local structure governs phase evolution, coherence stability, and dynamical persistence across physical systems. Prior work has demonstrated that standard quantum mechanical dynamics, including the Schr¨odinger and Dirac equations, emerge as limiting cases of scalar-time continuity, with Hamiltonian evolution weighted by the local scalar-time rate. In this work, we extend this formalism to biological cognition by modeling neural systems as multi-scale phase-coherent resonators embedded in scalar-time structure. We argue that cognition, memory access, and subjective continuity depend on stable phase synchronization across coupled neural oscillatory networks, whose quantum-relevant molecular substrates evolve under TSFT-modulated phase dynamics. This framework reframes memory not as exclusively local synaptic storage, but as a coherence-dependent retrieval process constrained by resonance stability. Pathological conditions such as Alzheimer’s disease are interpreted as failures of phase-coherent coupling rather than total informational erasure. Finally, we discuss implications for artificial resonant cognitive systems, neuromodulation strategies, and experimental tests of scalar-time coherence effects in neurobiological substrates. This work establishes a quantitative bridge between fundamental time-field physics and biological cognition, positioning TSFT as a candidate framework for neurophysical unification.
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Jordan Gabriel Farrell (Fri,) studied this question.
www.synapsesocial.com/papers/69a7cd3dd48f933b5eed95ff — DOI: https://doi.org/10.5281/zenodo.18286031
Jordan Gabriel Farrell
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