The Syncytial Mesh Model: A Mesoscale Control-Field Framework for Scale-Dependent Coherence in the Brain

Abstract

The Syncytial Mesh Model introduces a three-layered framework for large-scale brain dynamics integrating local neural circuitry, macrostructural connectivity, and a slow mesoscale control-field substrate associated with astrocytic syncytial organization. Rather than directly generating electrophysiological activity, the proposed syncytial layer modulates neuronal excitability, coherence structure, and metastable coordination across spatial scales. The framework is formulated as a phenomenological effective theory combining neural-mass dynamics, connectome-scale coupling, and continuous-field interactions. Within this architecture, the model provides a candidate explanation for large-scale traveling-wave organization, low-frequency coherence structure, and distributed plasticity phenomena that are not straightforwardly reducible to direct local synaptic connectivity alone. Numerical simulations of the effective field dynamics generate stable traveling-wave propagation, smooth phase-gradient organization, and low-frequency modal structure qualitatively resembling experimentally reported infra-slow and delta/theta coordination patterns. An analytic mesoscale coherence model further illustrates how scale-dependent synchronization probabilities may emerge from slow-field modulation and damping dynamics without requiring globally phase-locked neuronal oscillations.