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This series of papers models the dynamics of a large set of interactingneurons within the framework of statistical field theory. The system isdescribed using a two-field model. The first field represents the neuronalactivity, while the second field accounts for the interconnections betweencells. This model is derived by translating a probabilistic model involving alarge number of interacting cells into a field formalism. The current paperfocuses on deriving the background fields of the system, which describe thepotential equilibria in terms of interconnected groups. Dynamically, we explorethe perturbation of these background fields, leading to processes such asactivation, association, and reactivation of groups of cells.

Statistical Field Theory and Neural Structures Dynamics I: Action Functionals, Background States and External Perturbations