Statistical Field Theory and Neural Structures Dynamics I: Action Functionals, Background States and External Perturbations
Biological Physics
2023-12-01 v1 Statistical Mechanics
Neurons and Cognition
Abstract
This series of papers models the dynamics of a large set of interacting neurons within the framework of statistical field theory. The system is described using a two-field model. The first field represents the neuronal activity, while the second field accounts for the interconnections between cells. This model is derived by translating a probabilistic model involving a large number of interacting cells into a field formalism. The current paper focuses on deriving the background fields of the system, which describe the potential equilibria in terms of interconnected groups. Dynamically, we explore the perturbation of these background fields, leading to processes such as activation, association, and reactivation of groups of cells.
Cite
@article{arxiv.2311.18378,
title = {Statistical Field Theory and Neural Structures Dynamics I: Action Functionals, Background States and External Perturbations},
author = {Pierre Gosselin and Aïleen Lotz},
journal= {arXiv preprint arXiv:2311.18378},
year = {2023}
}