  Several differential equation models have been proposed to explain the
formation of patterns characteristic of the grid cell network. Understanding
the effect of noise on these models is one of the key open questions in
computational neuroscience. In the present work, we continue the analysis of an
SDE system commonly proposed for this aim, which we initiated in a previous
paper. We show that the fluctuations of the empirical measure associated to the
particle system around its mean field limit converge to the solution of a
Langevin SPDE. The interaction between different columns of neurons along the
cortex prescribes a peculiar scaling regime.
