  Using miniscope recordings of calcium fluorescence signals in the CA1 region
of the hippocampus of mice, we monitor the neural activity of hippocampal
regions while the animals are freely moving in an open chamber. Using a
data-driven statistical modeling approach, the statistical properties of the
recorded data are mapped to spin-glass models with pairwise interactions.
Considering the parameter space of the model, the observed system is generally
near a critical state between two distinct phases. The close proximity to the
criticality is found to be robust against different ways of sampling and
segmentation of the measured data. By independently altering the coupling
distribution and the network structure of the statistical model, the network
structures are found to be vital to maintain the proximity to the critical
state. We further find the observed assignment of the coupling strengths makes
the net coupling at each site more balanced with slight variation, which likely
helps the maintenance of the critical state. Network analysis on the
connectivity obtained by thresholding the coupling strengths find the
connectivity of the networks to be well described by a random network model.
These results are consistent across different experiments, sampling and
segmentation choices in our analysis.
